Search results for: representation selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3476

Search results for: representation selection

2366 A Flexible Pareto Distribution Using α-Power Transformation

Authors: Shumaila Ehtisham

Abstract:

In Statistical Distribution Theory, considering an additional parameter to classical distributions is a usual practice. In this study, a new distribution referred to as α-Power Pareto distribution is introduced by including an extra parameter. Several properties of the proposed distribution including explicit expressions for the moment generating function, mode, quantiles, entropies and order statistics are obtained. Unknown parameters have been estimated by using maximum likelihood estimation technique. Two real datasets have been considered to examine the usefulness of the proposed distribution. It has been observed that α-Power Pareto distribution outperforms while compared to different variants of Pareto distribution on the basis of model selection criteria.

Keywords: α-power transformation, maximum likelihood estimation, moment generating function, Pareto distribution

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2365 Genetic Algorithms for Feature Generation in the Context of Audio Classification

Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

Abstract:

Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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2364 A Method for Quantitative Assessment of the Dependencies between Input Signals and Output Indicators in Production Systems

Authors: Maciej Zaręba, Sławomir Lasota

Abstract:

Knowing the degree of dependencies between the sets of input signals and selected sets of indicators that measure a production system's effectiveness is of great importance in the industry. This paper introduces the SELM method that enables the selection of sets of input signals, which affects the most the selected subset of indicators that measures the effectiveness of a production system. For defined set of output indicators, the method quantifies the impact of input signals that are gathered in the continuous monitoring production system.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

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2363 Emotional Analysis for Text Search Queries on Internet

Authors: Gemma García López

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The goal of this study is to analyze if search queries carried out in search engines such as Google, can offer emotional information about the user that performs them. Knowing the emotional state in which the Internet user is located can be a key to achieve the maximum personalization of content and the detection of worrying behaviors. For this, two studies were carried out using tools with advanced natural language processing techniques. The first study determines if a query can be classified as positive, negative or neutral, while the second study extracts emotional content from words and applies the categorical and dimensional models for the representation of emotions. In addition, we use search queries in Spanish and English to establish similarities and differences between two languages. The results revealed that text search queries performed by users on the Internet can be classified emotionally. This allows us to better understand the emotional state of the user at the time of the search, which could involve adapting the technology and personalizing the responses to different emotional states.

Keywords: emotion classification, text search queries, emotional analysis, sentiment analysis in text, natural language processing

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2362 Constraint-Directed Techniques for Transport Scheduling with Capacity Restrictions of Automotive Manufacturing Components

Authors: Martha Ndeley, John Ikome

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In this paper, we expand the scope of constraint-directed techniques to deal with the case of transportation schedule with capacity restrictions where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to be executed, but also determining which set of alternative activities is to be executed at all level of transportation from input to output. Such problems encompass both alternative resource problems and alternative process plan problems. We formulate a constraint-based representation of alternative activities to model problems containing such choices. We then extend existing constraint-directed scheduling heuristic commitment techniques and propagators to reason directly about the fact that an activity does not necessarily have to exist in a final transportation schedule without being completed. Tentative results show that an algorithm using a novel texture-based heuristic commitment technique propagators achieves the best overall performance of the techniques tested.

Keywords: production, transportation, scheduling, integrated

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2361 Problems Confronting the Teaching of Sex Education in Some Selected Secondary Schools in the Akoko Region of Ondo State, Nigeria

Authors: Jimoh Abiodun Alaba

Abstract:

Context: In many traditional African societies, sex education is often considered a taboo topic. However, the importance of sex education is becoming increasingly evident. This study aims to investigate the challenges faced in teaching sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Research Aim: The aim of this study is to identify and examine the problems confronting the teaching of sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Methodology: The study utilized a multi-stage sampling method. The first stage involved a purposive selection of ten (10) secondary schools in the Akoko region of Ondo State, while the second stage was a random selection of twenty (20) students, each in the selected secondary schools of the study area. This makes a total of two (200) hundred students that were considered for the survey. Descriptive analysis using percentages was employed to analyze the collected data. Factor analysis was also used to identify the most significant problems. Findings: The study revealed that sex education has been neglected in the sampled secondary schools due to traditional African beliefs that do not support the teaching and learning of this subject. Furthermore, there was evidence to suggest that parents also displayed reluctance towards the teaching of sex education, fearing that it might expose students to inappropriate behavior. Consequently, students were deprived of this essential aspect of education necessary for self-awareness and development. Theoretical Importance: This study contributes to the understanding of the challenges faced in teaching sex education in traditional African societies, specifically in the selected secondary schools in the Akoko region of Ondo state, Nigeria. Data Collection: Data were collected through the administration of 200 questionnaires in ten selected secondary schools. Additionally, information was gathered from federal, state, and local government authorities. Analysis Procedures: The collected data were analyzed using descriptive analysis, employing percentage calculations for better interpretation. Furthermore, factor analysis was conducted to isolate the most significant problems identified. Conclusion: The study concludes that sex education in the sampled secondary schools in the Akoko region of Ondo state, Nigeria, has suffered neglect due to traditional African beliefs and parental concerns. Consequently, students are denied an important aspect of education necessary for their self-awareness and development. Recommendations are made to change the negative perception of sex education, enrich the curriculum, and employ qualified personnel for its teaching. Additionally, it is suggested that sex education should be integrated with moral instruction.

Keywords: African traditional belief, sex, sex education, sexual misdemeanor, morality

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2360 Study of Skid-Mounted Natural Gas Treatment Process

Authors: Di Han, Lingfeng Li

Abstract:

Selection of low-temperature separation dehydration and dehydrochlorination process applicable to skid design, using Hysys software to simulate the low-temperature separation dehydration and dehydrochlorination process under different refrigeration modes, focusing on comparing the refrigeration effect of different refrigeration modes, the condensation amount of hydrocarbon liquids and alcoholic wastewater, as well as the adaptability of the process, and determining the low-temperature separation process applicable to the natural gas dehydration and dehydrochlorination skid into the design of skid; and finally, to carry out the CNG recycling process calculations of the processed qualified natural gas and to determine the dehydration scheme and the key parameters of the compression process.

Keywords: skidding, dehydration and dehydrochlorination, cryogenic separation process, CNG recovery process calculations

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2359 Design of a Pneumonia Ontology for Diagnosis Decision Support System

Authors: Sabrina Azzi, Michal Iglewski, Véronique Nabelsi

Abstract:

Diagnosis error problem is frequent and one of the most important safety problems today. One of the main objectives of our work is to propose an ontological representation that takes into account the diagnostic criteria in order to improve the diagnostic. We choose pneumonia disease since it is one of the frequent diseases affected by diagnosis errors and have harmful effects on patients. To achieve our aim, we use a semi-automated method to integrate diverse knowledge sources that include publically available pneumonia disease guidelines from international repositories, biomedical ontologies and electronic health records. We follow the principles of the Open Biomedical Ontologies (OBO) Foundry. The resulting ontology covers symptoms and signs, all the types of pneumonia, antecedents, pathogens, and diagnostic testing. The first evaluation results show that most of the terms are covered by the ontology. This work is still in progress and represents a first and major step toward a development of a diagnosis decision support system for pneumonia.

Keywords: Clinical decision support system, Diagnostic errors, Ontology, Pneumonia

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2358 Comparative Analysis of Different Land Use Land Cover (LULC) Maps in WRF Modelling Over Indian Region

Authors: Sen Tanmoy, Jain Sarika, Panda Jagabandhu

Abstract:

The studies regarding the impact of urbanization using the WRF-ARW model rely heavily on the static geographical information selected, including domain configuration and land use land cover (LULC) data. Accurate representation of LULC data provides essential information for understanding urban growth and simulating meteorological parameters such as temperature, precipitation etc. Researchers are using different LULC data as per availability and their requirements. As far as India is concerned, we have very limited resources and data availability. So, it is important to understand how we can optimize our results using limited LULC data. In this review article, we explored how a LULC map is generated from different sources in the Indian context and what its significance is in WRF-ARW modeling to study urbanization/Climate change or any other meteorological parameters. Bibliometric analyses were also performed in this review article based on countries of study and indexed keywords. Finally, some key points are marked out for selecting the most suitable LULC map for any urbanization-related study.

Keywords: LULC, LULC mapping, LANDSAT, WRF-ARW, ISRO, bibliometric Analysis.

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2357 Visual Representation of Ancient Chinese Rites with Digitalization Technology: A Case of Confucius Worship Ceremony

Authors: Jihong Liang, Huiling Feng, Linqing Ma, Tianjiao Qi

Abstract:

Confucius is the first sage in Chinese culture. Confucianism, the theories represented by Confucius, has long been at the core of Chinese traditional society, as the dominating political ideology of centralized feudal monarchy for more than two thousand years. Confucius Worship Ceremony held in the Confucian Temple in Qufu (Confucius’s birthplace), which is dedicated to commemorate Confucius and other 170 elites in Confucianism with a whole set of formal rites, pertains to “Auspicious Rites”, which worship heaven and earth, humans and ghosts. It was first a medium-scaled ritual activity but then upgraded to the supreme one at national level in the Qing Dynasty. As a national event, it was celebrated by Emperor as well as common intellectuals in traditional China. The Ceremony can be solemn and respectful, with prescribed and complicated procedures, well-prepared utensil and matched offerings operated in rhythm with music and dances. Each participant has his place, and everyone follows the specified rules. This magnificent ritual Ceremony, while embedded with rich culture connotation, actually symbolizes the social acknowledgment for orthodox culture represented by Confucianism. Rites reflected in this Ceremony, is one of the most important features of Chinese culture, serving as the key bond in the identification and continuation of Chinese culture. These rites and ritual ceremonies, as culture memories themselves, are not only treasures of China, but of the whole world. However, while the ancient Chinese Rite has been one of the thorniest and most complicated topics for academics, the more regrettable is that due to their interruption in practice and historical changes, these rites and ritual ceremonies have already become a vague language in today’s academic discourse and strange terms of the past for common people. Luckily, we, today, by virtue of modern digital technology, may be able to reproduce these ritual ceremonies, as most of them can still be found in ancient manuscripts, through which Chinese ancestors tell the beauty and gravity of their dignified rites and more importantly, their spiritual pursuits with vivid language and lively pictures. This research, based on review and interpretation of the ancient literature, intends to construct the ancient ritual ceremonies, with the Confucius Worship Ceremony as a case and by use of digital technology. Using 3D technology, the spatial scenes in the Confucian Temple can be reconstructed by virtual reality; the memorial tablet exhibited in the temple by GIS and different rites in the ceremonies by animation technology. With reference to the lyrics, melodies and lively pictures recorded in ancient scripts, it is also possible to reproduce the live dancing site. Also, image rendering technology can help to show the life experience and accomplishments of Confucius. Finally, lining up all the elements in a multimedia narrative form, a complete digitalized Confucius Worship Ceremony can be reproduced, which will provide an excellent virtual experience that goes beyond time and space by bringing its audience back to that specific historical time. This digital project, once completed, will play an important role in the inheritance and dissemination of cultural heritage.

Keywords: Confucius worship ceremony, multimedia narrative form, GIS, visual representation

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2356 Gender and Science: Is the Association Universal?

Authors: Neelam Kumar

Abstract:

Science is stratified, with an unequal distribution of research facilities and rewards among scientists. Gender stratification is one of the most prevalent phenomena in the world of science. In most countries gender segregation, horizontal as well as vertical, stands out in the field of science and engineering. India is no exception. This paper aims to examine: (1) gender and science associations, historical as well as contemporary, (2) women’s enrolment and gender differences in selection of academic fields, (2) women as professional researchers, (3) career path and recognition/trajectories. The paper reveals that in recent years the gender–science relationship has changed, but is not totally free from biases. Women’s enrolment into various science disciplines has shown remarkable and steady increase in most parts of the world, including India, yet they remain underrepresented in the S&T workforce, although to a lesser degree than in the past.

Keywords: gender, science, universal, women

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2355 GIS Pavement Maintenance Selection Strategy

Authors: Mekdelawit Teferi Alamirew

Abstract:

As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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2354 Unveiling Comorbidities in Irritable Bowel Syndrome: A UK BioBank Study utilizing Supervised Machine Learning

Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

Abstract:

Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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2353 Leverage Effect for Volatility with Generalized Laplace Error

Authors: Farrukh Javed, Krzysztof Podgórski

Abstract:

We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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2352 Ontology-Driven Generation of Radiation Protection Procedures

Authors: Chamseddine Barki, Salam Labidi, Hanen Boussi Rahmouni

Abstract:

In this article, we present the principle and suitable methodology for the design of a medical ontology that highlights the radiological and dosimetric knowledge, applied in diagnostic radiology and radiation-therapy. Our ontology, which we named «Onto.Rap», is the subject of radiation protection in medical and radiology centers by providing a standardized regulatory oversight. Thanks to its added values of knowledge-sharing, reuse and the ease of maintenance, this ontology tends to solve many problems. Of which we name the confusion between radiological procedures a practitioner might face while performing a patient radiological exam. Adding to it, the difficulties they might have in interpreting applicable patient radioprotection standards. Here, the ontology, thanks to its concepts simplification and expressiveness capabilities, can ensure an efficient classification of radiological procedures. It also provides an explicit representation of the relations between the different components of the studied concept. In fact, an ontology based-radioprotection expert system, when used in radiological center, could implement systematic radioprotection best practices during patient exam and a regulatory compliance service auditing afterwards.

Keywords: knowledge, ontology, radiation protection, radiology

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2351 Reasons for the Selection of Information-Processing Framework and the Philosophy of Mind as a General Account for an Error Analysis and Explanation on Mathematics

Authors: Michael Lousis

Abstract:

This research study is concerned with learner’s errors on Arithmetic and Algebra. The data resulted from a broader international comparative research program called Kassel Project. However, its conceptualisation differed from and contrasted with that of the main program, which was mostly based on socio-demographic data. The way in which the research study was conducted, was not dependent on the researcher’s discretion, but was absolutely dictated by the nature of the problem under investigation. This is because the phenomenon of learners’ mathematical errors is due neither to the intentions of learners nor to institutional processes, rules and norms, nor to the educators’ intentions and goals; but rather to the way certain information is presented to learners and how their cognitive apparatus processes this information. Several approaches for the study of learners’ errors have been developed from the beginning of the 20th century, encompassing different belief systems. These approaches were based on the behaviourist theory, on the Piagetian- constructivist research framework, the perspective that followed the philosophy of science and the information-processing paradigm. The researcher of the present study was forced to disclose the learners’ course of thinking that led them in specific observable actions with the result of showing particular errors in specific problems, rather than analysing scripts with the students’ thoughts presented in a written form. This, in turn, entailed that the choice of methods would have to be appropriate and conducive to seeing and realising the learners’ errors from the perspective of the participants in the investigation. This particular fact determined important decisions to be made concerning the selection of an appropriate framework for analysing the mathematical errors and giving explanations. Thus the rejection of the belief systems concerning behaviourism, the Piagetian-constructivist, and philosophy of science perspectives took place, and the information-processing paradigm in conjunction with the philosophy of mind were adopted as a general account for the elaboration of data. This paper explains why these decisions were appropriate and beneficial for conducting the present study and for the establishment of the ensued thesis. Additionally, the reasons for the adoption of the information-processing paradigm in conjunction with the philosophy of mind give sound and legitimate bases for the development of future studies concerning mathematical error analysis are explained.

Keywords: advantages-disadvantages of theoretical prospects, behavioral prospect, critical evaluation of theoretical prospects, error analysis, information-processing paradigm, opting for the appropriate approach, philosophy of science prospect, Piagetian-constructivist research frameworks, review of research in mathematical errors

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2350 A Review of the Literature on Factors Impacting Women’s Retention in Science, Technology, Engineering, Mathematics: A Critical Analysis of Nigeria and Georgia

Authors: Josephine O. Okocha, Ifeanyi Adigwe

Abstract:

This research aims to examine the factors impacting women's retention in STEM in Nigeria and Georgia. In a bid to come up with strategies to enhance women’s participation in STEM, this study identifies and juxtaposes the factors impacting the retention of women in STEM and how they vary from one country to another are discussed. This study adopted the literature review method to perform the critical analysis. A total of 76 papers were retrieved from the Scopus database and were published between 2018 and 2023. Only 12 papers met the criteria for inclusion in the analysis. The findings reveal that the factors impacting women’s retention in STEM include funding (NGOs and government agencies), scholarship, specialized recruitment, mentoring, the establishment of women-only higher institutions, creating a balanced work and family environment, combating stereotypes, and enabling policies and laws. The paper highlights some key recommendations to help improve the retention of women in STEM in Africa and Nigeria in particular.

Keywords: STEM, women, retention, career, Nigeria, Georgia, women’s retention, women representation

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2349 Using Neural Networks for Click Prediction of Sponsored Search

Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

Abstract:

Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

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2348 Image Retrieval Based on Multi-Feature Fusion for Heterogeneous Image Databases

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: feature fusion, image retrieval, membership function, normalization

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2347 Data Gathering and Analysis for Arabic Historical Documents

Authors: Ali Dulla

Abstract:

This paper introduces a new dataset (and the methodology used to generate it) based on a wide range of historical Arabic documents containing clean data simple and homogeneous-page layouts. The experiments are implemented on printed and handwritten documents obtained respectively from some important libraries such as Qatar Digital Library, the British Library and the Library of Congress. We have gathered and commented on 150 archival document images from different locations and time periods. It is based on different documents from the 17th-19th century. The dataset comprises differing page layouts and degradations that challenge text line segmentation methods. Ground truth is produced using the Aletheia tool by PRImA and stored in an XML representation, in the PAGE (Page Analysis and Ground truth Elements) format. The dataset presented will be easily available to researchers world-wide for research into the obstacles facing various historical Arabic documents such as geometric correction of historical Arabic documents.

Keywords: dataset production, ground truth production, historical documents, arbitrary warping, geometric correction

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2346 Removing Maturational Influences from Female Youth Swimming: The Application of Corrective Adjustment Procedures

Authors: Clorinda Hogan, Shaun Abbott, Mark Halaki, Marcela Torres Catiglioni, Goshi Yamauchi, Lachlan Mitchell, James Salter, Michael Romann, Stephen Cobley

Abstract:

Introduction: Common annual age-group competition structures unintentionally introduce participation inequalities, performance (dis)advantages and selection biases due to the effect of maturational variation between youth swimmers. On this basis, there are implications for improving performance evaluation strategies. Therefore the aim was to: (1) To determine maturity timing distributions in female youth swimming; (2) quantify the relationship between maturation status and 100-m FC performance; (3) apply Maturational-based Corrective Adjustment Procedures (Mat-CAPs) for removal of maturational status performance influences. Methods: (1) Cross-sectional analysis of 663 female (10-15 years) swimmers who underwent assessment of anthropometrics (mass, height and sitting height) and estimations of maturity timing and offset. (2) 100-m front-crawl performance (seconds) was assessed at Australian regional, state, and national-level competitions between 2016-2020. To determine the relationship between maturation status and 100-m front-crawl performance, MO was plotted against 100-m FC performance time. The expected maturity status - performance relationship for females aged 10-15 years of age was obtained through a quadratic function (y = ax2 + bx + c) from unstandardized coefficients. The regression equation was subsequently used for Mat-CAPs. (3) Participants aged 10-13 years were categorised into maturity-offset categories. Maturity offset distributions for Raw (‘All’, ‘Top 50%’ & ‘Top 25%’) and Correctively Adjusted swim times were examined. Chi-square, Cramer’s V and ORs determined the occurrence of maturation biases for each age group and selection level. Results—: (1) Maturity timing distributions illustrated overrepresentation of ‘normative’ maturing swimmers (11.82 ± 0.40 years), with a descriptive shift toward the early maturing relative to the normative population. (2) A curvilinear relationship between maturity-offset and swim performance was identified (R2 = 0.53, P < 0.001) and subsequently utilised for Mat-CAPs. (3) Raw maturity offset categories identified partial maturation status skewing towards biologically older swimmers at 10/11 and 12 years, with effect magnitudes increasing in the ‘Top 50%’ and ‘25%’ of performance times. Following Mat-CAPs application, maturity offset biases were removed in similar age groups and selection levels. When adjusting performance times for maturity offset, Mat-CAPs was successful in mitigating against maturational biases until approximately 1-year post Peak Height Velocity. The overrepresentation of ‘normative’ maturing female swimmers contrasted with the substantial overrepresentation of ‘early’ maturing male swimmers found previously in 100-m front-crawl. These findings suggest early maturational timing is not advantageous in females, but findings associated with Aim 2, highlight how advanced maturational status remained beneficial to performance. Observed differences between female and male maturational biases may relate to the differential impact of physiological development during pubertal years. Females experience greater increases of fat mass and potentially differing changes in body shape which can negatively affect swim performance. Conclusions: Transient maturation status-based participation and performance advantages were apparent within a large sample of Australian female youth 100-m FC swimmers. By removing maturity status performance biases within female youth swimming, Mat-CAPs could help improve participation experiences and the accuracy of identifying genuinely skilled female youth swimmers.

Keywords: athlete development, long-term sport participation, performance evaluation, talent identification, youth competition

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2345 Unsupervised Text Mining Approach to Early Warning System

Authors: Ichihan Tai, Bill Olson, Paul Blessner

Abstract:

Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: early warning system, knowledge management, market prediction, topic modeling.

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2344 A Combined AHP-GP Model for Selecting Knowledge Management Tool

Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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2343 Pilot Study of the Psychometric Properties of the Test of Predisposition towards the Bullying

Authors: Rosana Choy, Fabiola Henostroza

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Actual theory suggests social-ecological factors as the main framework of bullying. Most previous research in this phenomenon is focused on the identification of bullying attitudes and conducts in puberty and adolescence periods. For this reason, this study is considered as a contribution to the existing knowledge in measuring matters, because of its non-traditional way of evaluation (graphic items), and because of its approach to a distinctive age group, children from 7 to 9 years-old, not regularly examined in current studies in this field. The research used a transversal descriptive investigation design for the development of a graphic test for bullying predisposition. The process began with the operationalization of the variable bullying predisposition, the structuring of the factors and variable indicators of a pilot instrument, evaluation by experts of the items representation, and finally it continued with the test application to children of two types of regular school population in Lima-Peru: private and public schools. The reliability level was 0.85 and the validity of the test corroborated the three-factor structure proposed by the researchers.

Keywords: bullying, graphic test, reliability, validity

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2342 Gender-Based Violence Public Art Projects: An Analysis of the Value of Including Social Justice Topics in Tertiary Courses

Authors: F. Saptouw

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This paper will examine the value of introducing social justice issues into the tertiary fine art curriculum at a first-year level. The paper will present detail of the conceptual impetus and the logistics related to the execution of a collaborative teaching project. The cohort of students was registered for the Fine Art Foundation course at the Michaelis School of Fine Art at the University of Cape Town. The course is dedicated to the development of critical thinking, communication skills, and varied approaches to knowledge construction within the first-year cohort. A core component of the course is the examination of the representation of gender, identity, politics, and power. These issues are examined within a range of public and private representations like art galleries, museum spaces, and contemporary popular culture. This particular project was a collaborative project with the Office of Inclusivity and Change, and the project leaders were Fabian Saptouw and Gabriel Khan. The paper will conclude by presenting an argument for the importance of such projects within the tertiary environment.

Keywords: art, education, gender-based violence, social responsiveness

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2341 Experimental Evaluation of Succinct Ternary Tree

Authors: Dmitriy Kuptsov

Abstract:

Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

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2340 Evolutionary Genomic Analysis of Adaptation Genomics

Authors: Agostinho Antunes

Abstract:

The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of varied species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: adaptation, animals, evolution, genomics

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2339 A Feminist Critical Discourse Analysis of the Representation of International Women’s Day in Algerian Print Media from 2003

Authors: Taoues Aimeur

Abstract:

The present study is the first comparative study of discourses surrounding women on International Women’s Day in French-language newspapers and Arabic-language newspapers in Algeria. It aims at critically examining the way women are positioned on International Women’s Day in four Algerian newspapers by focusing on the post-civil war era in Algeria (2003 till the present time). This is by applying Feminist Critical Discourse Analysis to question representations of women in the selected newspapers by revealing the gender ideologies embedded in their linguistic and visual discourses. The Francophone newspapers chosen for the present research are El Watan and Liberté. As for the Arabophone ones, El Khabar and Echorouk have been selected. The results of the study would help build an understanding of the meanings of gender that are embedded in the discourses of the selected news outlets which differ both linguistically and ideologically.

Keywords: Arabic-language newspapers, Critical Discourse Analysis, discourses, French-language newspapers, gender, International Women’s Day

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2338 Applying Hybrid Graph Drawing and Clustering Methods on Stock Investment Analysis

Authors: Mouataz Zreika, Maria Estela Varua

Abstract:

Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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2337 The Economic Implications of Cryptocurrency and Its Potential to Disrupt Traditional Financial Systems as a Store of Value

Authors: G. L. Rithika, Arvind B. S., Akash R., Ananda Vinayak, Hema M. S.

Abstract:

Cryptocurrencies were first launched in the year 2009 and have been a great asset to own. Cryptocurrencies are a representation of a completely distinct decentralization model for money. They also contribute to the elimination of currency monopolies and the liberation of money from control. The fact that no government agency can determine a coin's value or flow is what cryptocurrency advocates believe makes them safe and secure. The aim of this paper is to analyze the economic implications of cryptocurrency and how it would disrupt traditional financial systems. This paper analyses the growth of Cryptocurrency over the years and the potential threats of cryptocurrency to financial systems. Our analysis shows that although the DeFi design, like the traditional financial system, may have the ability to lower transaction costs, there are multiple layers where rents might build up because of endogenous competition limitations. The permissionless and anonymous design of DeFi poses issues for ensuring tax compliance, anti-money laundering laws and regulations, and preventing financial misconduct.

Keywords: cryptocurrencies, bitcoin, blockchain technology, traditional financial systems, decentralisation, regulatory framework

Procedia PDF Downloads 42