Search results for: learning environments

Authors: Vesile Evrim, Aliyu Awwal

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By the evolvement in technology, the way of expressing opinions switched the direction to the digital world. The domain of politics as one of the hottest topics of opinion mining research merged together with the behavior analysis for affiliation determination in text which constitutes the subject of this paper. This study aims to classify the text in news/blogs either as Republican or Democrat with the minimum number of features. As an initial set, 68 features which 64 are constituted by Linguistic Inquiry and Word Count (LIWC) features are tested against 14 benchmark classification algorithms. In the later experiments, the dimensions of the feature vector reduced based on the 7 feature selection algorithms. The results show that Decision Tree, Rule Induction and M5 Rule classifiers when used with SVM and IGR feature selection algorithms performed the best up to 82.5% accuracy on a given dataset. Further tests on a single feature and the linguistic based feature sets showed the similar results. The feature “function” as an aggregate feature of the linguistic category, is obtained as the most differentiating feature among the 68 features with 81% accuracy by itself in classifying articles either as Republican or Democrat.

Keywords: feature selection, LIWC, machine learning, politics

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Authors: C. A. Sharma, Birendra P. Singh

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Ichnofacies analysis is considered the best paleontological tool for interpreting ancient depositional environments. Nineteen (19) ichnogenera (namely: Bergaueria, Catenichnus, Cochlichnus, Cruziana, Diplichnites, Dimorphichnus, Diplocraterion, Gordia, Guanshanichnus, Lockeia, Merostomichnites, Monomorphichnus, Palaeophycus, Phycodes, Planolites, Psammichnites, Rusophycus, Skolithos and Treptichnus) are recocered from the Tal Group (Cambrian) of the Nigalidhar Syncline. The stratigraphic occurrences of these ichnogenera represent alternating proximal Cruziana and Skolithos ichnofacies along the contact of Sankholi and Koti-Dhaman formations of the Tal Group. Five ichnogenera namely Catenichnus, Guanshanichnus, Lockeia, Merostomichnites and Psammichnites are recorded for the first time from the Nigalidhar Syncline. Cruziana ichnofacies is found in the upper part of the Sankholi Formation to the lower part of the Koti Dhaman Formation in the NigaliDhar Syncline. The preservational characters here indicate a subtidal environmental condition with poorly sorted, unconsolidated substrate. Depositional condition ranging from moderate to high energy levels below the fair weather base but above the storm wave base under nearshore to foreshore setting in a wave dominated shallow water environment is also indicated. The proximal Cruziana-ichnofacies is interrupted by the Skolithos ichnofacies in the Tal Group of the Nigalidhar Syncline which indicate fluctuating high energy condition which was unfavorable for the opportunistic organism which were dominant during the proximal Cruziana ichnofacies. The excursion of Skolithos ichnofacies (as a pipe rock in the upper part of Sankholi Formation) into the proximal Cruziana ichnofacies in the Tal Group indicate that increased energy and allied parameters attributed to the high rate of sedimentation near the proximal part of the basin. The level bearing the Skolithos ichnofacies in the Nigalidhar Syncline at the juncture of Sankholi and Koti-Dhaman formations can be correlated to the level marked as unconformity in between the Deo-Ka-Tibba and the Dhaulagiri formations by the conglomeratic horizon in the Mussoorie Syncline, Lesser Himalaya, India. Thus, the Tal Group of the Nigalidhar syncline at this stratigraphic level represent slightly deeper water condition than the Mussoorie Syncline, where in the later the aerial exposure dominated which leads to the deposition of conglomeratic horizon and subsequent formation of unconformity. The overall ichnological and sedimentological dataset allow us to infer that the Cambrian successions of Nigalidhar Syncline were deposited in a wave-dominated proximal part of the basin under the foreshore to close to upper shoreface regimes of the shallow marine setting.

Keywords: Cambrian, Ichnofacies, Lesser Himalaya, Nigalidhar, Tal Group

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

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This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script which is a series of texts including directions and dialogues. The other is blogposts which possesses relatively abstracted contents, stories and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. In order to improve the quality of topics, it needs a method to consider the word difference. In this paper, we introduce a semantic vocabulary expansion method to solve the word difference. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can learn more salient topics for broadcasting contents.

Keywords: broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec

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Authors: Afroza Parvin, Md. Mahmudul Hasan, Md. Rokunozzaman, Papon Debnath

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The effluents of textile industries have considerable amounts of heavy metals, causing potential microbial metal loads if discharged into the environment without treatment. Aim: In this present study, both lactose and non-lactose fermenting bacterial isolates were isolated from textile industrial effluents of a specific region of Bangladesh, named Savar, to compare and understand the load of heavy metals in these microorganisms determining the effects of heavy metal resistance properties on antibiotic resistance. Methods: Five different textile industrial canals of Savar were selected, and effluent samples were collected in 2016 between June to August. Total bacterial colony (TBC) was counted for day 1 to day 5 for 10-6 dilution of samples to 10-10 dilution. All the isolates were isolated and selected using 4 differential media, and tested for the determination of minimum inhibitory concentration (MIC) of heavy metals and antibiotic susceptibility test with plate assay method and modified Kirby-Bauer disc diffusion method, respectively. To detect the combined effect of heavy metals and antibiotics, a binary exposure experiment was performed, and to understand the plasmid profiling plasmid DNA was extracted by alkaline lysis method of some selective isolates. Results: Most of the cases, the colony forming units (CFU) per plate for 50 ul diluted sample were uncountable at 10-6 dilution, however, countable for 10-10 dilution and it didn’t vary much from canal to canal. A total of 50 Shigella, 50 Salmonella, and 100 E.coli (Escherichia coli) like bacterial isolates were selected for this study where the MIC was less than or equal to 0.6 mM for 100% Shigella and Salmonella like isolates, however, only 3% E. coli like isolates had the same MIC for nickel (Ni). The MIC for chromium (Cr) was less than or equal to 2.0 mM for 16% Shigella, 20% Salmonella, and 17% E. coli like isolates. Around 60% of both Shigella and Salmonella, but only 20% of E.coli like isolates had a MIC of less than or equal to 1.2 mM for lead (Pb). The most prevalent resistant pattern for azithromycin (AZM) for Shigella and Salmonella like isolates was found 38% and 48%, respectively; however, for E.coli like isolates, the highest pattern (36%) was found for sulfamethoxazole-trimethoprim (SXT). In the binary exposure experiment, antibiotic zone of inhibition was mostly increased in the presence of heavy metals for all types of isolates. The highest sized plasmid was found 21 Kb and 14 Kb for lactose and non-lactose fermenting isolates, respectively. Conclusion: Microbial resistance to antibiotics and metal ions, has potential health hazards because these traits are generally associated with transmissible plasmids. Microorganisms resistant to antibiotics and tolerant to metals appear as a result of exposure to metal-contaminated environments.

Keywords: antibiotics, effluents, heavy metals, minimum inhibitory concentration, resistance

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Authors: Josselyn Mata Calidonio, Arianna I. Maddox, Kimberly Hamad-Schifferli

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Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.

Keywords: adaptive immunoassay, detecting unknown viruses, gold nanoparticles, paper immunoassay, repurposing antibodies

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Authors: Ali Aldakhil

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This paper explores the many faces of the barriers and exclusionary attitudes and practices that disabled teachers and students experience in a school where they teach or attend. Critical disability studies and inclusive education theory were used to conceptualise this inquiry and ground it in the literature. These theories were used because they magnify and expose the problems of disability/disablism as within-society instead of within-individual. Similarly, disability-first language was used in this study because it seeks to expose the social oppression and discrimination of disabled. Data were generated through conducting in-depth semi-structured interviews with six disabled teachers who teach disabled children in a Saudi mainstream school. Thematic analysis of data concludes that the school is fettered by disabling barriers, attitudes, and practices, which reflect the dominant culture of disablism that disabled people encounter in the Saudi society on a daily basis. This leads to the conclusion that overall deconstruction and reformation of Saudi mainstream schools are needed, including non-disabled people’s attitudes, policy, spaces, and overall arrangements of teaching and learning.

Keywords: disablism, disability studies, mainstream schools, Saudi Arabia

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Authors: Hestiasari Rante, Leonardo De Araújo, Heidi Schelhowe

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Usability testing with children is similar in many aspects to usability testing with adults. However, there are a few differences that one needs to be aware of in order to get the most out of the sessions, and to ensure that children are comfortable and enjoying the process. This paper presents the need to acquire methodological knowledge for involving children as test users in usability testing, with consideration on Piaget’s theory of cognitive growth. As a case study, we use BatiKids, an application developed to evoke children’s enthusiasm to be involved in culture heritage preservation. The usability test was applied to 24 children from 9 to 10 years old. The children were divided into two groups; one interacted with the application through a graphic tablet with pen, and the other through touch screen. Both of the groups had to accomplish the same amount of tasks. In the end, children were asked to give feedback. The results suggested that children who interacted using the graphic tablet with pen had more difficulties rather than children who interacted through touch screen. However, the difficulty brought by the graphic tablet with pen is an important learning objective in order to understand the difficulties of using canting, which is an important part of batik.

Keywords: batikids, children, child-computer interaction, usability test

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Authors: Chien-Jen Liu, Shu Ching Yang

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Using the technology acceptance model (TAM), this study examined the external variables of technological complexity (TC) to acquire a better understanding of the factors that influence the acceptance of computer application courses by learners at Active Aging Universities. After the learners in this study had completed a 27-hour Facebook course, 44 learners responded to a modified TAM survey. Data were collected to examine the path relationships among the variables that influence the acceptance of Facebook-mediated community learning. The partial least squares (PLS) method was used to test the measurement and the structural model. The study results demonstrated that attitudes toward Facebook use directly influence behavioral intentions (BI) with respect to Facebook use, evincing a high prediction rate of 58.3%. In addition to the perceived usefulness (PU) and perceived ease of use (PEOU) measures that are proposed in the TAM, other external variables, such as TC, also indirectly influence BI. These four variables can explain 88% of the variance in BI and demonstrate a high level of predictive ability. Finally, limitations of this investigation and implications for further research are discussed.

Keywords: technology acceptance model (TAM), technological complexity, partial least squares (PLS), perceived usefulness

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Authors: Po-Chun Wang, Yan-Ru Lai, Sophia I. C. Lin, Alvin W. Y. Su

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The Generative Theory of Tonal Music (GTTM) provides systematic approaches to recognizing local boundaries of music. The rules have been implemented in some automated melody segmentation algorithms. Besides, there are also deep learning methods with GTTM features applied to boundary detection tasks. However, these studies might face constraints such as a lack of or inconsistent label data. The GTTM database is currently the most widely used GTTM database, which includes manually labeled GTTM rules and local boundaries. Even so, we found some problems with these labels. They are sometimes discrepancies with GTTM rules. In addition, since it is labeled at different times by multiple musicians, they are not within the same scope in some cases. Therefore, in this paper, we examine this database with musicians from the aspect of classical music and relabel the scores. The relabeled database - GTTM Database v2.0 - will be released for academic research usage. Despite the experimental and statistical results showing that the relabeled database is more consistent, the improvement in boundary detection is not substantial. It seems that we need more clues than GTTM rules for boundary detection in the future.

Keywords: dataset, GTTM, local boundary, neural network

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Authors: Tripureshwari Paul

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We are born with nature molded by nurture. Studies have confirmed the productive role of genes and environment on an individual. This study examines the relationship of parental genotype values on the intellectual ability of their children. Keeping in mind that academic achievement-learning capacity of student through normative education, a function of exposure to family environment and pathology with intellectual quotient of the individual. Purposive sampling was used and children between ages 11 and 12 years and their respective parents were involved. Raven’s Standard Progressive Matrices (RSPM), Family Pathology Scale (FPS) and Family Environment Scale (FES) were administered. The results found significant relationship of Offspring IQ to Parental IQ, maternal IQ demonstrating higher values of correlation. Female IQ was significant to maternal IQ and male IQ was significant to paternal IQ. With Academic Achievement not significantly correlated to IQ, it was determined that Competitive framework, freedom to expression and Recreational Orientation in family affect a child’s intellectual performance.

Keywords: academic achievement, environment, family environment, family pathology, genotype, intelligence quotient, maternal IQ, paternal IQ

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Authors: S. O. Uwaifo

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The paper examines the pivotal role of the library in university education through the provision of a wide range of information materials (print and non- print) required for the teaching, learning and research activities of the university. However certain impediments to the effectiveness of Nigerian university libraries, such as financial constraints, high foreign exchange, global disparities in accessing the internet, lack of local area networks, erratic electric power supply, absence of ICT literacy, poor maintenance culture, etc., were identified. Also, the necessity of repositioning Nigerian university libraries for effective information provision and delivery was stressed by pointing out their dividends, such as users’ access to Directory of Open Access Journals (DOAJ), Online Public Access Catalogue (OPAC), Institutional Repositories, Electronic Document Delivery, Social Media Networks, etc. It therefore becomes necessary for the libraries to be repositioned by way of being adequately automated or digitized for effective service delivery, in this age of globalization. Based on the identified barriers by this paper, some recommendations were proffered.

Keywords: repositioning, Nigerian university libraries, effective information provision and delivery, globalization

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Authors: Adewale O. Adegbenjo, Elsie Nsiah-Baafi, Mxolisi B. Shongwe, Mercy Ramakokovhu, Peter A. Olubambi

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The sintering step in powder metallurgy (P/M) processes is very sensitive as it determines to a large extent the properties of the final component produced. Spark plasma sintering over the past decade has been extensively used in consolidating a wide range of materials including metallic alloy powders. This novel, non-conventional sintering method has proven to be advantageous offering full densification of materials, high heating rates, low sintering temperatures, and short sintering cycles over conventional sintering methods. Ti6Al4V has been adjudged the most widely used α+β alloy due to its impressive mechanical performance in service environments, especially in the aerospace and automobile industries being a light metal alloy with the capacity for fuel efficiency needed in these industries. The P/M route has been a promising method for the fabrication of parts made from Ti6Al4V alloy due to its cost and material loss reductions and the ability to produce near net and intricate shapes. However, the use of this alloy has been largely limited owing to its relatively poor hardness and wear properties. The effect of sintering temperature on the densification, hardness, and wear behaviors of spark plasma sintered Ti6Al4V powders was investigated in this present study. Sintering of the alloy powders was performed in the 650–850°C temperature range at a constant heating rate, applied pressure and holding time of 100°C/min, 50 MPa and 5 min, respectively. Density measurements were carried out according to Archimedes’ principle and microhardness tests were performed on sectioned as-polished surfaces at a load of 100gf and dwell time of 15 s. Dry sliding wear tests were performed at varied sliding loads of 5, 15, 25 and 35 N using the ball-on-disc tribometer configuration with WC as the counterface material. Microstructural characterization of the sintered samples and wear tracks were carried out using SEM and EDX techniques. The density and hardness characteristics of sintered samples increased with increasing sintering temperature. Near full densification (99.6% of the theoretical density) and Vickers’ micro-indentation hardness of 360 HV were attained at 850°C. The coefficient of friction (COF) and wear depth improved significantly with increased sintering temperature under all the loading conditions examined, except at 25 N indicating better mechanical properties at high sintering temperatures. Worn surface analyses showed the wear mechanism was a synergy of adhesive and abrasive wears, although the former was prevalent.

Keywords: hardness, powder metallurgy, spark plasma sintering, wear

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Authors: Samir Sarfraj Terdalkar

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India needs to step into affordable higher education with more focus on skill development and employability. The general scenario of higher education in India revolves around two major branches of higher education ie., Engineering and Medical Sciences. These two branches still cannot be considered as affordable. Hence, skill development of each and every student beginning from the school education should emphasize on learning skills with special focus on physics and mathematics. In India, the Central Government initiated a survey based process of all higher Educational Institutes/ Universities and colleges in India. This survey/ process was – All India Survey On Higher Education (AISHE). The focus of this process was understand and Though the increase is significant, it is necessary to propagate skill and vocational education which would add to the employability factor. Similarly, there has been a significant increase in number of higher education institutes, there is need to rethink on the type of education/ curriculum offered by these institutions. In this regard, vocational education has helped to build skill sets to certain extent. There is need to bring in this vocational educational in main stream education which could be complementary for undergraduate / post graduate education. The paper focuses on different policies to bring in vocational/ skill education.

Keywords: higher education, skill, vocational, India

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Authors: Saba Latif

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The use of social media among university students is a topic of ongoing debate, with conflicting views on its impact on academic achievement. This study aimed to explore the relationship between social media use and academic achievement among university students and to identify factors that may contribute to positive or negative effects. The study used a mixed-methods design, including a survey of 500 university students and qualitative interviews with a subset of participants. The survey results showed that social media use was prevalent among students, with Facebook and Instagram are the most commonly used platforms. The findings also indicated a positive relationship between social media use and academic achievement, with students who reported higher levels of social media use also reporting higher GPAs. However, the qualitative interviews revealed that excessive use of social media could be a distraction that hinders academic performance, especially when students use it to procrastinate or to stay up late at night. Overall, the findings suggest that social media use can have both positive and negative effects on academic achievement among university students. Responsible and balanced use of social media, such as setting limits on usage and avoiding procrastination, may help students maximize the benefits while minimizing the risks.

Keywords: social media, university, achievement, effective, learning

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Authors: Sebastiano Candamano, Antonio Iorfida, Patrizia Frontera, Anastasia Macario, Fortunato Crea

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Alkali-activated materials are promising binders obtained by an alkaline attack on fly-ashes, metakaolin, blast slag among others. In order to guarantee the highest ecological and cost efficiency, a proper selection of precursors and alkaline activators has to be carried out. These choices deeply affect the microstructure, chemistry and performances of this class of materials. Even if, in the last years, several researches have been focused on mix designs and curing conditions, the lack of exhaustive activation models, standardized mix design and curing conditions and an insufficient investigation on shrinkage behavior, efflorescence, additives and durability prevent them from being perceived as an effective and reliable alternative to Portland. The aim of this study is to develop alkali-activated cements mortars containing high amounts of industrial by-products and waste, such as ground granulated blast furnace slag (GGBFS) and ashes obtained from the combustion process of forest biomass in thermal power plants. In particular, the experimental campaign was performed in two steps. In the first step, research was focused on elucidating how the workability, mechanical properties and shrinkage behavior of produced mortars are affected by the type and fraction of each precursor as well as by the composition of the activator solutions. In order to investigate the microstructures and reaction products, SEM and diffractometric analyses have been carried out. In the second step, their durability in harsh environments has been evaluated. Mortars obtained using only GGBFS as binder showed mechanical properties development and shrinkage behavior strictly dependent on SiO2/Na2O molar ratio of the activator solutions. Compressive strengths were in the range of 40-60 MPa after 28 days of curing at ambient temperature. Mortars obtained by partial replacement of GGBFS with metakaolin and forest biomass ash showed lower compressive strengths (≈35 MPa) and shrinkage values when higher amount of ashes were used. By varying the activator solutions and binder composition, compressive strength up to 70 MPa associated with shrinkage values of about 4200 microstrains were measured. Durability tests were conducted to assess the acid and thermal resistance of the different mortars. They all showed good resistance in a solution of 5%wt of H2SO4 also after 60 days of immersion, while they showed a decrease of mechanical properties in the range of 60-90% when exposed to thermal cycles up to 700°C.

Keywords: alkali activated cement, biomass ash, durability, shrinkage, slag

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Authors: Jacquelyn Irene Eidson

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Women who leave the workforce due to motherhood and wish to return are a valuable, untapped resource for organizations. Levinson’s theory of adult development defines life as a sequence of transitions requiring difficult decisions that prompt humans to question their identity and their self-efficacy. The experience of being a working mother and the experience of workplace mentorship have received extensive research attention. Merging the two experiences and focusing on feelings of identity and self-efficacy provides a unique and focused opportunity for learning. Through one-on-one interviews and focus group discussion with working mothers that had previously left the workforce for an extended leave due to child-rearing, a meaningful description of their experiences will be obtained. Data is currently being collected via a collaboration with state banking associations in the United States. Results from the study will enable organizations worldwide to more effectively provide mentorship opportunities built around a culture of understanding while more effectively recruiting, supporting, developing, and retaining this valuable talent pool.

Keywords: identity, mentorship, self-efficacy, working mother

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Authors: Nikolina Ribarić

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This paper compares the readiness of chemistry teachers to use information and communication technologies in chemistry in 2018. and 2021. A survey conducted in 2018 on a sample of teachers showed that most teachers occasionally use visualization and digitization tools in chemistry teaching (65%) but feel that they are not educated enough to use them (56%). Also, most teachers do not have adequate equipment in their schools and are not able to use ICT in teaching or digital tools for visualization and digitization of content (44%). None of the teachers find the use of digitization and visualization tools useless. Furthermore, a survey conducted in 2021 shows that most teachers occasionally use visualization and digitization tools in chemistry teaching (83%). Also, the research shows that some teachers still do not have adequate equipment in their schools and are not able to use ICT in chemistry teaching or digital tools for visualization and digitization of content (14%). Advances in the use of ICT in chemistry teaching are linked to pandemic conditions and the obligation to conduct online teaching. The share of 14% of teachers who still do not have adequate equipment to use digital tools in teaching is worrying.

Keywords: chemistry, digital content, e-learning, ICT, visualization

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Authors: J. F. Pollo Gaspary, F. Peron Gaspary, E. M. Simão, R. Concatto Beltrame, G. Orengo de Oliveira, M. S. Ristow Ferreira, J.C. Mairesse Siluk, I. F. Minello, F. dos Santos de Oliveira

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Background: Although palliative care policies and services have been developed, research in this area continues to lag. An integrated model of palliative care is suggested, which includes complementary and alternative services aimed at improving the well-being of patients and their families. The palliative aquatics care multi-device (AuBento) uses several electromagnetic techniques to decrease pain and promote well-being through relaxation and interaction among patients, specialists, and family members. Aim: The scope of this paper is to present a preliminary design study of a device capable of exploring the various existing theories on the biomedical application of magnetic fields. This will be achieved by standardizing clinical data collection with sensory integration, and adding new therapeutic options to develop an advanced palliative aquatics care, innovating in symptom and pain management. Methods: The research methodology was based on the Work Package Methodology for the development of projects, separating the activities into seven different Work Packages. The theoretical basis was carried out through an integrative literature review according to the specific objectives of each Work Package and provided a broad analysis, which, together with the multiplicity of proposals and the interdisciplinarity of the research team involved, generated consistent and understandable complex concepts in the biomedical application of magnetic fields for palliative care. Results: Aubento ambience was idealized with restricted electromagnetic exposure (avoiding data collection bias) and sensory integration (allowing relaxation associated with hydrotherapy, music therapy, and chromotherapy or like floating tank). This device has a multipurpose configuration enabling classic or exploratory options on the use of the biomedical application of magnetic fields at the researcher's discretion. Conclusions: Several patients in diverse therapeutic contexts may benefit from the use of magnetic fields or fluids, thus validating the stimuli to clinical research in this area. A device in controlled and multipurpose environments may contribute to standardizing research and exploring new theories. Future research may demonstrate the possible benefits of the aquatics care multi-device AuBento to improve the well-being and symptom control in palliative care patients and their families.

Keywords: advanced palliative aquatics care, magnetic field therapy, medical device, research design

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Authors: Freja Rydahl Rasmussen, Naja Villadsen, Stig Koust

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Air purifiers have become widely implemented in a wide range of settings, including households, schools, institutions, and hospitals, as they tackle the pressing issue of indoor air pollution. With their ability to enhance indoor air quality and create healthier environments, air purifiers are particularly vital when ventilation options are limited. These devices incorporate a diverse array of technologies, including HEPA filters, active carbon filters, UV-C light, photocatalytic oxidation, and ionizers, each designed to combat specific pollutants and improve air quality within enclosed spaces. However, the safety of air purifiers has not been investigated thoroughly, and many questions still arise when applying them. Certain air purification technologies, such as UV-C light or ionization, can unintentionally generate undesirable byproducts that can negatively affect indoor air quality and health. It is well-established that these technologies can inadvertently generate nanoparticles or convert common gaseous compounds into harmful ones, thus exacerbating air pollution. However, the formation of byproducts can vary across products, necessitating further investigation. There is a particular concern about the formation of the carcinogenic substance formaldehyde from common gases like acetone. Many air purifiers use mechanical filtration to remove particles, dust, and pollen from the air. Filters need to be replaced periodically for optimal efficiency, resulting in an additional cost for end-users. Currently, there are no guidelines for filter lifespan, and replacement recommendations solely rely on manufacturers. A market screening revealed that manufacturers' recommended lifespans vary greatly (from 1 month to 10 years), and there is a need for general recommendations to guide consumers. Activated carbon filters are used to adsorb various types of chemicals that can pose health risks or cause unwanted odors. These filters have a certain capacity before becoming saturated. If not replaced in a timely manner, the adsorbed substances are likely to be released from the filter through off-gassing or losing adsorption efficiency. The goal of this study is to investigate the lifespan of filters as well as investigate the potentially harmful effects of air purifiers. Understanding the lifespan of filters used in air purifiers and the potential formation of harmful byproducts is essential for ensuring their optimal performance, guiding consumers in their purchasing decisions, and establishing industry standards for safer and more effective air purification solutions. At this time, a selection of air purifiers has been chosen, and test methods have been established. In the following 3 months, the tests will be conducted, and the results will be ready for presentation later.

Keywords: air purifiers, activated carbon filters, byproducts, clean air, indoor air quality

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Authors: Chuen-arom Janthimachai-amorn, Chirawadee Harnrittha

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This study aims to identify the factors facilitating the knowledge management to develop the graduate study programs to achieve success and to identify the approaches in developing the graduate study programs in the Rajbhat Suansunantha University. The 10 respondents were the administrators, the faculty, and the personnel of its Graduate School. The research methodology was based on Pla-too Model of the Knowledge Management Institute (KMI) by allocating the knowledge indicators, the knowledge creation and search, knowledge systematization, knowledge processing and filtering, knowledge access, knowledge sharing and exchanges and learning. The results revealed that major success factors were knowledge indicators, evident knowledge management planning, knowledge exchange and strong solidarity of the team and systematic and tenacious access of knowledge. The approaches allowing the researchers to critically develop the graduate study programs were the environmental data analyses, the local needs and general situations, data analyses of the previous programs, cost analyses of the resources, and the identification of the structure and the purposes to develop the new programs.

Keywords: program development, knowledge management, graduate study programs, Rajbhat Suansunantha University

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Authors: Alaa Alrakaf, Sk. Md. Mizanur Rahman

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Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation.

Keywords: Arabic natural language processing, machine learning, machine translation, Naive bayes classifier, word sense disambiguation

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Authors: Shyam Mehraaj, Samanthi E. R. Siriwardana, Shehara A. K. G. H., Wanigasinghe N. T., Wandana R. A. K., Wedage C. V.

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A presentation is a critical tool for conveying not just spoken information but also a wide spectrum of human emotions. The single most effective thing to make the presentation successful is to practice it beforehand. Preparing for a presentation has been shown to be essential for improving emotional control, intonation and prosody, pronunciation, and vocabulary, as well as the quality of the presentation slides. As a result, practicing has become one of the most critical parts of giving a good presentation. In this research, the main focus is to analyze the audio, video, and slides of the presentation uploaded by the presenters. This proposed solution is based on the Natural Language Processing and Computer Vision techniques to cater to the requirement for the presenter to do a presentation beforehand using a mobile responsive web application. The proposed system will assist in practicing the presentation beforehand by identifying the presenters’ emotions, body language, tonality, prosody, pronunciations and vocabulary, and presentation slides quality. Overall, the system will give a rating and feedback to the presenter about the performance so that the presenters’ can improve their presentation skills.

Keywords: presentation, self-evaluation, natural learning processing, computer vision

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Christoph Opperer

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Space syntax is a theory and method for analyzing the spatial layout of buildings and urban environments to understand how they can influence patterns of human movement, social interaction, and behavior. While direct visibility is a key factor in space syntax research, important visual information such as light, color, texture, etc., are typically not considered, even though psychological studies have shown a strong correlation to the human perceptual experience within physical space – with light and color, for example, playing a crucial role in shaping the perception of spaciousness. Furthermore, these surface properties are often the visual features that are most salient and responsible for drawing attention to certain elements within the environment. This paper explores the potential of integrating these factors into general space syntax methods and visibility-based analysis of space, particularly for architectural spatial layouts. To this end, we use a combination of geometric (isovist) and topological (visibility graph) approaches together with image-based methods, allowing a comprehensive exploration of the relationship between spatial geometry, visual aesthetics, and human experience. Custom-coded ray-tracing techniques are employed to generate spherical panorama images, encoding three-dimensional spatial data in the form of two-dimensional images. These images are then processed through computer vision algorithms to generate saliency-maps, which serve as a visual representation of areas most likely to attract human attention based on their visual properties. The maps are subsequently used to weight the vertices of isovists and the visibility graph, placing greater emphasis on areas with high saliency. Compared to traditional methods, our weighted visibility analysis introduces an additional layer of information density by assigning different weights or importance levels to various aspects within the field of view. This extends general space syntax measures to provide a more nuanced understanding of visibility patterns that better reflect the dynamics of human attention and perception. Furthermore, by drawing parallels to traditional isovist and VGA analysis, our weighted approach emphasizes a crucial distinction, which has been pointed out by Ervin and Steinitz: the difference between what is possible to see and what is likely to be seen. Therefore, this paper emphasizes the importance of including surface properties in visibility-based analysis to gain deeper insights into how people interact with their surroundings and to establish a stronger connection with human attention and perception.

Keywords: space syntax, visibility analysis, isovist, visibility graph, visual features, human perception, saliency detection, raytracing, spherical images

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Xian Xie, Qinghua Fang

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This study used quantitative and qualitative methods to explore the characteristics of flipped classroom’s influence on classroom environment of college English reading, writing, and translating, and to summarize and reflect on the teaching characteristics of college English Reading, writing, and translating. The results of the study indicated that after the flipped classroom applied to reading, writing, and translating, students’ performance was improved to a certain extent, the classroom environment was improved to some extent, students of the flipped classroom are generally satisfied with the classroom environment; students showed a certain degree of individual differences to the degree of cooperation, participation, self-responsibility, task-orientation, and the teacher leadership and innovation. The study indicated that the implementation of flipped classroom teaching mode can optimize College English reading, writing, and translating classroom environment and realize target－learner as the center in foreign language teaching and learning, but bring a greater challenge to teachers.

Keywords: classroom environment, college English reading, writing and translating, individual differences, flipped classroom

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Khadijat T. Bamigbade, Olufade F. W. Onifade

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The field of automatic facial expression analysis has been an active research area in the last two decades. Its vast applicability in various domains has drawn so much attention into developing techniques and dataset that mirror real life scenarios. Many techniques such as Local Binary Patterns and its variants (CLBP, LBP-TOP) and lately, deep learning techniques, have been used for facial expression recognition. However, the problem of occlusion has not been sufficiently handled, making their results not applicable in real life situations. This paper develops a simple, yet highly efficient method tagged Local Binary Pattern-Histogram of Gradient (LBP-HOG) with occlusion detection in face image, using a multi-class SVM for Action Unit and in turn expression recognition. Our method was evaluated on three publicly available datasets which are JAFFE, CK, SFEW. Experimental results showed that our approach performed considerably well when compared with state-of-the-art algorithms and gave insight to occlusion detection as a key step to handling expression in wild.

Keywords: automatic facial expression analysis, local binary pattern, LBP-HOG, occlusion detection

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Authors: Dinesh Khanduja, Pardeep Kumar Sharma

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Education as the most important resource in any country has multiplying effects on all facets of development in a society. The new social realities, particularly, the interplay between democratization of education; unprecedented developments in the IT sector; emergence of knowledge society, liberalization of economy, and globalization have greatly influenced the educational process of all nations. This turbulence entails upon education to undergo dramatic changes to keep up with the new expectations. Growth of entrepreneurship among Indian women is highly important for empowering them and this is highly essential for the socio-economic development of a society. Unfortunately, in India, there is poor acceptance of entrepreneurship among women as unfounded myths and fears restrain them to be enterprising. To remove these inhibitions, the education system needs to be re-engineered to make entrepreneurship more acceptable. This paper empirically analyses the results of a survey done on around 500 female graduates in North India to measure and evaluate various entrepreneurial traits present in them. A formative model has been devised in this context, which should improve the teaching-learning process in our education system, which can lead to a sustainable growth of women entrepreneurship in India.

Keywords: women empowerment, entrepreneurship, education system, women entrepreneurship, sustainable development

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Authors: Mikkel Snorre Wilms Boysen

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From a theoretical perspective, expertise is generally considered a precondition for creativity. The assumption is that an individual needs to master the common and accepted rules and techniques within a certain knowledge-domain in order to create something new and valuable. However, real life cases, and a limited amount of empirical studies, demonstrate that this assumption may be overly simple. In this article, this question is explored through a number of semi-experimental case studies conducted within the fields of music, technology, and youth culture. The studies indicate that, in various ways, expertise plays an important part in creative processes. However, the case studies also indicate that expertise sometimes leads to an entrenched perspective, in the sense that knowledge and experience may work as a path into the well-known rather than into the unknown. In this article, these issues are explored with reference to different theoretical approaches to creativity and learning, including actor-network theory, the theory of blind variation and selective retention, and Csikszentmihalyi’s system model. Finally, some educational aspects and implications of this are discussed.

Keywords: creativity, expertise , education, technology

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