Search results for: initial teacher training
3717 A Comparison of Performance Indicators Between University-Level Rugby Union and Rugby Union Sevens Matches
Authors: Pieter van den Berg, Retief Broodryk, Bert Moolman
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Firstly, this study aimed to identify which performance indicators (PIs) discriminate between winning and losing university-level Rugby Union (RU) teams and, secondly, to compare the significant PIs in RU and Rugby Union Sevens (RS) at university level. Understanding the importance of PIs and their effect on match outcomes could assist coaching staff to prioritise specific game aspects during training to increase performance. Twenty randomly selected round-robin matches of the 2018 Varsity Cup (n=20), and Varsity Sports sevens (n=20) tournaments were analysed. A linear mixed model was used to determine statistical significant differences set at p≤0.05 while effect size was reported according to Cohen's d value. Results revealed that various PIs discriminated between winning and losing RU teams and that specific PIs could be observed as significant in both RU and RS. Therefore, specific identified tactical aspects of RU and RS should be prioritised to optimise performanceKeywords: match success, notational analysis, performance analysis, rugby, video analysis
Procedia PDF Downloads 713716 Beneath the Leisurely Surface: An Analysis of the Piano Lesson Frenzy among Chinese Middle-Class Parents
Authors: Yijie Wang, Tianyue Wang
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In the past two decades, there has been a great ‘piano lesson frenzy’ among Chinese middle-class families, with a large number of parents adding piano training to children’s extra-curriculum lists. Superficially, the frenzy reflects a rather ‘leisurely’ attitude: parents typically claim that pianos lessons are ‘just for fun’ and will hopefully render children’s life more exciting. However, a closer scrutiny reveals that there is great social-status anxiety hidden beneath this ‘leisurely’ surface. Based on pre-interviews of six Chinese middle-class parents who have enthusiastically signed their children up for piano lessons, several tentative analysis are made: 1. Owing to a series of historical and social factors, the Chinese middle-class have yet to establish their cultural norms in the past few decades, resulting in great confusion concerning how to cultivate cultural tastes in their offspring. And partly due to the fact that the middle-class status of the past Chinese generation is mostly self-acquired rather than inherited, parents are much less confident about their cultural resources—which require long-time accumulation—than material ones. Both factors combine to lead to a sort of blind, overcompensating enthusiasm in culture-related education, and the piano frenzy is but a demonstration. 2. The piano has been chosen to be the object of the frenzy partly because of its inherent characteristics as well as socially-constructed ones. Costly, large in size, imported from another culture and so forth, the piano has acquired the meaning of being exclusive, high-end and exotic, which renders it a token of top-tier status among Chinese people, and piano lessons for offspring have therefore become parents’ paths towards a kind of ‘symbolic elevation’. A child playing piano is an exhibition as well as psychological assurance of the families’ middle-class status. 3. A closer look at children’s piano training process reveals that there is much more anxiety than leisurely elements involved. Despite parents’ claim that ‘piano is mainly for kids to have fun,’ the whole process is evidently of a rather ‘ascetic’ nature, with the demands of diligence and senses of time urgency throughout, and techniques rather than flair or styles are emphasized. This either means that the apparent ‘piano-for-fun’ stance is unauthentic and is only other motives in disguise, or that the Chinese middle-class parents are not yet capable of shaking off the sense of anxiety even if they sincerely intend to. 4. When viewed in relation to Chinese formal school system as well as the job market at large, it can be said that by signing children up for piano lessons, parents are consciously or unconsciously seeking to prepare for, or reduce the risks of, their children’s future social mobility. In face of possible failures in the highly-crucial, highly-competitive formal school system, piano-playing as an extra-curriculum activity may be conveniently transferred into an alternative career path. Besides, in contemporary China, as the occupational structure goes through change, and the school-related certificates decline in value, aspects such as a person’s overall deportment, which can be gained or proved by piano-learning, have been gaining in significance.Keywords: extra-curriculum activities, middle class, piano lesson frenzy, status anxiety
Procedia PDF Downloads 2453715 Synthesis of Nano Iron Copper Core-Shell by Using K-M Reactor
Authors: Mohamed Ahmed AbdelKawy, A. H. El-Shazly
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In this study, Nano iron-copper core-shell was synthesized by using Kinetic energy micro reactor ( K-M reactor). The reaction between nano-pure iron with copper sulphate pentahydrate (CuSO4.5H2O) beside NaCMC as a stabilizer at K-M reactor gives many advantages in comparison with the traditional chemical method for production of nano iron-Copper core-shell in batch reactor. Many factors were investigated for its effect on the process performance such as initial concentrations of nano iron and copper sulphate pentahydrate solution. Different techniques were used for investigation and characterization of the produced nano iron particles such as SEM, XRD, UV-Vis, XPS, TEM and PSD. The produced Nano iron-copper core-shell particle using micro mixer showed better characteristics than those produced using batch reactor in different aspects such as homogeneity of the produced particles, particle size distribution and size, as core diameter 10nm particle size were obtained. The results showed that 10 nm core diameter were obtained using Micro mixer as compared to 80 nm core diameter in one-fourth the time required by using traditional batch reactor and high thickness of copper shell and good stability.Keywords: nano iron, core-shell, reduction reaction, K-M reactor
Procedia PDF Downloads 3093714 Presenting the Mathematical Model to Determine Retention in the Watersheds
Authors: S. Shamohammadi, L. Razavi
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This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.Keywords: model, mathematical, retention, watershed, SCS
Procedia PDF Downloads 4573713 Development of Low-Cost Vibro-Acoustic, and Fire-Resistant, Insulation Material from Natural and Sustainable Sources
Authors: K. Nasir, S. Ahmad, A. Khan, H. Benkreira
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The topic of the research is to develop sustainable fire-resistant materials for vibration and acoustic damping of structure and airborne noises from sustainable recycled materials and biodegradable binders. The paper reports, methods and techniques of enhancing fire resistive, vibration and acoustic properties of building insulation materials made from natural resources like wood and recycled materials like rubber and textile waste. The structures are designed to optimize the number, size and stratification of closed (heat insulating) and open (noise insulating) pores. The samples produced are tested for their heat and noise insulating properties, including vibration damping and their structural properties (airflow resistivity, porosity, tortuosity and elastic modulus). The structural properties are then used in theoretical models to check the acoustic insulation measurements. Initial data indicate that one layer of such material can yield as much as 18 times more damping, increasing the loss factor by 18%.Keywords: fire resistant, vibration damping, acoustic material, vibro-acoustic, thermal insulation, sustainable material, low cost materials, recycled materials, construction material
Procedia PDF Downloads 1343712 An Empirical Study on the Integration of Listening and Speaking Activities with Writing Instruction for Middles School English Language Learners
Authors: Xueyan Hu, Liwen Chen, Weilin He, Sujie Peng
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Writing is an important but challenging skill For English language learners. Due to the small amount of time allocated for writing classes at schools, students have relatively few opportunities to practice writing in the classroom. While the practice of integrating listening and speaking activates with writing instruction has been used for adult English language learners, its application for young English learners has seldom been examined due to the challenge of listening and speaking activities for young English language learners. The study attempted to integrating integrating listening and speaking activities with writing instruction for middle school English language learners so as to improving their writing achievements and writing abilities in terms of the word use, coherence, and complexity in their writings. Guided by Gagne's information processing learning theory and memetics, this study conducted a 8-week writing instruction with an experimental class (n=44) and a control class (n=48) . Students in the experimental class participated in a series of listening and retelling activities about a writing sample the teacher used for writing instruction during each period of writing class. Students in the control class were taught traditionally with teachers’ direction instruction using the writing sample. Using the ANCOVA analysis of the scores of students’ writing, word-use, Chinese-English translation and the text structure, this study showed that the experimental writing instruction can significantly improve students’ writing performance. Compared with the students in the control class, the students in experimental class had significant better performance in word use and complexity in their essays. This study provides useful enlightenment for the teaching of English writing for middle school English language learners. Teachers can skillfully use information technology to integrate listening, speaking, and writing teaching, considering students’ language input and output. Teachers need to select suitable and excellent composition templates for students to ensure their high-quality language input.Keywords: wring instruction, retelling, English language learners, listening and speaking
Procedia PDF Downloads 823711 Immigrant Workers’ Perspectives of Occupational Health and Safety and Work Conditions that Challenge Work Safety
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
Procedia PDF Downloads 1133710 Deep Learning Strategies for Mapping Complex Vegetation Patterns in Mediterranean Environments Undergoing Climate Change
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
Procedia PDF Downloads 883709 Deep Learning in Chest Computed Tomography to Differentiate COVID-19 from Influenza
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
Procedia PDF Downloads 1423708 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models
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
Procedia PDF Downloads 1693707 Influence of the Compression Force and Powder Particle Size on Some Physical Properties of Date (Phoenix dactylifera) Tablets
Authors: Djemaa Megdoud, Messaoud Boudaa, Fatima Ouamrane, Salem Benamara
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In recent years, the compression of date (Phoenix dactylifera L.) fruit powders (DP) to obtain date tablets (DT) has been suggested as a promising form of valorization of non commercial valuable date fruit (DF) varieties. To further improve and characterize DT, the present study aims to investigate the influence of the DP particle size and compression force on some physical properties of DT. The results show that independently of particle size, the hardness (y) of tablets increases with the increase of the compression force (x) following a logarithmic law (y = a ln (bx) where a and b are the constants of model). Further, a full factorial design (FFD) at two levels, applied to investigate the erosion %, reveals that the effects of time and particle size are the same in absolute value and they are beyond the effect of the compression. Regarding the disintegration time, the obtained results also by means of a FFD show that the effect of the compression force exceeds 4 times that of the DP particle size. As final stage, the color parameters in the CIELab system of DT immediately after their obtaining are differently influenced by the size of the initial powder.Keywords: powder, tablets, date (Phoenix dactylifera L.), hardness, erosion, disintegration time, color
Procedia PDF Downloads 4303706 The Lean Manufacturing Practices in an Automotive Company Using Value Stream Mapping Technique
Authors: Seher Arslankaya, Merve Si̇mge Usuk
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Lean manufacturing, which is based on the Toyota Production System, has focused on increasing the performance in various fields by eliminating the waste. By waste elimination, the lead time is reduced significantly and lean manufacturing provides companies with an important privilege under today's competitive conditions. The initial point of lean thinking is the value. This notion create of a specific product with specific properties for which the customer is ready to pay and which satisfies his needs within a specific time frame and at a specific price. Considering this, the final customer determines the value but the manufacturer creates this value of the product. The value stream is the whole set of activities required for each product. These activities may or may not be essential for the value. Through value stream mapping, all employees can see the sources of waste and develop future cases to eliminate it. This study focused on manufacturing to eliminate the waste which created a cost but did not create any value. The study was carried out at the Department of Assembly/Logistics at Toyota Motor Manufacturing Turkey from the automotive industry with a high product mix and variable demands. As a result of the value stream analysis, improvements are planned for the future cases. The process was improved by applying these suggestions.Keywords: lead time, lean manufacturing, performance improvement, value stream papping
Procedia PDF Downloads 3113705 Application of Artificial Neural Network in Initiating Cleaning Of Photovoltaic Solar Panels
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
Procedia PDF Downloads 1443704 Construction and Evaluation of Soybean Thresher
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
Procedia PDF Downloads 4863703 Judicial Activism and the Supreme Court of India
Authors: Shreeya Umashankar
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The Supreme Court of India has emerged as the most powerful organ of State and amongst the foremost constitutional courts in the world through the instrument of Public Interest Litigation (PIL), the exercise of writ jurisdiction and the expansive interpretation of fundamental rights guaranteed by the Constitution of India. Judicial activism impinging on every facet of governance has become the norm in recent times. This paper traces the evolution of judicial activism since Independence through pronouncements of the Supreme Court. It brings out distinct phases in this evolution– the initial phase of judicial restraint, the first phase of an activist judiciary where the Supreme Court primarily was concerned with protection of fundamental rights and humane treatment of citizens; the second phase where the Supreme Court took keen interest in preservation and protection of the environment; the third phase where the Supreme Court extended its reach into the socio-economic arena and the fourth phase when issues of transparency and probity in governance led to interventions by the Supreme Court. The paper illustrates through judgements of the Supreme Court that the instrument of the PIL and the exercise of writ jurisdiction by the Supreme Court go beyond the traditional postulates of judicial processes and political theory on separation of powers between the organs of State.Keywords: fundamental rights, judicial activism, public interest litigation, Supreme Court of India
Procedia PDF Downloads 6263702 Improved Multi-Channel Separation Algorithm for Satellite-Based Automatic Identification System Signals Based on Artificial Bee Colony and Adaptive Moment Estimation
Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo
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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation
Procedia PDF Downloads 1863701 Comparing Nonverbal Deception Detection of Police Officers and Human Resources Students in the Czech Republic
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
Procedia PDF Downloads 4313700 Developed CNN Model with Various Input Scale Data Evaluation for Bearing Faults Prognostics
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
Procedia PDF Downloads 2103699 FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule
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
Procedia PDF Downloads 2533698 Application of Artificial Neural Network for Prediction of High Tensile Steel Strands in Post-Tensioned Slabs
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
Procedia PDF Downloads 2213697 A Theorem Related to Sample Moments and Two Types of Moment-Based Density Estimates
Authors: Serge B. Provost
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Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.Keywords: density estimation, log-density, polynomial adjustments, sample moments
Procedia PDF Downloads 1653696 Cultural Competence in Palliative Care
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
Procedia PDF Downloads 743695 Constraints Women Academician's Participation at Administrative Positions in Higher Education of Developing Countries
Authors: Bahieh Mohajeri, Mohamad Sharif Mustaf, Mahani Mokhtar
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Purpose: This paper attempts to set the stage for the exploration of female participation in administrative positions within non-western countries by reviewing the studies on female in administrative positions within non-western countries and suggesting guidelines for future studies in this area in developing countries. Methodology: The paper is based on a systematic review of papers that have been published in journals. Findings: The review focuses on constraints to female’s participation in higher education of developing countries (e.g. strong family responsibility, low levels of women faculty members, social values and gendered cultural factors). Practical Implications: Further guidelines for future examination of this field of study are suggested (e.g. adopting a different theoretical view).Value: The article is an initial attempt to gather knowledge about constraints of female administrators in higher education of developing countries. The subject has received less attention in studies on administration and gender. In addition, the article provides suggestions for future studies in order to understand women administrators’ experiences in different educational and cultural settings.Keywords: administrative position, female administrator, developing countries, participation
Procedia PDF Downloads 2603694 Effect of Digital Technology on Students Interest, Achievement and Retention in Algebra in Abia State College of Education (Technical) Arochukwu
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
Procedia PDF Downloads 2093693 Sustainable Development through Cleaner Production in India: Barriers and Possible Directions for Implementation Based on Case Study
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
Procedia PDF Downloads 3733692 Relay Node Placement for Connectivity Restoration in Wireless Sensor Networks Using Genetic Algorithms
Authors: Hanieh Tarbiat Khosrowshahi, Mojtaba Shakeri
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Wireless Sensor Networks (WSNs) consist of a set of sensor nodes with limited capability. WSNs may suffer from multiple node failures when they are exposed to harsh environments such as military zones or disaster locations and lose connectivity by getting partitioned into disjoint segments. Relay nodes (RNs) are alternatively introduced to restore connectivity. They cost more than sensors as they benefit from mobility, more power and more transmission range, enforcing a minimum number of them to be used. This paper addresses the problem of RN placement in a multiple disjoint network by developing a genetic algorithm (GA). The problem is reintroduced as the Steiner tree problem (which is known to be an NP-hard problem) by the aim of finding the minimum number of Steiner points where RNs are to be placed for restoring connectivity. An upper bound to the number of RNs is first computed to set up the length of initial chromosomes. The GA algorithm then iteratively reduces the number of RNs and determines their location at the same time. Experimental results indicate that the proposed GA is capable of establishing network connectivity using a reasonable number of RNs compared to the best existing work.Keywords: connectivity restoration, genetic algorithms, multiple-node failure, relay nodes, wireless sensor networks
Procedia PDF Downloads 2413691 Internal Power Recovery in Cryogenic Cooling Plants Part I: Expander Development
Authors: Ambra Giovannelli, Erika Maria Archilei
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The amount of the electrical power required by refrigeration systems is relevant worldwide. It is evaluated in the order of 15% of the total electricity production taking refrigeration and air-conditioning into consideration. For this reason, in the last years several energy saving techniques have been proposed to reduce the power demand of such plants. The paper deals with the development of an innovative internal recovery system for cryogenic cooling plants. Such a system consists in a Compressor-Expander Group (CEG) designed on the basis of the automotive turbocharging technology. In particular, the paper is focused on the design of the expander, the critical component of the CEG system. Due to the low volumetric flow entering the expander and the high expansion ratio, a commercial turbocharger expander wheel was strongly modified. It was equipped with a transonic nozzle, designed to have a radially inflow full admission. To verify the performance of such a machine and suggest improvements, two different set of nozzles have been designed and modelled by means of the commercial Ansys-CFX software. steady-state 3D CFD simulations of the second-generation prototype are presented and compared with the initial ones.Keywords: vapour cCompression systems, energy saving, refrigeration plant, organic fluids, radial turbine
Procedia PDF Downloads 2083690 Effective Teaching Pyramid and Its Impact on Enhancing the Participation of Students in Swimming Classes
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
Procedia PDF Downloads 1473689 Sustainable Wood Stains Derived From Natural Dyes for Green Applications
Authors: Alexis Dorado, Aralyn Quintos
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This study explores the utilization of natural dyes for wood stains as a transformative agent for wood, encompassing color alteration, grain enhancement, and protection against harm. Commonly, wood stains are petroleum-based and synthetically derived. Notably, commercially accessible wood stains exhibit around 4% greater volatility than the formulated wood stain (FWS), potentially indicating a heightened environmental impact. The application of FWS does not significantly affect the performance of polyurethane varnish. The impact of incorporating an FWS when was applied to Gmelina arborea wood sample, the initial lightness value (L*) of 68.5, a* 7.7, b* 29.2 decreased to 44.36, a* 23.49, b* 32.60, where a* denotes the red/ green value, b* denotes the yellow/ blue, indicating a shift towards darker shades. This alteration in lightness suggests that the FWS contains compounds or pigments that effectively absorb or scatter light, resulting in a change in the perceived color and visual appearance of the wood surface. Moreover, the successful formulation of an eco-friendly natural wood stain is detailed, presenting a promising alternative. This method finds applicability in the domains of furniture and handicraft creation, offering a sustainable choice for creative artisans.Keywords: formulated wood stain (FWS), natural dyes, wood stains, eco-friendly natural wood stain,
Procedia PDF Downloads 983688 Dismantling the School-to-Prison Pipeline through Technology: A Literature Review
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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