Search results for: news selection

Authors: Sabrina Howard

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'Window Seat' uses public transportation as an entry point for understanding the relationship between public space, politics, and social identity construction. This project argues that by bringing people of different races, classes, and genders in 'contact' with one another, public transit operates as a site of exposure, as people consciously and unconsciously perform social identity within these spaces. These performances offer a form of freedom that we associate with being in urban spaces while simultaneously rendering certain racialized, gendered, and classed bodies vulnerable to violence. Furthermore, due to its exposing function, public transit operates as a site through which we, as urbanites and scholars, can read social injustice and reflect on the work that is necessary to become a truly democratic society. The major questions guiding this research are: How does using public transit as the entry point provide unique insights into the relationship between social identity, politics, and public space? What ideas do Americans hold about public space and how might these ideas reflect a liberal yearning for a more democratic society? To address these research questions, 'Window Seat' critically examines ethnographic data collected on public buses and trains in Los Angeles, California, and online news media. It analyzes these sources through literature in socio-cultural psychology, sociology, and political science. It investigates the 'everyday urban hero' narrative or popular news stories that feature an individual or group of people acting against discriminatory or 'Anti-American' behavior on public buses and trains. 'Window Seat' studies these narratives to assert that by circulating stories of civility in news media, United Statsians construct and maintain ideas of the 'liberal city,' which is characterized by ideals of freedom and democracy. Furthermore, for those involved, these moments create an opportunity to perform the role of the Good Samaritan, an identity that is wrapped up in liberal beliefs in diversity and inclusion. This research expands conversations in urban studies by making a case for the political significance of urban public space. It demonstrates how these sites serve as spaces through which liberal beliefs are circulated and upheld through identity performance.

Keywords: social identity, public space, public transportation, liberalism

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Authors: Ahmed Elbeltagy, Francesca Bertolini, Damarius Fleming, Angelica Van Goor, Chris Ashwell, Carl Schmidt, Donald Kugonza, Susan Lamont, Max Rothschild

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The major factor in shaping genomic variation of the African indigenous rural chicken is likely natural selection drives the development genetic footprints in the chicken genomes. To investigate such a hypothesis of a selection footprint, a total of 292 birds were randomly sampled from three indigenous ecotypes from East Africa (Uganda, Rwanda) and North Africa (Egypt) and two registered Egyptian breeds (Fayoumi and Dandarawi), and from the synthetic Kuroiler breed. Samples were genotyped using the Affymetrix 600K Axiom® Array. A total of 526,652 SNPs were utilized in the downstream analysis after quality control measures. The intra-population runs of homozygosity (ROH) that were consensuses in > 50% of individuals of an ecotype or > 75% of a breed were studied. To identify inter-population differentiation due to genetic structure, FST was calculated for North- vs. East- African populations in addition to population-pairwise combinations for overlapping windows (500Kb with an overlap of 250Kb). A total of 28,563 ROH were determined and were classified into three length categories. ROH and Fst detected sweeps were identified on several autosomes. Several genes in these regions are likely to be related to adaptation to local environmental stresses that include high altitude, diseases resistance, poor nutrition, oxidative and heat stresses and were linked to gene ontology terms (GO) related to immune response, oxygen consumption and heme binding, carbohydrate metabolism, oxidation-reduction, and behavior. Results indicated a possible effect of natural selection forces on shaping genomic structure for adaptation to local environmental stresses.

Keywords: African Chicken, runs of homozygosity, FST, selection footprints

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Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Lamiche Chaabane

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In this study, a new method for solving sequence alignment problem is proposed, which is named ITS (Improved Tabu Search). This algorithm is based on the classical Tabu Search (TS). ITS is implemented in order to obtain results of multiple sequence alignment. Several ideas concerning neighbourhood generation, move selection mechanisms and intensification/diversification strategies for our proposed ITS is investigated. ITS have generated high-quality results in terms of measure of scores in comparison with the classical TS and simple iterative search algorithm.

Keywords: multiple sequence alignment, tabu search, improved tabu search, neighbourhood generation, selection mechanisms

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Authors: Mohammad Ali Alavidoost, Hossein Bozorgian

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Criterion-referenced tests (CRTs) are designed to measure student performance against a fixed set of predetermined criteria or learning standards. The reliability of such tests cannot be based on internal reliability. Threshold loss agreement is one way to calculate the reliability of CRTs. However, the selection of master and non-master in such agreement is determined by the threshold point. The problem is if the threshold point witnesses a minute change, the selection of master and non-master may have a drastic change, leading to the change in reliability results. Therefore, in this study, the Fuzzy logic approach is employed as a remedial procedure for data analysis to obviate the threshold point problem. Forty-one Iranian students were selected; the participants were all between 20 and 30 years old. A quantitative approach was used to address the research questions. In doing so, a quasi-experimental design was utilized since the selection of the participants was not randomized. Based on the Fuzzy logic approach, the threshold point would be more stable during the analysis, resulting in rather constant reliability results and more precise assessment.

Keywords: criterion-referenced tests, threshold loss agreement, threshold point, fuzzy logic approach

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Authors: Abena Abokoma Asemanyi

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The study examined how the National Disasters are framed in the print media: a study of Daily Graphic newspaper in Ghana. The communication theories employed to conduct this study was Agenda Setting Theory by McCombs and Shaw and the Framing theory by Goffman and Entman. The media’s coverage of National Disasters are of much concern to the general public. This research seeks to know how the Daily Graphic framed National Disasters that occurred in January 2015 and June 2015 respectively. The January 2015 National Disasters was termed as Fire Outbreaks while the June 2015 National Disasters was Twin Disasters. A total of 43 disaster news stories were analysed for this study. Out of the total number, 9 headline stories were analysed in the month of January 2015 and 34 headline stories were looked at in the month of June 2015. The study came up with five (5) themes. Through Content Analysis, the study also revealed that the theme of Action featured more than the other themes which are Fear, Violence, Sympathy and Confusion. Finally, the study showed the number of days disaster news headlines lasted in the Daily Graphic during the period stated above. It was revealed that the Fire Outbreaks in January 2015 appeared in the Daily Graphic for 8 days while the Twin Disasters appeared in 16 days in June 2015.

Keywords: national disaster framing, ghana, daily graphic, daily guide

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Authors: Alexandra Doga, Andreas Lioumpas, Sotiris Petropoulos

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This paper assesses China-Greece relations since 2006, examining them as part of China’s Grand Strategy and Greece’s perception of them. Τhe first aim of the paper is to provide an overview of China-Greece relations in connection with its long- and short-term goals. In essence, it focuses on understanding whether a Chinese grand strategy towards Greece exists. Secondly, it aims to examine the perception of Greeks over China’s foreign policy towards Greece. The intended contribution of the paper is to illustrate the response of national discourses over China’s increased presence in both the global sphere and specific countries in particular. This paper is based on qualitative analysis of secondary data as well as a thorough primary research scheme based on semi-structured interviews. The study made use of official Chinese government documents as well as academic journal articles and books. Local news outlets like newspapers provide data, and news surrounding Greece’s perception of China-Greece relations were also included. Moreover, a number of interviews of Greek officials, academics, journalists, and businessmen were conducted. This paper concluded that the period that began with the 2006 Joint Communiqué between China and Greece on the Establishment of Comprehensive Strategic Partnership has been one of the rapid strengthening of bilateral economic and political relations and frequent high-level visits. There are diverging/opposing views on whether China’s strategic choices towards Greece form part of a broader strategic approach and on whether this strategy is closely connected to the BRI initiative and its priorities.

Keywords: China, Greece, Grand Strategy, BRI, COSCO, Piraeus Port, Mediterranean

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Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Rania Al Namara

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During the Covid-19 pandemic, women disproportionately left the workforce compared to men, and many remained outside of the labor market during the Covid-19 recovery period—a phenomenon referred to as the “she-recession” or “shecession.” While the number of women returning to work has increased, long-standing systemic inequalities interfere with women's equal participation in the workforce. Previous research on media framing has explored the importance of news coverage of women’s issues in print and magazines to shaping the public’s views on an issue and the national response. This study adopts textual analysis to examine how 50 news stories published on CNN and CBS in March 2023 frame women’s employment challenges as a matter of choice or as a matter of insufficient systems and analyzes the narratives portrayed to understand how this discourse affects national policies regarding women’s equality in the workforce. Findings suggest that media coverage centers on four themes: unequal wages at work, work-life integration, experiences of minority women, and the struggle to acquire leadership positions. Media coverage gives space to women to tell personal stories about facing these four societal challenges. However, little coverage is devoted to the political figures and institutions that either reinforce gender inequalities or advance women’s rights in these areas. These findings highlight the need for media stories that discuss policies and reforms that broaden the choices available to women in the first place.

Keywords: Covid-19 recovery, media coverage, shecession, women’s employment

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Jhuang Jin-Jhong, Hsieh Wei-Fan

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Climate change causes natural disasters persistently. Therefore, nowadays environmental planning objective tends to the issues of respecting nature and coexisting with nature. As a result, the natural environment analysis, e.g., the analysis of topography, soil, hydrology, climate, vegetation, is highly emphasized. On the other hand, Feng Shui has been a criterion of site selection for residence in Eastern since the ancient times and has had farther influence on site selection for castles and even for temples and tombs. The primary criterion of site selection is judging the quality of Long: mountain range, Sha: nearby mountains, Shui: hydrology, Xue: foundation, Xiang: aspect, which are similar to the environmental variables of mountain range, topography, hydrology and aspect. For the reason, a lot researchers attempt to probe into the connection between the criterion of Feng Shui and environmental planning factors. Most researches only discussed with the composition and theory of space of Feng Shui, but there is no research which explained Feng Shui through the environmental field. Consequently, this study reviewed the theory of Feng Shui through the environmental planning viewpoint and assembled essential composition factors of Feng Shui. The results of this study point. From literature review and comparison of theoretical meanings, we find that the ideal principles for planning the Feng Shui environment can also be used for environmental planning. Therefore, this article uses 12 ideal environmental features used in Feng Shui to contrast the natural aspects of the environment and make comparisons with previous research and classifies the environmental factors into climate, topography, hydrology, vegetation, and soil.

Keywords: the composition of Feng Shui, environmental planning, site selection, main components of the Feng Shui environment

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Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Sophia Yakhlef

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In spring 2020, the spread of coronavirus disease 2019 (COVID-19) reached the epidemiological criteria to be declared a global pandemic. Global action was taken in order to stop the spread of the virus, such as, for example, restrictions regarding spending time outside of your home and, in several countries, periods of mandatory quarantine. Sweden's method of handling the pandemic has stood out among other European nations, and the tactic of relying on citizens' sense of civic solidarity, rather than enforcing legal restrictions preventing people from spending time outside, has been highly criticised in international news media. This situation has entailed a moral dilemma concerning the proper conduct of behaviour in everyday situations in Sweden, which is also reflected in public news media and social media. This media study focuses on Swedish social media debates and attitudes concerning moral dilemmas of handling this sense of civic solidarity. Comments on social media forums expressing outrage and anger regarding, amongst others, the actions of public media figures (such as celebrities, journalists, and bloggers) are analyzed. Drawing on a social psychological perspective on emotions, the study identifies ambiguities of moral disagreements and moral panics as ways of expressing that a moral norm has been violated. The findings suggest that social media is used in order to handle such ambiguities and make sense of the loosely defined norms of civic solidarity.

Keywords: COVID-19 crisis, moral disagreements, moral panic, social media, social norms, social psychology, Sweden

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Authors: Vanaja Rao

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In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

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Authors: Ali Asghar Memon

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A cautious and astute selection of switching devices used in power electronic converters of a switched reluctance (SR) motor is required. It is a matter of choice of best switching devices with respect to their switching ability rather than fulfilling the number of switches. This paper highlights the computational determination of switching losses comprising of switch-on, switch-off and conduction losses respectively by using experimental data in simulation model of a SR machine. The finding of this research is helpful for proper selection of electronic switches and suitable converter topology for switched reluctance motor.

Keywords: converter, operating modes, switched reluctance motor, switching losses

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Authors: Nisa Ertoy Inci, Cengiz Toker

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Winter or autumn-sown faba bean (Vicia faba L.) is one the most efficient ways to overcome drought since faba bean is usually grown under rainfed where drought and high-temperature stresses are the main growth constraints. The objectives of this study were assessment of (i) relationships between cold tolerance and agro-morphological traits, and (ii) the most suitable agro-morphological trait(s) under cold conditions. Three species of the genus Vicia L. includes 109 genotypes of faba bean (Vicia faba L.), three genotypes of narbon bean (V. narbonensis L.) and two genotypes of V. montbretii Fisch. & C.A. Mey. Davis and Plitmann were sown in autumn at highland of Mediterranean region of Turkey. All relatives of faba bean were more cold-tolerant than the faba bean genotypes. Three faba bean genotypes, ACV-42, ACV-84 and ACV-88, were selected as sources of cold tolerance under field conditions. Path and correlation coefficients and factor and principal component analyses indicated that biological yield should be evaluated in selection for cold tolerance under cold conditions ahead of many agro-morphological traits. The seed weight should be considered for selection in early breeding generations because they had the highest heritability.

Keywords: cold tolerance, faba bean, narbon bean, selection

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Authors: Anitha Narasimhan, Aarthy Anandan, Madhan Karky, C. N. Subalalitha

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Games can be the excellent tools for teaching a language. There are few e-learning games in Indian languages like word scrabble, cross word, quiz games etc., which were developed mainly for educational purposes. This paper proposes a Tamil word game called, “Porul”, which focuses on education as well as on players’ thinking and decision-making skills. Porul is a multiple choice based quiz game, in which the players attempt to answer questions correctly from the given multiple options that are generated using a unique algorithm called the Option Selection algorithm which explores the semantics of the question in various dimensions namely, synonym, rhyme and Universal Networking Language semantic category. This kind of semantic exploration of the question not only increases the complexity of the game but also makes it more interesting. The paper also proposes a Scoring Algorithm which allots a score based on the popularity score of the question word. The proposed game has been tested using 20,000 Tamil words.

Keywords: Porul game, Tamil word game, option selection, flash card, scoring, algorithm

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Authors: Melissa Angus Baboun

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Utilizing a Critical Discourse Analysis (CDA) methodology and a theoretical framework based on disability studies, how Jamaican and Trinidadian newspapers discussed issues relating to the Deaf community were examined. The term deaf was inputted into the search engine tool of the online website for the Jamaica Observer and the Trinidad & Tobago Guardian. All 27 articles that contained the term deaf in its content and were written between August 1, 2017 and November 15, 2017 were chosen for the study. The data analysis was divided into three steps: (1) listing and analysis instances of metaphorical deafness (e.g. fall on deaf ears), (2) categorization of the content of the articles into the models of disability discourse (the medical, socio-cultural, and superscrip models of disability narratives), and (3) the analysis of any additional data found. A total of 42% of the articles pulled for this study did not deal with the Deaf community in any capacity, but rather instances of the use of idiomatic expressions that use deafness as a metaphor for a non-physical, undesirable trait. The most common idiomatic expression found was fall on deaf ears. Regarding the models of disability discourse, eight articles were found to follow the socio-cultural model, two were found to follow the medical model, and two were found to follow the superscrip model. The additional data found in these articles include two instances of the term deaf and mute, an overwhelming use of lower case d for the term deaf, and the misuse of the term translator (to mean interpreter).

Keywords: deafness, disability, news coverage, Caribbean newspapers

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: Tao Song, Hao Cheng, Guangfeng Tian, Chuang Xu

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An autonomous emergency braking system is an advanced driving assistance system that enables vehicle collision avoidance and pedestrian collision avoidance to improve vehicle safety. At present, because the pedestrian target is small, and the mobility is large, the pedestrian AEB system is faced with more technical difficulties and higher functional requirements. In this paper, a method of pedestrian target selection based on a variable width funnel is proposed. Based on the current position and predicted position of pedestrians, the relative position of vehicle and pedestrian at the time of collision is calculated, and different braking strategies are adopted according to the hazard level of pedestrian collisions. In the CNCAP standard operating conditions, comparing the method of considering only the current position of pedestrians and the method of considering pedestrian prediction position, as well as the method based on fixed width funnel and variable width funnel, the results show that, based on variable width funnel, the choice of pedestrian target will be more accurate and the opportunity of the intervention of AEB system will be more reasonable by considering the predicted position of the pedestrian target and vehicle's lateral motion.

Keywords: automatic emergency braking system, pedestrian target selection, TTC, variable width funnel

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Authors: Caleb B. Sagwa, Tobias O. Okeno, Alexander K. Kahi

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Dairy cattle production plays an important role in the Kenyan economy. However, high incidences of mastitis is a major setback to the productivity in this industry. The current dairy cattle breeding objective in Kenya does not include mastitis resistance, mainly because the economic value of mastitis resistance has not been determined. Therefore this study aimed at estimating the economic value of mastitis resistance in dairy cattle in Kenya. Initial input parameters were obtained from literature on dairy cattle production systems in the tropics. Selection index methodology was used to derive the economic value of mastitis resistance. Somatic cell count (SCC) was used an indicator trait for mastitis resistance. The economic value was estimated relative to milk yield (MY). Economic values were assigned to SCC in a selection index such that the overall gain in the breeding goal trait was maximized. The option of estimating the economic value for SCC by equating the response in the trait of interest to its index response was considered. The economic value of mastitis resistance was US $23.64 while maximum response to selection for MY was US $66.01. The findings of this study provide vital information that is a pre-requisite for the inclusion of mastitis resistance in the current dairy cattle breeding goal in Kenya.

Keywords: somatic cell count, milk quality, payment system, breeding goal

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Authors: R. S. Vikaash, S. Vinodh, T. S. Sai Prashanth

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Six sigma is a defect reduction strategy enabling modern organizations to achieve business prosperity. The practitioners are in need to select best six sigma project among the available alternatives to achieve customer satisfaction. In this circumstance, this article presents a study in which six sigma project selection is formulated as Multi-Criteria Decision-Making(MCDM) problem and the best project has been found using AHP. Five main governing criteria and 14 sub criteria are being formulated. The decision maker’s inputs were gathered and computations were performed. The project with the high values from the set of projects is selected as the best project. Based on calculations, Project “P1”is found to be the best and further deployment actions have been undertaken in the organization.

Keywords: six Sigma, project selection, MCDM, analytic hierarchy process, business prosperity

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Authors: Jenq-Shyong Chen, Ben-Fong Yu

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CNC(computer numerical control) machining centers have been widely used for machining different metal components for various industries. For a specific CNC machine, its everyday job is assigned to cut different products with quite different attributes such as material type, workpiece weight, geometry, tooling, and cutting conditions. Theoretically, the dynamic characteristics of the CNC machine should be properly tuned match each machining job in order to get the optimal machining performance. However, most of the CNC machines are set with only a standard set of CNC parameters. In this study, we have developed an auto-tuning system which can automatically change the CNC parameters and in hence change the machine dynamic characteristics according to the selection of machining modes which are set by the mixed combination of three machine performance indexes: the HO (high surface quality) index, HP (high precision) index and HS (high speed) index. The acceleration, jerk, corner error tolerance, oscillation and dynamic bandwidth of machine’s feed axes have been changed according to the selection of the machine performance indexes. The proposed auto-tuning system of the CNC parameters has been implemented on a PC-based CNC controller and a three-axis machining center. The measured experimental result have shown the promising of our proposed auto-tuning system.

Keywords: auto-tuning, CNC parameters, machining mode, high speed, high accuracy, high surface quality

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Authors: Majority Oji

Abstract:

The print media played a major role in the agitation for self-rule in Nigeria in the 1950s. It remains as a bastion of hope in the dark days of military rule in the country. But in the troubled waters of Nigeria’s politics, accusing fingers are pointed in the direction of the print media as problematic to the political development of the nation. Thus, Nigeria as a nation is torn between the paralyzing forces of political instability and the building powers of political stability. The press assigned a constitutional role to hold everyone, especially government officials accountable to the public, appears to be at the center of these forays. The paper takes a look at the strength and weakness of the print media as a stabilizing or destabilizing agent to the political development of Nigeria. Engaging in this study is essential and the findings fundamental to the sustainability of Nigeria’s nascent democracy. The study draws on the content analysis method. News items from major newspapers across the country were content analyzed to test the validity of the claims that the press serve as agent of political stability or political instability, and whether to accept or reject such claims. The study found that the press has published more stories that unite the people politically as found in the tested hypothesis which shows that P>0.05 implying that media publications are not significant to political instability of the nation regardless of the number of published news stories. The study recommends that all issues relating to professional and ethical standards that affect the practice of journalism in the print media should be addressed by regulatory bodies to starve of chances of information that could lead to intolerance being peddled in the print media.

Keywords: Nigeria, political instability, political stability, print media

Procedia PDF Downloads 228

Authors: Abeer Amayri, Akif A. Bulgak

Abstract:

Due to today’s globalization as well as outsourcing practices of the companies, the Supply Chain (SC) performances have become more dependent on the efficient movement of material among places that are geographically dispersed, where there is more chance for disruptions. One such disruption is the quality and delivery uncertainties of outsourcing. These uncertainties could lead the products to be unsafe and, as is the case in a number of recent examples, companies may have to end up in recalling their products. As a result of these problems, there is a need to develop a methodology for selecting suppliers globally in view of risks associated with low quality and late delivery. Accordingly, we developed a two-stage stochastic model that captures the risks associated with uncertainty in quality and delivery as well as a solution procedure for the model. The stochastic model developed simultaneously optimizes supplier selection and purchase quantities under price discounts over a time horizon. In particular, our target is the study of global organizations with multiple sites and multiple overseas suppliers, where the pricing is offered in suppliers’ local currencies. Our proposed methodology is applied to a case study for a US automotive company having two assembly plants and four potential global suppliers to illustrate how the proposed model works in practice.

Keywords: global supply chains, quality, stochastic programming, supplier selection

Procedia PDF Downloads 430

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

Abstract:

Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

Procedia PDF Downloads 89

Authors: Essam Mansour

Abstract:

This study purposes to explore the adoption and use of social media as a source of information by Egyptian government journalists. It applied a survey with a total of 386 journalists representing the three official newspapers of Egypt. Findings showed that 27.2% of journalists were found to not use social media, mainly males (69.7%), older than 40 years (77.7%) and mostly with a BA degree (80.4%). On the other hand, 72.8% of them were found to use these platforms who were also males (59.1%), younger than 40 years (65.9%) and mostly with a BA degree (93.2%). More than two-thirds (69.9%) were somewhat old users whose experience ranged from seven to ten years, and more than two-thirds (73.5%) have been heavily using these platforms (four to more than six hours a day. Such results confirm that a large number (95.7%) of users were found to be at least advanced users. Social media users’ home and work were the most significant places to access these platforms, which were found to be easy and useful to use. Most types of social media used were social news, media sharing and micro blogging, blogs comments and forums, social networking sites and bookmarking sites to perform tasks, such as finding information, making communication, keeping up to date, checking materials, sharing information and making discussions. A large number of users tend to accept these media platforms to be a source of information since they are accessible, linked references updated sources, accurate, promote current work, convenient, secured, credible, reliable, stabled, easily identified, copyrighted, build confident and contain filtered information. However, lack of know-how to cite sources, followed by lack of credibility of the source of news, lack of quality of information sources and lack of time were at least significant to journalists when using social media platforms.

Keywords: social media, social networking sites, newspapers, journalists, Egypt

Procedia PDF Downloads 233