Search results for: contextualized classifier

Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

Abstract:

Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

Procedia PDF Downloads 427

Authors: Rana Alghamdi

Abstract:

This study explored teachers’ perceptions of rough-and-tumble (R&T) play in early childhood education in Saudi Arabia. The literature on rough-and-tumble play in Saudi Arabia is limited in scope, and more research is needed to explore teachers’ perceptions on this type of play for early learners. The pertinent literature reveals that R&T play, which includes running, jumping, fighting, wrestling, chasing, pulling, pushing, and climbing, among other rough playful activities, can positively impact learning and development across psychosocial, emotional, and cognitive domains. Teachers’ understanding of R & T play is key, and the attitudes of Saudi early childhood teachers who are responsible for implementing curriculum-based play have not been fully researched. Four early childhood teachers from an urban Saudi preschool participated in the study. The data collected in this study were interpreted through a sociocultural lens. Data sources included in-depth interviews, photo-elicitation interviews, and participant-generated drawings. Three overarching themes emerged: teachers’ concerns about rough-and-tumble play, teachers’ perceptions about the benefits of rough-and-tumble play, and teachers’ expression of gender roles in R & T play as contextualized within Saudi culture. Saudi teachers’ perceptions are discussed in detail, and implications of the findings and recommendations for future research are put forth.

Keywords: rough and tumble play, gender, culture, early childhood, Saudi Arabia

Procedia PDF Downloads 103

Authors: Rafik Ouared

Abstract:

The purpose of this paper is to invalidate decisions made by the Islamic conference led at Istanbul in 2016, which had defined two basic criteria to determine the start of the lunar month: (1)they are all based on the sighting of the crescent, be it observed or computed with modern methods, and (2) they've strongly recommended the adoption of the principle of 'unification of sighting', by which any occurrence of sighting anywhere would be applicable everywhere. To demonstrate the invalidation of those statements, a survey of 101 years of data, from 1938 to 2038, have been analyzed to compare the probability density function (PDF) of time difference between different types of fajr and new moon. Two groups of fajr have been considered: the 'natural fajr', which is the very first fajr following new moon, and the 'biased fajr', which is defined by human being inclusively of all chosen definitions. The parametric and non-parametric statistical comparisons between the different groups have shown the all the biased PDFs are significantly different from the unbiased (natural) PDF with probability value (p-value) less than 0.001. The significance level was fixed to 0.05. Conclusion: the on-going reference to sighting of crescent is inducing an significant bias in defining lunar calendar. Therefore, 'natural' calendar would be more applicable requiring a more contextualized revision of issue in fiqh.

Keywords: biased fajr, lunar calendar, natural fajr, probability density function, sighting of crescent, time difference between fajr and new moon

Procedia PDF Downloads 183

Authors: Andrey V. Timofeev

Abstract:

The paper presents new results concerning selection of optimal information fusion formula for ensembles of C-OTDR channels. The goal of information fusion is to create an integral classificator designed for effective classification of seismoacoustic target events. The LPBoost (LP-β and LP-B variants), the Multiple Kernel Learning, and Weighing of Inversely as Lipschitz Constants (WILC) approaches were compared. The WILC is a brand new approach to optimal fusion of Lipschitz Classifiers Ensembles. Results of practical usage are presented.

Keywords: Lipschitz Classifier, classifiers ensembles, LPBoost, C-OTDR systems

Procedia PDF Downloads 430

Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

Abstract:

Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

Procedia PDF Downloads 201

Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

Abstract:

Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

Procedia PDF Downloads 183

Authors: Ghada Shahrour, Nusiebeh Ananbh, Heyam Dalky, Mohammad Rababa, Fatmeh Alzoubi

Abstract:

Positive teacher-student relationship has been found to affect students’ attitudes towards bullying and, in turn, their engagement in bullying behavior. However, no investigation has been conducted to explore whether teacher-student relationship affects teachers’ attitudes towards bullying. The aim of this study was to examine the role of teacher-student relationship on teachers’ attitudes towards bullying in terms of bullying seriousness, empathic responding, and likelihood to intervene in bullying situation. A cross-sectional, descriptive design was employed among a convenience sample of 173 school teachers (50.9% female) of 12 to 17-year-old students. The teachers were recruited from secondary public schools of three governorates in the Northern district of Jordan. Each group of students has multiple teachers for different subjects. Results showed that teacher-student relationship is partially related to teachers’ attitudes towards bullying. More specifically, having a close teacher-student relationship significantly increased teachers’ perception of bullying seriousness and empathy but not the likelihood to intervene. Research is needed to examine teachers’ obstacles for not providing bullying interventions, as the barriers may be culturally contextualized. Meanwhile, interventions that promote quality teacher-student relationship are necessary to increase teachers’ perception of bullying seriousness and empathy. Students have been found to adopt the values of their teachers, and this may deter them from engaging in bullying behavior.

Keywords: school bullying, teachers’ attitudes, teacher-student relationship, adolescent students

Procedia PDF Downloads 70

Authors: Riham Debian

Abstract:

This paper deals with the translational mystic in Arabic aesthetics and their linguistic and narrative revelation and mediation across textual spaces. The paper particularly engages with the nature of the Egyptian Sufi Madad, its relation to spaces/places, its intergenerational and intertextual manifestations, and its intersection with questions of identity—the historical spaces and geographical places one inhabits and embodies. Opening a repertoire between contextualized stylistics and poetics semiology (Boise-Bier2011; Jackobson 1960), the paper reads in al-Ghitany’s Kitab al-Tagiliat (The Book of Revelation1983), Bassiouny’s Sabil Al-Ghareq (2018) and its translation (Fountain of the Drowning2022). The paper examines the stylistic and poetical encoding and recoding of the Sufi Madads from Ghitany to Bassiouny and their entanglement in the question of Egyptian identity-politics through the embodiment of historical places and geographical spaces. The paper argues for the intergenerational intertextuality of Arabic aesthetics that stylistically and poetically enacts the mysticism of Sufi Madad through historical and geographical semioticization of the Egyptian character continuity across time and space. Both Ghitany and Bassiouny engage with the historical novel as a form of delivery of their Egyptian mystical relation with time and place. Both novelist-historians are involved with the question of place and the life-worlds that spaces generate across time and gender.

Keywords: intertextuality, interdiscusivity, madad, egyptian identity

Procedia PDF Downloads 70

Authors: Sofia Matoug, Amr Abdel-Dayem

Abstract:

This paper presents a comprehensive survey of recent research studies to segment and classify brain MR (magnetic resonance) images in order to detect significant changes to brain ventricles. The paper also presents a general framework for detecting regions that atrophy, which can help neurologists in detecting and staging Alzheimer. Furthermore, a prototype was implemented to segment brain MR images in order to extract the region of interest (ROI) and then, a classifier was employed to differentiate between normal and abnormal brain tissues. Experimental results show that the proposed scheme can provide a reliable second opinion that neurologists can benefit from.

Keywords: Alzheimer, brain images, classification techniques, Magnetic Resonance Images MRI

Procedia PDF Downloads 274

Authors: Ravinder Barn, Balbir Barn

Abstract:

This paper outlines ethical and practical challenges in the building of social technology for use with socially excluded and marginalised groups. The primary aim of this study was to design, deploy and evaluate social technology that may help to promote better engagement between case workers and young people to help prevent recidivism, and support young people’s transition towards social inclusion in society. A total of 107 practitioners/managers (n=64), and young people (n=43) contributed to the data collection via surveys, focus groups and 1-1 interviews. Through a process of co-design where end-users are involved as key contributors to social technological design, this paper seeks to make an important contribution to the area of participatory methodologies by arguing that whilst giving ‘voice’ to key stakeholders in the research process is crucial, there is a risk that competing voices may lead to tensions and unintended outcomes. The paper is contextualized within a Foucauldian perspective to examine significant concepts including power, authority and surveillance. Implications for youth justice policy and practice are considered. The authors conclude that marginalized youth and over-stretched practitioners are better served when such social technology is perceived and adopted as a tool of empowerment within a framework of child welfare and child rights.

Keywords: youth justice, social technology, marginalization, participatory research, power

Procedia PDF Downloads 426

Authors: Thirayu Jumsai Na Ayudhya

Abstract:

The study of what architecture means to people in their everyday lives inadequately addresses the contextualized and holistic theoretical framework. This article succinctly presents theoretical framework obtained from the comparative study of how people experience the everyday architecture in three different contexts including 1) Bangkok CBD, 2) Phuket island old-town, and 3) Nan province old-town. The way people make sense of the everyday architecture can be addressed in four super-ordinate themes; (1) building in urban (text), (2) building in (text), (3) building in human (text), (4) and building in time (text). In this article, these super-ordinate themes were verified whether they recur in three studied-contexts. In each studied-context, the participants were divided into two groups, 1) local people, 2) visitors. Participants were asked to take photographs of the everyday architecture during the everyday routine and to participate the elicit-interview with photographs produced by themselves. Interpretative phenomenological analysis (IPA) was adopted to interpret elicit-interview data. Sub-themes emerging in each studied-context were brought into the cross-comparison among three studied- contexts. It is found that four super-ordinate themes recur with additional distinctive sub-themes. Further studies in other different contexts, such as socio-political, economic, cultural differences, are recommended to complete the theoretical framework.

Keywords: sense of place, the everyday architecture, architectural experience, the everyday

Procedia PDF Downloads 130

Authors: Viktorija Mano

Abstract:

The objective of my research is to critique the International Monetary Fund (IMF) stance on foreign investment and the benefits for small, open economies of allowing the free movement of capital. In my research as a whole I will explore the extent to which this stance impacted upon and influenced the economic policies of Macedonia. This will involve providing a contextualized, critical account of the policy of the IMF focusing on a comparison of its policies during the early 2000s through policy documents, political discourse and enacted policies in Macedonia. The conditionality associated with these policies, such as the enforcement of austerity measures (including cutting public spending and reducing debt) and the privatization of public institutions has provoked strong reactions in countries which receive such loans. My main focus in my research is on exploring how the process of Financial Liberalization (FL) of the Macedonian economy affected capital flows in the form of foreign direct investments (FDI) in the private sector and how the recent Greek crisis of 2008 has impacted on this. In the case of Macedonia, the reality of FL was tested by the collapse of the Greek economy. However, this paper will highlight the main duties of the IMF and the goals of the FL process implemented in various countries.Additionally, I will undertake a rhetorical documentary analysis on the IMF reports regarding the process of FL in Macedonia since its independence until today.

Keywords: FDI, financial liberalization, Greece, IMF, Macedonia

Procedia PDF Downloads 534

Authors: D. Touil, L. Ouadah

Abstract:

An industrial model of cement grinding circuit is proposed on the basis of sampling surveys undertaken in the Meftah cement plant in Algiers, Algeria. The ball mill is described by a series of equal fully mixed stages that incorporates the effect of air sweeping. The kinetic parameters of this material in the energy normalized form obtained using the data of batch dry ball milling are taken into account in developing the present scale-up procedure. The dynamic separator is represented by the air classifier selectivity equation corrected by empirical factors. The model is incorporated in computer program that predict full size distributions and mass flow rates for all streams in a circuit under a particular set of operating conditions.

Keywords: grinding circuit, clinker, cement, modeling, population balance, energy

Procedia PDF Downloads 499

Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

Abstract:

In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

Procedia PDF Downloads 198

Authors: Suzan Wedyan

Abstract:

Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

Procedia PDF Downloads 507

Authors: Jheanel E. Estrada, Larry A. Vea

Abstract:

This study developed model to detect proper/improper sitting posture using the built in web camera which detects the upper body points’ location and distances (chin, manubrium and acromion process). It also established relationships of human body frames and proper sitting posture. The models were developed by training some well-known classifiers such as KNN, SVM, MLP, and Decision Tree using the data collected from 60 students of different body frames. Decision Tree classifier demonstrated the most promising model performance with an accuracy of 95.35% and a kappa of 0.907 for head and shoulder posture. Results also showed that there were relationships between body frame and posture through Body Mass Index.

Keywords: posture, spinal points, gyroscope, image processing, ergonomics

Procedia PDF Downloads 299

Authors: Riona Dighe

Abstract:

This research attempts to identify an alternative approach to the measurement of Gross National Happiness (GNH). It uses artificial intelligence (AI), incorporating natural language processing (NLP) and sentiment analysis to measure GNH. We use ‘off the shelf’ NLP models responsible for the sentiment analysis of a sentence as a building block for this research. We constructed an algorithm using NLP models to derive a sentiment analysis score against sentences. This was then tested against a sample of 20 respondents to derive a sentiment analysis score. The scores generated resembled human responses. By utilising the MLP classifier, decision tree, linear model, and K-nearest neighbors, we were able to obtain a test accuracy of 89.97%, 54.63%, 52.13%, and 47.9%, respectively. This gave us the confidence to use the NLP models against sentences in websites to measure the GNH of a country.

Keywords: artificial intelligence, NLP, sentiment analysis, gross national happiness

Procedia PDF Downloads 70

Authors: Hsiao-Yung Wang

Abstract:

This essay aims to examine how the discursive formation of the 'transing-nationalism' (which is extended and slightly modified from 'homonationalism') had been constructed in the Taiwanese news media before the legalization of 'sex reassignment surgery (SRS)' in 1988. Samples for rhetorical analysis were selected from two mainstream newspapers, including China Times, and United Daily. The time frame for sample selection is from August 1953 (when the first transgender case was reported) to 1988, while the SRS was legalized in Taiwan. To enhance understanding of media representation as contextualized-based, the author refers to the representative of spatial rhetoric Mikhail Bakhtin for his late study on 'emergence' and 'visualization of time' in Bildungsroman; thereby categorizing the media discourse of transgender into two critical period: (1) transgender as 'misrecognized' and 'included' into the rhetoric of modern medical space; (2) transgender as 'institutionalized' into discourse of protection and salvation by the reified sympathy of nation-state. These two periods and relevant spatial rhetoric were of no immediate concern on the vital interest of transgender individuals; therefore constructed the imagery of transgender for the service of nationalism rather than gender consciousness or human right rhetoric. Based on the research findings, this essay concludes that 'queer multiplicity' should be regarded as not only the guideline for the amendment of the gendered policies and laws but the rhetorical resources for the mobilization of transgender movement in Taiwan from now on.

Keywords: Bakhtin, legalization, rhetoric, sex reassignment surgery, transgender, transing-nationalism

Procedia PDF Downloads 139

Authors: Djamila Meghraoui, Bachir Boudraa, Thouraya Meksen, M.Boudraa

Abstract:

Parkinson's disease is a pathology that involves characteristic perturbations in patients’ voices. This paper describes a proposed method that aims to diagnose persons with Parkinson (PWP) by analyzing on line their voices signals. First, Thresholds signals alterations are determined by the Multi-Dimensional Voice Program (MDVP). Principal Analysis (PCA) is exploited to select the main voice principal componentsthat are significantly affected in a patient. The decision phase is realized by a Mul-tinomial Bayes (MNB) Classifier that categorizes an analyzed voice in one of the two resulting classes: healthy or PWP. The prediction accuracy achieved reaching 98.8% is very promising.

Keywords: Parkinson’s disease recognition, PCA, MDVP, multinomial Naive Bayes

Procedia PDF Downloads 250

Authors: Punnoose A. K.

Abstract:

This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

Procedia PDF Downloads 95

Authors: Nadir Ali Mugheri, Shaukat Ali Lohar

Abstract:

In a multilingual society like Pakistan, code switching is commonly observed in different contexts. Mostly people use L1 (Native Languages) and L2 for common communications and L3 (i.e. English, Urdu, Sindhi) in formal contexts and for academic writings. Such a frequent code switching does affect EFL learners' acquisition of grammar and lexis of the target language which in the long run result in different types of errors in their writings. The current study is to investigate and identify common elements of L1 and L2 (spoken by students of the Universities in Pakistan) which create hindrances for EFL learners. Case study method was used for this research. Formal writings of 400 EFL learners (as participants from various Universities of the country) were observed. Among 400 participants, 200 were female and 200 were male EFL learners having different academic backgrounds. Errors found were categorized into different types according to grammatical items, the difference in meanings, structure of sentences and identifiers of tenses of L1 or L2 in comparison with those of the target language. The findings showed that EFL learners in Pakistani varsities have serious problems in their writings and they committed serious errors related to the grammar and meanings of the target language. After analysis of the committed errors, the results were found in the affirmation of the hypothesis that L1 or L2 does affect EFL learners. The research suggests in the end to adopt natural ways in pedagogy like task-based learning or communicative methods using contextualized material so as to avoid impediments of L1 or L2 in acquisition the target language.

Keywords: multilingualism, L2 acquisition, code switching, language acquisition, communicative language teaching

Procedia PDF Downloads 263

Authors: Eric Enongene Ekembe

Abstract:

Recent calls on EFL teaching posit the centrality of context factors and argue for a correlation between effectiveness in teaching with the learners’ culture in the EFL classroom. Context is not everything; it is defined with indicators of learners’ cultural artifacts and stereotypes in meaningful interactions in the language classroom. In keeping with this, it is difficult to universalise pedagogic procedures given that appropriate procedures are context-sensitive- and contexts differ. It is necessary to investigate what counts as cultural specificities or stereotypes of specific learners to reflect on how different language learning contexts affect or are affected by English language teaching procedures, most especially in under-represented cultures, which have appropriated the English language. This paper investigates cultural stereotypes of EFL learners in the culturally diverse Cameroon to examine how they mediate teaching and learning. Data collected on mixed-method basis from 83 EFL teachers and 1321 learners in Cameroon reveal a strong presence of typical cultural artifacts and stereotypes. Statistical analysis and thematic coding demonstrate that teaching procedures in place were insensitive to the cultural artifacts and stereotypes, resulting in trending tension between teachers and learners. The data equally reveal a serious contradiction between the communicative goals of language teaching and learning: what teachers held as effective teaching was diametrically opposed to success in learning. In keeping with this, the paper argues for a ‘decentred’ teacher preparation in Cameroon that is informed by systemic learners’ feedback. On this basis, applied linguistics has the urgent task of exploring dimensions of what actually counts as contextualized practice in ELT.

Keywords: cultural stereotypes, EFL, implications, procedures

Procedia PDF Downloads 98

Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

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

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

Procedia PDF Downloads 91

Authors: Sara Corvino

Abstract:

The aim of this study is to explore the potential of inclusive learning and assessment strategies to foster students' engagement with historical debates surrounding the field of graphic design. The goal is to respond to the diversity of L4 Graphic Design students, at Nottingham Trent University, in a way that instead of 'lowering standards' can benefit everyone. This research tests, measures, and evaluates the impact of a specific intervention, an assessment task, to develop students' critical visual analysis skills and stimulate a deeper engagement with the subject matter. Within the action research approach, this work has followed a case study research method to understand students' views and perceptions of a specific project. The primary methods of data collection have been: anonymous electronic questionnaire and a paper-based anonymous critical incident questionnaire. NTU College of Business Law and Social Sciences Research Ethics Committee granted the Ethical approval for this research in November 2019. Other methods used to evaluate the impact of this assessment task have been Evasys's report and students' performance. In line with the constructivist paradigm, this study embraces an interpretative and contextualized analysis of the collected data within the triangulation analytical framework. The evaluation of both qualitative and quantitative data demonstrates that active learning strategies and the disruption of thinking patterns can foster greater students' engagement and can lead to meaningful learning.

Keywords: active learning, assessment for learning, graphic design, higher education, student engagement

Procedia PDF Downloads 151

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

Procedia PDF Downloads 340

Authors: Thirayu Jumsai Na Ayudhya

Abstract:

The attempt to understand about what architecture means to people as they go about their everyday life revealed that knowledge such as environmental psychology, environmental perception, environmental aesthetics, inadequately address the contextualized and holistic theoretical framework. In my previous research, it was found that people’s making senses of their everyday architecture can be addressed in terms of four super‐ordinate themes; (1) building in urban (text), (2) building in (text), (3) building in human (text), (4) and building in time (text). In this research, Bangkok CBD was selected as the focal urban context that the integrated style of architecture is noticeable. It is expected that in a unique urban context like Bangkok CBD unprecedented super-ordinate themes will be unveiled through the reflection of people’s everyday experiences. In this research, people’s architectural experience conducted in Bangkok CBD, Thailand, will be presented succinctly. The research addresses the question of how do people make sense of their everyday architecture/buildings especially in a unique urban context, Bangkok CBD, and identifies ways in which people make sense of their everyday architecture. Two key methodologies are adopted. First, Participant-Produced-Photograph (PPP) allows people to express their experiences of the everyday urban context freely without any interference or forced-data generating by researchers. Second, Interpretative Phenomenological Analysis (IPA) are also applied as main methodologies. With IPA methodology, a small pool of participants is considered giving the detailed level of analysis and its potential to produce a meaningful outcome.

Keywords: architectural experience, building appreciation, design psychology, environmental psychology, sense-making, the everyday experience, transactional theory

Procedia PDF Downloads 300

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

Abstract:

The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

Procedia PDF Downloads 303

Authors: Refilwe Moeletsi

Abstract:

Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

Procedia PDF Downloads 282

Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

Abstract:

Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

Procedia PDF Downloads 202

Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

Procedia PDF Downloads 400