Search results for: unified theory of acceptance and use of technology (UTAUT) model

Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Leigha Inman

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One of the most cutting-edge interdisciplinary topics in the social sciences is the application of understandings from the humanities to traditionally social scientific disciplines such as education studies. This paper proposes such a topic. It has often been observed that children enjoy literature. The role of reading in the development of reading ability is an important area of research. However, the role of vocabulary in reading development has long been neglected. This paper reports an investigation into the number of words found in key works of children's literature and attempts to correlate that figure with years elapsed since publication of the work. Pedagogical implications will be discussed.

Keywords: educational pedagogy, young learners, vocabulary teaching, reading development

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Authors: Wanqing You, Kai Qian, Ying Qian

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The concepts of Cloud Computing provide users with infrastructure, platform and software as service, which make those services more accessible for people via Internet. To better analysis the performance of Cloud Computing provisioning policies as well as resources allocation strategies, a toolkit named CloudSim proposed. With CloudSim, the Cloud Computing environment can be easily constructed by modelling and simulating cloud computing components, such as datacenter, host, and virtual machine. A good scheduling strategy is the key to achieve the load balancing among different machines as well as to improve the utilization of basic resources. Recently, the existing scheduling algorithms may work well in some presumptive cases in a single machine; however they are unable to make the best decision for the unforeseen future. In real world scenario, there would be numbers of tasks as well as several virtual machines working in parallel. Based on the concepts of multi-queue, this paper presents a new scheduling algorithm to schedule tasks with CloudSim by taking into account several parameters, the machines’ capacity, the priority of tasks and the history log.

Keywords: hierarchical queue, load balancing, CloudSim, information technology

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Authors: Zahira Belkacemi

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One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. In this study, we used maximum-entropy niche modeling (Maxent) to predict the current and future distribution of Anthus pratensis using climatic variables. The results showed that the species would not be highly affected by the climate change in shifting its distribution; however, the results of this study should be improved by taking into account other predictors, and that the NATURA 2000 protected sites will be efficient at 42% in protecting the species.

Keywords: anthus pratensis, climate change, Europe, species distribution model

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Authors: Flavio Contrera, Paulo Cesar Gregorio

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Recent political developments and government control actions in the face of the COVID-19 pandemic draw attention to the contrast between the duties of government and the demands of democratic representation. Elected by mobilizing far-right issues, Trump and Bolsonaro moved away from the WHO guidelines but had to accommodate demands on the health and on the social protection system on the one hand and demands from the economic sector on the other. This study used the MARPOR Project method to assess the impact of the COVID-19 pandemic on the issue and ideological congruence between the electoral and governmental arena in both the Trump and Bolsonaro Administrations. Findings reveal issue congruence between arenas in "National Way of Life: Positive", "Law and Order," and "Technology and Infrastructure" for Donald Trump, and "Welfare State Expansion" for Bolsonaro. Ideological estimation results show that Trump and Bolsonaro positioned to the right in their presidential elections, initially moved to the center-right. However, welfare policies actions at high frequency during the COVID-19 pandemic moved the ideological estimations of both governments to the center-left, despite their denial rhetoric.

Keywords: congruence, COVID-19, Donald Trump, Jair Bolsonaro

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Authors: Rowland Brucken

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This paper argues that nation-building theories that prioritize democratic governance best explain the successful post-independence development of Botswana. Three main competing schools of thought exist regarding the sequencing of policies that should occur to re-build weakened or failed states. The first posits that economic development should receive foremost attention, while democratization and a binding sense of nationalism can wait. A second group of experts identified constructing a sense of nationalism among a populace is necessary first, so that the state receives popular legitimacy and obedience that are prerequisites for development. Botswana, though, transitioned into a multi-party democracy and prosperous open economy due to the utilization of traditional democratic structures, enlightened and accountable leadership, and an educated technocratic civil service. With these political foundations already in place when the discovery of diamonds occurred, the resulting revenues were spent wisely on projects that grew the economy, improved basic living standards, and attracted foreign investment. Thus democratization preceded, and therefore provided an accountable basis for, economic development that might otherwise have been squandered by greedy and isolated elites to the detriment of the greater population. Botswana was one of the poorest nations in the world at the time of its independence in 1966, with little infrastructure, a dependence on apartheid South Africa for trade, and a largely subsistence economy. Over the next thirty years, though, its economy grew the fastest of any nation in the world. The transparent and judicious use of diamond returns is only a partial explanation, as the government also pursued economic diversification, mass education, and rural development in response to public needs. As nation-building has become a project undertaken by nations and multilateral agencies such as the United Nations and the North Atlantic Treaty Organization, Botswana may provide best practices that others should follow in attempting to reconstruct economically and politically unstable states.

Keywords: Botswana, democratization, economic development, nation-building

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Authors: Dengyu You, Alireza Kashani

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This study explores the potential of 3D concrete printing in manufacturing prefabricated staircases. The applications of 3D concrete printing in large-scale construction could enhance the industry’s implementation of the Industry 4.0 concept. In addition, the current global challenge is to achieve Net Zero Emissions by 2050. Innovation in the construction industry could potentially speed up achieving this target. The 3D printing technology offers a possible solution that reduces cement usage, minimises framework wastes, and is capable of manufacturing complex structures. The performance of the 3D concrete printed lightweight staircase needs to be evaluated. In this study, the staircase is designed using computer-aided technologies, fabricated by 3D concrete printing technologies, and tested with Australian Standard (AS 1657-2018 Fixed platforms, walkways, stairways, and ladders – design, construction, and installation) under a laboratory environment. The experiment results will be further compared with the FEM analysis. The results indicate that 3D concrete printing is capable of fast production, reducing material usage, and is highly automotive, which meets the industry’s future development goal.

Keywords: concrete 3D printing, staircase, sustainability, automation

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Authors: David Shengelia, Tamara Tsutsunava, Manana Togonidze, Giorgi Chichinadze, Giorgi Beridze

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Orthoclase gabbro intrusive exposes in the Eastern part of the Dzirula crystalline massif of the Central Transcaucasian microcontinent. It is intruded in the Baikal quartz-diorite gneisses as a stock-like body. The intrusive is characterized by heterogeneity of rock composition: variability of mineral content and irregular distribution of rock-forming minerals. The rocks are represented by pyroxenites, gabbro-pyroxenites and gabbros of different composition – K-feldspar, pyroxene-hornblende and biotite bearing varieties. Scientific views on the genesis and age of the orthoclase gabbro intrusive are considerably different. Based on the long-term pertogeochemical and geochronological investigations of the intrusive with such an extraordinary composition the authors came to the following conclusions. According to geological and geophysical data, it is stated that in the Saurian orogeny horizontal tectonic layering of the Earth’s crust of the Central Transcaucasian microcontinent took place. That is precisely this fact that explains the formation of the orthoclase gabbro intrusive. During the tectonic doubling of the Earth’s crust of the mentioned microcontinent thick tectonic nappes of mafic and sialic layers overlap the sialic basement (‘inversion’ layer). The initial magma of the intrusive was of high-temperature basite-ultrabasite composition, crystallization products of which are pyroxenites and gabbro-pyroxenites. Petrochemical data of the magma attest to its formation in the Upper mantle and partially in the ‘crustal astenolayer’. Then, a newly formed overheated dry magma with phenocrysts of clinopyrocxene and basic plagioclase intruded into the ‘inversion’ layer. From the new medium it was enriched by the volatile components causing the selective melting and as a result the formation of leucocratic quartz-feldspar material. At the same time in the basic magma intensive transformation of pyroxene to hornblende was going on. The basic magma partially mixed with the newly formed acid magma. These different magmas intruded first into the allochthonous basite layer without its significant transformation and then into the upper sialic layer and crystallized here at a depth of 7-10 km. By petrochemical data the newly formed leucocratic granite magma belongs to the S type granites, but the above mentioned mixed magma – to H (hybrid) type. During the final stage of magmatic processes the gabbroic rocks impregnated with high-temperature feldspar-bearing material forming anorthoclase or orthoclase. Thus, so called ‘orthoclase gabbro’ includes the rocks of various genetic groups: 1. protolith of gabbroic intrusive; 2. hybrid rock – K-feldspar gabbro and 3. leucocratic quartz-feldspar bearing rock. Petrochemical and geochemical data obtained from the hybrid gabbro and from the inrusive protolith differ from each other. For the identification of petrogenetic model of the orthoclase gabbro intrusive formation LA-ICP-MS- U-Pb zircon dating has been conducted in all three genetic types of gabbro. The zircon age of the protolith – mean 221.4±1.9 Ma and of hybrid K-feldspar gabbro – mean 221.9±2.2 Ma, records crystallization time of the intrusive, but the zircon age of quartz-feldspar bearing rocks – mean 323±2.9 Ma, as well as the inherited age (323±9, 329±8.3, 332±10 and 335±11 Ma) of hybrid K-feldspar gabbro corresponds to the formation age of Late Variscan granitoids widespread in the Dzirula crystalline massif.

Keywords: The Caucasus, isotope dating, orthoclase-bearing gabbro, petrogenetic model

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Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Chi S. Lee

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Marvel superhero movies have obtained its unprecedented popularity around the globe. It is a dominant narrative in current scholarship on superhero studies that the political trauma of America, such as attack of September 11, and the masculinity represented in superhero genre are symbolically connected in a way of remasculinization, a standardized plot that before becoming a superhero, a man has to overcome its trauma in his life. Through this standardized plot, American audience finds their pleasure in the spectatorship of equating this plot of remasculinization with the situation of America, rewriting their traumatic memory and resolving around the economic, social, political, and psychological instability of precarity in their own context. Shifting the context to Hong Kong, where Marvel superhero movies have been reaching its dominant status in the local film market, this analysis finds its limitation in explaining the connection between text and context. This article aims to retain this connection through investigation of the Hong Kong audience’s spectatorship. It is argued that the masculinity represented in Marvel superhero movies no longer fits into the stereotypical image of superhero, but presents itself in crisis. This crisis is resolved by the technological excess of the superpower, namely, technological remasculinization. The technological remasculinization offers a sense of futurity through which it is felt that this remasculinization can be achieved in the foreseeable future instead of remaining imaginary and fictional. In this way, the political crisis of Hong Kong is gendered as masculinity in crisis which is worth being remasculinized in the future. This gendering process is a historical product as the symbolic equation between politics and masculinity has for long been encoded in the colonial history of Hong Kong. In short, Marvel superhero’s masculinity offers a sense of masculine hope for the Hong Kong audiences to overcome the political crisis they confront in reality through a postponed identification with the superhero’s masculinity. After the discussion of the Hong Kong audience’s spectatorship on Marvel superhero movies with the insights casted by spectatorship theory, above idea is generated.

Keywords: political crisis in Hong Kong, Marvel superhero movies, spectatorship, technological remasculinization

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Authors: Ahmed F. Elaksher, Islam Omar

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In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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Authors: Danielle Guerra, Marden Silva

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The use of active methodologies in the teaching of English has been widely encouraged recently, due to its potential to create propitious conditions for the learners to develop autonomy and studying skills that tend to keep them motivated throughout the learning process. The constant use of technology by the students makes it possible to implement strategies such as blended learning, which blends regular classes with online instruction and practice. (Horn and Staker, 2015) For that reason, the aim of this study was to implement the blended approach in a High School second-grade English class in Brazil, in order to analyze the impacts of this methodology on the students' autonomy. The teacher's role was that of a mediator, being responsible for selecting the best resources for students to study with, and also for helping them with questions when necessary. The results show that taking learner characteristics and learning experiences into account and allowing the students to follow their learning paths at their own pace was crucial to promoting engagement that led to the desired outcomes. In conclusion, the research shows that blended learning is a helpful strategy to foster autonomy and promote motivation in EFL students.

Keywords: active methodologies, autonomy, blended learning, motivation

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Authors: F. Fekak, A. Gravouil, M. Brun, B. Depale

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During an earthquake, a bridge crane may be subjected to multiple impacts between crane wheels and rail. In order to model such phenomena, a time-history dynamic analysis with a multi-scale approach is performed. The high frequency aspect of the impacts between wheels and rails is taken into account by a Lagrange explicit event-capturing algorithm based on a velocity-impulse formulation to resolve contacts and impacts. An implicit temporal scheme is used for the rest of the structure. The numerical coupling between the implicit and the explicit schemes is achieved with a heterogeneous asynchronous time-integrator.

Keywords: bridge crane, earthquake, dynamic analysis, explicit, implicit, impact

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Authors: I. M. Abd Rahim, H. Abdul Rahim, R. Ghazali

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There is numerous non-invasive blood glucose measurement technique developed by researchers, and near infrared (NIR) is the potential technique nowadays. However, there are some disagreements on the optimal wavelength range that is suitable to be used as the reference of the glucose substance in the blood. This paper focuses on the experimental data collection technique and also the analysis method used to analyze the data gained from the experiment. The selection of suitable linear and non-linear model structure is essential in prediction system, as the system developed need to be conceivably accurate.

Keywords: linear, near-infrared (NIR), non-invasive, non-linear, prediction system

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Authors: Katsumi Hirano, Yusuke Kakuta, Koji Yoshida, Shozo Itagaki, Masahiko Kajioka, Toshihiko Okada

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A conversion technology of cellulosic biomass and waste plastics to liquid fuel at low pressure and low temperature has been investigated. This study aims at the production of the liquefied fuel (CPLF) of substituting diesel oil by mixing cellulosic biomass and waste plastics in the presence of solvent. Co-liquefaction of cellulosic biomass (Japan cedar) and polypropylene (PP) using wood tar or mineral oil as solvent at 673K with an autoclave was carried out. It was confirmed that the co-liquefaction gave CPLF in a high yield among the cases of wood or of polypropylene Which was ascribed the acceleration of decomposition of plastics by radicals derived from the decomposition of wood. The co-liquefaction was also conducted by a small twin screw extruder. It was found that CPLF was obtained in the co-liquefaction, And the acceleration of decomposition of plastics in the presence of cellulosic biomass. The engine test of CPLF showed that the engine performances, Compression ignition and combustion　characteristics were almost similar to those of diesel fuel at any mixing ratio of CPLF and any load, Therefore, CPLF could be practically used as alternative fuel for diesel engines.

Keywords: Cellulosic Biomass, Co-liquefaction, Solvent, Waste Plastics

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Authors: Intesar Ibrahim

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Large-scale Libyan emigration is a relatively new phenomenon. Most of the Libyan families in the UK are new immigrants, unlike the other neighbouring countries of Egypt, Tunisia, Algeria and even Sudan. Libyans have no particular history of large-scale migration. On the other hand, many Libyan families live in modest homes located in large Muslim communities of Pakistanis and Yemenis. In the UK as a whole, there are currently 16 Libyan schools most of which are run during the weekend for children of school age. There are three such weekend schools in Sheffield that teach a Libyan school curriculum, and Libyan women and men run these schools. Further, there is also a Masjid (mosque) that is operated by Libyans, beside the other Masjids in the city, which most of the Libyan community attend for prayer and for other activities such as writing marriage contracts. The presence of this Masjid increases the attraction for Libyans to reside in the Sheffield area. This paper studies how Libyan immigrants in the UK make their decisions on their housing and living environment in the UK. Libyan residents in the UK come from different Libyan regions, social classes and lifestyles; this may have an impact on their choices in the interior designs of their houses in the UK. A number of case studies were chosen from Libyan immigrants who came from different types of dwellings in Libya, in order to compare with their homes and their community lifestyle in the UK and those in Libya. This study explores the meaning and the ways of using living rooms in Libyan emigrants’ houses in the UK and compares those with those in their houses back in their home country. For example, the way they set up furniture in rooms acts as an indicator of the hierarchical structure of society. The design of furniture for Libyan sitting rooms for floor-seating is different from that of the traditional English sitting room. The paper explores the identity and cultural differences that affected the style and design of the living rooms for Libyan immigrants in the UK. The study is carried out based on the "production of space" theory that any culture has its needs, style of living and way of thinking. I argue that the study found more than 70% of Libyan immigrants in the UK still furnish the living room in their traditional way (flooring seating).

Keywords: place, identity, culture, immigrants

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Authors: Zahra Neffah, Henda Kahalerras

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A numerical study is made in a parallel-plate porous channel subjected to an oscillating flow and an exothermic chemical reaction on its walls. The flow field in the porous region is modeled by the Darcy–Brinkman–Forchheimer model and the finite volume method is used to solve the governing equations. The effects of the modified Frank-Kamenetskii (FKm) and Damköhler (Dm) numbers, the amplitude of oscillation (A), and the Strouhal number (St) are examined. The main results show an increase of heat and mass transfer rates with A and St, and their decrease with FKm and Dm.

Keywords: chemical reaction, heat and mass transfer, oscillating flow, porous channel

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Authors: Dong Nyoung Heo, Il Keun Kwon

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Three-dimensional (3D) technology is a promising method for bone tissue engineering. In order to enhance bone tissue regeneration, it is important to have ideal 3D constructs with biomimetic mechanical strength, structure interconnectivity, roughened surface, and the presence of chemical functionality. In this respect, a 3D printing system combined with cold atmospheric plasma (CAP) was developed to fabricate a 3D construct that has a rough surface with polar functional chemical groups. The CAP-etching process leads to oxidation of chemical groups existing on the polycaprolactone (PCL) surface without conformational change. The surface morphology, chemical composition, mean roughness of the CAP-treated PCL surfaces were evaluated. 3D printed constructs composed of CAP-treated PCL showed an effective increment in the hydrophilicity and roughness of the PCL surface. Also, an in vitro study revealed that CAP-treated 3D PCL constructs had higher cellular behaviors such as cell adhesion, cell proliferation, and osteogenic differentiation. Therefore, a 3D printing system with CAP can be a highly useful fabrication method for bone tissue regeneration.

Keywords: bone tissue engineering, cold atmospheric plasma, PCL, 3D printing

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Authors: Kazem Bashirnezhad, Seyed Ahmad Kebriyaee, saeed hoseyngholizadeh moghadam

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The urea–SCR catalyst system has the advantages of high NOx conversion efficiency and a wide range of operating conditions. The key factors for successful implementation of urea–SCR technology is good mixing of urea (ammonia) and gas to reduce ammonia slip. Urea mixer components are required to facilitate evaporation and mixing, because it is difficult to evaporate urea in the liquid state; the injection parameters are the most critical factors affecting mixer performance. In this study, The effect of urea injection on NOx emissions in a six-cylinder, four-stroke internal combustion engine fueled with B80 biodiesel has been experimentally investigated. The results reveal that urea injection leads to a reduction of NOx emissions of B80 biodiesel fuel. Moreover, the influence of injection parameters on NOx reductions has been studied. The findings show that by increasing the injection temperature, more reduction in NOx emissions has been occurred. Also, urea mass flow rate increment leads to more NOx reduction. The same result has been obtained by an increase in spray angle.

Keywords: urea, NOx emissions, diesel engines, biodiesels

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Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

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Authors: Sheriff Folarin, Oluwafunke Folarin, Hadassah Hussaini, Victor Jubril, Olaniyi Ayodele

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Using a famous, unrestrained and fiery United States-based, Nigerian-owned Sahara Reporters as a case study, this paper examined the impact of online-based media on governance in Nigeria. The discourse is premised on the thesis that the internet has changed the face of journalism and that the mainstream but online-based media have made journalism more participatory than ever. Everyone who has something to say finds it easy to say it quickly and conveniently, unhinged or without being censored. This has made online journalism very popular and the number of online-based news platforms to be on the increase. As these platforms have given the citizens a means to interact and added to the content of the news, they have also succeeded in promoting partisanship. It thus becomes necessary to study the impact of the rabid news platform, Sahara Reporters, on governance in Africa’s biggest democracy, Nigeria. Few studies have examined the impact on governance of mainstream-online media platforms and those studies that did, have only focused on social media, such as Facebook and Twitter. This paper is a product of a bigger study, in which the research design entailed semi-structured interviews with participants from different sectors of the society and an analysis of contents from the Sahara Reporters website, from which data were collected. The findings revealed that through uncensored reporting and citizen participation on the platform of Sahara Reporters, there had been a significant people influence on governance in Nigeria, with government at two levels (national and state) sometimes shifting or yielding grounds, particularly from 2011-2016. The study also recognized the presence of counter-forces in the online community who want to discredit the information on the site. Through the lens of media dependency theory, the study concluded that the public now increasingly depends on online news media for information and the more news these media provide, the more the people depend on it, making it easy for them to influence governance.

Keywords: governance, media, online news, Sahara reporters

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Authors: A. H. Alenezi

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Cooling by impingement jet is known to have a significant high local and average heat transfer coefficient which make it widely used in industrial cooling systems. The heat transfer characteristics of an impinging jet on rib-roughened flat plate has been investigated numerically. This paper was set out to investigate the effect of rib height on the heat transfer rate. Since the flow needs to have enough spacing after passing the rib to allow reattachment especially for high Reynolds numbers, this study focuses on finding the optimum rib height which would be the best to maximize the heat transfer rate downstream the plate. This investigation employs a round nozzle with hydraulic diameter (Dh) of 13.5 mm, Jet-to-target distance of (H/D) of 4, rib location=1.5D and and finally jet angels of 45˚ and 90˚ under the influence of Re =10,000.

Keywords: jet impingement, CFD, turbulence model, heat transfer

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Authors: Wu Sa, Zhang Qian, Li Qi, Wang Ye

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Currently in humidity tests having not put the Dew point temperature as a control parameter, this paper selects wet and dry bulb thermometer to measure the vapor pressure, and introduces several the saturation vapor pressure formulas easily calculated on the controller. Then establish the Dew point temperature calculation model to obtain the relationship between the Dew point temperature and vapor pressure. Finally check through the 100 groups of sample in the range of 0-100 ℃ from "Psychrometric handbook", find that the average error is small. This formula can be applied to calculate the Dew point temperature in the humidity test.

Keywords: dew point temperature, psychrometric handbook, saturation vapor pressure, wet and dry bulb thermometer

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Authors: Navid Mirzaei Varzeghani, Mahmoud Saffarzadeh, Ali Naderan, Amirhossein Taheri

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Countries are progressing, and the world's busiest airports see year-on-year increases in travel demand. Passenger acceptability of an airport depends on the airport's appeals, which may include one of these routes between the city and the airport, as well as the facilities to reach them. One of the critical roles of transportation planners is to predict future transportation demand so that an integrated, multi-purpose system can be provided and diverse modes of transportation (rail, air, and land) can be delivered to a destination like an airport. In this study, 356 questionnaires were filled out in person over six days. First, the attraction of business and non-business trips was studied using data and a linear regression model. Lower travel costs, a range of ages more significant than 55, and other factors are essential for business trips. Non-business travelers, on the other hand, have prioritized using personal vehicles to get to the airport and ensuring convenient access to the airport. Business travelers are also less price-sensitive than non-business travelers regarding airport travel. Furthermore, carrying additional luggage (for example, more than one suitcase per person) undoubtedly decreases the attractiveness of public transit. Afterward, based on the manner and purpose of the trip, the locations with the highest trip generation to the airport were identified. The most famous district in Tehran was District 2, with 23 visits, while the most popular mode of transportation was an online taxi, with 12 trips from that location. Then, significant variables in separation and behavior of travel methods to access the airport were investigated for all systems. In this scenario, the most crucial factor is the time it takes to get to the airport, followed by the method's user-friendliness as a component of passenger preference. It has also been demonstrated that enhancing public transportation trip times reduces private transportation's market share, including taxicabs. Based on the responses of personal and semi-public vehicles, the desire of passengers to approach the airport via public transportation systems was explored to enhance present techniques and develop new strategies for providing the most efficient modes of transportation. Using the binary model, it was clear that business travelers and people who had already driven to the airport were the least likely to change.

Keywords: multimodal transportation, demand modeling, travel behavior, statistical models

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Authors: Chia-Lin Tu

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Towards the end of the 20th century, a reductive picture has dominated in philosophy of science and philosophy of mind. Reductive physicalism claims that all entities and properties in this world are eventually able to be reduced to the physical level. It means that all phenomena in the world are able to be explained by laws of physics. However, quantum physics provides another picture. It says that the world is undergoing change and the energy of change is, in fact, the most important part to constitute world phenomena. Quantum physics provides us another point of view to reconsider the reality of the world. Throughout the history of philosophy of mind, reductive physicalism tries to reduce the conscious phenomena to physical particles as well, meaning that the reality of consciousness is composed by physical particles. However, reductive physicalism is unable to explain conscious phenomena and mind-body causation. Conscious phenomena, e.g., qualia, is not composed by physical particles. The current popular theory for consciousness is emergentism. Emergentism is an ambiguous concept which has not had clear idea of how conscious phenomena are emerged by physical particles. In order to understand the emergence of conscious phenomena, it seems that quantum physics is an appropriate analogy. Quantum physics claims that physical particles and processes together construct the most fundamental field of world phenomena, and thus all natural processes, i.e., wave functions, have occurred within. The traditional space-time description of classical physics is overtaken by the wave-function story. If this methodology of quantum physics works well to explain world phenomena, then it is not necessary to describe the world by the idea of physical particles like classical physics did. Conscious phenomena are one kind of world phenomena. Scientists and philosophers have tried to explain the reality of them, but it has not come out any conclusion. Quantum physics tells us that the fundamental field of the natural world is processed metaphysics. The emergence of conscious phenomena is only possible within this process metaphysics and has clearly occurred. By the framework of quantum physics, we are able to take emergence more seriously, and thus we can account for such emergent phenomena as consciousness. By questioning the particle-mechanistic concept of the world, the new metaphysics offers an opportunity to reconsider the reality of conscious phenomena.

Keywords: quantum physics, reduction, emergence, qualia

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Authors: Rama Bhargava, Mania Goyal

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The problem of magnetohydrodynamics boundary layer flow and heat transfer on a permeable stretching surface in a second grade nanofluid under the effect of heat generation and partial slip is studied theoretically. The Brownian motion and thermophoresis effects are also considered. The boundary layer equations governed by the PDE’s are transformed into a set of ODE’s with the help of local similarity transformations. The differential equations are solved by variational finite element method. The effects of different controlling parameters on the flow field and heat transfer characteristics are examined. The numerical results for the dimensionless velocity, temperature and nanoparticle volume fraction as well as the reduced Nusselt and Sherwood number have been presented graphically. The comparison confirmed excellent agreement. The present study is of great interest in coating and suspensions, cooling of metallic plate, oils and grease, paper production, coal water or coal-oil slurries, heat exchangers technology, materials processing exploiting.

Keywords: viscoelastic nanofluid, partial slip, stretching sheet, heat generation/absorption, MHD flow, FEM

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Authors: Wei-Kuo Soong

Abstract:

The forecasting of typhoon tracks remains a formidable challenge, primarily attributable to the paucity of observational data in the open sea and the intricate influence of weather systems at varying scales. This study investigates the case of Typhoon Hinnamnor in 2022, examining its trajectory and intensity fluctuations in relation to the interaction with a concurrent tropical cyclone and sea surface temperatures (SST). Utilizing the Weather Research and Forecasting Model (WRF), to simulate and analyze the interaction between Typhoon Hinnamnor and its environmental factors, shedding light on the mechanisms driving typhoon development and enhancing forecasting capabilities.

Keywords: typhoon, sea surface temperature, forecasting, WRF

Procedia PDF Downloads 49