Search results for: autonomous learning system

Authors: Valerie Triggs, Michele Sorensen

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As two university professors in postsecondary faculties of social work and education, we have observed that students often recognize the importance of learning facts about colonization but have difficulty grappling with how they themselves might be implicated in reconciliation or how they might respond to these facts in meaningful ways. The detachment observed between students and factual information results in the initiation of a research study centered around an approach to teaching the course. This involved transitioning its pedagogical format to embrace a/r/tographic methods of teaching, learning, and inquiry. By taking seriously the arguments of various Indigenous scholars for learning from the land and by working alongside traditional Indigenous knowledge, we chose to engage a speculative approach to course design and teaching, which actually used the land as one of the course texts. We incorporated art practices that involved connecting bodies with land as well as using land materials in various creative and aesthetic projects while being informed by Medicine Keepers, Indigenous and settler artists, and knowledge-keeper helpers. In this study, we share some of the unanticipated themes that arose when students began to allow land and artmaking, both aesthetically and intuitively, through both joy and sorrow, to affect a reimagining and repositioning of selves and relations. We found that time and engagement with land and art began to build more empathic understanding and foster personal and professional practices grounded in respect, relevance, reciprocity, and responsibility.

Keywords: reconciliation, decolonization, artmaking, respect

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Authors: Na Li, Yunwei Zhang, Yuhong Niu

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The study discussed the patent protections of health system and enterprises in Shanghai. The comparisons of technical distribution and scopes of patent protections between Shanghai health system and enterprises were used by the methods of IPC classification, co-words analysis and visual social network. Results reflected a decreasing order within IPC A61 area, namely A61B, A61K, A61M, and A61F. A61B required to be further investigated. The highest authorized patents A61B17 of A61B of IPC A61 area was found. Within A61B17, fracture fixation, ligament reconstruction, cardiac surgery, and biopsy detection were regarded as common concerned fields by Shanghai health system and enterprises. However, compared with cardiac closure which Shanghai enterprises paid attention to, Shanghai health system was more inclined to blockages and hemostatic tools. The results also revealed that the scopes of patent protections of Shanghai enterprises were relatively centralized. Shanghai enterprises had a series of comprehensive strategies for protecting core patents. In contrast, Shanghai health system was considered to be lack of strategic patent protections for core patents.

Keywords: co-words analysis, IPC classification, patent protection, technical distribution

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Authors: Ehsan Soleymaninejadian

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As the field of immunology is growing day by day, and its chaotic system amazes more people, greed of research in this area is growing; however dealing with human or mammalian cells such as mice make the research expensive. Although there are some differences between higher animals with insects, importance of innate immunity during evolution made it untouched. So, for understanding the innate immunity insects can be good models. They are cheap; reproduction is fast and in the case genetics, less complicated. In this review, we tried to briefly tackle with important factors in insects’ innate immunity such as melanization, encapsulation, JAK-STAT, IMD, and Toll pathways. At the end, we explained how hormones and nerve system also can impact on immune system and make it more beautiful. In concluding remarks, the possibility of taking help from insect immune system to fight against diseases such as cancer has been considered.

Keywords: insects, innate immunity, melanization, intracellular pathways, hormones

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Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy

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Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.

Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink

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Authors: Obi Olor, Asu-Nnandi Judith, Ishiekwen Bridget

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Regardless of the settled perception that the substitution of saturated fats for starches or unsaturated fats builds low-density lipoprotein (LDL) cholesterol in people, in animal models, the relationship of saturated fat intake to the hazard of atherosclerotic cardiovascular ailment in people remains controversial. Clinical trials that supplanted immersed fat with polyunsaturated fat have, for the most part, demonstrated a lessening in CVD occasions, albeit a few reviews demonstrated no impacts. An autonomous relationship of soaked fat admission with CVD chance has not reliably appeared in planned epidemiologic reviews, albeit some have confirmed an expanded hazard in youthful people and in ladies. Substitution of soaked fat by polyunsaturated or monounsaturated fat reduces LDL and HDL cholesterol. Given the differing qualities of these cardio-protective eating methodologies and their healthy parts, one of the needs in research should be to attempt more near trials. These trials decide persistent worthiness, consequences for surrogate markers of hazard, and which at last affects morbidity and mortality.

Keywords: cardiovascular disease, dietary saturated fat, saturated fat, unsaturated fat

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Caje F. Pinto, Jivan S. Parab, Gourish M. Naik

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This paper is about the development of non-invasive heart rate and oxygen saturation in human blood using Altera NIOS II soft-core processor system. In today's world, monitoring oxygen saturation and heart rate is very important in hospitals to keep track of low oxygen levels in blood. We have designed an Embedded System On Peripheral Chip (SOPC) reconfigurable system by interfacing two LED’s of different wavelengths (660 nm/940 nm) with a single photo-detector to measure the absorptions of hemoglobin species at different wavelengths. The implementation of the interface with Finger Probe and Liquid Crystal Display (LCD) was carried out using NIOS II soft-core system running on Altera NANO DE0 board having target as Cyclone IVE. This designed system is used to monitor oxygen saturation in blood and heart rate for different test subjects. The designed NIOS II processor based non-invasive heart rate and oxygen saturation was verified with another Operon Pulse oximeter for 50 measurements on 10 different subjects. It was found that the readings taken were very close to the Operon Pulse oximeter.

Keywords: heart rate, NIOS II, oxygen saturation, photoplethysmography, soft-core, SOPC

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Authors: Nazym Zhumabayeva, Aleksandr Mezin, Alexandra Knysheva

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Women's underrepresentation in STEM is critical, worsened by ineffective engagement in educational practices. UNICEF Kazakhstan and GameLab KBTU's collaborative initiatives aim to enhance female STEM participation by fostering an inclusive environment. Learning from LEVEL UP's 2023 program, which featured a hackathon, the 2024 strategy pivots towards non-competitive gamification. Although the data from last year's project showed higher than average student engagement, observations and in-depth interviews with participants showed that the format was stressful for the girls, making them focus on points rather than on other values. This study presents a gamified educational system, DPG Lab, aimed at incentivizing young women's participation in STEM through the development of digital public goods (DPGs). By prioritizing collaborative gamification elements, the project seeks to create an inclusive learning environment that increases engagement and interest in STEM among young women. The DPG Lab aims to find a solution to minimize competition and support collaboration. The project is designed to motivate female participants towards the development of digital solutions through an introduction to the concept of DPGs. It consists of a short online course, a simulation videogame, and a real-time online quest with an offline finale at the KBTU campus. The online course offers short video lectures on open-source development and DPG standards. The game facilitates the practical application of theoretical knowledge, enriching the learning experience. Learners can also participate in a quest that encourages participants to develop DPG ideas in teams by choosing missions throughout the quest path. At the offline quest finale, the participants will meet in person to exchange experiences and accomplishments without engaging in comparative assessments: the quest ensures that each team’s trajectory is distinct by design. This marks a shift from competitive hackathons to a collaborative format, recognizing the unique contributions and achievements of each participant. The pilot batch of students is scheduled to commence in April 2024, with the finale anticipated in June. It is projected that this group will comprise 50 female high-school students from various regions across Kazakhstan. Expected outcomes include increased engagement and interest in STEM fields among young female participants, positive emotional and psychological impact through an emphasis on collaborative learning environments, and improved understanding and skills in DPG development. GameLab KBTU intends to undertake a hypothesis evaluation, employing a methodology similar to that utilized in the preceding LEVEL UP project. This approach will encompass the compilation of quantitative metrics (conversion funnels, test results, and surveys) and qualitative data from in-depth interviews and observational studies. For comparative analysis, a select group of participants from the previous year's project will be recruited to engage in the DPG Lab. By developing and implementing a gamified framework that emphasizes inclusion, engagement, and collaboration, the study seeks to provide practical knowledge about effective gamification strategies for promoting gender diversity in STEM. The expected outcomes of this initiative can contribute to the broader discussion on gamification in education and gender equality in STEM by offering a replicable and scalable model for similar interventions around the world.

Keywords: collaborative learning, competitive learning, digital public goods, educational gamification, emerging regions, STEM, underprivileged groups

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Authors: Sweta Sinha

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Rapid evolution of technology has changed language pedagogy as well as perspectives on language use, leading to strategic changes in discourse studies. We are now firmly embedded in a time when digital technologies have become an integral part of our daily lives. This has led to generalized approaches to English Language Teaching (ELT) which has raised two-pronged concerns in linguistically diverse settings: a) the diverse linguistic background of the learner might interfere/ intervene with the learning process and b) the differential level of already acquired knowledge of target language might make the classroom practices too easy or too difficult for the target group of learners. ELT needs a more systematic and differential pedagogical approach for greater efficiency and accuracy. The present research analyses the need of identifying learner groups based on different levels of target language proficiency based on a longitudinal study done on 150 undergraduate students. The learners were divided into five groups based on their performance on a twenty point scale in Listening Speaking Reading and Writing (LSRW). The groups were then subjected to varying durations of technology aided language learning sessions and their performance was recorded again on the same scale. Identifying groups and introducing differential teaching and learning strategies led to better results compared to generalized teaching strategies. Language teaching includes different aspects: the organizational, the technological, the sociological, the psychological, the pedagogical and the linguistic. And a facilitator must account for all these aspects in a carefully devised differential approach meeting the challenge of learner diversity. Apart from the justification of the formation of differential groups the paper attempts to devise framework to account for all these aspects in order to make ELT in multilingual setting much more effective.

Keywords: differential groups, English language teaching, language pedagogy, multilingualism, technology aided language learning

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Authors: Sebastián Olivares Lizana, Marianna Oyanedel González

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This study takes part of a major project based on implementing a CLIL program (Content and Language Integrated Learning) at Universidad Técnica Federico Santa María, a leading Chilean tertiary Institution. It aims at examining the relationship between the development of Reflective Processes (RP) and Cognitive Academic Language Proficiency (CALP) in weekly learning logs written by faculty members, participants of an initial professional development online course on English for Academic Purposes (EAP). Such course was designed with a genre-based approach, and consists of multiple tasks directed to academic writing proficiency. The results of this analysis will be described and classified in a scale of key indicators that represent both the Reflective Processes and the advances in CALP, and that also consider linguistic proficiency and task progression. Such indicators will evidence affordances and constrains of using a genre-based approach in an EFL Engineering CLIL program implementation at tertiary level in Chile, and will serve as the starting point to the design of a professional development course directed to teaching methodologies in a CLIL EFL environment in Engineering education at Universidad Técnica Federico Santa María.

Keywords: EFL, EAL, genre, CLIL, engineering

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Authors: Ann Dashwood

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Using Standard Australian English with confidence is a cultural expectation of parents of primary school aged children who want to engage effectively with their children’s teachers and school administration. That confidence in support of their children’s learning at school is seldom experienced by parents whose first language is not English. Sharing language with competence in an intercultural environment is the common denominator for meaningful communication and engagement to occur in a school community. Experience in relevant, interactive sessions is known to enhance engagement and participation. The purpose of this paper is to identify a pedagogy for parents otherwise isolated from daily use of functional Australian cultural language learned to engage effectively in their children’s learning at school. The outcomes measure parents’ intercultural engagement with classroom teachers and attention to the school’s administrative procedures using quantitative and qualitative methods. A principled communicative task-based language learning approach, combined with intercultural communication strategies provide the theoretical base for intensive English inquiry-based learning and engagement. The quantitative analysis examines data samples collected by classroom teachers and administrators and parents’ writing samples. Interviews and observations qualitatively inform the study. Currently, significant numbers of projects are active in community centers and schools to enhance English language knowledge of parents from Language Backgrounds Other Than English (LBOTE). The study is significant to explore the effects of an intensive English pedagogy with parents of varied English language backgrounds, by targeting inquiry-based language use for social interactions in the school and wider community, specific engagement and cultural interaction with teachers and school activities and procedures.

Keywords: engagement, intercultural communication, language teaching pedagogy, LBOTE, school community

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Authors: José L. Jiménez

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The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: digital tools, on-line learning, social networks, technology

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Authors: A. A. Hassani, M. Nasri Nasrabadi

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According to population growth and increasing water needs of industrial and agricultural sections and lack of existing water sources, also increases of wastewater and new wastewater treatment plant construction’s high costs, it is inevitable to reuse wastewater with the approach of increasing wastewater treatment capacity and output sewage quality. In this regard, the first sewage reuse plan in industrial uses was designed with the approach of qualitative and quantitative improvement due to the increased organic load of the output sewage of Qom Shokohieh city’s’ in wastewater treatment plant. This research investigated qualitative factors COD, BOD, TSS, TDS, and input and output heavy metal of MBR-RO system and ability of increase wastewater acceptance capacity by existing in wastewater treatment plant. For this purpose, experimental results of seven-month navigation system have been used from 07/01/2013 to 02/01/2014. Existing data analysis showed that MBR system is able to remove 93.2% COD, 94.4% BOD, 13.8% TDS, 98% heavy metals and RO system is able to remove 98.9% TDS. This study showed that MBR-RO integration system is able to increase the capacity of refinery by 30%.

Keywords: industrial wastewater, wastewater reuse, MBR, RO

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Authors: S. R. A. Rahim, I. Musirin, M. M. Othman, M. H. Hussain

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Loss minimization is a long progressing issue mainly in distribution system. Nevertheless, its effect led to temperature rise due to significant voltage drop through the distribution line. Thus, compensation scheme should be proper scheduled in the attempt to alleviate the voltage drop phenomenon. Distributed generation has been profoundly known for voltage profile improvement provided that over-compensation or under-compensation phenomena are avoided. This paper addresses the issue of voltage improvement through different type DG installation. In ensuring optimal sizing and location of the DGs, predeveloped EMEFA technique was made to be used for this purpose. Incremental loading condition subjected to the system is the concern such that it is beneficial to the power system operator.

Keywords: distributed generation, EMEFA, power loss, voltage profile

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Authors: E. J. Spamer, J. M. Van Zyl, MHA Combrinck

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The Unit for Open Distance Learning (UODL) at the North-West University (NWU), South Africa was established in 2013 with its main function to deliver open distance learning (ODL) programmes to approximately 30 000 students from the Faculties of Education Sciences, Health Sciences, Theology and Arts and Culture. Quality operational and administrative processes are key components in the delivery of these programmes and they need to function optimally for students to be successful in their studies. Operational and administrative processes include aspects such as applications, registration, dissemination of study material, availability of electronic platforms, the management of assessment, and the dissemination of important information. To be able to ensure and enhance quality during these processes, it is vital to determine students’ perceptions with regards to these mentioned processes. A questionnaire was available online and also distributed to the 63 tuition centres. The purpose of this research was to determine the perceptions of ODL students from NWU regarding operational and administrative processes. 1903 students completed and submitted the questionnaire. The data was quantitatively analysed and discussed. Results indicated that the majority of students are satisfied with the operational and administrative processes; however, the results also indicated some areas that need improvement. The data gathered is important to identify strengths and areas for improvement and form part of a bigger strategy of qualitative assurance at the UODL.

Keywords: administrative support, ODL programmes, quantitative study, students' perceptions

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Authors: Ivana Hrebickova, Maria Sevcikova, Romana Slamberova

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The present study was aimed at evaluation of cognitive changes following scheduled neonatal methamphetamine exposure in combination with long-term exposure in adulthood of female Wistar rats. Pregnant mothers were divided into two groups: group with indirect exposure (methamphetamine in dose 5 mg/ml/kg, saline in dose 1 ml/kg) during early lactation period (postnatal day 1–11) - progeny of these mothers were exposed to the effects of methamphetamine or saline indirectly via the breast milk; and the second group with direct exposure – all mothers were left intact for the entire lactation period, while progeny was treated with methamphetamine (5 mg/ml/kg) by injection or the control group, which was received needle pick (shame, not saline) at the same time each day of period of application (postnatal day 1–11). Learning ability and memory consolidation were tested in the Morris Water Maze, which consisted of three types of tests: ‘Place Navigation Test ‘; ‘Probe Test ‘; and ‘Memory Recall Test ‘. Adult female progeny were injected daily, after completion last trial with saline or methamphetamine (1 mg/ml/kg). We compared the effects of indirect/direct neonatal methamphetamine exposure and adult methamphetamine treatment on cognitive function of female rats. Statistical analyses showed that neonatal methamphetamine exposure worsened spatial learning and ability to remember the position of the platform. The present study demonstrated that direct methamphetamine exposure has more significant impact on process of learning and memory than indirect exposure. Analyses of search strategies (thigmotaxis, scanning) used by females during the Place Navigation Test and Memory Recall Test confirm all these results.

Keywords: methamphetamine, Morris water maze, neonatal exposure, strategies, Wistar rats

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

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Authors: Waqas A. Toor, Anis U. Baig, Nuaman Shafqat, Raafia Irfan, Muhammad Ashraf

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A 2.45GHz microwave plasma system and its few applications have been developed. Argon and helium plasma is produced by metallic nozzle and also in a quartz tube at atmospheric pressure, using WR-340 waveguide and its tapered version. The waveguide applicator is also simulated in HFSS and field patterns are analyzed for maximum power absorption in the load. The system is tuned to operate at less than 10% reflected power. Various experimental techniques are used to initiate and sustain the plasma at atmospheric pressure. Plasma of atmospheric air is also produced without using any other shielding gas. The plasma flame is also characterized by its spectrum. Spectral analyses of plasma flame can be used for online analysis of combustion gases produced in industry. The applications of the system include glass and quartz processing, vitrification, emission spectroscopy, plasma coating. Low pressure plasma applications of the system include intense UV light for water purification and ozone generation.

Keywords: HFSS high frequency structure simulator, Microwave plasma, UV ultraviolet, WR rectangular waveguide

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Authors: Hyeon-seoung Kim, Sang-mi Park, Sun-ju Han, Leen-seok Kang

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The visualization technology of construction information using 3D and nD modeling can satisfy the visualization needs of each construction project participant. The nD CAD system is a tool that the construction information, such as construction schedule, cost and resource utilization, are simulated by 4D, 5D and 6D object formats based on 3D object. This study developed a methodology and simulation engine for nD CAD system for construction project management. It has improved functions such as built-in schedule generation, cost simulation of changed budget and built-in resource allocation comparing with the current systems. To develop an integrated nD CAD system, this study attempts an integrated method to link 5D and 6D objects based on 4D object.

Keywords: building information modeling, visual simulation, 3D object, nD CAD augmented reality

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Authors: Yi-Ju Lee

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This study identified the hypothesised relationship between creative experience, and revisit intention of handmade oriental parasol umbrella in Kaohsiung, Taiwan. A face-to-face questionnaire survey was administered in Meinong town, Kaohsiung. The components of creative experience were found as “sense of achievement”, “unique learning” and “interaction with instructors” in creative tourism. The result also revealed significant positive relationships between creative experience and revisit intention in handmade activities. This paper provides additional suggestions for enhancing revisit intention and guidance regarding creative tourism.

Keywords: creative tourism, sense of achievement, unique learning, interaction with instructors, folk art

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Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

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Sub-Saharan Africa is described as the second fastest growing mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying various bills such as water, TV, and electricity. However, the potential of using mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS quizzes questions that were used to assess mastery of the subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of science and mathematics subjects. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. The results showed that chemistry and biology had better performance compared to mathematics and physics. Teachers reported some challenges that led to poor performance, invalid answers, and non-responses and they are presented. This research has several practical implications for those who are implementing or planning to use mobile phones for teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: mobile learning, elearning, educational technolgies, SMS, secondary education, assessment

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Alejandra Yanez, Teresa Benavides, Zita Lopez

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Even before COVID-19, one of the most important challenges that Higher Education faces today is the need for innovative educational methodologies and flexibility. We could all agree that one of the objectives of Higher Education is to provide students with a variety of intellectual and practical skills that, at the same time, will help them develop competitive advantages such as adaptation and critical thinking. Among the strategic objectives of Universidad de Monterrey (UDEM) has been to provide flexibility and satisfaction to students in the delivery modes of the academic offer. UDEM implemented a methodology that combines face to face with synchronous and asynchronous as delivery modes. UDEM goal, in this case, was to implement new technologies and different teaching methodologies that will improve the students learning experience. In this study, the experience of students during courses implemented in new delivery mode was compared with students in courses with traditional delivery modes. Students chose openly either way freely. After everything students around the world lived in 2020 and 2021, one can think that the face to face (traditional) delivery mode would be the one chosen by students. The results obtained in this study reveal that both delivery modes satisfy students and favor their learning process. We will show how the combination of delivery modes provides flexibility, so the proposal is that universities can include them in their academic offer as a response to the current student's learning interests and needs.

Keywords: flexibility, new delivery modes, student satisfaction, academic offer

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: J. R. Wang, Y. Chiang, W. Y. Li, H. T. Lin, H. C. Chen, C. Shih, S. W. Chen

Abstract:

The dry-storage systems of nuclear power plants (NPPs) in Taiwan have become one of the major safety concerns. There are two steps considered in this study. The first step is the verification of the TRACE by using VSC-17 experimental data. The results of TRACE were similar to the VSC-17 data. It indicates that TRACE has the respectable accuracy in the simulation and analysis of the dry-storage systems. The next step is the application of TRACE in the dry-storage system of Kuosheng NPP (BWR/6). Kuosheng NPP is the second BWR NPP of Taiwan Power Company. In order to solve the storage of the spent fuels, Taiwan Power Company developed the new dry-storage system for Kuosheng NPP. In this step, the dry-storage system model of Kuosheng NPP was established by TRACE. Then, the steady state simulation of this model was performed and the results of TRACE were compared with the Kuosheng NPP data. Finally, this model was used to perform the safety analysis of Kuosheng NPP dry-storage system. Besides, FRAPTRAN was used tocalculate the transient performance of fuel rods.

Keywords: BWR, TRACE, FRAPTRAN, dry-storage

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Authors: Ziyu Liu, Martin Buijsen

Abstract:

Although great achievements have been made since the beginning of the Chinese healthcare system reform in 1978, there still remain unresolved problems. Currently, the two leading social issues are accessibility and affordability of healthcare. Facing those challenges, Chinese government initiated the third round of healthcare system reform, accompanied by an array of measures. The newly launched strategies show a tendency to deliver healthcare as welfare goods, achieving equality through an ex-post perspective instead of an ex-ante view. However, if the reform efforts rely solely on the notion of “welfare”, the wrong idea of the government as the only duty-bearer in healthcare will arise. Several major threats, such as high costs as a result of inefficiencies and free riding then become imminent. Therefore, on the basis of Dworkin’s theory, this paper argues that individual responsibility should be introduced when constructing a sustainable healthcare system. And it should be equally highlighted as the duties of government. Furthermore, the notion of individual responsibility is believed to be necessary for promoting the justice of a healthcare system.

Keywords: Chinese healthcare system reform, individual responsibility, right to healthcare, social justice

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Authors: Mohammad Reza Fooladi

Abstract:

The patent system which fits with industrial and economic situation in the country, by strengthening research and development, technology transfer and increasing foreign investment can provide economic and industrial growth of the countries. However, the extent and manner of support should be commensurate with the country's conditions and comply with significant rules to have a positive effect on research and development, technology transfer and the amount of foreign investment. The present article tries to while reviewing the state of effectiveness of the patent system on economic growth, to illustrate the characteristics of the patent system fits Afghanistan and according to this matter provide the necessary recommendations about the improvement of laws and regulations related to the patent in Afghanistan.

Keywords: patent, economic growth, technology transfer, Afghanistan

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Authors: Amer Momani, Tarek Al-Hawari, Abdallah Alakayleh

Abstract:

This study explains how to construct an actionable activity-based costing and management system to accurately track and account the total costs of architectural aluminum projects. Two ABC models were proposed to accomplish this purpose. First, the learning and development model was introduced to examine how to apply an ABC model in an architectural aluminum firm for the first time and to be familiar with ABC concepts. Second, an actual ABC model was built on the basis of the results of the previous model to accurately trace the actual costs incurred on each project in a year, and to be able to provide a quote with the best trade-off between competitiveness and profitability. The validity of the proposed model was verified on a local architectural aluminum company.

Keywords: activity-based costing, activity-based management, construction, architectural aluminum

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Authors: Tadesse Anberbir, Bankole Felix, Tomio Takara

Abstract:

In the development of a text-to-speech synthesizer, automatic derivation of correct pronunciation from the grapheme form of a text is a central problem. Particularly deriving phonological features which are not shown in orthography is challenging. In the Amharic language, geminates and epenthetic vowels are very crucial for proper pronunciation, but neither is shown in orthography. In this paper, to proposed and integrated a morphological analyzer into an Amharic Text-to-Speech system, mainly to predict geminates and epenthetic vowel positions and prepared a duration modeling method. Amharic Text-to-Speech system (AmhTTS) is a parametric and rule-based system that adopts a cepstral method and uses a source filter model for speech production and a Log Magnitude Approximation (LMA) filter as the vocal tract filter. The naturalness of the system after employing the duration modeling was evaluated by sentence listening test, and we achieved an average Mean Opinion Score (MOS) 3.4 (68%), which is moderate. By modeling the duration of geminates and controlling the locations of epenthetic vowel, we are able to synthesize good quality speech. Our system is mainly suitable to be customized for other Ethiopian languages with limited resources.

Keywords: amharic, gemination, Speech synthesis, morphology, epenthesis

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