Search results for: large language models (LLMS)

Authors: Savita Tangwongkit, Chittur S Srinivasan, Philip J. Jones

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Thailand has become the world’s fourth largest sugarcane producer and second largest sugar exporter. While there have been a number of drivers of this growth, the primary driver has been wide-ranging government support measures. Recently, the Thai government has emphasized the need for policy reform as part of a broader industry restructuring to bring the sector up-to-date with the current and future developments in the international sugar market. Because of the sectors historical dependence on government support, any such reform is likely to have a very significant impact on the fortunes of Thai cane farmers. This study explores the impact of three policy scenarios, representing a spectrum of policy approaches, on Thai cane producers. These reform scenarios were designed in consultation with policy makers and academics working in the cane sector. Scenario 1 captures the current ‘government proposal’ for policy reform. This scenario removes certain domestic production subsidies but seeks to maintain as much support as is permissible under current WTO rules. The second scenario, ‘protectionism’, maintains the current internal market producer supports, but otherwise complies with international (WTO) commitments. Third, the ‘libertarian scenario’ removes all production support and market interventions, trade and domestic consumption distortions. Most important driver of producer behaviour in all of the scenarios is the producer price of cane. Cane price is obviously highest under the protectionism scenario, followed by government proposal and libertarian scenarios, respectively. Likely producer responses to these three policy scenarios was determined by means of a large-scale survey of cane farmers. The sample was stratified by size group and quotas filled by size group and region. One scenario was presented to each of three sub-samples, consisting of approx.150 farmers. Total sample size was 462 farms. Data was collected by face-to-face interview between June and August 2019. There was a marked difference in farmer response to the three scenarios. Farmers in the ‘Protectionism’ scenario, which maintains the highest cane price and those who farm larger cane areas are more likely to continue cane farming. The libertarian scenario is likely to result in the greatest losses in terms of cane production volume broadly double that of the ‘protectionism’ scenario, primarily due to farmers quitting cane production altogether. Over half of loss cane production volume comes from medium-size farm, i.e. the largest and smallest producers are the most resilient. This result is likely due to the fact that the medium size group are large enough to require hired labour but lack the economies of scale of the largest farms. Over all size groups the farms most heavily specialized in cane production, i.e. those devoting 26-50% of arable land to cane, are also the most vulnerable, with 70% of all farmers quitting cane production coming from this group. This investigation suggests that cane price is the most significant determinant of farmer behaviour. Also, that where scenarios drive significantly lower cane price, policy makers should target support towards mid-sized producers, with policies that encourage efficiency gains and diversification into alternative agricultural crops.

Keywords: farmer intentions, farm survey, policy reform, Thai cane production

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Authors: Santhosh Ravichandran, F. J. Rodríguez-Varela

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In this study, a biocarbon (BC) was made from sewage sludge from the water treatment plant (PTAR) in Saltillo, Coahuila, Mexico. The sludge was carbonized in water and then chemically activated by pyrolysis. The biocarbon was evaluated physicochemically using XRD, SEM-EDS, and FESEM. A broad (002) peak attributable to graphitic structures indicates that the material is amorphous. The resultant biocarbon has a high specific surface area (412 m2 g-1), a large pore volume (0.39 cm3 g-1), interconnected hierarchical porosity, and outstanding electrochemical performance. It is appropriate for high-performance supercapacitor electrode materials due to its high specific capacitance of 358 F g-1, great rate capability, and outstanding cycling stability (around 87% capacitance retention after 10,000 cycles, even at a high current density of 19 A g-1). In an aqueous solution, the constructed BC/BC symmetric supercapacitor exhibits increased super capacitor behavior with a high energy density of 29.5 Whkg-1. The concept provides an efficient method for producing high-performance electrode materials for supercapacitors from conventional water treatment biomass wastes.

Keywords: supercapacitors, carbon, material science, batteries

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Authors: Jaroslav Kušnír

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Hawaiian literature in English has been researched more intensively in the past decades, mostly in the context of Asian American literature. In his collection of stories Language of the Gecko's and Other Stories, Hawaiian author Gary Pak explores complex relationships between Asian, Native Hawaiian, and American characters living mostly in Hawaii. Through a depiction of these complex relationships, Pak also explores the interaction between different cultures in Hawaii as well as the formation of Asian/Hawaiian identity in the modern world. Based on a comparative approach and close analysis method, this paper will explore the role of place and its historical and cultural background in the formation of modern Asian/Hawaiian cultural identity as manifested in Pak's stories My Friend Kammy and Ishmael Reed or Me. At the same time, through the use of Bill Ashcroft´s concept of transnation, the author of this paper will analyze Pak's depiction of the formation of the cultural identity of characters from Gary Pak's stories My Friend Kammy and Ishmael Reed or Me, which are, in the author of this paper´s view, the characters close to the concept of Ashcroft's transnation which makes them different from traditional cosmopolitan or diasporic characters.

Keywords: culture, cultural identity, Hawaiian identity, Hawaiian literature, place, transnation

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Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

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Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

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Authors: Qian Pei, Hengjian Tong, Weitao Chen, Hai Wang, Yanrong Feng

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Horizontal parallax is the foundation of stereoscopic viewing. However, the human eye will feel uncomfortable and it will occur diplopia if horizontal parallax is larger than eye separation. Therefore, we need to do parallax refining before conducting stereoscopic observation. Although some scholars have been devoted to online remote sensing refining, the main work of image refining is completed on the server side. There will be a significant delay when multiple users access the server at the same time. The emergence of HTML5 technology in recent years makes it possible to develop rich browser web application. Authors complete the image parallax refining on the browser side based on HTML5, while server side only need to transfer image data and parallax file to browser side according to the browser’s request. In this way, we can greatly reduce the server CPU load and allow a large number of users to access server in parallel and respond the user’s request quickly.

Keywords: 3D remote sensing images, parallax, online refining, rich browser web application, HTML5

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Authors: Carolina Cuéllar, Paz González

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Research has shown that school leadership has a significant indirect effect on students’ achievements. In Chile, evidence has also revealed that this impact is stronger in vulnerable schools. With the aim of strengthening school leadership, public policy has taken up the challenge of enhancing capabilities of novice principals through the implementation of induction programs, which include a mentoring component, entrusting the task of delivering these programs to universities. The importance of using mentoring or coaching models in the preparation of novice school leaders has been emphasized in the international literature. Thus, it can be affirmed that building leadership capacity through partnership is crucial to facilitate cognitive and affective support required in the initial phase of the principal career, gain role clarification and socialization in context, stimulate reflective leadership practice, among others. In Chile, mentoring is a recent phenomenon in the field of school leadership and it is even more new in the preparation of new principals who work in public schools. This study, funded by the Chilean Ministry of Education, sought to explore the challenges and lessons arising from the design and implementation of mentoring processes which are part of the induction programs, according to the perception of the different actors involved: ministerial agents, university coordinators, mentors and novice principals. The investigation used a qualitative design, based on a study of three cases (three induction programs). The sources of information were 46 semi-structured interviews, applied in two moments (at the beginning and end of mentoring). Content analysis technique was employed. Data focused on the uniqueness of each case and the commonalities within the cases. Five main challenges and lessons emerged in the design and implementation of mentoring within the induction programs for new principals from Chilean public schools. They comprised the need of (i) developing a shared conceptual framework on mentoring among the institutions and actors involved, which helps align the expectations for the mentoring component within the induction programs, along with assisting in establishing a theory of action of mentoring that is relevant to the public school context; (ii) recognizing trough actions and decisions at different levels that the role of a mentor differs from the role of a principal, which challenge the idea that an effective principal will always be an effective mentor; iii) improving mentors’ selection and preparation processes trough the definition of common guiding criteria to ensure that a mentor takes responsibility for developing critical judgment of novice principals, which implies not limiting the mentor’s actions to assist in the compliance of prescriptive practices and standards; (iv) generating common evaluative models with goals, instruments and indicators consistent with the characteristics of mentoring processes, which helps to assess expected results and impact; and (v) including the design of a mentoring structure as an outcome of the induction programs, which helps sustain mentoring within schools as a collective professional development practice. Results showcased interwoven elements that entail continuous negotiations at different levels. Taking action will contribute to policy efforts aimed at professionalizing the leadership role in public schools.

Keywords: induction programs, mentoring, novice principals, school leadership preparation

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Authors: Tajinder Kaur, Anu Bala

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An image retrieval system is a computer system for browsing, searching, and retrieving images from a large database of digital images a new algorithm meant for content-based image retrieval (CBIR) is presented in this paper. The proposed method combines the color and texture features which are extracted the global and local information of the image. The local texture feature is extracted by using local binary patterns (LBP), which are evaluated by taking into consideration of local difference between the center pixel and its neighbors. For the global color feature, the color histogram (CH) is used which is calculated by RGB (red, green, and blue) spaces separately. In this paper, the combination of color and texture features are proposed for content-based image retrieval. The performance of the proposed method is tested on Corel 1000 database which is the natural database. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to LBP and CH.

Keywords: color, texture, feature extraction, local binary patterns, image retrieval

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Authors: Nadeem Akhtar, Hira Javed

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An important aspect of research is literature survey. Availability of a large amount of literature across different domains triggers the need for optimized systems which provide relevant literature to researchers. We propose a search system based on keywords for text documents. This experimental approach provides a hierarchical structure to the document corpus. The documents are labelled with keywords using KEA (Keyword Extraction Algorithm) and are automatically organized in a lattice structure using Formal Concept Analysis (FCA). This groups the semantically related documents together. The hierarchical structure, based on keywords gives out only those documents which precisely contain them. This approach open doors for multi-domain research. The documents across multiple domains which are indexed by similar keywords are grouped together. A hierarchical relationship between keywords is obtained. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on Semeval-2010 Dataset. Results depict that the presented method is considerably successful in indexing of scientific papers.

Keywords: formal concept analysis, keyword extraction algorithm, scientific documents, lattice

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Gokul G. Kshirsagar

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Native folk theatre and folk songs have a significant influence on the origin and development of Indian cinema. Therefore, the presence of songs and music has been an integral part and special characteristics of Indian cinema which is popularly known as Bollywood. An Indian cinema without songs, either in Hindi or other regional languages, is simply unimaginable. The present paper, in the first part, attempts to explain the use and need of musical songs and also the psychology of Indian audience in this respect with reference to some of the films which give primary importance to songs. In the second part, the paper tries to situate the present study in the context by referring to the Hindi language drama film Teesari Kasam directed by Basu Bhattacharys. The film is based on the Hindi novelist Phanishwarnath Renu’s short story Teesari Kasam (Mare Gaye Gulfam) in this adapted film, the director has made use of eight songs, but these songs are the extensive versions of the songs as used in the original story. Thus, the main aim of the paper is to underscore the fact that through artistic use of the musical, the director has succeeded in transforming the central feelings conveyed in the original story. Eventually, through the present study of the film adaptation, the relevance of songs in films will be illustrated and understood.

Keywords: Bollywood, folk theatre, folk songs, film adaptation

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Authors: Olha Yarova

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This study is a collaborative project between the American University of Central Asia and parent association of children with Down syndrome ‘Sunterra’ that took place in Bishkek, Kyrgyzstan. The purpose of the study was to explore whether principles and techniques of applied behavior analysis (ABA) could be used to teach children with Down syndrome socially significant behaviors. ABA is considered to be one of the most effective treatment for children with autism, but little research is done on the particularity of using ABA to children with Down syndrome. The data for the study was received during clinical observations; work with children with Down syndrome and interviews with their mothers. The results show that many ABA principles make the work with children with Down syndrome more effective. Although such children very rarely demonstrate aggressive behavior, they show a lot of escape-driven and attention seeking behaviors that are reinforced by their parents and educators. Thus functional assessment can be done to assess the function of problem behavior and to determine appropriate treatment. Prompting and prompting fading should be used to develop receptive and expressive language skills, and enhance motor development. Even though many children with Down syndrome work for praise, it is still relevant to use tangible reinforcement and to know how to remove them. Based on the results of the study, the training for parents of children with Down syndrome will be developed in Kyrgyzstan, country, where children with Down syndrome are not accepted to regular kindergartens and where doctors in maternity hospitals tell parents that their child will never talk, walk and recognize them

Keywords: down syndrome, applied behavior analysis, functional assessment, problem behavior, reinforcement

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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Authors: A. Shafaghat, H. Khabbaz, S. Moravej, Ah. Shafaghat

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The bearing capacity of closely spaced shallow footings alters with their spacing and the shape of footing. In this study, the bearing capacity and settlement of two adjacent footings constructed on a sand layer are investigated. The effect of different footing shapes including square, circular, ring and strip on sandy soil is captured in the calculations. The investigations are carried out numerically using PLAXIS-3D software and analytically employing conventional settlement equations. For this purpose, foundations are modelled in the program with practical dimensions and various spacing ratios ranging from 1 to 5. The spacing ratio is defined as the centre-to-centre distance to the width of foundations (S/B). Overall, 24 models are analyzed; and the results are compared and discussed in detail. It can be concluded that the presence of adjacent foundation leads to the reduction in bearing capacity for round shape footings while it can increase the bearing capacity of rectangular footings in some specific distances.

Keywords: bearing capacity, finite element analysis, loose sand, settlement equations, shallow foundation

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Authors: Nel Jayson Santos

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The growing number of international students in post-secondary institutions in Canada has positively contributed to the country’s economy and educational systems while also enriching cultural diversity in the classrooms. However, international students face social and relational challenges as they try to adapt to their host nation’s culture. One specific area of cultural adaptation among international students that has yet to be studied extensively is dating experiences and romantic relationships. Although numerous studies have been done regarding the relational challenges and dating experiences of American international students, only a few studies have focused on international students based in Canada. Hence, this study examines the dating preferences, dating challenges, and dating adaptations of international students based in Vancouver, Canada. Using a social constructivist approach, a semi-structured interview was conducted among fifteen heterosexual international college students. Inductive thematic analysis was then used to analyze the gathered data and identify common themes. Findings suggest that students’ (1) preferences were influenced by racial background and parental approval of dating partners; (2) students experienced language barriers and cultural differences; (3) students adapted through constant communication and being open-minded. Finally, the analysis intends to help counselors and psychologists in various colleges to help understand the issues of international students in terms of intimate and romantic relationships.

Keywords: higher education, international students, dating experiences, cultural adaptation

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Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

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To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

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Authors: Nathi Ram, Saurabh K. Yadav

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In turbomachinery, the turbulent flow occurs due to the use of high velocity of low kinematic viscosity lubricants and used in many industrial applications. In the present work, the performance of symmetric slot-entry hybrid worn journal bearing under laminar and turbulent lubrication has been investigated. For turbulent lubrication, the Reynolds equation has been modified using Constantinescu turbulent model. This modified equation has been solved using the finite element method. The effect of turbulent lubrication on bearing’s performance has been presented for symmetric hybrid journal bearing. The slot-entry hybrid worn journal bearing under turbulent/laminar regimes have been investigated. It has been observed that the stiffness and damping coefficients are more for the bearing having slot width ratio (SWR) of 0.25 than the bearing with SWR of 0.5 and 0.75 under the turbulent regime. Further, it is also observed that for constant wear depth parameter, stability threshold speed gets increased for bearing operates at slot width ratio 0.25 under turbulent lubrication.

Keywords: hydrostatic bearings, journal bearings, restrictors, turbulent flow models, finite element technique

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Authors: Aster Misganaw

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This study investigates the reach, influence, and credibility of international broadcasters—specifically Voice of America (VOA), Deutsche Welle (DW), and British Broadcasting Corporation (BBC)—among Ethiopian audiences, comparing these perceptions to local media sources. Utilizing a mixed-methods approach that included quantitative surveys and qualitative interviews, the research reveals that the majority of respondents engage regularly with international broadcasters, with younger audiences showing a marked preference. Findings indicate that most of the participants perceive these international sources as more credible than local media, largely due to concerns over government influence on local reporting. Furthermore, the study finds that the majority of respondents believe international broadcasters significantly shape their understanding of both domestic and international issues, highlighting their critical role in public discourse. To enhance their relevance, it is recommended that international broadcasters incorporate more localized content while local media must work to improve their credibility and independence to better serve the Ethiopian public. This research contributes to the understanding of media consumption dynamics in Ethiopia, emphasizing the interplay between local and international narratives in shaping public opinion.

Keywords: international media, BBC, Deutsche Welle, Ethiopian media, Voice of America, audience

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Yihao Kuang, Bowen Ding

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With the increasing scale and complexity of knowledge graph, modern knowledge graph contains more and more types of entity, relationship, and attribute information. Therefore, in recent years, it has been a trend for knowledge graph inference to use reinforcement learning to deal with large-scale, incomplete, and noisy knowledge graphs and improve the inference effect and interpretability. The Proximal Policy Optimization (PPO) algorithm utilizes a near-end strategy optimization approach. This allows for more extensive updates of policy parameters while constraining the update extent to maintain training stability. This characteristic enables PPOs to converge to improved strategies more rapidly, often demonstrating enhanced performance early in the training process. Furthermore, PPO has the advantage of offline learning, effectively utilizing historical experience data for training and enhancing sample utilization. This means that even with limited resources, PPOs can efficiently train for reinforcement learning tasks. Based on these characteristics, this paper aims to obtain a better and more efficient inference effect by introducing PPO into knowledge inference technology.

Keywords: reinforcement learning, PPO, knowledge inference

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Authors: Nabi Ullah

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The energy crisis of the current society has attracted research attention for alternative energy sources. Methanol oxidation is the source of energy but needs efficient electrocatalysts like Pt. However, their practical ability is hindered due to cost and poisoning effects. In this regard, an efficient catalyst is required for methanol oxidation. Herein, high temperature, pressure, and diethylenetryamine (DETA) as reaction medium/structure directing agent during the solvothermal method are used for nanobelt Cu₃Se₂/Cu₁.₈Se (mostly hexagonal appearance) formation. The electrocatalyst shows optimized methanol electrooxidation reaction (MOR) response in 1 M KOH and 0.5 M methanol at a scan rate of 50 mV/s and delivers a current density of 7.12 mA/mg at a potential of 0.65 V (vs Ag/AgCl). The catalyst exhibits high electrochemical active surface area (ECSA) (0.088 mF/cm²) and low Rct with good stability for 3600 s, which favors its high MOR performance. This high response is due to its 2D hexagonal nanobelt morphology, which provides a large surface area for reaction. The space among nanobelts reduces diffusion kinetics, and the rough/irregular edge increases the reaction site to improve the methanol oxidation reaction overall.

Keywords: energy application, electrocatalysis, MOR, nanobelt

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Authors: Zhuo Jing-Schmidt, Jun Lang

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Numeral classifiers are common in Asian languages. Research on numeral classifiers primarily focuses on noun classifiers that quantify and individuate nominal referents. There is a scarcity of research on event quantification using verb classifiers. This study aims to understand the semantic and conceptual basis of event quantification in Chinese. From a usage-based Construction Grammar perspective, this study presents a corpus analysis of event quantification in Chinese. Drawing on a large balanced corpus of contemporary Chinese, we analyze 667 NOUN col-lexemes totaling 31136 tokens of a productive numeral classifier construction in Chinese. Using collostructional analysis of the collexemes, the results show that the construction quantifies and classifies dramatic events using a theater-based conceptual metaphor. We argue that the usage patterns reflect the cultural entrenchment of theater as in Chinese conceptualization and the construal of theatricality in linguistic expression. The study has implications for cognitive semantics and construction grammar.

Keywords: event quantification, classifier, corpus, metaphor

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Aleksandar Hatzivelkos

Abstract:

The term ”compromise” is mostly used casually within the social choice theory. It is usually used as a mere result of the social choice function, and this omits its deeper meaning and ramifications. This paper is based on a mathematical model for the description of a compromise as a version of the Sorites paradox. It introduces a formal definition of d-measure of divergence from a compromise and models a notion of compromise that is often used only colloquially. Such a model for vagueness phenomenon, which lies at the core of the notion of compromise enables the introduction of new mathematical structures. In order to maximize compromise, different methods can be used. In this paper, we explore properties of a social welfare function TdM (from Total d-Measure), which is defined as a function which minimizes the total sum of d-measures of divergence over all possible linear orderings. We prove that TdM satisfy strict Pareto principle and behaves well asymptotically. Furthermore, we show that for certain domain restrictions, TdM satisfy positive responsiveness and IIIA (intense independence of irrelevant alternatives) thus being equivalent to Borda count on such domain restriction. This result gives new opportunities in social choice, especially when there is an emphasis on compromise in the decision-making process.

Keywords: borda count, compromise, measure of divergence, minimization

Procedia PDF Downloads 133

Authors: E. Prema

Abstract:

Biotechnology is a study relating to the practical application of living beings in different fields. Generally, it is a study with regard to living organisms in the industrial utilization. It is the technology, which uses living organisms or its parts for specific commercial use. Modification and application of living beings for different practical purposes is possible through biotechnology. Furthermore, today biotechnology is being used in different fields for better results. It is worthwhile to note here that biotechnology is one of the most innovative and intensive industries. It has used the genetically based characteristics in microorganisms, plants and animals to create drugs and to develop drug therapies, which may prevent, cure or alleviate disease and their symptoms. Drugs are basically chemicals and while patenting drugs, the conditions of patentability of chemicals and the types that can be patented are equally applicable to drugs also. Nowadays, the role of biotechnology for manufacturing drugs has assumed much importance because of intellectual property rights. By way using biotechnology, most of the pharmaceutical inventions are getting protection for the period of 20 years as per the Patents Act, 1970 as amended in 2005. There is no doubt that biotechnology is serving the public at large with regard manufacturing drugs and helping the needy people on time.

Keywords: biotechnology, drugs, intellectual property rights, patents

Procedia PDF Downloads 454

Authors: Bruno Kinyaga

Abstract:

Motorcycles transport commonly known as (Boda boda) in Tanzania has been growing up in the recent years in both urban and rural areas. Since motorcycles have been authorized to carry passengers in Tanzania they have been associated with many accidents resulting in large number of deaths and injuries in the country. Most of the road traffic injury victims are passengers, motorcyclists and pedestrians. Males are over represented in all cases. Most of the deceased were 18-29 years old. The increase of motorcycles has been accompanied with the increase of motorcycle crashes causing deaths and injuries to passengers as well as riders. According to the data collected, the statistics shows that from January to December 2015, the total number of 4079 motorcycles was involved in accidents in the country, causing 1747 deaths and 4826 injuries. Compares to the report of January to December 2014 whereby the total number of motorcycles involved in accidents were 3710, causing 1423 deaths and 3622 injuries. This is according to the report provided by the Road safety Chief Commander in Tanzania.

Keywords: accidents, road, safety, Tanzania

Procedia PDF Downloads 167

Authors: Mohammad Reza Dahmardeh Ghaleno, Mohammad Nohtani, Saeedeh Khaledi

Abstract:

Hydrological models are applied to simulation and prediction floods in watersheds. WetSpa is a distributed, continuous and physically model with daily or hourly time step that explains of precipitation, runoff and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave Equation which depend on the slope, velocity and flow route characteristics. Garmabrood watershed located in Mazandaran province in Iran and passing over coordinates 53° 10´ 55" to 53° 38´ 20" E and 36° 06´ 45" to 36° 25´ 30"N. The area of the catchment is about 1133 km2 and elevations in the catchment range from 213 to 3136 m at the outlet, with average slope of 25.77 %. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe Model Efficiency Coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 61% and 83.17 % respectively.

Keywords: watershed simulation, WetSpa, runoff, flood prediction

Procedia PDF Downloads 336

Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

Abstract:

Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

Procedia PDF Downloads 574

Authors: Babak Kamrani, Nozar Kishi

Abstract:

Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

Procedia PDF Downloads 299