Search results for: electronic learning platform
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10146

Search results for: electronic learning platform

1146 Visual Inspection of Road Conditions Using Deep Convolutional Neural Networks

Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

Abstract:

This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

Procedia PDF Downloads 125
1145 Assessment of the Illustrated Language Activities of the Portage Guide to Early Education

Authors: Ofelia A. Damag

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The study was focused on the development and assessment of the illustrated language activities of the 1996 Edition of the Portage Guide to Early Education. It determined the extent of appropriateness, applicability, time efficiency and aesthetics of the illustrated language activities to be used as instructional material not only by teachers, but parents and caregivers as well. The eclectic research design was applied in this study using qualitative and quantitative methods. To determine the applicability and time efficiency of the study, a try out was done. Since the eclectic research design was used, it made use of a researcher-made survey questionnaire and focus group discussion. Analysis of the data was done through weighted mean and ANOVA. The respondents of the study were representatives of Special Education (SPED) teachers, caregivers and parents of a special-needs child, particularly with difficulties in learning basic language skills. The results of the study show that a large number of respondents are SPED teachers and caregivers and are mostly college graduates. Many of them have earned units towards Master’s studies. Moreover, a majority of the respondents have not attended seminars or in-service training in early intervention for them to be more competent in the area of specialization. It is concluded that the illustrated language activities under review in this study are appropriate, applicable, time efficient and aesthetic for use as a tool in teaching. The recommendations are focused on the advocacy for SPED teachers, caregivers and parents of special-needs children to be more consistent in the implementation of the new instructional materials as an aid in an intervention program.

Keywords: illustrated language activities, inclusion, portage guide to early education, special educational needs

Procedia PDF Downloads 154
1144 Image Processing of Scanning Electron Microscope Micrograph of Ferrite and Pearlite Steel for Recognition of Micro-Constituents

Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

Procedia PDF Downloads 195
1143 Story of Alex: Sociology of Gender

Authors: Karen V. Lee

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The significance of this study involves autoethnographic research about a music teacher learning about the socialization of gender issues in teaching. Mentorship involving intervention helps with the consequences influencing a transgendered music teacher. Basic storytelling methodology involves the qualitative method of research as a theoretical framework where the author provides a storied reflection about political issues surrounding teachers and the sociology of gender. Sub-themes involve counseling, adult education to ensure students and teachers receive social, emotional, physical, spiritual, and educational resources that evoke visceral, emotional responses from the audience. Major findings share how stories are helpful resources for others who struggle with the socialization of gender. It is hoped the research dramatizes an episodic yet incomplete story that highlights the circumstances surrounding the protagonist having his sex reassignment surgery during his undergraduate education degree. In conclusion, the research is a reflexive storied framework that embraces a positive outlook about a transgendered teacher during his masectomy. The sensory experience seeks verisimilitude by evoking lifelike and believable feelings from others. Thus, the scholarly importance of the sociology of gender and society provides transformative aspects that contributes to social change. Overall, the surgery surrounding the story about transgendered issues are not uncommon in society. Thus, continued education supports the moral mission to help teachers overcome and understand issues of gender that can socially impacts their professional lives as teachers.

Keywords: sociology of gender, transgender, music teachers, story, autoethnography as research, ideology

Procedia PDF Downloads 302
1142 Societal Acceptability Conditions of Genome Editing for Upland Rice in Madagascar

Authors: Anny Lucrece Nlend Nkott, Ludovic Temple

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The appearance in 2012 of the CRISPR-CaS9 genome editing technique marks a turning point in the field of genetics. This technique would make it possible to create new varieties quickly and cheaply. Although some consider CRISPR-CaS9 to be revolutionary, others consider it a potential societal threat. To document the controversy, we explain the socioeconomic conditions under which this technique could be accepted for the creation of a rainfed rice variety in Madagascar. The methodological framework is based on 38 individual and semistructured interviews, a multistakeholder forum with 27 participants, and a survey of 148 rice producers. Results reveal that the acceptability of genome editing requires (i) strengthening the seed system through the operationalization of regulatory structures and the upgrading of stakeholders' knowledge of genetically modified organisms, (ii) assessing the effects of the edited variety on biodiversity and soil nitrogen dynamics, and (iii) strengthening the technical and human capacities of the biosafety body. Structural mechanisms for regulating the seed system are necessary to ensure safe experimentation of genome editing techniques. Organizational innovation also appears to be necessary. The study documents how collective learning between communities of scientists and nonscientists is a component of systemic processes of varietal innovation. This study was carried out with the financial support of the GENERICE project (Generation and Deployment of Genome-Edited, Nitrogen-use-Efficient Rice Varieties), funded by the Agropolis Foundation.

Keywords: CRISPR-CaS9, varietal innovation, seed system, innovation system

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1141 An Elasto-Viscoplastic Constitutive Model for Unsaturated Soils: Numerical Implementation and Validation

Authors: Maria Lazari, Lorenzo Sanavia

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Mechanics of unsaturated soils has been an active field of research in the last decades. Efficient constitutive models that take into account the partial saturation of soil are necessary to solve a number of engineering problems e.g. instability of slopes and cuts due to heavy rainfalls. A large number of constitutive models can now be found in the literature that considers fundamental issues associated with the unsaturated soil behaviour, like the volume change and shear strength behaviour with suction or saturation changes. Partially saturated soils may either expand or collapse upon wetting depending on the stress level, and it is also possible that a soil might experience a reversal in the volumetric behaviour during wetting. Shear strength of soils also changes dramatically with changes in the degree of saturation, and a related engineering problem is slope failures caused by rainfall. There are several states of the art reviews over the last years for studying the topic, usually providing a thorough discussion of the stress state, the advantages, and disadvantages of specific constitutive models as well as the latest developments in the area of unsaturated soil modelling. However, only a few studies focused on the coupling between partial saturation states and time effects on the behaviour of geomaterials. Rate dependency is experimentally observed in the mechanical response of granular materials, and a viscoplastic constitutive model is capable of reproducing creep and relaxation processes. Therefore, in this work an elasto-viscoplastic constitutive model for unsaturated soils is proposed and validated on the basis of experimental data. The model constitutes an extension of an existing elastoplastic strain-hardening constitutive model capable of capturing the behaviour of variably saturated soils, based on energy conjugated stress variables in the framework of superposed continua. The purpose was to develop a model able to deal with possible mechanical instabilities within a consistent energy framework. The model shares the same conceptual structure of the elastoplastic laws proposed to deal with bonded geomaterials subject to weathering or diagenesis and is capable of modelling several kinds of instabilities induced by the loss of hydraulic bonding contributions. The novelty of the proposed formulation is enhanced with the incorporation of density dependent stiffness and hardening coefficients in order to allow the modeling of the pycnotropy behaviour of granular materials with a single set of material constants. The model has been implemented in the commercial FE platform PLAXIS, widely used in Europe for advanced geotechnical design. The algorithmic strategies adopted for the stress-point algorithm had to be revised to take into account the different approach adopted by PLAXIS developers in the solution of the discrete non-linear equilibrium equations. An extensive comparison between models with a series of experimental data reported by different authors is presented to validate the model and illustrate the capability of the newly developed model. After the validation, the effectiveness of the viscoplastic model is displayed by numerical simulations of a partially saturated slope failure of the laboratory scale and the effect of viscosity and degree of saturation on slope’s stability is discussed.

Keywords: PLAXIS software, slope, unsaturated soils, Viscoplasticity

Procedia PDF Downloads 219
1140 A Bioinspired Anti-Fouling Coating for Implantable Medical Devices

Authors: Natalie Riley, Anita Quigley, Robert M. I. Kapsa, George W. Greene

Abstract:

As the fields of medicine and bionics grow rapidly in technological advancement, the future and success of it depends on the ability to effectively interface between the artificial and the biological worlds. The biggest obstacle when it comes to implantable, electronic medical devices, is maintaining a ‘clean’, low noise electrical connection that allows for efficient sharing of electrical information between the artificial and biological systems. Implant fouling occurs with the adhesion and accumulation of proteins and various cell types as a result of the immune response to protect itself from the foreign object, essentially forming an electrical insulation barrier that often leads to implant failure over time. Lubricin (LUB) functions as a major boundary lubricant in articular joints, a unique glycoprotein with impressive anti-adhesive properties that self-assembles to virtually any substrate to form a highly ordered, ‘telechelic’ polymer brush. LUB does not passivate electroactive surfaces which makes it ideal, along with its innate biocompatibility, as a coating for implantable bionic electrodes. It is the aim of the study to investigate LUB’s anti-fouling properties and its potential as a safe, bioinspired material for coating applications to enhance the performance and longevity of implantable medical devices as well as reducing the frequency of implant replacement surgeries. Native, bovine-derived LUB (N-LUB) and recombinant LUB (R-LUB) were applied to gold-coated mylar surfaces. Fibroblast, chondrocyte and neural cell types were cultured and grown on the coatings under both passive and electrically stimulated conditions to test the stability and anti-adhesive property of the LUB coating in the presence of an electric field. Lactate dehydrogenase (LDH) assays were conducted as a directly proportional cell population count on each surface along with immunofluorescent microscopy to visualize cells. One-way analysis of variance (ANOVA) with post-hoc Tukey’s test was used to test for statistical significance. Under both passive and electrically stimulated conditions, LUB significantly reduced cell attachment compared to bare gold. Comparing the two coating types, R-LUB reduced cell attachment significantly compared to its native counterpart. Immunofluorescent micrographs visually confirmed LUB’s antiadhesive property, R-LUB consistently demonstrating significantly less attached cells for both fibroblasts and chondrocytes. Preliminary results investigating neural cells have so far demonstrated that R-LUB has little effect on reducing neural cell attachment; the study is ongoing. Recombinant LUB coatings demonstrated impressive anti-adhesive properties, reducing cell attachment in fibroblasts and chondrocytes. These findings and the availability of recombinant LUB brings into question the results of previous experiments conducted using native-derived LUB, its potential not adequately represented nor realized due to unknown factors and impurities that warrant further study. R-LUB is stable and maintains its anti-fouling property under electrical stimulation, making it suitable for electroactive surfaces.

Keywords: anti-fouling, bioinspired, cell attachment, lubricin

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1139 Teachers’ Intention to Leave: Educational Policies as External Stress Factor

Authors: A. Myrzabekova, D. Nurmukhamed, K. Nurumov, A. Zhulbarissova

Abstract:

It is widely believed that stress can affect teachers’ intention to change the workplace. While existing research primarily focuses on the intrinsic sources of stress stemming from the school climate, the current attempt analyzes educational policies as one of the determinants of teacher’s intention to leave schools. In this respect, Kazakhstan presents a unique case since the country endorsed several educational policies which directly impacted teaching and administrative practices within schools. Using Teaching and Learning International Survey 2018 (TALIS) data with the country specific questionnaire, we construct a statistical measure of stress caused by the implementation of educational policies and test its impact on teacher’s intention to leave through the logistic regression. In addition, we control for sociodemographic, professional, and students related covariates while considering the intrinsic dimension of stress stemming from the school climate. Overall, our results suggest that stress caused by the educational policies has a statistically significant positive effect on teachers’ intentions to transfer between schools. Both policy makers and educational scholars could find these results beneficial. For the former careful planning and addressing the negative effects of the educational policies is critical for the sustainability of the educational process. For the latter, accounting for exogenous sources of stress can lead to a more complete understanding of why teachers decide to change their schools.

Keywords: educational policies, Kazakhstani teachers, logistic regression factor analysis, sustainability education TALIS, teacher turnover intention, work stress

Procedia PDF Downloads 104
1138 Mapping of Urban Micro-Climate in Lyon (France) by Integrating Complementary Predictors at Different Scales into Multiple Linear Regression Models

Authors: Lucille Alonso, Florent Renard

Abstract:

The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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1137 Distribution System Modelling: A Holistic Approach for Harmonic Studies

Authors: Stanislav Babaev, Vladimir Cuk, Sjef Cobben, Jan Desmet

Abstract:

The procedures for performing harmonic studies for medium-voltage distribution feeders have become relatively mature topics since the early 1980s. The efforts of various electric power engineers and researchers were mainly focused on handling large harmonic non-linear loads connected scarcely at several buses of medium-voltage feeders. In order to assess the impact of these loads on the voltage quality of the distribution system, specific modeling and simulation strategies were proposed. These methodologies could deliver a reasonable estimation accuracy given the requirements of least computational efforts and reduced complexity. To uphold these requirements, certain analysis assumptions have been made, which became de facto standards for establishing guidelines for harmonic analysis. Among others, typical assumptions include balanced conditions of the study and the negligible impact of impedance frequency characteristics of various power system components. In latter, skin and proximity effects are usually omitted, and resistance and reactance values are modeled based on the theoretical equations. Further, the simplifications of the modelling routine have led to the commonly accepted practice of neglecting phase angle diversity effects. This is mainly associated with developed load models, which only in a handful of cases are representing the complete harmonic behavior of a certain device as well as accounting on the harmonic interaction between grid harmonic voltages and harmonic currents. While these modelling practices were proven to be reasonably effective for medium-voltage levels, similar approaches have been adopted for low-voltage distribution systems. Given modern conditions and massive increase in usage of residential electronic devices, recent and ongoing boom of electric vehicles, and large-scale installing of distributed solar power, the harmonics in current low-voltage grids are characterized by high degree of variability and demonstrate sufficient diversity leading to a certain level of cancellation effects. It is obvious, that new modelling algorithms overcoming previously made assumptions have to be accepted. In this work, a simulation approach aimed to deal with some of the typical assumptions is proposed. A practical low-voltage feeder is modeled in PowerFactory. In order to demonstrate the importance of diversity effect and harmonic interaction, previously developed measurement-based models of photovoltaic inverter and battery charger are used as loads. The Python-based script aiming to supply varying voltage background distortion profile and the associated current harmonic response of loads is used as the core of unbalanced simulation. Furthermore, the impact of uncertainty of feeder frequency-impedance characteristics on total harmonic distortion levels is shown along with scenarios involving linear resistive loads, which further alter the impedance of the system. The comparative analysis demonstrates sufficient differences with cases when all the assumptions are in place, and results indicate that new modelling and simulation procedures need to be adopted for low-voltage distribution systems with high penetration of non-linear loads and renewable generation.

Keywords: electric power system, harmonic distortion, power quality, public low-voltage network, harmonic modelling

Procedia PDF Downloads 153
1136 Cognitive and Environmental Factors Affecting Graduate Student Perception of Mathematics

Authors: Juanita Morris

Abstract:

The purpose of this study will examine the mediating relationships between the theories of intelligence, mathematics anxiety, gender stereotype threat, meta-cognition and math performance through the use of eye tracking technology, affecting student perception and problem-solving abilities. The participants will consist of (N=80) female graduate students. Test administered were the Abbreviated Math Anxiety Scale, Tobii Eye Tracking software, gender stereotype threat through Google images, and they will be asked to describe their problem-solving approach allowed to measure metacognition. Participants will be administered mathematics problems while having gender stereotype threat shown to them through online images while being directed to look at the eye tracking software Tobii. We will explore this by asking ‘Is mathematics anxiety associated with the theories of intelligence and gender stereotype threat and how does metacognition and math performance place a role in mediating those perspectives?’. It is hypothesized that math-anxious students are more likely affected by the gender stereotype threat and that may play a role in their performance? Furthermore, we also want to explore whether math anxious students are more likely to be an entity theorist than incremental theorist and whether those who are math anxious will be more likely to be fixated on variables associated with coefficients? Path analysis and independent samples t-test will be used to generate results for this study. We hope to conclude that both the theories of intelligence and metacognition mediate the relationship between mathematics anxiety and gender stereotype threat.

Keywords: math anxiety, emotions, affective domains fo learning, cognitive underlinings

Procedia PDF Downloads 262
1135 Content Analysis of Gucci’s ‘Blackface’ Sweater Controversy across Multiple Media Platforms

Authors: John Mark King

Abstract:

Beginning on Feb. 7, 2019, the luxury brand, Gucci, was met with a firestorm on social media over fashion runway images of its black balaclava sweater, which covered the bottom half of the face and featured large, shiny bright red lips surrounding the mouth cutout. Many observers on social media and in the news media noted the garment resembled racist “blackface.” This study aimed to measure how items were framed across multiple media platforms. The unit of analysis was any headline or lead paragraph published using the search terms “Gucci” and “sweater” or “jumper” or “balaclava” during the one-year timeframe of Feb. 7, 2019, to Feb. 6, 2020. Limitations included headlines and lead paragraphs published in English and indexed in the Lexis/Nexis database. Independent variables were the nation in which the item was published and the platform (newspapers, blogs, web-based publications, newswires, magazines, or broadcast news). Dependent variables were tone toward Gucci (negative, neutral or positive) and frame (blackface/racism/racist, boycott/celebrity boycott, sweater/balaclava/jumper/fashion, apology/pulling the product/diversity initiatives by Gucci or frames unrelated to the controversy but still involving Gucci sweaters) and word count. Two coders achieved 100% agreement on all variables except tone (94.2%) and frame (96.3%). The search yielded 276 items published from 155 sources in 18 nations. The tone toward Gucci during this period was negative (69.9%). Items that were neutral (16.3%) or positive (13.8%) toward the brand were overwhelmingly related to items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters. The most frequent frame was apology/pulling the product/diversity initiatives by Gucci (35.5%). The tone was most frequently negative across all continents, including the Middle East (83.3% negative), Asia (81.8%), North America (76.6%), Australia/New Zealand (66.7%), and Europe (59.8%). Newspapers/magazines/newswires/broadcast news transcripts (72.4%) were more negative than blogs/web-based publications (63.6%). The most frequent frames used by newspapers/magazines/newswires/broadcast news transcripts were apology/pulling the product/diversity initiatives by Gucci (38.7%) and blackface/racism/racist (26.1%). Blogs/web-based publications most frequently used frames unrelated to the controversial garment, but about other Gucci sweaters (42.9%) and apology/pulling the product/diversity initiatives by Gucci (27.3%). Sources in Western nations (34.7%) and Eastern nations (47.1%) most frequently used the frame of apology/pulling the product/diversity initiatives by Gucci. Mean word count was higher for negative items (583.58) than positive items (404.76). Items framed as blackface/racism/racist or boycott/celebrity boycott had higher mean word count (668.97) than items framed as sweater/balaclava/jumper/fashion or apology/pulling the product/diversity initiatives by Gucci (498.22). The author concluded that during the year-long period, Gucci’s image was likely damaged by the release of the garment at the center of the controversy due to near-universally negative items published, but Gucci’s apology/pulling the product off the market/diversity initiatives by Gucci and items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters were the most common frames across multiple media platforms, which may have mitigated the damage to the brand.

Keywords: Blackface, branding, Gucci, media framing

Procedia PDF Downloads 142
1134 Effect of Video-Based Instructional Strategy on Junior Secondary School Students' Academic Achievement in Social Studies in Ondo State, Nigeria

Authors: Abidoye James Alabi

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This study investigated the effect of video-based instructional strategy on junior secondary school academic achievement in social studies. The influence of gender on the academic achievement of student taught with video-based instructional strategy was also examined. The study adopted a pre-test and pro-test control group quasi-experimental design. Simple random sampling technique was used to select 40 students from two schools in Akure town in Ondo State. The researcher developed instructional video package on social studies concept which was used as treatment instrument for the experimental group while the control group was exposed to conventional teaching method. The instruments used in this study are social studies achievement test and instructional video package (IVP). T-test statistic was used to analyse the hypotheses. The findings revealed that experimental group performed better than the control group. It was also shown that gender has no significant effect on students’ academic achievement when exposed to an instructional video package. It was recommended that appropriate training and workshop should be organized by the government for the social studies teachers for effective use of instructional video package in order to enhance teachers productivities and learning among students in secondary schools.

Keywords: instructional video package, conventional teaching method, social studies, junior secondary school

Procedia PDF Downloads 417
1133 Big Data in Construction Project Management: The Colombian Northeast Case

Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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1132 Valence and Arousal-Based Sentiment Analysis: A Comparative Study

Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

Procedia PDF Downloads 91
1131 Computer Countenanced Diagnosis of Skin Nodule Detection and Histogram Augmentation: Extracting System for Skin Cancer

Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

Abstract:

Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

Procedia PDF Downloads 144
1130 Velocity Profiles of Vowel Perception by Javanese and Sundanese English Language Learners

Authors: Arum Perwitasari

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Learning L2 sounds is influenced by the first language (L1) sound system. This current study seeks to examine how the listeners with a different L1 vowel system perceive L2 sounds. The fact that English has a bigger number of vowel inventory than Javanese and Sundanese L1 might cause problems for Javanese and Sundanese English language learners perceiving English sounds. To reveal the L2 sound perception over time, we measured the mouse trajectories related to the hand movements made by Javanese and Sundanese language learners, two of Indonesian local languages. Do the Javanese and Sundanese listeners show higher velocity than the English listeners when they perceive English vowels which are similar and new to their L1 system? The study aims to map the patterns of real-time processing through compatible hand movements to reveal any uncertainties when making selections. The results showed that the Javanese listeners exhibited significantly slower velocity values than the English listeners for similar vowels /I, ɛ, ʊ/ in the 826-1200ms post stimulus. Unlike the Javanese, the Sundanese listeners showed slow velocity values except for similar vowel /ʊ/. For the perception of new vowels /i:, æ, ɜ:, ʌ, ɑː, u:, ɔ:/, the Javanese listeners showed slower velocity in making the lexical decision. In contrast, the Sundanese listeners showed slow velocity only for vowels /ɜ:, ɔ:, æ, I/ indicating that these vowels are hard to perceive. Our results fit well with the second language model representing how the L1 vowel system influences the L2 sound perception.

Keywords: velocity profiles, EFL learners, speech perception, experimental linguistics

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1129 Context Detection in Spreadsheets Based on Automatically Inferred Table Schema

Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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1128 Importance of Women Education: Mother To Be Education in Order to Brighten Future Generation’s Foredoom

Authors: Ummi Sholihah Pertiwi Abidin, Eva Fadhilah

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Social changes are more and more growing and having many different forms as the time passed and thought methods in the society. One of many forms of that social changes is the emancipation of women that is flourishing by the inception of gender equality perception between men and women in all aspects including education. It’s not anymore found the distinction between genders in learning and the education achieving right at this globalized era. But, it is still many perceptions which are against that equality of education achieving right, either come from the women’s selves or many external factors. They assumed that they are going to be a mother in the future, and a wife, someone with responsible for taking care of the household and everything inside, while the husband is the one who has the responsible for looking for the living. So comes from this kind of assumption, the perception against the education equality between genders, which means there is no need for them –women- to achieve the high education because they will still end up as housewives. Except those working or career women that need high education to support their works. These women are not aware that even a mother needs the high and capable education. Because, as the 'mother to be,' they surely need broad knowledge from the education to educate their children in the future. It is such a big fault to say the kind of thing, 'It is no matter that I am not educated, in case I’m just a housewife. The important thing is my children get a great education'. Unfortunately, it is still often found, saying 'A housewife job is not a big deal to do with high education.' This qualitative method paper raises a theme about the importance of education for women, no matter what will they be in the future. Because however, and whatever is the woman’s career outside the house, or even not working outside, she’s still a mother for her children, and 'educational provision' is a great need. And so forth, this educational provision is a big deal to do with future generation’s foredoom, regarding the first source of children’s knowledge and the first school for them is their mother.

Keywords: women education, mother to be, educational provision, first school, future generation’s foredoom

Procedia PDF Downloads 264
1127 Commercialization of Research Outputs in Kenyan Universities

Authors: John Ayisi, Gideon M. Kivengea, George A. Ombakho

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In this emerging era of knowledge economy, universities, as major centres of learning and research, are becoming increasingly important as sources of ideas, knowledge, skills, innovation and technological advances. These ideas can be turned into new products, processes and systems needed to drive their respective national economies, and thus placing universities at the centre of the national innovation systems. Thus, commercialization of research outputs from universities to industry has become an area of strong policy interest in African countries. To assess the level of commercialization of research outputs in Kenyan universities, a standardized questionnaire covering seven sub-sections, namely: University Commercialization Environment, Management of Commercialization Activities, Commercialization Office, Intellectual Property Rights (IPRs), Early Stage Financing and Venture Capital; Industrial Linkages; and Technology Parks and Incubators was administered among a few selected public and private universities. Results show that all the universities have a strategic plan; though not all have innovation and commercialization as part of it. Half the nineteen surveyed universities indicated they have created designated offices for fostering commercialization. Majority have guidelines on IPRs which advocate IP to be co-owned by researcher/university. University-industry linkages are weak. Most universities are taking precursory steps to incentivise and encourage entrepreneurial activities among their academic staff and students, even though the level of resources devoted to them is low. It is recommended that building capacity in entrepreneurship among staff and students and committing more resources to R&D activities hold potential to increased commercialization of university research outputs.

Keywords: commercialization, knowledge, R&D, university

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1126 Isolation of Bacterial Species with Potential Capacity for Siloxane Removal in Biogas Upgrading

Authors: Ellana Boada, Eric Santos-Clotas, Alba Cabrera-Codony, Maria Martin, Lluis Baneras, Frederic Gich

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Volatile methylsiloxanes (VMS) are a group of manmade silicone compounds widely used in household and industrial applications that end up on the biogas produced through the anaerobic digestion of organic matter in landfills and wastewater treatment plants. The presence of VMS during the biogas energy conversion can cause damage on the engines, reducing the efficiency of this renewable energy source. Non regenerative adsorption onto activated carbon is the most widely used technology to remove siloxanes from biogas, while new trends point out that biotechnology offers a low-cost and environmentally friendly alternative to conventional technologies. The first objective of this research was to enrich, isolate and identify bacterial species able to grow using siloxane molecules as a sole carbon source: anoxic wastewater sludge was used as initial inoculum in liquid anoxic enrichments, adding D4 (as representative siloxane compound) previously adsorbed on activated carbon. After several months of acclimatization, liquid enrichments were plated onto solid media containing D4 and thirty-four bacterial isolates were obtained. 16S rRNA gene sequencing allowed the identification of strains belonging to the following species: Ciceribacter lividus, Alicycliphilus denitrificans, Pseudomonas aeruginosa and Pseudomonas citronellolis which are described to be capable to degrade toxic volatile organic compounds. Kinetic assays with 8 representative strains revealed higher cell growth in the presence of D4 compared to the control. Our second objective was to characterize the community composition and diversity of the microbial community present in the enrichments and to elucidate whether the isolated strains were representative members of the community or not. DNA samples were extracted, the 16S rRNA gene was amplified (515F & 806R primer pair), and the microbiome analyzed from sequences obtained with a MiSeq PE250 platform. Results showed that the retrieved isolates only represented a minor fraction of the microorganisms present in the enrichment samples, which were represented by Alpha, Beta, and Gamma proteobacteria as dominant groups in the category class thus suggesting that other microbial species and/or consortia may be important for D4 biodegradation. These results highlight the need of additional protocols for the isolation of relevant D4 degraders. Currently, we are developing molecular tools targeting key genes involved in siloxane biodegradation to identify and quantify the capacity of the isolates to metabolize D4 in batch cultures supplied with a synthetic gas stream of air containing 60 mg m⁻³ of D4 together with other volatile organic compounds found in the biogas mixture (i.e. toluene, hexane and limonene). The isolates were used as inoculum in a biotrickling filter containing lava rocks and activated carbon to assess their capacity for siloxane removal. Preliminary results of biotrickling filter performance showed 35% of siloxane biodegradation in a contact time of 14 minutes, denoting that biological siloxane removal is a promising technology for biogas upgrading.

Keywords: bacterial cultivation, biogas upgrading, microbiome, siloxanes

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1125 Preserving Digital Arabic Text Integrity Using Blockchain Technology

Authors: Zineb Touati Hamad, Mohamed Ridda Laouar, Issam Bendib

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With the massive development of technology today, the Arabic language has gained a prominent position among the languages most used for writing articles, expressing opinions, and also for citing in many websites, defying its growing sensitivity in terms of structure, language skills, diacritics, writing methods, etc. In the context of the spread of the Arabic language, the Holy Quran represents the most prevalent Arabic text today in many applications and websites for citation purposes or for the reading and learning rituals. The Quranic verses / surahs are published quickly and without cost, which may cause great concern to ensure the safety of the content from tampering and alteration. To protect the content of texts from distortion, it is necessary to refer to the original database and conduct a comparison process to extract the percentage of distortion. The disadvantage of this method is that it takes time, in addition to the lack of any guarantee on the integrity of the database itself as it belongs to one central party. Blockchain technology today represents the best way to maintain immutable content. Blockchain is a distributed database that stores information in blocks linked to each other through encryption, where the modification of each block can be easily known. To exploit these advantages, we seek in this paper to justify the use of this technique in preserving the integrity of Arabic texts sensitive to change by building a decentralized framework to authenticate and verify the integrity of the digital Quranic verses/surahs spread on websites.

Keywords: arabic text, authentication, blockchain, integrity, quran, verification

Procedia PDF Downloads 154
1124 A Twelve-Week Intervention Programme to Improve the Gross Motor Skills of Selected Children Diagnosed with Autism Spectrum Disorder

Authors: Eileen K. Africa, Karel J. van Deventer

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Neuro-typical children develop the motor skills necessary to play, do schoolwork and interact with others. However, this is not observed in children who have learning or behavioural problems. Children with Autism Spectrum Disorder (ASD) are often referred to as clumsy because their body parts do not work well together in a sequence. Physical Activity (PA) has shown to be beneficial to the general population, therefore, providing children with ASD opportunities to take part in PA programmes, could prove to be beneficial in many ways and should be investigated. The purpose of this study was to design a specialised group intervention programme, to attempt to improve gross motor skills of selected children diagnosed with ASD between the ages of eight and 13 years. A government school for ASD learners was recruited to take part in this study, and a sample of convenience (N=7) was selected. Children in the experimental group (n=4) participated in a 12-week group intervention programme twice per week, while the control group continued with their normal daily routine. The Movement Assessment Battery for Children-Second Edition (MABC-2), was administered pre- and post-test to determine the children’s gross motor proficiency and to determine if the group intervention programme had an effect on the gross motor skills of the experimental group. Statistically significant improvements were observed in total motor skill proficiency (p < 0.05), of the experimental group. These results demonstrate the importance of gross motor skills interventions for children diagnosed with ASD. Future research should include more participants to ensure that the results can be generalised.

Keywords: autism spectrum disorder, children, gross motor skills, group intervention programme

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1123 An Introduction to the Current Epistemology of Ethical Philosophy of Islamic Banking

Authors: Mohd Iqbal Malik

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Ethical philosophy of Quran pinnacled virtue and economics as the part and parcel of human life. Human beings are to be imagined by the sign of morals. Soul and morality are both among the essences of human personality. Islam lays the foundation of ethics by installation of making a momentous variance between virtue and vice. It suggests for the distribution of wealth in-order to terminate accumulation of economic resources. Quran claims for the ambiguous pavement to attain virtue by saying, ‘Never will you attain the good (reward) until you spend (in the way of Allah) from that which you love. And whatever you spend indeed, Allah knows of it.’ The essence of Quran is to eliminate all the deep-seated approaches through which the wealth of nations is being accumulated within few hands. The paper will study the Quranic Philosophy Of Islamic Economic System. In recent times, to get out of the human resource development mystery of Muslims, Ismail Al-Raji Faruqi led the way in the so-called ‘Islamization’ of knowledge. Rahman and Faruqi formed opposite opinions on this project. Al-Faruqi thought of the Islamization of knowledge in terms of introducing Western learning into received Islamic values and vice versa. This proved to be a mere peripheral treatment of Islamic values in relation to Western knowledge. It is true that out of the programme of Islamization of knowledge arose Islamic universities in many Muslim countries. Yet the academic programmes of these universities were not founded upon a substantive understanding and application of the tawhidi epistemology.

Keywords: ethical philosophy, modern Islamic finance, knowledge of finance, Islamic banking

Procedia PDF Downloads 297
1122 The Impact of School Environment and Peer Relation on Anti-Social Behaviour of Students in Science Secondary Schools in Katsina State

Authors: Umar Mamman

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The study investigated the impact of school environment and peer relations on antisocial behaviour of the students of science secondary schools in Katsina State. The study sought to achieve the following objectives: to determine whether school influences antisocial behaviour among science secondary school students, and to determine whether peer relation influences anti-social behaviour among science secondary school students. The study population composed of all the students in science secondary schools in Katsina State. The study used a sample of 378 students and 18 teachers randomly selected from eleven science secondary schools in Katsina state. Three instruments were used to collect data for the study, thus: socio-economic status background questionnaire, antisocial process screening device (APSD), and inventory of parent and peer relationship questionnaire. The study findings revealed that school environment has significant effect on antisocial behaviour of the students in science secondary school (F (7, 372) = 52.08, p ≤ .01), and there is a significant effect of peer relation on antisocial behaviour of the students in science secondary school (F (7, 372) = 14.229, p ≤ .01). Based on these findings the following major recommendations were made: School environment should be made attractive and conducive for learning and character development. Teachers, as role model, should desist from indecent acts. School environment should be made learner-centered and friendly. Functional guidance and counselling outfits need to be provided in all secondary schools in Katsina state.

Keywords: school environment, peer relation, anti-social behaviour, psychology

Procedia PDF Downloads 347
1121 Impact of Using Peer Instruction and PhET Simulations on the Motivation and Physics Anxiety

Authors: Jaypee Limueco

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This research focused on the impact of Peer Instruction and PhET Simulations on the level of motivation and Physics anxiety of Grade 9 students. Two groups of students were used in the study. The experimental group involved 65 registered students while the control group has 64 registered students. To determine the level of motivation of students in learning physics, the Physics Motivation Questionnaire was administered. On the other hand, to determine the level of Physics anxiety of the students in each group, Physics Anxiety Rating Scale was used. Peer Instruction supplemented with PhET simulations was implemented in the experimental group while the traditional lecture method was used in the control group. Both instruments were again administered after the implementation of the two different teaching approaches. “Wilcoxon Signed Rank test” was used to test the significant difference between pretest and posttest of each group. “Mann Whitney U” was used to test if significant differences exist between each group before and after instruction. Results showed that there is no significant difference between the level of motivation and anxiety of the experimental and control group before the implementation at p<0.05 significance level. It implies that the students have the same level of motivation and physics anxiety before instruction. However, the results of both tests have significant differences between the groups after instruction. It is also found that there is a significant positive change in the responses of the students in the experimental group while no change was evident on the control. The result of the analysis of the Mann Whitney U shows that the change in the attributes of the students is caused by the treatment. Therefore, it is concluded that Peer Instruction and PhET simulation helped in alleviating motivation of students and minimizing their anxiety towards Physics.

Keywords: anxiety, motivation, peer instruction, PhET simulations

Procedia PDF Downloads 348
1120 Guard@Lis: Birdwatching Augmented Reality Mobile Application

Authors: Jose A. C. Venancio, Alexandrino J. M. Goncalves, Anabela Marto, Nuno C. S. Rodrigues, Rita M. T. Ascenso

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Nowadays, it is common to find people who are concerned about getting away from the everyday life routine, looking forward to outcome well-being and pleasant emotions. Trying to disconnect themselves from the usual places of work and residence, they pursue different places, such as tourist destinations, aiming to have unexpected experiences. In order to make this exploration process easier, cities and tourism agencies seek new opportunities and solutions, creating routes with diverse cultural landmarks, including natural landscapes and historic buildings. These offers frequently aspire to the preservation of the local patrimony. In nature and wildlife, birdwatching is an activity that has been increasing, both in cities and in the countryside. This activity seeks to find, observe and identify the diversity of birds that live permanently or temporarily in these places, and it is usually supported by birdwatching guides. Leiria (Portugal) is a well-known city, presenting several historical and natural landmarks, like the Lis river and the castle where King D. Dinis lived in the 13th century. Along the Lis River, a conservation process was carried out and a pedestrian route was created (Polis project). This is considered an excellent spot for birdwatching, especially for the gray heron (Ardea cinerea) and for the kingfisher (Alcedo atthis). There is also a route through the city, from the riverside to the castle, which encloses a characterized variety of species, such as the barn swallow (Hirundo rustica), known for passing through different seasons of the year. Birdwatching is sometimes a difficult task since it is not always possible to see all bird species that inhabit a given place. For this reason, a need to create a technological solution was found to ease this activity. This project aims to encourage people to learn about the various species of birds that live along the Lis River and to promote the preservation of nature in a conscious way. This work is being conducted in collaboration with Leiria Municipal Council and with the Environmental Interpretation Centre. It intends to show the majesty of the Lis River, a place visited daily by several people, such as children and families, who use it for didactic and recreational activities. We are developing a mobile multi-platform application (Guard@Lis) that allows bird species to be observed along a given route, using representative digital 3D models through the integration of augmented reality technologies. Guard@Lis displays a route with points of interest for birdwatching and a list of species for each point of interest, along with scientific information, images and sounds for every species. For some birds, to ensure their observation, the user can watch them in loco, in their real and natural environment, with their mobile device by means of augmented reality, giving the sensation of presence of these birds, even if they cannot be seen in that place at that moment. The augmented reality feature is being developed with Vuforia SDK, using a hybrid approach to recognition and tracking processes, combining marks and geolocation techniques. This application proposes routes and notifies users with alerts for the possibility of viewing models of augmented reality birds. The final Guard@Lis prototype will be tested by volunteers in-situ.

Keywords: augmented reality, birdwatching route, mobile application, nature tourism, watch birds using augmented reality

Procedia PDF Downloads 164
1119 Predicting the Next Offensive Play Types will be Implemented to Maximize the Defense’s Chances of Success in the National Football League

Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

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1118 Feature Analysis of Predictive Maintenance Models

Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

Procedia PDF Downloads 122
1117 Non-Linear Assessment of Chromatographic Lipophilicity and Model Ranking of Newly Synthesized Steroid Derivatives

Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 313