Search results for: masked language model

Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Usama Shahid, Muhammad Zunnurain Hussain

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This research paper presents a comprehensive analysis of a sentiment analysis approach that employs valence and arousal as its foundational pillars, in comparison to traditional techniques. Sentiment analysis is an indispensable task in natural language processing that involves the extraction of opinions and emotions from textual data. The valence and arousal dimensions, representing the intensity and positivity/negativity of emotions, respectively, enable the creation of four quadrants, each representing a specific emotional state. The study seeks to determine the impact of utilizing these quadrants to identify distinct emotional states on the accuracy and efficiency of sentiment analysis, in comparison to traditional techniques. The results reveal that the valence and arousal-based approach outperforms other approaches, particularly in identifying nuanced emotions that may be missed by conventional methods. The study's findings are crucial for applications such as social media monitoring and market research, where the accurate classification of emotions and opinions is paramount. Overall, this research highlights the potential of using valence and arousal as a framework for sentiment analysis and offers invaluable insights into the benefits of incorporating specific types of emotions into the analysis. These findings have significant implications for researchers and practitioners in the field of natural language processing, as they provide a basis for the development of more accurate and effective sentiment analysis tools.

Keywords: sentiment analysis, valence and arousal, emotional states, natural language processing, machine learning, text analysis, sentiment classification, opinion mining

Procedia PDF Downloads 101

Authors: Sikander Ali

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English is being used as linguafranca in most of the formal and informal situations of Pakistan. This extensive use has been rapidly replacing the identity of national language of Pakistani.e. Urdu. The nature of syntactic representation has always been the matter of confusion among linguists. Being unaware of the correct plural forms the non-natives commit mistakes while making plurals. But the situation is reverse when non-natives of English irrespective of knowing the right plurals make wrong plurals usually talking in their native language. The observation method was opted to check this hypothesis. Along with it, a checklist has been made in which these certain occurrences have been mentioned, where this flouting of the norms is a normal routine. The result confirms that Pakistani commit this mistake, i.e. ‘tablian’ the plural of tables, ‘filain’ the plural of files, though this is done by them on unconscious level. This emerging trend of unconscious mistake is leading Pakistani bilinguals towards a diglossic situation where they are coining portmanteau.

Keywords: bilinguals, emerging trend, portmanteau, trends

Procedia PDF Downloads 176

Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

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Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

Procedia PDF Downloads 280

Authors: Dong-Bo Hsu

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Universal Grammar (UG) claims that the constraints that are derived from this should operate in language users’ L2 grammars. This study investigated this hypothesis on knowledge of Subjacency and resumptive pronoun usage among Chinese learners of English. Chinese fulfills two requirements to examine the existence of UG, i.e., Subjacency does not operate in Chinese and resumptive pronouns in English are very different from those in Chinese and second L2 input undermines the knowledge of Subjacency. The results indicated that Chinese learners of English demonstrated a nearly identical pattern as English native speakers do but the resumptive pronoun in the embedding clauses. This may be explained in terms of the case that Chinese speakers’ usage of pronouns is not influenced by the number of embedding clauses. Chinese learners of English have full access to knowledge endowed by UG but their processing of English sentences may be different from native speakers as a general slow rate for processing in their L2 English.

Keywords: universal grammar, Chinese, English, wh-questions, resumption

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Authors: D. Beziakina, E. Bulgakova

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This study continues the research on Tuvinian intonation and presents a general cross-dialect analysis of intonation of Tuvinian declarative utterances, specifically the character of the tone movement in order to test the hypothesis about the prevalence of level tone in some Tuvinian dialects. The results of the analysis of basic pitch characteristics of Tuvinian speech (in general and in comparison with two other Turkic languages - Uzbek and Azerbaijani) are also given in this paper. The goal of our work was to obtain the ranges of pitch parameter values typical for Tuvinian speech. Such language-specific values can be used in speaker identification systems in order to get more accurate results of ethnic speech analysis. We also present the results of a cross-dialect analysis of declarative intonation in the poorly studied Tuvinian language.

Keywords: speech analysis, statistical analysis, speaker recognition, identification of person

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Authors: Sadullah Rahmani

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Legends, stories, beliefs and traditions in every nation represent the collective dreams, secrets and aspirations of a nation and on the other hand, the foundation of their collective memory; What generally forms the foundation of the culture of any nation has undergone changes and transformations due to the passage of time and changes in political, religious and social conditions. Afghanistan is one of the richest countries in terms of cultural diversity. This country is home to people of different languages, ethnicities and religions. The purpose of this article is to analyze the contrasts and cultural commonalities between two ethnic groups in Afghanistan, namely the Hazara and Uzbek peoples. This research was done with qualitative method and structured interview tool. The method of data analysis is content analysis. In order to explain the intercultural sensitivities of the two groups, Milton Bennett's intercultural sensitivities measures have been used. Based on the theory of intercultural sensitivities, the development of communication is an important factor in reducing intercultural sensitivities. In this research, 8 people from the Hazara and Uzbek tribes were interviewed. Various factors such as customs and manners, music, language, art, lifestyle, etc. have been examined in the article. These factors can contribute to cultural differences and commonalities between the Hazara and Uzbek peoples. The results of this research show that according to Bennett's theory, there are less cultural sensitivities between the Hazara and Uzbek peoples of Afghanistan, especially in matters of marriage, language, economic poverty, being discriminated against, and work relationships; But cultural sensitivities are more in many other cases such as education, religion and the formation of cultural communities.

Keywords: Keywords: Uzbek, language, culture, religion, Hazara.

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Idrissa Kayijuka

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The logistic regression and Cox regression models (proportional hazard model) at present are being employed in the analysis of prospective epidemiologic research looking into risk factors in their application on chronic diseases. However, a theoretical relationship between the two models has been studied. By definition, Cox regression model also called Cox proportional hazard model is a procedure that is used in modeling data regarding time leading up to an event where censored cases exist. Whereas the Logistic regression model is mostly applicable in cases where the independent variables consist of numerical as well as nominal values while the resultant variable is binary (dichotomous). Arguments and findings of many researchers focused on the overview of Cox and Logistic regression models and their different applications in different areas. In this work, the analysis is done on secondary data whose source is SPSS exercise data on BREAST CANCER with a sample size of 1121 women where the main objective is to show the application difference between Cox regression model and logistic regression model based on factors that cause women to die due to breast cancer. Thus we did some analysis manually i.e. on lymph nodes status, and SPSS software helped to analyze the mentioned data. This study found out that there is an application difference between Cox and Logistic regression models which is Cox regression model is used if one wishes to analyze data which also include the follow-up time whereas Logistic regression model analyzes data without follow-up-time. Also, they have measurements of association which is different: hazard ratio and odds ratio for Cox and logistic regression models respectively. A similarity between the two models is that they are both applicable in the prediction of the upshot of a categorical variable i.e. a variable that can accommodate only a restricted number of categories. In conclusion, Cox regression model differs from logistic regression by assessing a rate instead of proportion. The two models can be applied in many other researches since they are suitable methods for analyzing data but the more recommended is the Cox, regression model.

Keywords: logistic regression model, Cox regression model, survival analysis, hazard ratio

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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Authors: Bharati Mehta, Manish Parakh, Bharti Bhandari, Sneha Ambwani

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Speech and language delay (SLD) is seen commonly as a co-morbidity in children having severe resistant focal and generalized, syndromic and symptomatic epilepsies. It is however not clear whether epilepsy contributes to or is a mere association in the pathogenesis of SLD. Also, it is acknowledged that Auditory Brainstem Evoked Responses (ABER), besides used for evaluating hearing threshold, also aid in prognostication of neurological disorders and abnormalities in the hearing pathway in the brainstem. There is no circumscribed or surrogate neurophysiologic laboratory marker to adjudge the extent of SLD. The current study was designed to evaluate the abnormalities in Electroencephalography (EEG) and ABER in children with SLD who do not have an overt hearing deficit or autism. 94 children of age group 2-8 years with predominant SLD and without any gross motor developmental delay, head injury, gross hearing disorder, cleft lip/palate and autism were selected. Standard video Electroencephalography using the 10:20 international system and ABER after click stimulus with intensities 110 db until 40 db was performed in all children. EEG was abnormal in 47.9% (n= 45; 36 boys and 9 girls) children. In the children with abnormal EEG, 64.5% (n=29) had an abnormal background, 57.8% (n=27) had presence of generalized interictal epileptiform discharges (IEDs), 20% (n=9) had focal epileptiform discharges exclusively from left side and 33.3% (n=15) had multifocal IEDs occurring both in isolation or associated with generalised abnormalities. In ABER, surprisingly, the peak latencies for waves I, III & V, inter-peak latencies I-III & I-V, III-V and wave amplitude ratio V/I, were found within normal limits in both ears of all the children. Thus in the current study it is certain that presence of generalized IEDs in EEG are seen in higher frequency with SLD and focal IEDs are seen exclusively in left hemisphere in these children. It may be possible that even with generalized EEG abnormalities present in these children, left hemispheric abnormalities as a part of this generalized dysfunction may be responsible for the speech and language dysfunction. The current study also emphasizes that ABER may not be routinely recommended as diagnostic or prognostic tool in children with SLD without frank hearing deficit or autism, thus reducing the burden on electro physiologists, laboratories and saving time and financial resources.

Keywords: ABER, EEG, speech, language delay

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 478

Authors: Zineb Touati Hamad, Mohamed Ridda Laouar, Issam Bendib

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With the massive development of technology today, the Arabic language has gained a prominent position among the languages most used for writing articles, expressing opinions, and also for citing in many websites, defying its growing sensitivity in terms of structure, language skills, diacritics, writing methods, etc. In the context of the spread of the Arabic language, the Holy Quran represents the most prevalent Arabic text today in many applications and websites for citation purposes or for the reading and learning rituals. The Quranic verses / surahs are published quickly and without cost, which may cause great concern to ensure the safety of the content from tampering and alteration. To protect the content of texts from distortion, it is necessary to refer to the original database and conduct a comparison process to extract the percentage of distortion. The disadvantage of this method is that it takes time, in addition to the lack of any guarantee on the integrity of the database itself as it belongs to one central party. Blockchain technology today represents the best way to maintain immutable content. Blockchain is a distributed database that stores information in blocks linked to each other through encryption, where the modification of each block can be easily known. To exploit these advantages, we seek in this paper to justify the use of this technique in preserving the integrity of Arabic texts sensitive to change by building a decentralized framework to authenticate and verify the integrity of the digital Quranic verses/surahs spread on websites.

Keywords: arabic text, authentication, blockchain, integrity, quran, verification

Procedia PDF Downloads 164

Authors: Ayodele James Akinola

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This study investigated the use of English in doctor-patient interaction in a university teaching hospital from a southwestern state in Nigeria with the aim of identifying the role of communication in an L2, patterns of communication, discourse strategies, pragmatic acts, and contexts that shape the interaction. Jacob Mey’s Pragmatic Acts notion complemented with Emanuel and Emanuel’s model of doctor-patient relationship provided the theoretical standpoint. Data comprising 7 audio-recorded doctors-patient interactions were collected from a University Hospital in Oyo state, Nigeria. Interactions involving the use of English language were purposefully selected. These were supplemented with patients’ case notes and interviews conducted with doctors. Transcription was patterned alongside modified Arminen’s notations of conversation analysis. In the study, interaction in English between doctor and patients has the preponderance of direct-translation, code-mixing and switching, Nigerianism and use of cultural worldviews to express medical experience. Irrespective of these, three patterns communication, namely the paternalistic, interpretive, and deliberative were identified. These were exhibited through varying discourse strategies. The paternalistic model reflected slightly casual conversational conventions and registers. These were achieved through the pragmemic activities of situated speech acts, psychological and physical acts, via patients’ quarrel-induced acts, controlled and managed through doctors’ shared situation knowledge. All these produced empathising, pacifying, promising and instructing practs. The patients’ practs were explaining, provoking, associating and greeting in the paternalistic model. The informative model reveals the use of adjacency pairs, formal turn-taking, precise detailing, institutional talks and dialogic strategies. Through the activities of the speech, prosody and physical acts, the practs of declaring, alerting and informing were utilised by doctors, while the patients exploited adapting, requesting and selecting practs. The negotiating conversational strategy of the deliberative model featured in the speech, prosody and physical acts. In this model, practs of suggesting, teaching, persuading and convincing were utilised by the doctors. The patients deployed the practs of questioning, demanding, considering and deciding. The contextual variables revealed that other patterns (such as phatic and informative) are also used and they coalesced in the hospital within the situational and psychological contexts. However, the paternalistic model was predominantly employed by doctors with over six years in practice, while the interpretive, informative and deliberative models were found among registrar and others below six years of medical practice. Doctors’ experience, patients’ peculiarities and shared cultural knowledge influenced doctor-patient communication in the study.

Keywords: pragmatics, communication pattern, doctor-patient interaction, Nigerian hospital situation

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Authors: Jiangbo Hu, Frances Hoyte, Haiquan Huang

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Research identifies that mealtime talk can be a significant learning context that provides children with rich experiences to foster their language and cognitive development. Middle-classed parents create an extended learning discourse for their children through sophisticated vocabulary, narrative and explanation genres at dinner table. However, mealtime opportunities vary with some parents having little interaction with their children and some parents focusing on directive of children’s behaviors. This study investigated five Chinese families’ parent-child interaction during mealtime that was rarely reported in the literature. The five families differ in terms of their living styles. Three families are from professional background where both mothers the fathers work in Australian companies and both of them present at dinner time. The other two families own business. The mothers are housemakers and the fathers are always absent at dinner time due to their busy business life. Employing case study method, the five Chinese families’ parent-child interactions at dinner table were recorded using a video camera. More than 3000 clauses were analyzed with the framework of 'systems of clause complexing' from systemic functional linguistic theory. The finding shows that mothers played a critical role in the interaction with their children by initiating most conversations. The three mothers from professional background tended to use more language in extending and expanding pattern that is beneficial for children’s language development and high level of thinking (e.g., logical thinking). The two house making mothers’ language focused more on the directive of their children’s social manners and dietary behaviors. The fathers though seemed to be less active, contributing to the richness of the conversation through their occasional props such as asking open questions or initiating a new topic. In general, the families from professional background were more advantaged in providing learning opportunities for their children at dinner table than the families running business were. The home experiences of Chinese children is an important topic in research due to the rapidly increasing number of Chinese children in Australia and other English speaking countries. Such research assist educators in the education of Chinese children with more awareness of Chinese children experiences at home that could be very unlike the settings in English schools. This study contributes to the research in this area through the analysis of language in parent-child interaction during mealtime, which is very different from previous research that mainly investigated Chinese families through survey and interview. The finding of different manners in language use between the professional families and business families has implication for the understanding of the variation of Chinese children’s home experiences that is influenced not only by parents’ socioeconomic status but their lifestyles.

Keywords: Chinese children, Chinese parents, mealtime talk, parent-child interaction

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Authors: S. O. Oyamakin, A. U. Chukwu

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Richard's growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richard's growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richard's growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richard's nonlinear growth models better than the classical Richard's growth model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, Richard's, stochastic

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Dina Zakeri, Ali Aminzad

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Multimedia-assisted teaching results in eliminating traditional training barriers, facilitating the cognition process and upgrading learning outcomes. This study attempted to examine the effects of implementing multimedia on teaching technical translation model and on the technical text translation ability of Iranian students of translation. To fulfill the purpose of the study, a total of forty-six learners were selected out of fifty-seven participants in a higher education center in Tehran based on their scores in Preliminary English Test (PET) and were divided randomly into the experimental and control groups. Prior to the treatment, a technical text translation questionnaire was devised and then approved and validated by three assistant professors of technical fields and three assistant professors of Teaching English as a Foreign Language (TEFL) at the university. This questionnaire was administered as a pretest to both groups. Control and experimental groups were trained for five successive weeks using identical course books but with a different lesson plan that allowed employing multimedia for the experimental group only. The devised and approved questionnaire was administered as a posttest to both groups at the end of the instruction. A multivariate ANOVA was run to compare the two groups’ means on the PET, pretest and posttest. The results showed the rejection of all null hypotheses of the study and revealed that multimedia significantly improved technical text translation ability of the learners.

Keywords: multimedia, multimedia-mediated teaching, technical translation model, technical text, translation ability

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Yacoub Aljaffery

Abstract:

Many English writing instructors try to avoid creative writing in their classrooms thinking they need to teach essay rules and organization skills. They seem to forget that creative writing has do’s and don’ts as well. While academic writing is different from fiction writing in some important ways (although perhaps the boundaries are fruitfully blurring), there is much that can be writerly selves. The differences between creative writing and academic writing are that creative writing is written mainly to entertain with the creativity of the mind and academic writing is written mainly to inform in a formal manner or to incite the reader to make an action such as purchase the writer’s product. In this research paper, we are going to find out how could Arabic speaking students, who are learning academic writing in universities, benefit from creative writing such as literature, theatrical scripts, music, and poems. Since Arabic language is known as poetic language, students from this culture tend to like writing with creativity. We will investigate the positive influence of creative writing rules on academic essays and paragraphs in universities, and We will prove the importance of using creative writing activities in any academic writing classroom.

Keywords: ESL teaching, motivation, teaching methods, academic writing , creative writing

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Authors: Elena Puica

Abstract:

This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

Abstract:

Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

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Authors: Zachary Huffman, Joana Rocha

Abstract:

Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

Abstract:

Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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Authors: Volker Mittendorf, Andre Schmale

Abstract:

In this case study, we want to explore the Twitter-use of candidates during the state parliamentary elections-year 2018 in Bavaria, Germany. This paper focusses on the seven parties that probably entered the parliament. Against this background, the paper classifies the use of language as populism which itself is considered as a political communication style. First, we determine the election campaigns which started in the years 2017 on Twitter, after that we categorize the posting times of the different direct candidates in order to derive ideal types from our empirical data. Second, we have done the exploration based on the dictionary of concerned citizens which contains German political language of the right and the far right. According to that, we are analyzing the corpus with methods of text mining and social network analysis, and afterwards we display the results in a network of words of concerned citizen communication style (CCCS).

Keywords: populism, communication style, election, text mining, social media

Procedia PDF Downloads 149