Search results for: clustering comparison.

Authors: Lena Payati, Maria Kazou, Effie Tsakalidou

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Table olives are one of the most popular fermented vegetables worldwide, which along with olive oil, have a crucial role in the world economy. They are highly appreciated by the consumers for their characteristic taste and pleasant aromas, while several health and nutritional benefits have been reported as well. Until recently, microbial biogeography, i.e., the study of microbial diversity over time and space, has been mainly associated with wine. However, nowadays, the term 'terroir' has been extended to other crops and food products so as to link the geographical origin and environmental conditions to quality aspects of fermented foods. Taking the above into consideration, the present study focuses on the microbial fingerprinting of the most important olive varieties of Greece with the state-of-the-art amplicon-based metagenomics analysis. Towards this, in 2019, 61 samples from 38 different olive varieties were collected at the final stage of ripening from 13 well spread geographical regions in Greece. For the metagenomics analysis, total DNA was extracted from the olive samples, and the 16S rRNA gene and ITS DNA region were sequenced and analyzed using bioinformatics tools for the identification of bacterial and yeasts/fungal diversity, respectively. Furthermore, principal component analysis (PCA) was also performed for data clustering based on the average microbial composition of all samples from each region of origin. According to the composition, results obtained, when samples were analyzed separately, the majority of both bacteria (such as Pantoea, Enterobacter, Roserbergiella, and Pseudomonas) and yeasts/fungi (such as Aureobasidium, Debaromyces, Candida, and Cladosporium) genera identified were found in all 61 samples. Even though interesting differences were observed at the relative abundance level of the identified genera, the bacterial genus Pantoea and the yeast/fungi genus Aureobasidium were the dominant ones in 35 and 40 samples, respectively. Of note, olive samples collected from the same region had similar fingerprint (genera identified and relative abundance level) regardless of the variety, indicating a potential association between the relative abundance of certain taxa and the geographical region. When samples were grouped by region of origin, distinct bacterial profiles per region were observed, which was also evident from the PCA analysis. This was not the case for the yeast/fungi profiles since 10 out of the 13 regions were grouped together mainly due to the dominance of the genus Aureobasidium. A second cluster was formed for the islands Crete and Rhodes, both of which are located in the Southeast Aegean Sea. These two regions clustered together mainly due to the identification of the genus Toxicocladosporium in relatively high abundances. Finally, the Agrinio region was separated from the others as it showed a completely different microbial fingerprinting. However, due to the limited number of olive samples from some regions, a subsequent PCA analysis with more samples from these regions is expected to yield in a more clear clustering. The present study is part of a bigger project, the first of its kind in Greece, with the ultimate goal to analyze a larger set of olive samples of different varieties and from different regions in Greece in order to have a reliable olives’ microbial biogeography.

Keywords: amplicon-based metagenomics analysis, bacteria, microbial biogeography, olive microbiota, yeasts/fungi

Procedia PDF Downloads 104

Authors: Renalda El Samra, Elie Bou-Zeid, Hamza Kunhu Bangalath, Georgiy Stenchikov, Mutasem El Fadel

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The regional-scale impact of climate change over complex terrain was examined through high-resolution dynamic downscaling conducted using the Weather Research and Forecasting (WRF) model, with initial and boundary conditions from a High-Resolution Atmospheric Model (HiRAM). The analysis was conducted over the eastern Mediterranean, with a focus on the country of Lebanon, which is characterized by a challenging complex topography that magnifies the effect of orographic precipitation. Four year-long WRF simulations, selected based on HiRAM time series, were performed to generate future climate projections of extreme temperature and precipitation over the study area under the conditions of the Representative Concentration Pathway (RCP) 4.5. One past WRF simulation year, 2008, was selected as a baseline to capture dry extremes of the system. The results indicate that the study area might be exposed to a temperature increase between 1.0 and 3ºC in summer mean values by 2050, in comparison to 2008. For extreme years, the decrease in average annual precipitation may exceed 50% at certain locations in comparison to 2008.

Keywords: HiRAM, regional climate modeling, WRF, Representative Concentration Pathway (RCP)

Procedia PDF Downloads 386

Authors: Moohyun Lee, Soojung Hur, Yongwan Park

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In this paper is proposed a method uses only LIDAR system to classification an obstacle and determine its type by establishing database for classifying obstacles based on LIDAR. The existing LIDAR system, in determining the recognition of obstruction in an autonomous vehicle, has an advantage in terms of accuracy and shorter recognition time. However, it was difficult to determine the type of obstacle and therefore accurate path planning based on the type of obstacle was not possible. In order to overcome this problem, a method of classifying obstacle type based on existing LIDAR and using the width of obstacle materials was proposed. However, width measurement was not sufficient to improve accuracy. In this research, the width data was used to do the first classification; database for LIDAR intensity data by four major obstacle materials on the road were created; comparison is made to the LIDAR intensity data of actual obstacle materials; and determine the obstacle type by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that data declined in quality in comparison to 3D LIDAR and it was possible to classify obstacle materials using 2D LIDAR.

Keywords: obstacle, classification, database, LIDAR, segmentation, intensity

Procedia PDF Downloads 332

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

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Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

Procedia PDF Downloads 575

Authors: Rugang Tian

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In this study, we generated whole-genome sequence (WGS) data from110 native cattle. Together with whole-genome sequences from world-wide cattle populations, we estimated the genetic diversity and population genetic structure of different cattle populations. Our findings revealed clustering of cattle groups in line with their geographic locations. We identified noticeable genetic diversity between indigenous cattle breeds and commercial populations. Among all studied cattle groups, lower genetic diversity measures were found in commercial populations, however, high genetic diversity were detected in some local cattle, particularly in Rashoki and Mongolian breeds. Our search for potential genomic regions under selection in native cattle revealed several candidate genes related with immune response and cold shock protein on multiple chromosomes such as TRPM8, NMUR1, PRKAA2, SMTNL2 and OXR1 that are involved in energy metabolism and metabolic homeostasis.

Keywords: cattle, whole-genome, population structure, adaptation

Procedia PDF Downloads 53

Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

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The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

Procedia PDF Downloads 357

Authors: Seyed Hossein Alavi, Farshad Ghazalian, Soghra Jamshidi

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Nowadays, athletic aggression discussion is considered as an important issue in sports psychology and sports effects have been noted by researchers from a long time ago. In this research, the amount of aggression among athletic students of different sport courses will be surveyed and compared. Statistics society in this research consists of all of boy athletic students in wrestling, taekwondo, football, and basketball of Mahmoudabad City that are 200 persons and the limitation of their ages are between 12-15 years old. Among all athletic students of different sport courses, 40 persons were chosen randomly for the sample. The method of research is a descriptive-comparative type that has been done according to field study and for measurement of examinations aggression amount, we have used Ayzank exam. In analysis step of foundations, for comparison of aggression of examined group, we have used Varian’s analysis exam. Research results show that among aggression amounts of athletic students of wrestling, taekwondo, football and basketball, there is no fundamental difference (p < 0.05). Stimulation of guest team with the host team fans, referees performance, exhaustion, physical confrontations, team position in the tournament table, and so on. There is no significant difference among aggression amount of selected sport athletic students.

Keywords: aggression, athletic, student, sports

Procedia PDF Downloads 473

Authors: Rajeev Kumar Bedi, Jaswinder Singh, Sunil Kumar Gupta

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Cloud storage is a model of online data storage where data is stored in virtualized pool of servers hosted by third parties (CSPs) and located in different geographical locations. Cloud storage revolutionized the way how users access their data online anywhere, anytime and using any device as a tablet, mobile, laptop, etc. A lot of issues as vendor lock-in, frequent service outage, data loss and performance related issues exist in single cloud storage systems. So to evade these issues, the concept of multi cloud storage introduced. There are a lot of multi cloud storage systems exists in the market for mobile devices. In this article, we are providing comparison of four multi cloud storage systems for mobile devices Otixo, Unclouded, Cloud Fuze, and Clouds and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on three mobile phones Nexus 5, Moto G and Nexus 7 tablet and using Wi-Fi network. Finally, open research challenges and future scope are discussed.

Keywords: cloud storage, multi cloud storage, vendor lock-in, mobile devices, mobile cloud computing

Procedia PDF Downloads 391

Authors: Sirous Eydivandi

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Diacylglycerol-O-acyltransferase (DGAT1) gene encodes diacylglycerol transferase enzyme that plays an important role in glycerol lipid metabolism. DGAT1 is considered to be the key enzyme in controlling the synthesis of triglycerides in adipocytes. This enzyme catalyzes the final step of triglyceride synthesis (transform triacylglycerol (DAG) into triacylglycerol (TAG). A total of 20 DGAT1 gene sequences and corresponding amino acids belonging to 4 species include cattle, goats, sheep and yaks were analyzed, and the differentiation within and among the species was also studied. The length of the DGAT1 gene varies greatly, from 1527 to 1785 bp, due to deletion, insertion, and stop codon mutation resulting in elongation. Observed genetic diversity was higher among species than within species, and Goat had more polymorphisms than any other species. Novel amino acid variation sites were detected within several species which might be used to illustrate the functional variation. Differentiation of the DGAT1 gene was obvious among species, and the clustering result was consistent with the taxonomy in the National Center for Biotechnology Information.

Keywords: DGAT1gene, bioinformatic, ruminnants, biotechnology information

Procedia PDF Downloads 478

Authors: Swarnadip Ghosh

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Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

Procedia PDF Downloads 387

Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

Procedia PDF Downloads 358

Authors: C. Rana, S. K. Jain

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The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

Procedia PDF Downloads 400

Authors: O’Day Luke

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Purpose: To validate virtual non-contrast reconstructions generated from dual-layer spectral computed tomography (DL-CT) data as an alternative for the acquisition of a dedicated true non-contrast dataset during multiphase contrast studies. Material and methods: Thirty-three patients underwent a routine multiphase clinical CT examination, using Dual-Layer Spectral CT, from March to August 2021. True non-contrast (TNC) and virtual non-contrast (VNC) datasets, generated from both portal venous and arterial phase imaging were evaluated. For every patient in both true and virtual non-contrast datasets, a region-of-interest (ROI) was defined in aorta, liver, fluid (i.e. gallbladder, urinary bladder), kidney, muscle, fat and spongious bone, resulting in 693 ROIs. Differences in attenuation for VNC and TNV images were compared, both separately and combined. Consistency between VNC reconstructions obtained from the arterial and portal venous phase was evaluated. Results: Comparison of CT density (HU) on the VNC and TNC images showed a high correlation. The mean difference between TNC and VNC images (excluding bone results) was 5.5 ± 9.1 HU and > 90% of all comparisons showed a difference of less than 15 HU. For all tissues but spongious bone, the mean absolute difference between TNC and VNC images was below 10 HU. VNC images derived from the arterial and the portal venous phase showed a good correlation in most tissue types. The aortic attenuation was somewhat dependent however on which dataset was used for reconstruction. Bone evaluation with VNC datasets continues to be a problem, as spectral CT algorithms are currently poor in differentiating bone and iodine. Conclusion: Given the increasing availability of DL-CT and proven accuracy of virtual non-contrast processing, VNC is a promising tool for generating additional data during routine contrast-enhanced studies. This study shows the utility of virtual non-contrast scans as an alternative for true non-contrast studies during multiphase CT, with potential for dose reduction, without loss of diagnostic information.

Keywords: dual-layer spectral computed tomography, virtual non-contrast, true non-contrast, clinical comparison

Procedia PDF Downloads 131

Authors: Sergio S. De Jesus, Aline Santana, Rubens Maciel Filho

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The objective of this study was to choose and determine a green solvent system with similar extraction efficiencies as the traditional Bligh and Dyer method. Sunflower seed oil was extracted using Bligh and Dyer method with 2-methyltetrahydrofuran and isoamyl using alcohol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. At the same time comparative experiments was performed with chloroform and methanol ratios of 1:1; 2:1; 3:1; 1:2; 3:1. Comparison study was done using 5 replicates (n=5). Statistical analysis was performed using Microsoft Office Excel (Microsoft, USA) to determine means and Tukey’s Honestly Significant Difference test for comparison between treatments (α = 0.05). The results showed that using classic method with methanol and chloroform presented the extraction oil yield with the values of 31-44% (w/w) and values of 36-45% (w/w) using green solvents for extractions. Among the two extraction methods, 2 methyltetrahydrofuran and isoamyl alcohol ratio 2:1 provided the best results (45% w/w), while the classic method using chloroform and methanol with ratio of 3:1 presented a extraction oil yield of 44% (w/w). It was concluded that the proposed extraction method using 2-methyltetrahydrofuran and isoamyl alcohol in this work allowed the same efficiency level as chloroform and methanol.

Keywords: extraction, green solvent, lipids, sugarcane

Procedia PDF Downloads 363

Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

Procedia PDF Downloads 479

Authors: Imam Taufik, Hilkatul Ilmi, Puryani, Mochammad Yuwono, Aty Widyawaruyanti

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Artocarpus champeden Spreng stembark (Moraceae) in Indonesia well known as ‘cempedak’ had been traditionally used for malarial remedies. The difference of growth locations could cause the difference of metabolite profiling. As a consequence, there were difference antimalarial activities in spite of the same plants. The aim of this research was to obtain the profile of metabolites that contained in A. champeden stembark from different locations in Indonesia for authentication and quality control purpose of this extract. The profiling had been performed by HPTLC-Densitometry technique and antimalarial activity had been also determined by HRP2-ELISA technique. The correlation between metabolite fingerprinting and antimalarial activity had been analyzed by Principle Component Analysis, Hierarchical Clustering Analysis and Partial Least Square. As a result, there is correlation between the difference metabolite fingerprinting and antimalarial activity from several different growth locations.

Keywords: antimalarial, artocarpus champeden spreng, metabolite fingerprinting, multivariate analysis

Procedia PDF Downloads 298

Authors: Monirah Alkathiry, Hanan Aljarwan

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Cloud computing is one of the most significant technologies that the world deals with, in different sectors with different purposes and capabilities. The cloud faces various challenges in securing data from unauthorized access or modification. Consequently, security risks and levels have greatly increased. Therefore, cloud service providers (CSPs) and users need secure mechanisms that ensure that data are kept secret and safe from any disclosures or exploits. For this reason, CSPs need a number of techniques and technologies to manage and secure access to the cloud services to achieve security goals, such as confidentiality, integrity, identity access management (IAM), etc. Therefore, this paper will review and explore various access controls implemented in a cloud environment that achieve different security purposes. The methodology followed in this survey was conducting an assessment, evaluation, and comparison between those access controls mechanisms and technologies based on different factors, such as the security goals it achieves, usability, and cost-effectiveness. This assessment resulted in the fact that the technology used in an access control affects the security goals it achieves as well as there is no one access control method that achieves all security goals. Consequently, such a comparison would help decision-makers to choose properly the access controls that meet their requirements.

Keywords: access controls, cloud computing, confidentiality, identity and access management

Procedia PDF Downloads 122

Authors: N. A. Soliman, A. F. Omran, A. Tagnit-Hamou

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The finely ground waste glass has successfully used by the authors to develop and patent an ecological ultra-high-performance concrete (UHPC), which was named as ultra-high-performance-glass concrete (UHPGC). After the successful development in laboratory, the current research presents a comparison between traditional UHPC and UHPGC produced using large-scale pilot plant mixer, in terms of rheology, mechanical, and durability properties. The rheology of the UHPGCs was improved due to the non-absorptive nature of the glass particles. The mechanical performance of UHPGC was comparable and very close to the traditional UHPC due to the pozzolan reactivity of the amorphous waste glass. The UHPGC has also shown excellent durability: negligible permeability (chloride-ion ≈ 20 Coulombs from the RCPT test), high abrasion resistance (volume loss index less than 1.3), and almost no freeze-thaw deterioration even after 1000 freeze-thaw cycles. The enhancement in the strength and rigidity of the UHPGC mixture can be referred to the inclusions of the glass particles that have very high strength and elastic modulus.

Keywords: ground glass pozzolan, large-scale production, sustainability, ultra-high performance glass concrete

Procedia PDF Downloads 142

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 140

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 545

Authors: Henry Nicholas Lee, George Thomas, Juliana Johari, Carmilla Freddie, Caroline Val Madin

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Research in comparative and international education often provides value-laden views of an education system within and in between other countries. These views are frequently used by policy makers or educators to explore similarities and differences for, among others, benchmarking purposes. In this study, a comparison is made between Malaysia and England, focusing on the process of writing children went through to create a text, using a multimodal theoretical framework to analyse this comparison. The main purpose is political in nature as it served as an answer to Malaysia’s call for benchmarking of best practices for language learning. Furthermore, the focus on writing in this study adds into more empirical findings about early writers’ writing development and writing improvement, especially for children at the ages of 5-9. In research, comparative studies in English as a Second Language (ESL) writing pedagogy – particularly in Malaysia since the introduction of the Standard- based English Language Curriculum (KSSR) in 2011 as a draft and its full implementation in 2017; reviewed 2018 KSSR-CEFR aligned – has not been done comparatively. In theory, a multimodal theoretical framework somehow allows a logical comparison between first language and ESL which would provide useful insights to illuminate the writing process between Malaysia and England. The comparisons are not representative because of the different school systems in both countries. So far, the literature informs us that the curriculum for language learning is very much emphasised on children’s linguistic abilities, which include their proficiency and mastery of the language, its conventions, and technicalities. However, recent empirical findings suggested that literacy in its concepts and characters need change. In view of this suggestion, the comparison will look at how the process of writing is implemented through the five modes of communication: linguistic, visual, aural, spatial, and gestural. This project draws on data from Malaysia and England, involving 10 teachers, 26 classroom observations, 20 lesson plans, 20 interviews, and 20 brief conversations with teachers. The research focused upon 20 primary children of different genders aged 5-9, and in addition to primary data descriptions, 40 children’s works, 40 brief classroom conversations, 30 classroom photographs, and 30 school compound photographs were undertaken to investigate teachers and children’s use of modes and semiotic resources to design a text. The data were analysed by means of within-case analysis, cross-case analysis, and constant comparative analysis, with an initial stage of data categorisation, followed by general and specific coding, which clustered the data into thematic groups. The study highlights the importance of teachers’ and children’s engagement and interaction with various modes of communication, an adaptation from the English approaches to teaching writing within the KSSR framework and providing ‘voice’ to ESL writers to ensure that both have access to the knowledge and skills required to make decisions in developing multimodal texts and artefacts.

Keywords: comparative education, early writers, KSSR, multimodal theoretical framework, writing development

Procedia PDF Downloads 56

Authors: Jamil Jafari, Sharafat Karimi

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The Arabic Language has a complicated system of prosody invented by the great grammarian Khalil Ibn Ahmad Farahidi. He could extract 15 meters out of his innovative five circles, which were used in Arabic poetry of the 7th and 8th centuries. Then after a while, his student Akhfash added or compensated another meter to his tutor's meters, so overall, we now have 16 different meters in Arabic poetry. These meters have been formed by various combinations of 8 different feet and each foot is combined of rudimentary units called Sabab and Wated which are combinations of movement (/) and silent (ʘ) letters. On the other hand in English, we are dealing with another system of metrical prosody. In this language, feet are consisted of stressed and unstressed syllables and are of six types: iamb, trochee, dactyl, anapest, spondee, and pyrrhic. Using the descriptive-analytic method, in this research we aim at making a comparison between Arabic and English systems of metrical prosody to investigate their similarities and differences. The results show that both of them are quantitative and both of them rely on syllables in afoot. But unlike Arabic, English is utilizing another rhyme system and the number of feet in a line differs from Arabic; also, its feet are combined of stressed and unstressed syllables, while those of Arabic is a combination of movement and silent letters.

Keywords: Arabic prosody, English prosody, foot, meter, poetry

Procedia PDF Downloads 135

Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

Procedia PDF Downloads 160

Authors: Xun Li, Haojie Wang

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Federated learning is a kind of distributed training and centralized training mode, which is of great value in the protection of user privacy. In order to solve the problem that the model is vulnerable to backdoor attacks in federated learning, a backdoor attack detection method based on a weighted k-medoids algorithm is proposed. First of all, this paper collates the update parameters of the client to construct a vector group, then uses the principal components analysis (PCA) algorithm to extract the corresponding feature information from the vector group, and finally uses the improved k-medoids clustering algorithm to identify the normal and backdoor update parameters. In this paper, the backdoor is implanted in the federation learning model through the model replacement attack method in the simulation experiment, and the update parameters from the attacker are effectively detected and removed by the defense method proposed in this paper.

Keywords: federated learning, backdoor attack, PCA, k-medoids, backdoor defense

Procedia PDF Downloads 96

Authors: Nor Khaizan Anuar, Nur Karimah Aziz, Tin Wui Wong, Ahmad Sazali Hamzah, Wan Rozita Wan Engah

Abstract:

The physicochemical attributes and wound healing activity of pectin hydrogel in rat models, following partial thickness thermal injury were investigated. The pectin hydrogel was prepared by solvent evaporation method with the aid of glutaraldehyde as crosslinking agent and glycerol as plasticizer. The physicochemical properties were mainly evaluated using differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) spectroscopy, while the wound healing activity was examined by the macroscopic images, wound size reduction and histological evaluation using haematoxylin and eosin (H&E) stain for 14 days. The DSC and FTIR analysis suggested that pectin hydrogel exhibited higher extent of polymer-polymer interaction at O-H functional group in comparison to the unprocessed pectin. This was indicated by the increase of endothermic enthalpy values from 139.35 ± 13.06 J/g of unprocessed pectin to 156.23 ± 2.86 J/g of pectin hydrogel, as well as the decrease of FTIR wavenumber corresponding to O-H at 3432.07 ± 0.49 cm-1 of unprocessed pectin to 3412.62 ± 13.06 cm-1 of pectin hydrogel. Rats treated with pectin hydrogel had significantly smaller wound size (Student’s t-test, p<0.05) when compared to the untreated group starting from day 7 until day 14. H&E staining indicated that wounds received pectin hydrogel had more fibroblasts, blood vessels and collagen bundles on day 14 in comparison to the untreated rats.

Keywords: pectin, physicochemical, rats, wound

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Authors: Amina Oukennou, Zitouni Beidouri, Otmane Bouksour

Abstract:

Small to Medium-sized enterprises are a very important component of the economy. They are present in the whole industries all over the world. They are considered as the engine for future growth in the economy. Project management is an economical international factor impacting all types of enterprises including the SMEs. This paper has the aim of measuring the weight of using projects and project management in Moroccan SMEs in comparison with the large companies. The study is based on interviews with experts: project managers, managers, directors, and consultants. They were asked questions measuring the weight of using projects, the level of using project management, and the resources employed. Eighteen Moroccan companies from a range of industries and sizes were consulted. All the companies consider projects as a key element in their strategy. Most of them affirm the great usefulness of the approach 'project', especially for the external activities. The main differences lie in the duration and the size of used projects. Despite the commonly shared idea about the importance of the project management, the interviewed persons believe that the project management knowledge has the same importance or less than the technical knowledge. All the companies affirm the need for a simpler version of project management. The content varies from one company to another.

Keywords: project dimension, project management, small to medium-sized entreprise, Morocco

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Authors: Saim Iftikhar Awan, Farhan Ali

Abstract:

Wind power has now become one of the most important resources of renewable energy. The machine which extracts kinetic energy from wind is wind turbine. This work is all about the electrical power analysis of horizontal axis wind turbine to check the efficiency of different configurations of wind turbines to get maximum output and comparison of experimental and Computational Fluid Dynamics (CFD) results. Different experiments have been performed to obtain that configuration with the help of which we can get the maximum electrical power output by changing the different parameters like the number of blades, blade shape, wind speed, etc. in first step experimentation is done, and then the similar configuration is designed in 3D CAD software. After a series of experiments, it has been found that the turbine with four blades at an angle of 75° gives maximum power output and increase in wind speed increases the power output. The models designed on CAD software are imported on ANSYS-FLUENT to predict mechanical power. This mechanical power is then converted into electrical power, and the results were approximately the same in both cases. In the end, a comparison has been done to compare the results of experiments and ANSYS-FLUENT.

Keywords: computational analysis, power efficiency, wind energy, wind turbine

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Authors: Nety Trisnawaty, Mirna Febriani

Abstract:

The use of stainless steel wires in the field of dentistry is widely used, especially for orthodontic and prosthodontic treatment using stainless steel wire. The oral cavity is the ideal environment for corrosion, which can be caused by saliva. Prevention of corrosion on stainless steel wires can be done by using an organic or non-organic corrosion inhibitor. One of the organic inhibitors that can be used to prevent corrosion is black tea leaves extracts. To explain the comparison of chromium ions release for stainlees steel between artificial saliva and black tea leaves extracts. In this research we used artificial saliva, black tea leaves extracts, stainless steel wire and using Atomic Absorption Spectrophometric testing machine. The samples were soaked for 1, 3, 7 and 14 days in the artificial saliva and black tea leaves extracts. The results showed the difference of chromium ion release soaked in artificial saliva and black tea leaves extracts on days 1, 3, 7 and 14. Statistically, calculation with independent T-test with p < 0,05 showed a significant difference. The longer the duration of days, the more ion chromium were released. The conclusion of this study shows that black tea leaves extracts can inhibit the corrosion rate of stainless steel wires.

Keywords: chromium ion, stainless steel, artificial saliva, black tea leaves extracts

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Authors: Linyu Wang, Furui Huo, Jianhong Xiang

Abstract:

The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low SNR stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

Procedia PDF Downloads 85

Authors: Muhammad Yusuf, Abdul Latief Toleng, Djoni Prawira Rahardja, Ambo Ako, Sahiruddin Sahiruddin, Abdi Eriansyah

Abstract:

The objective of this study was to know the reproductive performance of dairy cows at different parities. A total of 60 dairy Holstein-Friesian cows with parity one to three from five small farms raised by the farmers were used in the study. All cows were confined in tie stall barn with rubber on the concrete floor. The herds were visited twice for survey with the help of a questionnaire. Reproductive parameters used in the study were days open, calving interval, and service per conception (S/C). The results of this study showed that the mean (±SD) days open of the cows in parity 2 was slightly longer than those in parity 3 (228.2±121.5 vs. 205.5±144.5; P=0.061). None cows conceived within 85 days postpartum in parity 3 in comparison to 13.8% cows conceived in parity 2. However, total cows conceived within 150 days post partum in parity 2 and parity 3 were 30.1% and 36.4%, respectively. Likewise, after reaching 210 days after calving, number of cows conceived in parity 3 had higher than number of cows in parity 2 (72.8% vs. 44.8%; P<0.05). The mean (±SD) calving interval of the cows in parity 2 and parity 3 were 508.2±121.5 and 495.5±144.1, respectively. Number of cows with calving interval of 400 and 450 days in parity 3 was higher than those cows in parity 2 (23.1% vs. 17.2% and 53.9% vs. 31.0%). Cows in parity 1 had significantly (P<0.01) lower number of S/C in comparison to the cows with parity 2 and parity 3 (1.6±1.2 vs. 3.5±3.4 and 3.3±2.1). It can be concluded that reproductive performance of the cows is affected by different parities.

Keywords: dairy cows, parity, days open, calving interval, service per conception

Procedia PDF Downloads 246