Search results for: gender classification

Authors: Zouhair Gassim

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The reconfiguration of representations of women's bodies as a "chest of pregnancies", the growing commitment of their bodies to the decision of pregnancies previously monopolized by men, the emergence of new practices of the bodies of men and women suggest that the borders between the masculine and the feminine in Morocco are moving. However, the persistence of sexual violence against girls/women indicates that these changes did not contribute to the lifting of the men's control over the bodies of women. This paper aims to analyze the lessons learned about sex education as a discourse related to the fabric of bodies in relation to sexuality in school in order to understand to what extent this institution contributes to the (re) production of gender inequalities. As a result, the educational discourse on sexuality still remains one of the spaces of resistance against gender equality and thus contributes to the (re) production of gender inequalities.

Keywords: gender, sexual education, Morocco, educational system

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Kuay Hue San, Muaz Haqim Shaharum, Nasir Yusoff

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Gender plays a big role in psychosocial development. This study aimed to investigate whether gender moderates the relationship between moral identity (internalization and symbolization) and risk-smoking behavior. An online cross-sectional study was carried out on 388 (61% female) youths who fulfilled the study’s inclusion and exclusion criteria. While viewing images of smoking behavior, participants rated their emotional state, which ranged from unpleasant to pleasant. Participants were also asked to fill out the eight-item Moral Identity Scale and provide their socio-demographic information. Gender significantly moderated the relationship between symbolization and smoking behavior. However, the moderation effect was not shown by internalization Finding highlights the implication of gender on moral identity and smoking behavior and the importance of considering this in the public health intervention and program.

Keywords: smoking behaviour, gender, emotion, moral identity

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Baglan Bazylova

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The purpose of our article is to consider the social and psychological conflicts in Lyudmila Petrushevskaya’s stories as an artistic presentation of gender structure of modern society; to reveal originality of the characters’ inner world, the models of their behavior expressing the gender specific nature of modern feminine prose. Gender conflicts have taken the leading place in the modern prose. L. Petrushevskaya represents different types of conflicts including those which are shown in the images of real contradictions in the stories "Narratrix", "Thanks to Life”, "Virgin's Case", "Father and Mother". In the prose of Petrushevskaya the gender conflicts come out in two dimensions: The first one is love relations between a man and a woman. Because of the financial indigence, neediness a woman can’t afford herself even to fall in love and arrange her family happiness. The second dimension is the family conflict because of the male adultery. Petrushevskaya fixed on the unmanifistated conflict in detail. In the real life such gender conflict can appear in different forms but for the writer is important to show it as a life basis, hidden behind the externally safe facade of “the family happiness”. In the stories of L. Petrushevskaya the conflicts reflect the common character of the social and historical situations in which her heroines find themselves, in situations where a woman feels her opposition to the customary mode of life. The types of gender conflicts of these stories differ in character of verbal images. They are presented by the verbal and event ranks creating the conflicts just in operation.

Keywords: gender behavior of heroes, gender conflict, gender picture of the world, gender structure

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Authors: Kyung-Im Han

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This study examines dialect and gender variations in the place and manner of articulation between the two Korean fricatives, /s/ and /s’/, as produced by speakers of the Daegu and Jeju dialects. The acoustic parameters of center of gravity and skewness for the place of articulation, and the rise time and the amplitude rise slope for the manner of articulation were measured. The study results revealed a gender effect, but no dialect effect, for the center of gravity and the skewness. No main effect for either the gender or dialect was found for the rise time and the amplitude rise slope. These findings indicated that, with regard to the place of articulation, Korean fricative sound differences are a gender distinction, not a dialectal one.

Keywords: dialect, gender, Korean fricative, manner of articulation, place of articulation, spectral moments

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Authors: Carlos David Carrillo Trujillo, Rebelín Echeverría Echeverría, Nancy Evia Alamilla, Rocío Quintal López

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Gender as a social construct is a term now widely studied. Within the social sciences it has become very important. In this sense, psychology tries to make some contributions from your area. The intention is to promote equal opportunities for men and women. Social, employment and educational inequities perpetuate sexism, violence and other important social problems in Mexico. The gender perspective is conceptualized as a tool to promote laws, policies, plans, programs and procedures where women are made ​​visible and empowered. The aim of this is the pursuit of equality. Thus, gender mainstreaming is one of the main challenges of education in Mexico. Only a few universities have programs, research or subjects related to the topic. Human resources, and time allocated to teachers are identified as obstacles to the institutionalization of gender. The objective was to make a diagnosis on course offerings and policies on gender. A documentary study and interviews with managers of at least 20 higher education institutions (IES's) were performed. The results indicate the need for greater gender courses, research projects and intervention. The need to promote policies that seek equal opportunities between men and women is also noted.

Keywords: gender mainstreaming, institutionalization, universities, intervention

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Authors: Marina Yurievna Aleksandrova

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Research of the Holocaust retains value not only for history but also for sociology and psychology. One of the most important fields of study is how people were coping during and after this traumatic event. The aim of this paper is to identify the main contexts of the topic of love and to determine which contexts are more characteristic for different groups of victims of the Holocaust (gender, nationality, age). In this research, transcripts of interviews with Holocaust victims that were collected during 1946 for the "Voices of the Holocaust" project were used as data. Main contexts were analyzed with methods of network analysis and latent semantic analysis and classified by gender, age, and nationality with random forest. The results show that love is articulated and described significantly differently for male and female informants, nationality is shown results with lower values of quality metrics, as well as the age.

Keywords: Holocaust, latent semantic analysis, network analysis, text-mining, random forest

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Authors: Fung Sze Wai Veera, Peter W. Ferretto

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Gender functions as a principle in organizing society based on the cultural meanings given to males and females. It is an essential component in constructing the spatial reality, one that is in most cases in favor of men’s needs and disregards that of women’s. Similar to other minorities in China, men of the Dong community hold the primary position in policymaking, moral standards, social values, and, furthermore, the building of the physical environment. This study, therefore, aims to investigate the residential architecture of Dong through the lens of gender. Specifically, it examines how the patriarchal practice of Dong is manifested in terms of the spatial organization, the architectural feature, and the construction process of Dong houses in the southern dialect areas. While the residential architecture of Dong has been extensively researched, the role of gender culture in designing and constructing it deserves more research attention. Ultimately, the objective of this study is to challenge the notion of gender-inclusive design in the rural China context while opening up a cross-disciplinary discussion concerning Chinese minority architecture and gender studies.

Keywords: Dong minority residential architecture, gender study, built environment, male-dominated society, gender-inclusive design

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Authors: Moor Avigail

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This research examines gender norms that underlie the propensity to commit sexual assault and to carry it out. Factors that have been shown to relate to such propensity will be enumerated and tied to their ramifications. These include sexual objectification of women, endorsement of gender-based rape myths blaming the victim, masculine entitlement, low empathy to victims, along with elevated empathy towards rapists. Heavy use of pornography as well as a misconstruing of the meaning of refusal to sex, have also been implicated. Additionally, a cutting-edge investigation, which we have just completed, examined what seems to occur in the perpetrator's mind during the assault. No research to date has ventured to uncover what essentially allows the rape to be carried out in real time, in the sense of what mental mechanisms go into operation in rapists during the assault itself. Our findings demonstrate that dehumanization and rationalization are pivotal. On the one hand, the perpetrator apparently allows himself to disregard the victim's humanity while simultaneously justifying his actions in relation to the victim's behavior.

Keywords: gender norms, gender psychology, sexual assault, gender

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Authors: Tipu Sultan

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The proposed research intends to explore the gender role attitudes and work-life balance among dual-earner couples in Pakistan. With the increase of female labor force participation in Pakistan, the trend of dual-earner couples has been increased than ever before. This new trend of dual-earner families has significantly affected the personal life of dual-earner couples. Due to major change in household structures, the traditions and the routine activities are in continuous transition. Balancing work and family life is more complex in the patriarchal society of Pakistan because of the social expectations of gender roles. A dichotomous behavioral reflection is being observed in Pakistani society. The one group of people having an egalitarian attitude are supporting the new gender roles of females, whereas the other group of people having a traditional mindset is still in the favor of patriarchy. Therefore, gender roles are re-evaluated, and it would be more interesting to raise questions on the interplay of new gender roles and work-life balance among dual-earners. The semi-structured interview guide will be utilized to explore gender role attitudes, ideal and in-practice gender roles, experiences of work-life imbalances/balances, possible strategies to create a balance between work and family life among dual-earner couples.

Keywords: dual-earner couples, gender role attitudes, Pakistan, work-life balance

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Authors: Hamza Iftikhar

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The research study focuses on the transgender community's gender recognition challenges. It is one of the issues for the transgender community, interacting directly with the difficulties of gender identity and the lives of these people who are facing gender disapproval from society. This study investigates the major flaws of the transgender act. The study's goal is to look into the strange implications of self-perceived identity as a policy tool for transgender recognition. This policy tool jeopardises the rights of Pakistan's indigenous gender-variant people as well as the country's legal and social framework. Qualitative research using semi structured interviews will be carried out. This study proposes developing a scheme for mainstreaming gender-variant people on the basis of the Pakistani Constitution, Supreme Court guidelines, and internationally recognised principles of law. This would necessitate a thorough review of current law using a new approach and reference point.

Keywords: transgender act, self perceived identity, gender variant, policy tool

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Authors: Tracey Jean Boisseau

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In the United States and around the world, we see liberal democracies attacked, from within and without, on a number of grounds. One of the primary assaults on the liberal ideology of feminism has been to ban or severely curtail the teaching of and scholarship on gender as constructed rather than as a biological and binarist component of human identity. On every continent, women’s and gender studies at the university level have become targets of rightwing movements aligning with authoritarian regimes to suppress queer and trans people as well as feminist scholars and academics who define gender as fluid, contingent on culture, and as reflective of a political commitment rather than timeless, sacred, natural, biological, or god-given. Rightwing movements calling for an end to gender studies have put already-marginalized academic and scholarly projects under new scrutiny, in some cases resulting in the dismantlement of long-standing women’s and gender studies programs. This paper evaluates the cross-cultural effects such movements have had on our discipline worldwide and documents the strategic responses engaged in by gender studies scholars and leaders to resist the erasure of our field. Evidence is drawn from surveys of thousands of programs and dozens of interviews conducted in the past year with gender studies scholars, administrators, and practitioners. This paper’s main objective is to highlight the international linkages between movements aiming to suppress or erase gender studies as a field of research and teaching and to identify collaborative responses and promising solutions that can protect our discipline from these assaults.

Keywords: anti-feminist, anti-LGBTQ, authoritarianism, movements, gender studies, globalization

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Authors: R. Alothaim, T. Mishra

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Different researchers have reviewed the gender wage gap since early days between women and men to point out their difference to help bring about equality in production among them. Many fingers have been pointed out towards culture and religion as one of the major factors contributing to the gender wage gap throughout the years passed. Recent research has been done to give out equalization to this gap between men and women. The gender wage gap has raised serious concerns among nations and societies. Additionally, data, methodology and time periods have been affected by the gender wage gap, thus needing special decision making to help in the meta-study in the provision of quantitative review. Quality indicators have played a crucial role towards the education through stressing on enough consideration to help give a solution of equality and worth in the research study. The different research reviewed have given enough evidence and impact to point out that the major causes of this gender wage gap has resulted due to culture. On the other pedestal, religion may play a role to the issues of gender wage gap but with more emphasis on culture playing the bigger part. Furthermore, social status of individual has contributed to the wage gap difference between men and women. Labor market has played a vital role in empowering women, leading to the lower rate of the raw wage difference in the recent years.

Keywords: culture, gender wage gap, social, religion

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Authors: Mitja Dečman

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The ever-increasing presence and use of information and communication technology (ICT) influences the different social relationships of today's society. Gender differences are especially important from the viewpoint of modern society since ICT can either deepen the existing inequalities or diminish them. In a developed Western world, gender equality has been a well-focused area for decades in many parts of society including education, employment or politics and has led to a decrease in the inequality of women and men in these and other areas. The area of digital equality, or inequality for that matter, is one of the areas where gender differences still exist in many countries of the world. The research presented in this paper focuses on Slovenia, one of the smallest EU member states, being an average achiever in the area of e-society according to the many different European benchmarking indexes. On the other hand, Slovenia is working in an alignment with many European gender equality guidelines and showing good results. The results of our research are based on the analysis of survey data from 2014 to 2017 dealing with Slovenian citizens and their households and the use of ICT. Considering gender issues, the synthesis showed that cultural differences influence some measured ICT indicators but on the other hand the differences are low and only sometimes statistically significant.

Keywords: digital divide, gender inequality, Slovenia, e-society

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Authors: Tsoaledi D. Thobejane, Barnabas C. Okere

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Gender mainstreaming has been adopted as a strategy for promoting gender equality in institutions of higher learning Worldwide, not least in Africa. This study investigated Gender Mainstreaming at the University of Venda, in Limpopo Province, South Africa. The study was based on the Feminist Theoretical Framework. Both qualitative and quantitative approaches were used. A case study research design was adopted. The study involved a population of 60 participants and a sample of 25 male and female workers selected using the purposive sampling technique. Data were presented in pie charts, tables, themes and in textual forms. Data were analysed through descriptive statistics and thematic analysis. The major findings and conclusions of the study were that the University of Venda faces enormous challenges in mainstreaming gender in the university functions. There are perceptions that most strategic higher positions in the institution are dominated by men while women are marginalized. Although the University has policies on gender, staff members do not know about them while management does not implement its policies. University of Venda makes use of the Employment Equity Act of 1998, but it is not clear whether line managers are aware of its implementation and how. In addition, favouritism, nepotism, patronage, and patriarchy played a role in gender mainstreaming. The study recommended that there should be more gender awareness activities, such as workshops, conferences, and symposia for workers and staff members in order to sensitize them about gender towards understanding. The study also recommended that deserving female staff members should be promoted, and all employees should be encouraged to read and understand gender policies. In addition, management should implement the institutions and national gender policies without fear or favour.

Keywords: gender mainstreaming, gender equality, institutions, representation

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Authors: Gehad S. Kaseb, Mona F. Ahmed

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Arabic Sentiment Analysis (SA) is one of the most common research fields with many open areas. Few studies apply SA to Arabic dialects. This paper proposes different pre-processing steps and a modified methodology to improve the accuracy using normal Support Vector Machine (SVM) classification. The paper works on two datasets, Arabic Sentiment Tweets Dataset (ASTD) and Extended Arabic Tweets Sentiment Dataset (Extended-AATSD), which are publicly available for academic use. The results show that the classification accuracy approaches 86%.

Keywords: Arabic, classification, sentiment analysis, tweets

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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Authors: M. Karthigayan, M. Rizon, Sazali Yaacob, R. Nagarajan, M. Muthukumaran, Thinaharan Ramachandran, Sargunam Thirugnanam

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In this paper, using a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA) are applied to the lip and eye features to classify the human emotions. Two South East Asian (SEA) faces are considered in this work for the emotion classification. There are six emotions and one neutral are considered as the output. Each subject shows unique characteristic of the lip and eye features for various emotions. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters and it had been proven by applying to two SEA subjects and have improved the classification rate.

Keywords: ellipse fitness function, genetic algorithm, emotion recognition, fuzzy clustering

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

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Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

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In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: association rules, rule-based classification, classification quality, validation

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: Qiong Hu

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From old English to modern English, the gender category has changed from grammatical gender system to natural gender system. The word classes that reflected gender has changed from pronouns, adjectives, and numerals in old English to only pronouns in modern English. In present-day English, the third person singular pronouns are the only paradigm that keeps an intact gender. 'He' and 'they' used as epicene pronouns are one of the two commonest phenomena of gender disagreement (the other being those against the natural gender). Considering the convenience of corpus concordance, epicene pronoun usage is selected in this study in which the anaphors are restricted to possessives (eg. his, their), and the antecedents are restricted to compound indefinite pronouns (eg. someone, somebody). Factors like writing form (eg. someone vs. some one), the semantics of the prefixes (eg. some- vs. any-), and suffixes (eg. -one vs. -body), as well as frequency, are taken into consideration. Statistics indicate that 'their' is increasingly used as the epicene pronoun compared with the decline of 'his' (when both writing forms are considered). This is influenced by social factors such as feminist movement, as well as the semantics and frequency of antecedents. Their (plural) used in anaphoric reference to various indefinite pronouns (singular in form) can also be treated as number variation in third person pronouns, and the trend that 'their' in place of his can also be treated as a change in number category. Among different candidates for the gender-neutral function, 'their' is proven to be the most promising one based on the diachronic data. This does not reject any new competitors in the future which still remains to be seen.

Keywords: language variation and change, epicene pronouns, gender, number

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

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Authors: Pragya Paneru

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This paper explores ten primary teachers’ views on gender representation in primary-level textbooks altogether. Data was collected from the teachers who taught in private schools in Kailali and Kathmandu District. This research uses a semi-structured interview method to obtain information regarding teachers’ attitudes toward gender representations in textbook content. The interview data were analysed by using critical skills of qualitative research analysis methods, as suggested by Saldana and Omasta (2018). The findings revealed that most of the teachers were unaware and regarded gender issues as insignificant to discuss in primary-level classes. Most of them responded to the questions personally and claimed that there were no gender issues in their classrooms. Some of the teachers connected gender issues with contexts other than textbook representations, such as school discrimination in the distribution of salary among male and female teachers, school practices of awarding girls rather than boys as the most disciplined students, following girls’ first rule in the assembly marching, encouraging only girls in the stage shows, and involving students in gender-specific activities such as decorating works for girls and physical tasks for boys. The interview also revealed teachers’ covert gendered attitudes in their remarks. Nevertheless, most of the teachers accepted that gender-biased contents have an impact on learners, and this problem can be solved with more gender-centred research in the education field, discussions, and training to increase awareness regarding gender issues. Agreeing with the suggestion of teachers, this paper recommends proper training and awareness regarding how to confront gender issues in textbooks.

Keywords: content analysis, gender equality, school education, critical awareness

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