Search results for: gender prediction

Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 116

Authors: Raluca Ionela Maxim

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Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.

Keywords: design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models

Procedia PDF Downloads 116

Authors: Milind Patil

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Present paper is a discussion on Hindi-Marathi Morphological Analysis and generating rules for Machine Translation on the basis of Machine Readable Dictionary (MRD). This used Transformative Generative Grammar (TGG) rules to design the MRD. As per TGG rules, the suffix of a particular root word is based on its Tense, Aspect, Modality and Voice. That's why the suffix is very important for the word meanings (or root meanings). The Hindi and Marathi Language both have relation with Indo-Aryan language family. Both have been derived from Sanskrit language and their script is 'Devnagari'. But there are lots of differences in terms of semantics and grammatical level too. In Marathi, there are three genders, but in Hindi only two (Masculine and Feminine), the Natural gender is absent in Hindi. Likewise other grammatical categories also differ in their level of use. For MRD the suffixes (or Morpheme) are of particular root word for GNP (Gender, Number and Person) are based on its natural phenomena. A particular Suffix and Morphine change as per the need of person, number and gender. The design of MRD also based on this format. In first, Person, Number, Gender and Tense are key points than root words and suffix of particular Person, Number Gender (PNG). After that the inferences are drawn on the basis of rules that is (V.stem) (Pre.T/Past.T) (x) + (Aux-Pre.T) (x) → (V.Stem.) + (SP.TM) (X).

Keywords: MRD, TGG, stem, morph, morpheme, suffix, PNG, TAM&V, root

Procedia PDF Downloads 295

Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

Procedia PDF Downloads 379

Authors: Humera Malik

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Gender inequality, as a societal issue, is prevalent in all spheres of life in Pakistan. It is world-wide understood that gender equality is a basic right of every human being as well as the source of development and prosperity for the whole country. In fact, many countries endeavor to ensure equal opportunities for men and women which will, in turn, help to attain sustainable growth in every field. Most of the women in Pakistan live their life under the societal pressure which is exerted by centuries old traditions. This archaic setup restricts women to stay at home because their survival is conditional to their total subjugation to the male member of the family. This patriarchal structure confers men the right to deal women as their property. It is not wrong to say that women endure severe discrimination in their whole life. No doubt, women are confronted with multifaceted discrimination in the field of education, health, politics, social status, etc. The main theme of this research is to ascertain the present condition of gender inequality in the field of economy in Pakistan. Pakistan’s poor ranking in Global Gender Gap Index, 2016 clearly depicts that women are deprived of fundamental rights as well as equal opportunities of development. This very state of affairs depicts the real picture of government’s commitment to women empowerment and gender equality. The nature of this research is descriptive which helps to determine the status of women in Pakistan on the basis of labour force participation, wage gap, estimated incomes, and ratio of high ranking positions secured by women. It is an endeavor to understand the reasons of economic inequality by following qualitative method of research. Moreover, few recommendations will be suggested to get rid of this issue.

Keywords: dismal, discrimination, feudal, patriarchal, wage gap

Procedia PDF Downloads 144

Authors: Ramona Georgeta Biholar

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Gender-based violence against women plagues societies around the world. The work to eliminate it is an ongoing battle. At the international level, Article 5 (a) CEDAW establishes an agenda for social and cultural transformation: it imposes on States parties to CEDAW an obligation to modify sex roles and stereotypical social and cultural patterns of conduct. Also, it provides for the protection of women from violence stemming from such gender norms. Yet, the lived realities of women are frequently disconnected from this agenda. Nonetheless, it is the reality of the local that is crucial for the articulation, implementation and realization of women’s rights in general, and for the elimination of gender-based violence against women in particular. In this paper we discuss the transformation of sex roles and gender stereotyping with a view to realize women’s right to be free from gender-based violence. This paper is anchored in qualitative data collection undertaken in Jamaica and socio-legal research. Based on this research, 1) We explain the process of vernacularisation as a strategy that enables women’s human rights to hit the ground and benefit rights holders, and 2) We present a synergistic model for the implementation of Article 5 (a) CEDAW so that women’s right to be free from gender-based violence can be realized in a concrete national jurisdiction. This model is grounded in context-based demands and recommendations for social and cultural transformation as a remedy for the incidence of gender-based violence against women. Moreover, the synergistic model offers directions that have a general application for the implementation of CEDAW and Article 5 (a) CEDAW in particular, with a view to realize women’s right to be free from gender-based violence. The model is thus not only a conceptual tool of analysis, but also a prescriptive tool for action. It contributes to the work of both academics and practitioners, such as Governmental officials, and national and local civil society representatives. Overall, this paper contributes to understanding the process necessary to bridge that gap between women’s human rights norms and women’s life realities of discrimination and violence.

Keywords: CEDAW, gender-based violence against women, international human rights law, women’s rights implementation, the Caribbean

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Authors: Jagadish Rao Padubidri, Mehak Bhandary, Sowmya J. Rao

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Introduction: The significance of the human foot and its measurements in identifying an individual has been proved a lot of times by different studies in different geographical areas and its association to the stature and gender of the individual has been justified by many researches. In our study we have used different foot measurements including the length, width, malleol height and navicular height for establishing its association to stature and gender and to find out its accuracy. The purpose of this study is to show the relation of foot measurements with stature and gender, and to derive Multiple and Logistic regression equations for stature and gender estimation in South Indian population. Materials and Methods: The subjects for this study were 200 South Indian students out of which 100 were females and 100 were males, aged between 18 to 24 years. The data for the present study included the stature, foot length, foot breath, foot malleol height, foot navicular height of both right and left foot. Descriptive statistics, T-test and Pearson correlation coefficients were derived between stature, gender and foot measurements. The stature was estimated from right and left foot measurements for both male and female South Indian population using multiple regression analysis and logistic regression analysis for gender estimation. Results: The means, standard deviation, stature, right and left foot measurements and T-test in male population were higher than in females. LFL (Left foot length) is more than RFL (Right Foot length) in male groups, but in female groups the length of both foot are almost equal [RFL=226.6, LFL=227.1]. There is not much of difference in means of RFW (Right foot width) and LFW (Left foot width) in both the genders. Significant difference were seen in mean values of malleol and navicular height of right and left feet in male gender. No such difference was seen in female subjects. Conclusions: The study has successfully demonstrated the correlation of foot length in stature estimation in all the three study groups in both right and left foot. Next in parameters are Foot width and malleol height in estimating stature among male and female groups. Navicular height of both right and left foot showed poor relationship with stature estimation in both male and female groups. Multiple regression equations for both right and left foot measurements to estimate stature were derived with standard error ranging from 11-12 cm in males and 10-11 cm in females. The SEE was 5.8 when both male and female groups were pooled together. The logistic regression model which was derived to determine gender showed 85% accuracy and 92.5% accuracy using right and left foot measurements respectively. We believe that stature and gender can be estimated with foot measurements in South Indian population.

Keywords: foot length, gender, stature, South Indian

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Authors: A. K. O'Loughlin

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In Simone de Beauvoir’s climatic 1959 meditation, The Second Sex, she avows that 'On ne naît pas femme; on le devient,' translated most recently in the unabridged text (2010) as 'One is not born, but rather becomes, woman.' The signifier ‘woman’ in this context, signifies Beauvoir’s contemplation of the institution, the concept of woman(ness) defined in relation to the binary and hegemonic man(ness.) She is 'the other.' This paper is a theoretical contemplation of (1) how we actively teach 'othering' in the institution of schooling and (2) new considerations of pluralism for self-reflection and subversion that teachers, in particular, are faced with. How, in schooling, do we learn one’s options for racialized, classed and sexualized gender identification and the hierarchical signification that define these signifiers? Just like the myth of apolitical schooling, we cannot escape teaching social organization in the classroom. Yet, we do have a choice. How do we as educators learn about our own embodied intersectionalities? How do we unlearn our own binaries? How do we teach about intersectional gender? How do we teach 'the other'? We posit the processes of these reflections by educators may move our classrooms beyond binaries, engage pluralism and queer alterity itself.

Keywords: othering, alterity, education, schooling, identity, racialization, gender, intersectionality, pluralism

Procedia PDF Downloads 218

Authors: Szymon Misiek

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The genderqueer (or gender non-binary, both terms referring to those individuals who are identified as neither men nor women) community has been gaining greater visibility over the last few years. This includes legal recognition, representation in popular media, and inclusion of non-binary perspectives in research on transgender issues. Another important aspect of visibility is language. Gender-neutrality, often associated with genderqueer people, is relatively easy to achieve in natural-gender languages such as English. This can be observed in the growing popularity of the 'singular they' pronoun (used specifically with reference to genderqueer individuals) or the gender-neutral title 'Mx.' (as an alternative to 'Ms./Mr.'). 'Singular they' seems to have become a certain standard in the genderqueer community. Grammatical-gender languages, such as Polish, provide for a greater challenge to genderqueer speakers. In Polish, every noun is inherently gendered, while verbs, adjectives, and pronouns inflect for gender. Those who do not wish to settle for using only either masculine or feminine forms (which some genderqueer Polish speakers do choose) have to somehow mix the two, attempt to avoid gendered forms altogether, or turn to non-standard forms, such as neuter (not used for people in standard Polish), plurals (vaguely akin to English 'singular they'), or neologisms (such as verb forms using the '-u-' affix). The following paper presents the results of a survey conducted among genderqueer speakers of Polish regarding their choice of linguistic strategies. As no definitive standard such as 'singular they' has (yet) emerged, it rather seeks to emphasize the diversity of chosen strategies and their relation to a person's specific identity as well as the context an exchange takes place. The findings of the study may offer an insight into how heavily gendered languages deal with non-normatively gendered experiences, and to what extent English influences this process (e.g., the majority of genderqueer poles choose English terms to label their identity), as well as help design good practices aimed at achieving gender-equality in speech.

Keywords: genderqueer, grammatical gender in Polish, non-binary, transgender

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

Procedia PDF Downloads 352

Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

Procedia PDF Downloads 111

Authors: C. Leiber

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International human rights treaties ensure basic rights to all people, regardless of nationality. These treaties have developed in a predominantly Western environment, and their implementation into non-western contexts often raises questions of the transfer-ability of value systems and governance structures. International human rights treaties also postulate the right to the full enjoyment and expression of one’s own culture, known as cultural rights. Many cultural practices and traditions in South Sudan serve as an obstacle to the adaptation of human rights and internationally agreed-upon standards, specifically those pertaining to women’s rights and gender equality. This paper analyzes the specific social, political, and economic conflicts between women’s rights and cultural rights within the context of South Sudan’s evolution into a sovereign nation. It comprehensively evaluates the legal status of South Sudanese women and –based on the empirical evidence- assesses gender equality in four key areas: Marriage, Education, Violence against Women, and Inheritance. This work includes an exploration into how South Sudanese culture influences, and indeed is intertwined with, social, political, and economic spheres, and how it limits gender equality and impedes the full implementation of international human rights treaties. Furthermore, any negative effects which systemic gender inequality and cultural practices that are oppressive to women have on South Sudan as a developing nation are explored. Finally, those areas of conflict between South Sudanese cultural rights and international women’s rights are outlined which can be mitigated or resolved in favor of elevating gender equality without imperializing or destroying South Sudanese culture.

Keywords: cultural rights, gender equality, international human rights, South Sudan

Procedia PDF Downloads 325

Authors: Jin Koo

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The main purpose of this study is to investigate the comparability of student scores obtained from Test Center (TC) vs. Online-Proctored (OP) Delivery in the three subject areas of Verbal, Reading, and Mathematics for each level (Middle and Upper). Also, this study examines whether there is an interaction effect between test deliveries (TC vs. OP) and gender/ethnicity/ability level in each subject area. The test used in this study is a multiple-choice standardized test for students in grades 5-11. For this study, data were collected during the 2022-23 test administration. This research used a one-factor between-subjects ANOVA and Cohen’s d to compare the TC and OP groups’ test means for each level and each subject area. Also, 2-factor between-subjects ANOVAs were conducted to investigate examinee characteristics: gender (male and female), ethnicity (African-American, Asian, Hispanic, Multi-racial, and White), and ability level (low, average, and high-ability groups). The author found that students’ test scores in some subject areas varied between TC and OP test deliveries by gender, ethnicity, and ability level, meaning that gender, ethnicity, and ability level were related to the score difference. These results will be discussed according to the current testing systems.

Keywords: ability level, ethnicity, gender, online-proctored delivery, standardized test, test center

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 115

Authors: Juanita Morris

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The purpose of this study will examine the mediating relationships between the theories of intelligence, mathematics anxiety, gender stereotype threat, meta-cognition and math performance through the use of eye tracking technology, affecting student perception and problem-solving abilities. The participants will consist of (N=80) female graduate students. Test administered were the Abbreviated Math Anxiety Scale, Tobii Eye Tracking software, gender stereotype threat through Google images, and they will be asked to describe their problem-solving approach allowed to measure metacognition. Participants will be administered mathematics problems while having gender stereotype threat shown to them through online images while being directed to look at the eye tracking software Tobii. We will explore this by asking ‘Is mathematics anxiety associated with the theories of intelligence and gender stereotype threat and how does metacognition and math performance place a role in mediating those perspectives?’. It is hypothesized that math-anxious students are more likely affected by the gender stereotype threat and that may play a role in their performance? Furthermore, we also want to explore whether math anxious students are more likely to be an entity theorist than incremental theorist and whether those who are math anxious will be more likely to be fixated on variables associated with coefficients? Path analysis and independent samples t-test will be used to generate results for this study. We hope to conclude that both the theories of intelligence and metacognition mediate the relationship between mathematics anxiety and gender stereotype threat.

Keywords: math anxiety, emotions, affective domains fo learning, cognitive underlinings

Procedia PDF Downloads 247

Authors: Jin Koo

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During the coronavirus pandemic, there has been a further increasing demand for computer-based tests (CBT), and now it has become an important test mode. The main purpose of this study is to investigate the comparability of student scores obtained from computerized-based formats of a standardized test in the two subject areas of reading and mathematics. Also, this study investigates whether there is an interaction effect between test modes of CBT and paper-based tests (PBT) and gender/ability level in each subject area. The test used in this study is a multiple-choice standardized test for students in grades 8-11. For this study, data were collected during four test administrations: 2015-16, 2017-18, and 2020-21. This research used a one-factor between-subjects ANOVA to compute the PBT and CBT groups’ test means for each subject area (reading and mathematics). Also, 2-factor between-subjects ANOVAs were conducted to investigate examinee characteristics: gender (male and female), ethnicity (African-American, Asian, Hispanic, multi-racial, and White), and ability level (low, average, and high-ability groups). The author found that students’ test scores in the two subject areas varied across CBT and PBT by gender and ability level, meaning that gender, ethnicity, and ability level were related to the score difference. These results will be discussed according to the current testing systems. In addition, this study’s results will open up to school teachers and test developers the possible influence that gender, ethnicity, and ability level have on a student’s score based on whether they take the CBT or PBT.

Keywords: ability level, computer-based, gender, paper-based, test

Procedia PDF Downloads 73

Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

Procedia PDF Downloads 99

Authors: KangQi Jin

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School-Related Gender-Based Violence (SRGBV) seriously impacts the victim's physical and mental health and academic and employment prospects. Due to the lack of protective policies for sexual minority students in mainland China at present, the well-being of those students in China is seriously endangered by SRGBV, and their physical and mental health is at great risk. By analyzing the current situation of stigmatization of sexual minority students and the harm brought to them by gender violence, this study proposes some strategies to reduce SRGBV on sexual minorities. First, the nation should set laws to protect the rights and interests of sexual minorities, and second, universities should make multifaceted efforts to reduce these violent phenomena. The violence experienced by students of sexual minorities has a crucial impact on their future physiology and psychology, and through the research, in this paper, the author hope can provide suggestions for scholars who try to study related fields in the future.

Keywords: sexual minority, school-related gender-based violence, response, strategies

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Authors: Sonia Wahengbam, Natasha Elangbam

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Female impersonation has existed through the length of human civilization and the breadth of its cultures. Transvestism and drag queen cultures have created multi-sited spaces where in the shadow of art, one can cross the gender barrier and express one’s hidden identity. This paper will explore a dynamic cultural space that exists in Manipur, a state in the northeastern region of India, where the female impersonators (nupi shabis) of a folk theater (Shumang Leela) are using this traditional and popular art form to claim social acceptance of their homosexual identities through the medium of entertainment. It will highlight how by crossing the gender boundary, this third gender group has carved out a unique socio-economic niche where they have exploited their sexual identities to their advantage. The paper will trace the expanding cultural ‘’borderland’’ of Manipur where there is an increasing sense of ‘becoming’, belonging and sharing” of identities through the interweaving of old and new media. The research will be based on interviews with the nupi shabis, cultural critics and other experts.

Keywords: transvestism, Manipur, female impersonators (nupi shabis), Shumang Leela, gender

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

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Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Zeeshan Muzammal, Usama Latif, Fouzia Younas, Syed Muhammad Hassan, Samia Razaq

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Unexpected rainfall has always been an issue in the lifetime of crops and brings destruction for the farmers who harvest them. Unfortunately, Pakistan is one of the countries in which untimely rain impacts badly on crops like wash out of seeds and pesticides etc. Pakistan’s GDP is related to agriculture, especially in rural areas farmers sometimes quit farming because leverage of huge loss to their crops. Through our surveys and research, we came to know that farmers in the rural areas of Pakistan need rain information to avoid damages to their crops from rain. We developed a prototype using ICTs to inform the farmers about rain one week in advance. Our proposed solution has two ways of informing the farmers. In first we send daily messages about weekly prediction and also designed a helpline where they can call us to ask about possibility of rain.

Keywords: ICTD, farmers, mobile based, Pakistan, rural areas, weather prediction

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Authors: Mary-Magdalene N. Chumbow

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This study explores how a reality TV show which aired in Nigeria in 2019 (Big Brother Naija - BBN), played a role in enhancing gender-biased conversations among its viewers and social media followers. Thematic analysis is employed here to study Twitter conversations among BBN 2019 followers, which ensued after the show had stopped airing. The study reveals that the show influenced the way viewers and fans engaged with each other, as well as with the show’s participants, on Twitter, and argues that, despite having aired for a short period of time, BBN 2019 was able to draw people together and provide a community where viewers could engage with each other online. Though the show aired on TV, the viewers found a digital space where they could air their views, react to what was happening on the show, as well as simply catch up on action that they probably missed. Within these digital communities, viewers expressed their attractions, disgust and identities, most of these having a form of reference to sexuality and gender identities and roles, as were also portrayed by the show’s producers both on TV and on social media.

Keywords: commodification of bodies, gender stereotypes, Big Brother Naija, social media

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Authors: María Del Carmen Pardo Ferreira, Fernando Rodriguez Cortes, Juan Carlos Rubio Romero

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According to the International Labor Organization, every day there is more presence of women in the labor market although inequality between women and men persists in world labor markets. In order to try to reduce this gender inequality in the work environment, the present study is proposed, which aims to analyze the occupational accidents suffered by women and occurred in Spain between 2015 and 2018. For this, the methodology used was based on a statistical analysis of the data provided by the Government of Spain. The results will allow to know in which jobs women suffer accidents, in what type of companies and the severity of the accident. Based on these results, specific intervention policies may be defined according to the needs detected in each sector.

Keywords: Injured women, Gender perspective, Occupational accidents, Occupational health and safety

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Authors: Tracey Jean Boisseau

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Recently, the rise of concerted right-wing and authoritarian movements has put feminists as well as women, queer, trans, and non-binary folk, immigrants, refugees, the global poor, and people of color in their crosshairs. The U.S. is seeing unprecedented attacks on liberal democratic institutions, escalating “culture wars,” and increased anti-intellectual vitriol specifically targeting feminist and anti-racist educators and scholars. Such vitriol has fueled new legislation curtailing or outright banning of “gender studies” for its ideological commitment to theorizing gender identity as a cultural construct and an inherently political project rather than a “natural” binary that can not be contested or interrogated. At the same time, across the globe—in Afghanistan, Argentina, Brazil, France, Haiti, Hungary, Kenya, Nicaragua, Nigeria, Pakistan, the Philippines, Poland, Russia, South Korea, Sweden, Turkey, Uganda, the United Kingdom, and elsewhere—emergent anti-feminist, nativist, and white-supremacist political parties, as well as established autocratic and authoritarian regimes, have instituted blatantly misogynistic, anti-queer, and anti-trans legislation, often accompanied by governmental and extra-governmental policies explicitly intended to marginalize, erase, suppress, or extinguish gender studies as a legitimate academic discipline, topic of research, and teaching field. This paper considers the origins and effects of such legislation -as well as the strategies exhibited by practitioners of gender studies to counter these effects and resist erasure- from a cross-cultural perspective. The research underpinning this paper’s conclusions includes a survey of nearly 2000 gender studies programs in the U.S. and interviews with dozens of gender studies scholars and administrative leaders of gender-studies programs located worldwide. The goal of this paper is to illuminate distinctions, continuities, and global connections between anti-gender studies legislation that emanates from within national borders but arises from rightwing movements that supercede those borders, and that, ultimately, require globalist responses.

Keywords: anti-feminist, anti-LGBTQ, legislation, criminalization, authoritarianism, globalization

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 87

Authors: Thomas Suarez, Anne-Sophie Grenouilleau, Erwan Autin, Alexandre Biosse-Duplan, Emmanuelle Blondet, Laurence Chazalette, Marie Coniel, Agnes Dessaigne, Sylvie Lascols, Andrea Lasserre, Candice Legris, Pierre Liot, Aline Metais, Karine Petitprez, Christophe Varlet, Christian Saout

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Background: The role of biological sex and gender identity -whether assigned or chosen- as health determinants are far from a recent discovery: several reports have stressed out how being a woman or a man could affect health on various scales. However, taking it into consideration beyond stereotypes and rigid binary assumptions still seems to be a work in progress. Method: The report is a synthesis on a variety of specific topics, each of which was studied by a specialist from the French National Authority for Health (HAS), through an analysis of existing literature on both healthcare policy construction process and instruments (norms, data analysis, clinical trials, guidelines, and professional practices). This work also implied a policy analysis of French recent public health laws and a retrospective study of guidelines with a gender mainstreaming approach. Results: The analysis showed that though sex and gender were well-known determinants of health, their consideration by both public policy and health operators was often incomplete, as it does not incorporate how sex and gender interact, as well as how they interact with other factors. As a result, the health and social care systems and their professionals tend to reproduce some stereotypical and inadequate habits. Though the data available often allows to take sex and gender into consideration, such data is often underused in practice guidelines and policy formulation. Another consequence is a lack of inclusiveness towards transgender or intersex persons. Conclusions: This report first urges for raising awareness of all the actors of health, in its broadest definition, that sex and gender matter beyond first-look conclusions. It makes a series of recommendations in order to reshape policy construction in the health sector on the one hand and to design public health instruments to make them more inclusive regarding sex and gender on the other hand. The HAS finally committed to integrate sex and gender preoccupations in its workings methods, to be a driving force in the spread of these concerns.

Keywords: biological sex, determinants of health, gender, healthcare policy instruments, social accompaniment

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Authors: Xiao Zhou, Jianlin Cheng

Abstract:

A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

Procedia PDF Downloads 431

Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar

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Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.

Keywords: machine learning, hydro-gravimetry, ground water level, predictive model

Procedia PDF Downloads 99