Search results for: pre-service teacher training program

Authors: Janki Shankar, Shu-Ping Chen

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This Canadian study explored the perspectives of recent immigrant workers regarding occupational health and safety (OHS) and workplace conditions that increase workers’ vulnerability to sustaining injury or illness. Using an interpretive research approach and semi structured qualitative interviews, 42 recent immigrant workers from a range of industries operating in two cities in a province in Canada were interviewed. A constant comparative approach was used to identify key themes across the workers’ experiences. The findings revealed that these workers have an incomplete understanding of OHS. In many workplaces, poor job training, little worker support, lack of power in the workplace, and a poor workplace safety culture make it difficult for recent immigrant workers to acquire OHS information and implement safe work practices. This study proposes workplace policies and practices that will improve worker OHS awareness and make workplaces safer for immigrant workers.

Keywords: new immigrant workers, occupational health and safety, workplace challenges, policy, practice

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Authors: Ratchaneewan Salao, Steven W. Edwards, Kiatichai Faksri, Kanin Salao

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Background: A two-dose regimen of COVID-19 vaccination (inactivated whole virion SARS-CoV-2 and adenoviral vector) has been widely used. Side effects are very low, but several adverse effects have been reported. Methods: A 40-year-old female patient, with a previous history of thyroid goitre, developed severe neck pain, headache, nausea and fatigue 7-days after receiving second vaccination with Vaxzevria® (Oxford-AstraZeneca). Clinical and laboratory findings, including thyroid function tests and ultrasound of thyroid glands, were performed. Results: Her left thyroid gland was multinodular enlarged, and severely tender on palpation. She had difficulty in swallowing and had tachycardia but no signs of hyperthyroidism. Laboratory results supported a diagnosis of subacute thyroiditis. She was prescribed NSAID (Ibuprofen 400 mg) and dexamethasone for 3-days and her symptoms resolved. Conclusions: Although this is an extremely rare event, physicians may encounter more cases of this condition due to the extensive vaccination program using this combination of vaccines.

Keywords: SARS-CoV-2, adenoviral vector vaccines, vaccination, subacute thyroiditis

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Authors: Foroozan Sadri, Mohammadmehdi Moulaii, Farkhondeh Vahdati

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Smart materials can create a great revolution in our built environment, as living systems do. In this research, the optimal structure of healthcare building envelopes is analyzed in terms of thickness according to the utility of the smart-nano materials as nontoxic substances in the region. The research method in this paper is based on library studies and simulation. Grasshopper program is employed to simulate thermal characteristics to achieve the optimum U-value in Semnan desert climate, according to Iranian national standards. The potential of healthcare envelope layouts in thermal properties development (primarily U-value) of these buildings is discussed due to the high thermal loads of healthcare buildings and also toxicity effects of conventional materials. As a result, envelope thicknesses are calculated, and the performance of the nano-PCM and gypsum wallboards are compared. A solution with comparable performance using smart-nano materials instead of conventional materials would determine a decrease in wall thickness.

Keywords: energy saving, exterior envelope, smart-nano materials, thermal performance, U-value

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Authors: Matan Cohen, Maxim Shoshany

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Climatic, topographic and geological diversity, together with frequent disturbance and recovery cycles, produce highly complex spatial patterns of trees, shrubs, dwarf shrubs and bare ground patches. Assessment of spatial and temporal variations of these life-forms patterns under climate change is of high ecological priority. Here we report on one of the first attempts to discriminate between images of three Mediterranean life-forms patterns at three densities. The development of an extensive database of orthophoto images representing these 9 pattern categories was instrumental for training and testing pre-trained and newly-trained DL models utilizing DenseNet architecture. Both models demonstrated the advantages of using Deep Learning approaches over existing spectral and spatial (pattern or texture) algorithmic methods in differentiation 9 life-form spatial mixtures categories.

Keywords: texture classification, deep learning, desert fringe ecosystems, climate change

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

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Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

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Authors: Oladimeji Adetona Adeyeye, Emmanuel Rotimi Sadiku, Oluwaseun Olayinka Adeyeye

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In order to resuscitate soybean production and post-harvest processing especially, in term of threshing, there is need to develop an affordable threshing machine which will reduce drudgery associated with manual soybean threshing. Soybean thresher was fabricated and evaluated at Institute of Agricultural Research and Training IAR&T Apata Ibadan. The machine component includes; hopper, threshing unit, shaker, cleaning unit and the seed outlet, all working together to achieve the main objective of threshing and cleaning. TGX1835 - 10E variety was used for evaluation because of its high resistance to pests, rust and pustules. The final moisture content of the used sample was about 15%. The sample was weighed and introduced into the machine. The parameters evaluated includes moisture content, threshing efficiency, cleaning efficiency, machine capacity and speed. The threshing efficiency and capacity are 74% and 65.9kg/hr respectively. All materials used were sourced locally which makes the cost of production of the machine extremely cheaper than the imported soybean thresher.

Keywords: efficiency, machine capacity, speed, soybean, threshing

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Authors: Sarah M. Bolger

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There is a clear recognition that humanitarian and development workers are operating more and more frequently in situations of protracted crises, with conflict and violence undermining long-term development efforts. First coined at the World Humanitarian Summit in 2016, the humanitarian-development-peacebuilding nexus – or 'Triple Nexus' - seeks to promote greater cooperation and policy and program coherence amongst organizations working within and across the nexus. However, despite the clear need for such an approach, the Triple Nexus has failed to gain much traction. This is largely due to the lack of conceptual clarity for actors on the ground and the disconnect between the theory of the Triple Nexus and what that means in practice. This paper seeks to identify the key challenges in shifting from the conceptual definition of the Triple Nexus and what that can look like, particularly for multi-mandated organizations, to the operationalization of the Triple Nexus approach. It adopts a case study approach, examining a selection of organizations and programs and their approaches to the Triple Nexus in order to extract key challenges and lessons learned. Finally, key recommendations are provided on how these challenges can be overcome, allowing for the operationalization of the Triple Nexus and ultimately for a more integrated and sustainable approach to humanitarian, development, and peacebuilding work.

Keywords: development, humanitarian, peacebuilding, triple nexus

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Authors: Lenka Mynaříková, Hedvika Boukalová

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The study looks at the ability to detect nonverbal deception among police officers and management students in the Czech Republic. Respondents from police departments (n=197) and university students of human resources (n=161) completed a deception detection task and evaluated veracity of the statements of suspects in 21 video clips from real crime investigations. Their evaluations were based on nonverbal behavior. Voices in the video clips were modified so that words were not recognizable, yet paraverbal voice characteristics were preserved. Results suggest that respondents have a tendency to lie bias based on their profession. In the evaluation of video clips, stereotypes also played a significant role. The statements of suspects of a different ethnicity, younger age or specific visual features were considered deceitful more often. Research might be beneficial for training in professions that are in need of deception detection techniques.

Keywords: deception detection, police officers, human resources, forensic psychology, forensic studies, organizational psychology

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Gunawan Prayitno, Kakuya Matshusima, Kiyoshi Kobayashi

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Indonesia’s rural regions are characterized by wide-spread poverty, under-employment, and surplus of low-skilled labor. The aim of this paper is to empirically prove the effect of social ties (strong and weak tie) as social capital construct on households’ migration decision in the case of developing country (Indonesia). The methodology incorporated indicators of observe variables (four demographic attributes data: income, occupation, education, and family members) and indicators of latent variables (ties to neighbors, ties to community and sense of place) provided by responses to survey questions to aid in estimating the model. Using structural equation model that we employed in Mplus program, the result of our study shows that ties to community positively have a significant impact to the decision of respondents (migrate or not). Besides, education as observed variable directly influences the migration decisions. It seems that higher level of education have impact on migration decision. Our current model so far could explain the relation between social capital and migration decision choice.

Keywords: migration, ties to community, ties to neighbors, education

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Authors: Gaurav Sancheti

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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

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Authors: Mariia Karizhenskaia, Tanvi Nandani, Ali Tafazoli Moghadam

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Hospice palliative care (HPC) is one of the most complicated philosophies of care in which physical, social/cultural, and spiritual aspects of human life are intermingled with an undeniably significant role in every aspect. Among these dimensions of care, culture possesses an outstanding position in the process and goal determination of HPC. This study shows the importance of cultural elements in the establishment of effective and optimized structures of HPC in the Canadian healthcare environment. Our systematic search included Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 1998 to 2023 to identify recent national literature connecting culture and palliative care delivery. The most frequently presented feature among the articles is the role of culture in the efficiency of the HPC. It has been shown frequently that including the culturespecific parameters of each nation in this system of care is vital for its success. On the other hand, ignorance about the exclusive cultural trends in a specific location has been accompanied by significant failure rates. Accordingly, implementing a culture-wise adaptable approach is mandatory for multicultural societies. The following outcome of research studies in this field underscores the importance of culture-oriented education for healthcare staff. Thus, all the practitioners involved in HPC will recognize the importance of traditions, religions, and social habits for processing the care requirements. Cultural competency training is a telling sample of the establishment of this strategy in health care that has come to the aid of HPC in recent years. Another complexity of the culturized HPC nowadays is the long-standing issue of racialization. Systematic and subconscious deprivation of minorities has always been an adversity of advanced levels of care. The last part of the constellation of our research outcomes is comprised of the ethical considerations of culturally driven HPC. This part is the most sophisticated aspect of our topic because almost all the analyses, arguments, and justifications are subjective. While there was no standard measure for ethical elements in clinical studies with palliative interventions, many research teams endorsed applying ethical principles for all the involved patients. Notably, interpretations and projections of ethics differ in varying cultural backgrounds. Therefore, healthcare providers should always be aware of the most respectable methodologies of HPC on a case-by-case basis. Cultural training programs have been utilized as one of the main tactics to improve the ability of healthcare providers to address the cultural needs and preferences of diverse patients and families. In this way, most of the involved health care practitioners will be equipped with cultural competence. Considerations for ethical and racial specifications of the clients of this service will boost the effectiveness and fruitfulness of the HPC. Canadian society is a colorful compilation of multiple nationalities; accordingly, healthcare clients are diverse, and this divergence is also translated into HPC patients. This fact justifies the importance of studying all the cultural aspects of HPC to provide optimal care on this enormous land.

Keywords: cultural competence, end-of-life care, hospice, palliative care

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Authors: Pawinee Innark, Hudsaya Punyanitikul, Chanuluk Khanobdee, Chatchawan Jantasuriyarat, Sompid Samipak

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One of the most devastating diseases in cucumber is downy mildew caused by the fungus Pseudoperonospora cubensis. To enable the use of marker-assisted breeding for resistance cultivars, sixty six microsatellite markers were used to map (quantitative trait loci) QTLs for DM resistance. Total of 315 F2 population from the cross between DM-resistant inbred line CSL0067 and susceptible CSL0139 were evaluated for downy mildew resistance in cotyledon, first and second true leaf at 7, 10, and 14 day after inoculation. The QTL analysis revealed that the downy mildew resistant genes were controlled by multiple recessive genes. From eight linkage groups (LG 1.1, 1.2, 2, 3, 4, 5.1, 5.2 and 6), fourteen QTL positions were detected on 4 linkage groups (LG 1.1, 2, 5.1 and 6) with the log of odd scores ranged from 3.538 to 9.165. Among them, Cot7_5.1_2 and Cot10_5.1 had major-effect QTL with the R2 values of 10.9 and 12.5%, respectively. The flanking markers for Cot7_5.1_2 were SSR19172 - SSR07531 markers and for Cot10_5.1 were SSR03943 - SSR00772. Besides QTLs on chromosome 1, 5 and 6 that were previously reported, this study also revealed a QTL for DM resistance on chromosome 2 that can be used as a new source in cucumber breeding program.

Keywords: cucumber, DNA marker, downy mildew, QTL

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Authors: Stephen O. Amaraihu

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This research investigated the effect of Computer Based Instruction on Students’ interest, achievement, and retention in Algebra in Abia State College of Education (Technical), Arochukwu. Three research questions and two hypotheses guided the study. Two instruments, Maths Achievement Test (MAT) and Maths Interest Inventory were employed, to test a population of three hundred and sixteen (316) NCE 1 students in algebra. It is expected that this research will lead to the improvement of students’ performance and enhance their interest and retention of basic algebraic concept. It was found that the majority of students in the college are not proficient in the use of ICT as a result of a lack of trained personnel. It was concluded that the state government was not ready to implement the usage of mathematics in Abia State College of Education. The paper recommends, amongst others, the employment of mathematics Lectures with competent skills in ICT and the training of lecturers of mathematics.

Keywords: achievement, computer based instruction, interest, retention

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Authors: Aparajita Mukherjee, D. P. Mukherjee

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This paper critically assessed pollution problems in small and medium enterprises with unique references to foundries and sponge iron industries to survey the adverse impact on human societies and the environment. The objective of this paper was to show how cleaner production concept was implemented in one foundry through improvisation of existing technology in India. Incremental advancement of existing technology minimized environmental issues and resource utilization. This study depicted that poor fiscal help, poor enforcement of government regulations, owners’ attitude and lacking specialized technical workers were the significant hindrances towards cleaner production. The paper explored the possible ways to overcome these hindrances for cleaner production. On a more general level, findings raise important questions regarding the need for a new paradigm for the implementation of cleaner production. Improvisation of existing technology in these enterprises would be cost effective towards sustainable development.

Keywords: SME pollution, ecological crisis, sustainable development, cleaner production, training

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Authors: Jingwen Shan

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In order to explore the key factors affecting the robot program learning intention of school students, this study takes the technology acceptance model as the theoretical basis and invites 167 students from Jiading District of Shanghai as the research subjects. In the robot course, the model of school students on their learning behavior is constructed. By verifying the causal path relationship between variables, it is concluded that teachers can enhance students’ perceptual usefulness to robotics courses by enhancing subjective norms, entertainment perception, and reducing technical anxiety, such as focusing on the gradual progress of programming and analyzing learner characteristics. Students can improve perceived ease of use by enhancing self-efficacy. At the same time, robot hardware designers can optimize in terms of entertainment and interactivity, which will directly or indirectly increase the learning intention of the robot course. By changing these factors, the learning behavior of primary and secondary school students can be more sustainable.

Keywords: TAM, learning behavior intentions, robot courses, primary and secondary school students

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Authors: Yuan Jie Kelvin Lu, Amin Chegenizadeh

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Asphalt pavement itself is a mixture made up of mainly aggregates, binders, and fillers that acts as a composition used for pavement construction. An experimental program was setup to determine the fatigue performance test of Asphalt with three different grades of conventional binders. Asphalt specimen has achieved the maximum optimum bulk density and air voids with a consistent bulk density of 2.3 t/m3, with an air void of 5% ± 0.5, before loading into the Asphalt Mixture Performance Tested (AMPT) for fatigue test. The number of cycles is defined as the point where phase angle drops, which is caused by the formation of cracks due to the increasing micro cracks when asphalt is undergoing repeated cycles of loading. Thus, the data collected are analyzed using the drop of phase angle as failure criteria. Based in the data analyzed, it is evident that the fatigue life of asphalt lies on the grade of binder. The result obtained shows that all specimens do experience a drop in phase angle due to macro cracks in the asphalt specimen.

Keywords: asphalt binder, AMPT, CX test, simplified – viscoelastic continuum damage (S-VECD)

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Authors: Salam M. H. Kareem

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Instructional or teaching procedures and their proper sequence are essential for high-quality learning outcomes. These actions are the path that the teacher takes during the learning process after setting the learning objectives. Teachers and specialists in the education field should include teaching procedures with putting in place an effective mechanism for the procedure’s implementation to achieve a logical sequence with the desired output of overall education process. Determining the sequence of these actions may be a strategic process outlined by a strategic educational plan or drawn by teachers with a high level of experience, enabling them to determine those logical procedures. While specific actions may be necessary for a specific form, many Physical Education (PE) teachers can work out on various sports disciplines. This study was conducted to investigate the impact of using the teaching sequence of the teaching pyramid in raising the level of enjoyment in swimming classes. Four months later of teaching swimming skills to the control and experimental groups of the study, we figured that using the tools shown in the teaching pyramid with the experimental group led to statistically significant differences in the positive tendencies of students to participate in the swimming classes by using the traditional procedures of teaching and using of successive procedures in the teaching pyramid, and in favor of the teaching pyramid, The students are influenced by enhancing their tendency to participate in swimming classes when the teaching procedures followed are sensitive to individual differences and are based on the element of pleasure in learning, and less positive levels of the tendency of students when using traditional teaching procedures, by getting the level of skills' requirements higher and more difficult to perform. The level of positive tendencies of students when using successive procedures in the teaching pyramid was increased, by getting the level of skills' requirements higher and more difficult to perform, because of the high level of motivation and the desire to challenge the self-provided by the teaching pyramid.

Keywords: physical education, swimming classes, teaching process, teaching pyramid

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Authors: Yusra A. Ibrahim

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Educational efforts to address the school-to-prison pipeline (STPP) and retain students in school require equipping teachers with evidence-based approaches to handle social-emotional behavior (SEB) needs. One aspect of these efforts involves training teachers to utilize effective and current technologies, thereby reducing SEB challenges faced by students with disabilities in their classrooms. This literature review examines eight studies conducted within the past 10 years (from 2013 to 2023) that focus on enhancing SEB needs of students with disabilities using technology. The review reveals that autism spectrum disorder (ASD), emotional behavioral disorder (EBD), and attention deficit and hyperactivity disorder (ADHD) are the predominant disabilities studied through technology interventions. Additionally, it highlights that these studies focused on examining the effectiveness of technologies in reducing disruptive behaviors, increasing on-task behaviors, reducing anxiety, and promoting social skills.

Keywords: school-to-prison pipeline, technology, evidence-based practices, EBD

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Authors: Mohammed Ali Hadj Ammar, Fethi Bouras, Kamel Sahlaoui

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This article presents a detailed study of two working pairs intended for use in solar adsorption refrigeration (SAR) system. The study was based on two indicators: the daily production and coefficient of performance (COP). The thermodynamic cycle of the system is based on the adsorption phenomena at a constant temperature. A computer simulation program has been developed for modeling and performance evaluation for the solar-powered adsorption refrigeration cycle. It was found that maximal cycled mass is obtained by S40/water (0.280kg/kg) followed by CarboTech C40/1/methanol (0.260kg/kg). At a condenser temperature of 30°C, with an adsorbent mass of 38.59 kg, and an integrated collector/bed configuration, the couple CarboTech C40/1/methanol for the ice-maker purpose can reach cycle COP of 0.63 and can produce about 13.6kg ice per day, while the couple S40/water for the air-conditioning can reach cycle COP of 0.66 and 212kg as daily cold-water production. Additionally, adequate indicators are evaluated addressing the economic and environmental associated with each working pair.

Keywords: solar adsorption, refrigeration, activated carbon, silica gel

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Authors: Madhura Bandyopadhyay

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Teaching writing within multicultural and multiethnic communities poses many unique challenges not the least of which is that of intercultural communication. When the writing is in English, pedagogical imperatives often encounter the universalizing tendencies of standardization of both language use and structural parameters which are often at odds with maintaining local practices which preserve cultural pluralism. English often becomes the contact zone within which individual identities of students play out against the standardization imperatives of the larger world. Writing classes can serve as places which become instruments of assimilation of ethnic minorities to a larger globalizing or nationalistic agenda. Hence, for those outside of the standard practices of writing English, adaptability towards a mastery of those practices valued as standard become the focus of teaching taking away from diversity of local English use and other modes of critical thinking. In a very multicultural and multiethnic context such as the US or Singapore, these dynamics become very important. This paper will argue that multiethnic writing classrooms can greatly benefit from taking up a cultural studies approach whereby the students’ lived environments and experiences are analyzed as cultural texts to produce writing. Such an approach eliminates limitations of using both literary texts as foci of discussion as in traditional approaches to teaching writing and the current trend in teaching composition without using texts at all. By bringing in students’ lived experiences into the classroom and analyzing them as cultural compositions stressing the ability to communicate across cultures, cultural competency is valued rather than adaptability while privileging pluralistic experiences as valuable even as universal shared experience are found. Specifically, while teaching writing in English in a multicultural classroom, a cultural studies approach makes both teacher and student aware of the diversity of the English language as it exists in our global context in the students’ experience while making space for diversity in critical thinking, structure and organization of writing effective in an intercultural context.

Keywords: English, multicultural, teaching, writing

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Authors: Wenzhe Li, Xiaoyu Ying, Grace Ding

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Architecture plane form is an important consideration in the design of green buildings due to its significant impact on energy performance. The most effective method to consider energy performance in the early design stages is parametric modelling. This paper presents a methodology to program plane forms using MATLAB language, generating 16 kinds of plane forms by changing four designed parameters. DesignBuilder (an energy consumption simulation software) was proposed to simulate the energy consumption of the generated planes. A regression mathematical model was established to study the relationship between the plane forms and their energy consumption. The main finding of the study suggested that there was a cubic function relationship between the depth-ratio of U-shaped buildings and energy consumption, and there is also a cubic function relationship between the width-ratio and energy consumption. In the design, the depth-ratio of U-shaped buildings should not be less than 2.5, and the width-ratio should not be less than 2.

Keywords: graphic parameterization, green building design, mathematical model, plane form

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Karima Sifi, Noureddine Soltani

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Annaba gulf is the most important touristic and economic area located on the east coast of Algeria. However, these fishery resources are threatened by the pollution due to the progress of economic activity. As part of a biomonitoring program on the quality of waters of the Gulf of Annaba, the specific activity of two biomarkers, acetylcholinesterase (AChE) and glutathion S-transferase (GST) has been measured in edible bivalve Donax trunculus. The samples have been collected during the year 2013 in two sites: El Battah, distant from polluted sources, and Sidi Salem, located near the harbor and different industrial waste. The results showed a significant inhibition of AChE activity and a significant increase in the activity of the GST in samples collected from Sidi Salem as compared to El Battah. The inhibition of the AChE and the increase of the GST in Sidi Salem are in relation with the level of exposition of this site to the pollution.

Keywords: Donax trunculus, annaba gulf, acetylcholinesterase, glutathion s-transferase, biomonitoring, pollution

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Authors: Chuen-arom Janthimachai-amorn, Chirawadee Harnrittha

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

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

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Authors: Jorge Ferro-Diaz, Lazaro Marquez-Llauger, Jose Alberto Camejo-Lamas, Lazaro Marquez-Govea

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The invasion of Scaevola sericea Vahl (Goodeniaceae) in Cuba is a recent process, this exotic invasive species was reported for the first time, in the national territory, by 2008. S. sericea is native to the coasts around the Indian Ocean and western Pacific, common on sandy beaches; it has expanded rapidly around the planet by either natural or anthropic causes, mainly due to its use in hotel gardening. Cuba is highly vulnerable to the colonization of these species, mainly due to tropical hurricanes which have increased in the last decades; it also affects other native species such as Tournefortia gnaphalodes (L.) R. Br. (Boraginaceae) that show invasive manifestations because of the unbalanced state of demographic processes of littoral vegetation, which has been studied by authors during the last 10 years. The fast development of Cuban tourism has encouraged the use of exotic species in gardening that invade large sectors of sandy coasts. Taking into account the importance of assessing the impacts dimensions and adopting effective control measures, a monitoring program for the invasion of S. sericea in Cuba was undertaken. The program has been implemented since 2013 and the main objective was to identify invasive patterns and interactions with other native species of coastal vegetation. This experience also aimed to validate the design and propose a standardized monitoring protocol to be applied throughout the country. In the Cuban territory, 12 sites were chosen, where there were established 24 permanent plots of 100 m2; measurements were taken twice a year taking into consideration variables such as abundance, plant height, soil cover, flora and companion vegetation, density and frequency; other physical variables of the beaches were also measured. Similarly, for associated individuals of T. gnaphalodes, the same variables were measured. The results of these first four years allowed us to document patterns of S. sericea invasion, highlighting the use of adventitious roots to enhance their colonization, and to characterize demographic indicators, ecosystem affections, and interactions with native plants. A density-dependent relationship with T. gnaphalodes was documented, finding a controlling effect on S. sericea, so that a manipulation experiment was applied to evaluate possible management actions to be incorporated in the Plans of the protected areas involved. With these results, it was concluded, for the evaluated sites, that S. sericea has had an invasion dynamics ruled by effects of coastal dynamics, more intense in beaches with affectations to the native vegetation, and more controlled in beaches with more preserved vegetation. It was found that when S. sericea is established, the mechanism that most reinforces its invasion is the use of adventitious roots, used to expand the patches and colonize beach sectors. It was also found that when the density of T. gnaphalodes increases, it detains the expansion of S. sericea and reduces its colonization possibilities, behaving as a natural controller of its biological invasion. The results include a proposal of a new Monitoring Protocol for Scaevola sericea in Cuba, with the possibility of extending its implementation to other countries in the region.

Keywords: biological invasion, exotic invasive species, plant interactions, Scaevola sericea

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Authors: Gabriel Jinga, Madalina Dumitru

Abstract:

The objective of this paper is to present the process of change in management accounting in Romania, a former communist country from Eastern Europe. In order to explain this process, we used the contingency and institutional theories. We focused on the following directions: the presentation of the scientific context and motivation of this research and the case study. We presented the state of the art in the process of change in the management accounting from the international and national perspective. We also described the evolution of management accounting in Romania in the context of economic and political changes. An important moment was the fall of communism in 1989. This represents a starting point for a new economic environment and for new management accounting. Accordingly, we developed a case study which presented this evolution. The conclusion of our research was that the changes in the management accounting system of the company analysed occurred in the same time with the institutionalization of some elements (e.g. degree of competition, training and competencies in management accounting). The management accounting system was modeled by the contingencies specific to this company (e.g. environment, industry, strategy).

Keywords: management accounting, change, Romania, contingency, institutional theory

Procedia PDF Downloads 516