Search results for: embedded learning support

Authors: Lisandro Blas, Héctor Tamanini

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From earliest 90 to now, no many companies or organization can “really” implement a knowledge management (KM) system that works (no only viewed from a measurement model, but in this continuity). Which are the reasons of that? Some of the reason maybe could be embedded in how KM is demanded (usefulness, priority, experts, a definition of KM) vs the importance and resources that the organizations afford (budget, responsible of a specific area of KM, intangibility). Many organizations “claim” the importance of Knowledge Management but thhese demands are not reflecting these claims in their future actions. With another’s tools or managements ideas the organizations put the economics and human resources to work. Why it´s not occur in KM? This paper tray to explain some of this reasons and tray to deal with this situations through a survey done in 2011 for a IAPG (Argentinean Institute from Oil & Gas) Congress.

Keywords: knowledge management into organizations, new perspectives, failure in implementation, claim

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Authors: Akiko Kondo

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Although the effects of working memory capacity on second/foreign language speaking skills have been researched in depth, few studies have focused on Japanese English as a foreign language (EFL) learners as compared to other languages (Indo-European languages), and the sample sizes of the relevant Japanese studies have been relatively small. Furthermore, comparing the effects of working memory capacity and motivation which is another kind of frequently researched individual factor on L2 speaking skills would add to the scholarly literature in the field of second language acquisition research. Therefore, the purposes of this study were to investigate whether working memory capacity and motivation have significant relationships with Japanese EFL learners’ speaking skills and to investigate the degree to which working memory capacity and motivation contribute to their English speaking skills. One-hundred and ten Japanese EFL students aged 18 to 26 years participated in this study. All of them are native Japanese speakers and have learned English as s foreign language for 6 to 15. They completed the Versant English speaking test, which has been widely used to measure non-native speakers’ English speaking skills, two types of working memory tests (the L1-based backward digit span test and the L1-based listening span test), and the language learning motivation survey. The researcher designed the working memory tests and the motivation survey. To investigate the relationship between the variables (English speaking skills, working memory capacity, and language learning motivation), a correlation analysis was conducted, which showed that L2 speaking test scores were significantly related to both working memory capacity and language learning motivation, although the correlation coefficients were weak. Furthermore, a multiple regression analysis was performed, with L2 speaking skills as the dependent variable and working memory capacity and language learning motivation as the independent variables. The results showed that working memory capacity and motivation significantly explained the variance in L2 speaking skills and that the L2 motivation had slightly larger effects on the L2 speaking skills than the working memory capacity. Although this study includes several limitations, the results could contribute to the generalization of the effects of individual differences, such as working memory and motivation on L2 learning, in the literature.

Keywords: individual differences, motivation, speaking skills, working memory

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Authors: Monojit Manna, Arpan Adhikary

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In Mobile cloud sensing across the globe, an emerging paradigm is selected by the user to compute sensing tasks. In urban cities current days, Mobile vehicles are adapted to perform the task of data sensing and data collection for universality and mobility. In this work, we focused on the optimality and mobile nodes that can be selected in order to collect the maximum amount of data from urban areas and fulfill the required data in the future period within a couple of minutes. We map out the requirement of the vehicle to configure the maximum data optimization problem and budget. The Application implementation is basically set up to generalize a realistic online platform in which real-time vehicles are moving apparently in a continuous manner. The data center has the authority to select a set of vehicles immediately. A deep learning-based scheme with the help of mobile vehicles (DLMV) will be proposed to collect sensing data from the urban environment. From the future time perspective, this work proposed a deep learning-based offline algorithm to predict mobility. Therefore, we proposed a greedy approach applying an online algorithm step into a subset of vehicles for an NP-complete problem with a limited budget. Real dataset experimental extensive evaluations are conducted for the real mobility dataset in Rome. The result of the experiment not only fulfills the efficiency of our proposed solution but also proves the validity of DLMV and improves the quantity of collecting the sensing data compared with other algorithms.

Keywords: mobile crowdsensing, deep learning, vehicle recruitment, sensing coverage, data collection

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

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Authors: E. Ruíz, W. Aperador

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In this article evaluates the protective effect of the concrete alternative obtained from the fly ash and iron and steel slag mixed in binary form and were placed on structural steel ASTM A 706. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The effect of chloride ion on the specimens was generated of form accelerated under controlled conditions (3.5% NaCl and 25 ° C temperature). The Impedance data were acquired over a range of 1 mHz to 100 kHz. At frequencies high is found the response of the interface means of the exposure-concrete and to frequency low the response of the interface corresponding to concrete-steel.

Keywords: alternative concrete, corrosion, alkaline activation, impedance spectroscopy

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Authors: Muhammad A. Alsubaie

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An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

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Authors: Olugbade Damola, Adekomi Adebimbo, Sofowora Olaniyi Alaba

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One of the major problems facing education in Nigeria is the provision of quality Science and Technology education. Inadequate teaching facilities, non-usage of innovative teaching strategies, ineffective classroom management, lack of students’ motivation and poor integration of ICT has resulted in the increase in percentage of students who failed Basic Science and Technology in Junior Secondary Certification Examination for National Examination Council in Nigeria. To address these challenges, the Federal Government came up with a road map on education. This was with a view of enhancing quality education through integration of modern technology into teaching and learning, enhancing quality assurance through proper monitoring and introduction of innovative methods of teaching. This led the researcher to investigate how MOODLE LMS could be used to enhance students’ learning outcomes in BST. A sample of 120 students was purposively selected from four secondary schools in Ogbomoso. The experimental group was taught using MOODLE LMS, while the control group was taught using the conventional method. Data obtained were analyzed using mean, standard deviation and t-test. The result showed that MOODLE LMS was an effective learning platform in teaching BST in junior secondary schools (t=4.953, P<0.05). Students’ attitudes towards BST was also enhanced through MOODLE LMS (t=15.632, P<0.05). The use of MOODLE LMS significantly enhanced students’ retention (t=6.640, P<0.05). In conclusion, the Federal Government efforts at enhancing quality assurance through integration of modern technology and e-learning in Secondary schools proved to have yielded good result has students found MOODLE LMS to be motivating and interactive. Attendance was improved.

Keywords: basic science and technology, MOODLE LMS, performance, quality assurance

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Authors: E. Didaskalou, C. Roussi-Vergou, E. Andreou, G. Skrzypiec, P. Slee

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There has been growing interest lately, in the study of victimization among adolescent students in Greece and elsewhere with a view to improve school policies concerning anti-bullying practices. Researchers have recently focused on investigating the relationships between the extent of students’ victimization and the distinct mechanisms that they employ for coping with this particular problem. In particular, the emphasis has been placed on exploring the relationship between the coping strategies students use to counteract bullying, their sense of belonging at school, and extent of their victimization. Methods: Within the research framework outlined above, we set out to: a) examine the frequency of self-reported victimization among secondary school students, b) investigate the coping strategies employed by students when confronted with school bullying and c) explore any differences between bullied and non-bullied students with regard to coping strategies and school belongingness. The sample consisted of 860 from fifteen secondary public schools in central Greece. The schools were typical Greek secondary schools and the principals volunteered to participate in this study. Participants’ age ranged from 12 to 16 years. Measures: a) Exposure to Victimization: The frequency of victimization was directly located by asking students the question: ‘Over the last term, how often have you been bullied or harassed by a student or students at this high school?’ b) Coping Strategies: The ‘Living and Learning at School: Bullying at School’ was administered to students, c) School belongingness was assessed by the Psychological Sense of School Membership Scale, that students completed. Results: Regarding the frequency of self-reported victimization, 1.5% of the students reported being victimized every day, 2.8% most days of the week, 2.1% one or more days a week, 2.9% about once a week, 22.6% less than once a week and 68.1% never. The coping strategies that the participants employed for terminating their victimization included: a) adult support seeking, b) emotional coping/keep away from school, c) keeping healthy and fit, d) demonstrating a positive attitude towards the bully, d) peer support seeking, e) emotional out bursting, f) wishful thinking and self-blaming, g) pretending as if it is not happening, h) displaying assertive behaviors and i) getting away from the bullies. Bullied from non-bullied children did not differ as much in coping, as in feelings of being rejected in school. Discussion: The findings are in accordance with accumulated research evidence which points to a strong relationship between student perceptions of school belongingness and their involvement in bullying behaviors. We agree with the view that a positive school climate is likely to serve as a buffer that mitigates wider adverse societal influences and institutional attitudes which favor violence and harassment among peers.

Keywords: school bullying, school belonging, student coping strategies, victimization

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Authors: Olga Giovani

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In this research, Bronfenbrenner's theory will be used to investigate the individual, microsystemic, and exosystemic factors that may affect adolescents' academic achievement as well as their expectations in Greece. First, the topic of academic achievement in an adolescent developmental context will be set as the target of the proposed study while focusing on the aspects of community influences on adolescents. More specifically, the effect of available resources and the perceived sense of safety and support will be further investigated. Then the issue of family factors will be analyzed, as they are subjectively perceived by the adolescents, focusing on the perceived parental style, parental monitor, and involvement as a mesosystemic factor. In turn, the school will also be discussed with emphasis on the perceived school climate and support as well as the academic aspects of student achievement. Finally, the adolescent's individual perspective will be taken into consideration in developmental terms, examining their perceptions regarding their community/neighborhood, their family, their school, as well as their sense of self-concept and self-esteem as these are expressed through their academic performance and prosocial behavior. The aim of the proposed research is to study these associations through the prism of the systemic perspective, the relationship between aspects of educational achievement and socioeconomic background, with an emphasis on the role of the community, which has not been adequately researched in the Greek context. Community will be defined by the available community resources (recreational activities, public library, local orchestras, free entrance museums, etc.), adolescents' own perception of social support, safety, and support inside that community. These perceptions need to be investigated since they may serve as possible predictors of a child's current cognitive, developmental, and psycho-social outcomes, such as their perceived self-concept and self-esteem, as well as on their future expectations related to the entrance to university and job expectations.

Keywords: bioecological model, developmental psychology, ecosystemic approach, student achievement, microsystemic factors, mesosystemic factors, individual perceptions

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Authors: Loo Fung Ying, Loo Fung Chiat

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The formation of a musical identity that shapes the nation in this multiracial country reveals many complexities, conundrums, and contingencies. Creativity and identity formation at the level of an individual or a collective group further diversified musical expression, representation, and style, which has led to an absence of regularities. In addition, ‘contemporizing accretion,’ borrowing a term used by Schnelle in theology (2009), further complicates musical identity, authenticity, conception, and realization. Thus, in this paper, we attempt to define the issues surrounding the teaching and learning of the multiracial Malaysian national music identity. We also discuss unnecessary power hierarchies, interracial conflicts, and sentiments in the construct of a multiracial national music identity by referring to genetic origins, the evolution of music, and the neglected issues of representation and reception at a global level from a diachronic perspective. Lastly, by synthesizing Ladson-Billings, Gay, Kruger, and West-Burns’s culturally relevant/responsive pedagogical theories, we discuss possible analytic tools for consideration that are more multiculturally relevant and responsive for the teaching, learning, and construction of a multiracial Malaysian national music identity.

Keywords: Malaysia, music, multiracial, national music identity, culturally relevant/responsive pedagogy

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Supranee Wattanasin

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The objectives of this research are to find and collect the knowledge in order to transmit the food wisdom of Salaya community. The research is qualitative tool to gather the data. Phase 1: Collect and analyze related literature review on food wisdom including documents about Salaya community to have a clear picture on Salaya community context. Phase 2: Conduct an action research, stage a people forum to exchange knowledge in food wisdom of Salaya community. Learning stage on cooking, types, and benefits of the food wisdom of Salaya community were also set up, as well as a people forum to find ways to transmit and add value to the food wisdom of Salaya community. The result shows that Salaya old market community was once a marketplace located by Mahasawat canal. The old market had become sluggish due to growing development of land transportation. This had affected the ways of food consumption. Residents in the community chose 3 menus that represent the community’s unique food: chicken green curry, desserts in syrup and Khanom Sai-Sai (steamed flour with coconut filling). The researcher had the local residents train the team on how to make these meals. It was found that people in the community transmit the wisdom to the next generation by teaching and telling from parents to children. ‘Learning through the back door’ is one of the learning methods that the community used and still does.

Keywords: transmission, food wisdom, Salaya, cooking

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Authors: K. Durairaj, I. N. Umar

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Lately, asynchronous discussion forum is integrated in higher educational institutions as it may increase learning process, learners’ understanding, achievement and knowledge construction. Asynchronous discussion forum is used to complement the traditional, face-to-face learning session in hybrid learning courses. However, studies have proven that students’ engagement in online forum are still unconvincing. Thus, the aim of this study is to investigate the motivating factors and obstacles that affect the learners’ engagement in asynchronous discussion forum. This study is carried out in one of the public higher educational institutions in Malaysia with 18 postgraduate students as samples. The authors have developed a 40-items questionnaire based on literature review. The results indicate several factors that have encouraged or limited students’ engagement in asynchronous discussion forum: (a) the practices or behaviors of peers, or instructors, (b) the needs for the discussions, (c) the learners’ personalities, (d) constraints in continuing the discussion forum, (e) lack of ideas, (f) the level of thoughts, (g) the level of knowledge construction, (h) technical problems, (i) time constraints and (j) misunderstanding. This study suggests some recommendations to increase the students’ engagement in online forums. Finally, based upon the findings, some implications are proposed for further research.

Keywords: asynchronous discussion forum, engagement, factors, motivating, limiting

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Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

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The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

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Authors: Eddiebal P. Layco

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The purpose of this study is to describe students' virtual classroom relationships in terms of their relationship to their peers and teachers; academic resilience; and performance. Further, the researcher wants to examine if these virtual classroom relations predict students' resilience and performance in their academics. The data were collected from 720 junior and senior high school or grade 7 to 12 students in selected state universities and colleges (SUCs) in Region III offering online or virtual classes during S.Y. 2020-2021. Results revealed that virtual classroom relationships such as teacher-student and peer relationships predict academic resilience and performance. This implies that students' academic relations with their teachers and peers have something to do with their ability to bounce back and beat the odds amidst challenges they faced in the online or virtual learning environment. These virtual relationships significantly influence also their academic performance. Adequate teacher support and positive peer relations may lead to enhanced academic resilience, which may also promote a meaningful and fulfilled life academically. Result suggests that teachers should develop their students' academic resiliency and maintain good relationships in the classroom since these results in academic success.

Keywords: virtual classroom relationships, teacher-pupil relationship, peer-relationship, academic resilience, academic performance

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Nadia Nisha Musa, Nur Atirah Hasmi, Hasnun Nita Ismail, Zulfadli Mahfodz

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In Malaysian Education System, subject related to biodiversity has started in the curriculum from Foundation Study until tertiary education. Biodiversity become the focus of attention due to awareness on global warming which potentially leads to a loss of biodiversity. A loss in biodiversity means a loss in medicinal discoveries and reduces food supply. It is of great important to ensure that young generations become aware of biodiversity conservation. The more interactive approaches are needed to build society with a high awareness for biodiversity conservation. To address this challenge, the goal of this study is to enhance intrinsic motivation of biological students via ARCS model of instruction. Self-access learning materials such as tutorial, module and fieldwork were designed with ARCS elements to a sample size of 70 university students from the beginning of the semester. Both paper and online surveys were used to collect data from the respondents. The results showed that elements of attention, relevance, confidence and satisfaction have a positive impact on intrinsic motivation of students and their academic performance.

Keywords: intrinsic motivation, ARCS model of instruction, biodiversity, self-access learning

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Authors: Sonia Saddiqui, Maya Marcus

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UTS STEAMpunk Girls is an educational program for young women (aged 12-16), to empower them to be more informed and active members of the 21st century workforce. With the number of STEM graduates on the decline, especially among young women, an additional aim of the program is to trial a STEAM (Science, Technology, Engineering, Arts/Humanities/Social Sciences, Mathematics), inter-disciplinary approach to improving STEM engagement. In-line with UNESCO’s recent focus on promoting ‘transversal competencies’ in future graduates, the program utilised co-design, project-based learning, entrepreneurial processes, and inter-disciplinary learning. The program consists of two phases. Taking a participatory design approach, the first phase (co-design workshops) provided valuable insight into student perspectives around engaging young women in STEM and inter-disciplinary thinking. The workshops positioned 26 young women from three schools as subject matter experts (SMEs), providing a platform for them to share their opinions, experiences and findings around the STEAM disciplines. The second (pilot) phase put the co-design phase findings into practice, with 64 students from four schools working in groups to articulate problems with real-world implications, and utilising design-thinking to solve them. The pilot phase utilised project-based learning to engage young women in entrepreneurial and STEAM frameworks and processes. Scalable program design and educational resources were trialed to determine appropriate mechanisms for engaging young women in STEM and in STEAM thinking. Across both phases, data was collected via longitudinal surveys to obtain pre-program, baseline attitudinal information, and compare that against post-program responses. Preliminary findings revealed students’ improved understanding of the STEM disciplines, industries and professions, improved awareness of STEAM as a concept, and improved understanding regarding inter-disciplinary and design thinking. Program outcomes will be of interest to high-school educators in both STEM and the Arts, Humanities and Social Sciences fields, and will hopefully inform future programmatic approaches to introducing inter-disciplinary STEAM learning in STEM curriculum.

Keywords: co-design, STEM, STEAM, project-based learning, inter-disciplinary

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Authors: Tesfahiwot Abay Weldearegay

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Ethiopian Federal ministry of health, in collaboration with different partners, provides financial support from sustainable development grants and global fund budget sources to Regional health science colleges through the regional health bureau to improve the quality of training and avail professionals based on the regional health bureau demand from the year of 2012 to 2019EC. It was mainly focused on health extension workers (HEW) Level III&IV, Health Information technicians (HIT), Emergency Medical technicians (EMT), laboratory technicians, Pharmacy technicians, Anesthesia Level V, Radiography, midwifery, Environmental health and biomedical equipment technician. Laboratory technician, Radiography and Pharmacy technician, was retooling program. The study aims at assessing the Utilization and outcome of budgets transferred through regional health bureau to regional health science colleges. The study used both quantitative and qualitative approaches to develop sufficient data to explain the utilization of the budget, and outcomes obtained from the transferred budget and to identify the gaps. The data for the study were obtained through structured questionnaires and interviews was conducted to increase the reliability of the data. Nationally, students enrolled in different disciplines at RHSC through budget support for RHB to improve the quality of training were 87 840 students and the total Budget transferred, according to MOU was 895,752,038 Ethiopian birr. Among the students enrolled nationally in different disciplines at RHSC through budget support only 72% of students have graduated from different disciplines. In Hareri and Addis Ababa, all enrolled students were graduated (100%). At the same time, Oromia 69%, Amara 77%, SNNP 58% students graduated, respectively. The demand of the regional health bureau and the enrollment capacity of health science colleges increased from year to year. The financial support added great value to the HSCs to cop with problems related to student fees, skill lab materials and renovation.

Keywords: emergency medical technician, radiography, Biomedical, health extension

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Authors: Sehreen Moorat, Hiba, Maham Mahnoor, Faryal Soomro

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Leakage of gases in a system makes infrastructures and users vulnerable; it can occur due to its environmental conditions or old groundwork. In hospitals and industries, it is very important to detect any small level of gas leakage because of their sensitivity. In this research, a portable detection system for the small leakage of gases has been developed, gas sensor (MQ-2) is used to find leakage when it’s at its initial phase. The sensor and transmitting module senses the change in level of gas by using a sensing circuit. When a concentration of gas reach at a specified threshold level, it will activate an alarm and send the alarming situation notification to receiver through GSM module. The proposed system works well in hospitals, home, and industries.

Keywords: gases, detection, Arduino, MQ-2, alarm

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Authors: Amina El-Warari, Agata Vitale, Laura Caulfield, Jennifer Kinloch

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Background: Unemployment levels among refugees in the UK are much higher than voluntary migrants and UK-born citizens. The lack of employment and/or of suitable employment has detrimental consequences on refugees’ ability to integrate and become active citizens in the host country. Research indicates that, when individuals are forced to migrate, one of the most significant aspects to building their identity is their previous profession; this particularly applies to qualified refugees. Despite this, there is little support available to them. The current study is set in this context and aims to explore highly qualified refugees’ employment-related experiences in the UK as well as their suggestions on how to develop specific interventions that can support them in finding suitable employment. Methods: A qualitative study design was employed. Qualitative methods are in fact well suited to research with refugees, as they allow them to give their direct opinion, rather than this being filtered by stakeholders. Listening to ‘the refugee’s voice’ means developing ‘a refugee centered perspective’ where the diverse narratives told by participants are organized to tell their direct collective story. A total of 12 refugees, attending a non-profit refugee organization in the south-west of England, took part in the study. The selection criteria were being over 18, having a level of English that allows them to sustain a conversation, and having a University degree and/or professional qualification. All participants were interviewed individually; the data were transcribed and analyzed thematically. Findings: Participants had very little support in finding suitable employment; this often only consisted of a few sessions in their local job centers and English tutorials. They indicated that being unemployed/underemployed negatively affected their sense of identity, their acculturative stress, and their in-group/ out-group relations. They suggested that specific employment interventions for qualified refugees should be delivered to them individually in order to address their specific needs. Furthermore, most participants suggested that these interventions should support them in volunteering in organizations that match their skills/ qualifications. They also indicated that the employment interventions should support them in having their qualifications recognized in the UK as well as building links with universities/ centers where they can receive adequate training on how to understand and adapt to the employments needs in the UK. Conclusions: These findings will provide the basis for the second stage of the research where specific employment interventions will be designed and tested with highly qualified refugees. In addition, these findings shed light refugee integration policy.

Keywords: employment interventions, identity, integration, qualified refugees

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Authors: Babatunde Kasim Oladele

Abstract:

This current study investigated students’ characteristics as factors that influence Mathematics Achievement of junior secondary school students. The study adopted a descriptive survey design. The population of the study was one hundred and twenty-three (123) JSS students of secondary schools in Ibadan North Local Government in Oyo State. A Mathematics achievement test and three questionnaires on student’s self-efficacy belief, attitude, and learning style were the instruments used. Prior to the administration of the constructed mathematics achievement test, 100-item mathematics was subjected to the expert review, and items analysis was carried out. Fifty items were retained. The Cronbach Alpha reliability coefficients of the instruments were 0.71, 0.76, and 0.83, respectively. Collected data were analysed using the frequency count, percentages, mean, standard deviation, and Path Analysis in Amos SPSS Version 20. Students characteristics: gender, age, self-efficacy, attitude and learning style had positive direct effects on students’ achievement in Mathematics as indicated by their respective beta weights (β = 0.36, 0.203, 0.92, 0.079, 0.69 p < 0.05). Consequently, the study concluded that student’s characteristics (Age, gender, and learning style) explained a significant part of the variability in students’ achievement in Mathematics.

Keywords: mathematics achievement, students’ characteristics, junior secondary school, Ibadan

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Authors: Ben D. Atkins

Abstract:

This study will examine the impact of September 11, 2001, terrorist attacks on the organizational development of American federal law enforcement through focusing on the Federal Bureau of Investigation. Content analysis of discourse in a federal law enforcement practitioner publication along with official FBI statements will be used to gain a better understanding of FBI organizational changes that have taken place since the events of September 11, 2001. Analysis of content trends in the FBI Law Enforcement Bulletin and public discourse of FBI officials from 1999 to 2005 indicate that, in addition to structural changes, the bureau has also undergone a variety of cultural changes. The results offer some support for the institutional theoretical perspective, suggesting that post-9/11 organizational changes such as new mission priorities and the establishment of new branches were partially initiated due to a variety external pressures, which lends support for coercive isomorphism. Furthermore, structural changes are discussed in relation to the attainment and maintenance of organizational legitimacy.

Keywords: institutional theory, organizational theory, law enforcement, public administration

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Authors: Zayen Chagra

Abstract:

Several educational institutions are experimenting new approaches in learning in order to guarantee the success of its students. In Tunisia, and since 2011, the experience of making a new software engineering branch called mobile software engineering began at ESPRIT: Higher School of Engineering and Technology. The project was surprisingly a success since its creation, and even before the graduation of the first generation, partnerships were held with the biggest mobile technology manufacturers and several international awards were won by teams of students. This session presents this experience with details of the approaches made from idea stage to the actual stage where the project counts 32 graduated engineers, 90 graduate students and 120 new participants.

Keywords: innovation, education, engineering education, mobile

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Authors: Yang Yang, Dan Liu

Abstract:

Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Abdelbasit Gadour

Abstract:

This study explores the function of schools’ psychosocial services within Libyan mainstream schools in relation to children’s special educational needs (SEN). This is with the aim to examine the role of school social workers and psychologists in the assessment procedure of children with special educational needs. A semi-structured interview was used in this study, with 21 professionals working in the schools’ psychosocial services, of whom thirteen were school social workers (SSWs) and eight were school psychologists (SPs). The results of the interviews with SSWs and SPs provided insights into how SEN children are identified, assessed, and dealt with by school professionals. It appears from the results that what constitutes a problem has not changed significantly, and the link between learning difficulties and behavioral difficulties is also evident from this study. Children with behavior difficulties are more likely to be referred to school psychosocial services than children with learning difficulties. Yet, it is not clear from the interviews with SSWs and SPs whether children are excluded merely because of their behavior problems. Instead, they would surely be expelled from the school if they failed academically. Furthermore, the interviews with SSWs and SPs yield a rather unusual source accountable for children’s SEN; school-related difficulties were a major factor in which almost all participants attributed children’s learning and behavior problems to teachers’ deficiencies, followed by school lack of resources.

Keywords: psychologist, school, social workers, special education

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Authors: Mahathir Sarjan, Ramos Radzly, Noor Baiti Jamaluddin, Mohd Hafiz Zakaria, Hisham Suhadi

Abstract:

Creativity is marked by the ability or power, to produce through imaginative skill and create something anew. The University is one of the great places to improve the talent in imaginative skill. Thus, it is important that for the student have a creativity to adapt the multimedia element in the development of presentation products for learning and teaching the process. The purpose of this study was to identify a creativity of the student in presentation product development. Two hundred seventeen Technical and Vocational Education (TVE) students in Universiti Tun Hussein Onn had chosen as a respondent. This study is to survey the level of creativity which is focused on knowledge, skills, presentation style and character of creative personnel. The level of creativity was measured based on the scale at low, medium and high followed by mean score level. The data collected by questionnaire then analyzed using SPSS version 20.0. The result of the study indicated that the students showed a higher of creativity (mean score in Knowledge = 4.12 and Skills= 4.02). In conjunction with the findings s implications and recommendations were suggested forward like to ensconce the research and improve with a more creativity concept in presentation product of development for learning and teaching the process.

Keywords: creativity, technical, vocational education, presentation products and development for learning and teaching process

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Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Aswathy Sampath

Abstract:

The study examined the levels of self esteem and attachment among adolescents of divorced and non-divorced parents. Adolescent is a period which is most prodigious yet stressful period of development in a human’s life hence it is important to study the effects on them. The study was conducted on total 60 adolescents, 30 in each group, from the area of Trivandrum, Kerala as it is the top rated in the number of divorce cases in India. The data was collected using Rosenberg’s self esteem scale and IPPA (father, mother and peer) The results of this study were analyzed using t test and found that there is no significance difference in the level of self esteem and attachment (father, mother and peer). This is due to the cultural elements that give support to the individual and also the type of family as it is much different from the west. Although, there was no significant result, there were higher mean scores in the attachment towards peer for children who are from separated family background or in other words adolescents whose parents were divorced. This tells us the essence of social support.

Keywords: adolescent, attachment, self esteem, separation

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