Search results for: priority class

Authors: Purba Biswas, Priyanka Dey

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Worldwide rapid urbanisation has accelerated city expansion in both developed and developing nations. This unprecedented urbanisation trend due to the increasing population and economic growth has caused challenges for the decision-makers in city planning and urban management. Metropolitan cities, class-I towns, and major urban centres undergo a continuous process of evolution due to interaction between socio-cultural and economic attributes. This constant evolution leads to urban expansion in all directions. Understanding the patterns and dynamics of urban built-up growth is crucial for policymakers, urban planners, and researchers, as it aids in resource management, decision-making, and the development of sustainable strategies to address the complexities associated with rapid urbanisation. Identifying spatio-temporal patterns of urban growth has emerged as a crucial challenge in monitoring and assessing present and future trends in urban development. Analysing urban growth patterns and tracking changes in land use is an important aspect of urban studies. This study analyses spatio-temporal urban transformations and land-use and land cover changes using remote sensing and GIS techniques. Built-up growth analysis has been done for the city of Surat as a case example, using the GIS tools of NDBI and GIS models of the Built-up Urban Density Index and Shannon Entropy Index to identify trends and the geographical direction of transformation from 2005 to 2020. Surat is one of the fastest-growing urban centres in both the state and the nation, ranking as the 4th fastest-growing city globally. This study analyses the dynamics of urban built-up area transformations both zone-wise and geographical direction-wise, in which their trend, rate, and magnitude were calculated for the period of 15 years. This study also highlights the need for analysing and monitoring the urban growth pattern of class-I cities in India using spatio-temporal and quantitative techniques like GIS for improved urban management.

Keywords: urban expansion, built-up, geographic information system, remote sensing, Shannon’s entropy

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Authors: Ndumbe Eric Esongami, Manga Veronica Ebot, Foba Josepha Tendo, Yengong Fabrice Lamfu, Tiku David Tambe

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The prevalence and unpleasant nature of plastics pollution constantly observed on beach shore on stormy events has prompt researchers worldwide to thesis on sustainable economic and environmental designs on plastics, especially in Cameroon, a major touristic destination in the Central Africa Region. The inconsistent protocols develop by researchers has added to this burden, thus the morphological nature of microplastic remediation is a call for concerns. The prime aim of the study is to morphologically identify, quantify and forensically understands the distribution of each plastics polymer composition. Duplicates of 2×2 m (4m2) quadrants were sampled in each beach/month over 8 months period across five purposive beaches along the Limbe – Idenau coastline, Cameroon. Collected plastic samples were thoroughly washed and separation done using a 2 mm sieve. Only particles of size, < 2 mm, were considered and forward follow the microplastics laboratory analytical processes. Established step by step methodological procedures of particle filtration, organic matter digestion, density separation, particle extraction and polymer identification including microscope and were applied for the beach microplastics samples. Microplastics were observed in each sample/beach/month with an overall abundance of 241 particles/number weighs 89.15 g in total and with a mean abundance of 2 particles/m2 (0.69 g/m2) and 6 particles/month (2.0 g/m2). The accumulation of beach shoreline MPs rose dramatically towards decreasing size with microbeads and fiber only found in the < 1 mm size fraction. Approximately 75% of beach MPs contamination were found in LDB 2, LDB 1 and IDN beaches/average particles/number while the most dominant polymer type frequently observed also were PP, PE, and PS in all morphologically parameters analysed. Beach MPs accumulation significantly varied temporally and spatially at p = 0.05. ANOVA and Spearman’s rank correlation used shows linear relationships between the sizes categories considered in this study. In terms of polymer MPs analysis, the colour class recorded that white coloured MPs was dominant, 50 particles/number (22.25 g) with recorded abundance/number in PP (25), PE (15) and PS (5). The shape class also revealed that irregularly shaped MPs was dominant, 98 particles/number (30.5 g) with higher abundance/number in PP (39), PE (33), and PS (11). Similarly, MPs type class shows that fragmented MPs type was also dominant, 80 particles/number (25.25 g) with higher abundance/number in PP (30), PE (28) and PS (15). Equally, the sized class forward revealed that 1.5 – 1.99 mm sized ranged MPs had the highest abundance of 102 particles/number (51.77 g) with higher concentration observed in PP (47), PE (41), and PS (7) as well and finally, the weight class also show that 0.01 g weighs MPs was dominated by 98 particles/number (56.57 g) with varied numeric abundance seen in PP (49), PE (29) and PS (13). The forensic investigation of the pollution indicated that majority of the beach microplastic is sourced from the site/nearby area. The investigation could draw useful conclusions regarding the pathways of pollution. The fragmented microplastic, a significant component in the sample, was found to be sourced from recreational activities and partly from fishing boat installations and repairs activities carried out close to the shore.

Keywords: forensic analysis, beach MPs, particle/number, polymer composition, cameroon

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Authors: Ashish Kumar Agrahari, Amit Kumar

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Paroxysmal nocturnal hemoglobinuria (PNH) is an acquired clonal blood disorder that manifests with hemolytic anemia, thrombosis, and peripheral blood cytopenias. The disease is caused by the deficiency of two glycosylphosphatidylinositols (GPI)-anchored proteins (CD55 and CD59) in the hemopoietic stem cells. The deficiency of GPI-anchored proteins has been associated with the somatic mutations in phosphatidylinositol glycan class A (PIGA). However, the mutations that do not cause PNH is associated with the multiple congenital anomalies-hypotonia-seizures syndrome 2 (MCAHS2). To best of our knowledge, no computational study has been performed to explore the atomistic level impact of PIGA mutations on the structure and dynamics of the protein. In the current work, we are mainly interested to get insights into the molecular mechanism of PIGA mutations. In the initial step, we screened the most pathogenic mutations from the pool of publicly available mutations. Further, to get a better understanding, pathogenic mutations were mapped to the modeled structure and subjected to 50ns molecular dynamics simulation. Our computational study suggests that four mutations are highly vulnerable to altering the structural conformation and stability of the PIGA protein, which illustrates its association with PNH and MCAHS2 phenotype.

Keywords: homology modeling, molecular dynamics simulation, missense mutations PNH, MCAHS2, PIGA

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Authors: A. K. Tsafe

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The study investigates the efficacy of Special Mathematics Teaching Strategy (SMTS) as against Conventional Mathematics Teaching Strategy (CMTS) in teaching students identified with Mathematics Learning Disabilities (MLDs) – dyslexia, Down syndrome, dyscalculia, etc., in some junior secondary schools around Sokoto metropolis. Errors and misconceptions in learning Mathematics displayed by these categories of students were observed. Theory of variation was used to provide a prism for viewing the MLDs from theoretical perspective. Experimental research design was used, involving pretest-posttest non-randomized approach. Pretest was administered to the intact class taught using CMTS before the class was split into experimental and control groups. Experimental group of the students – those identified with MLDs was taught with SMTS and later mean performance of students taught using the two strategies was sought to find if there was any significant difference between the performances of the students. A null hypothesis was tested at α = 0.05 level of significance. T-test was used to establish the difference between the mean performances of the two tests. The null hypothesis was rejected. Hence, the performance of students, identified with MLDs taught using SMTS was found to be better than their earlier performance taught using CMTS. The study, therefore, recommends amongst other things that teachers should be encouraged to use SMTS in teaching mathematics especially when students are found to be suffering from MLDs and exhibiting errors and misconceptions in the process of learning mathematics.

Keywords: disabilities, errors, learning, misconceptions

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Authors: Renz Paolo B. Ramos, Jake S. Espina

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The Local Government Academy of the Philippines explains that Local legislation is both a power and a process by which it enacts ordinances and resolutions that have the force and effect of law while engaging with a range of stakeholders for their implementation. Legislative effectiveness is crucial for the development of any given area. This study's objective is to evaluate the legislative performance of the 10th Sangguniang of Kawayan, a legislative body in a fifth-class municipality in the Province of Biliran, during the height of the COVID-19 pandemic (2019-2021) with a focus on legislation, accountability, and participation, institution-building, and intergovernmental relations. The aim of the study was that a mixed-methods strategy was used to gather data. The Local Legislative Performance Appraisal Form (LLPAF) was completed, while Focus Interviews for Local Government Unit (LGU) personnel, a survey questionnaire for constituents, and ethnographic diary-writing were conducted. Convenience Sampling was utilized for LGU workers, whereas Simple Random Sampling was used to identify the number of constituents participating. Interviews were analyzed using thematic analysis, while frequency data analysis was employed to describe and evaluate the nature and connection of the data to the underlying population. From this data, the researchers draw opportunities and challenges met by the local legislature during the height of the pandemic.

Keywords: local legislation, local governance, legislative effectiveness, legislative analysis

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Authors: L. Bih Ni, D. Norizah Ag Kiflee, T. Choon Keong, R. Talip, S. Singh Bikar Singh, M. Noor Mad Japuni, R. Talin

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The purpose of this study is to determine the effectiveness of video clips to enhance students' achievement and motivation towards learning and facilitating of history. We use narrative literature studies to illustrate the current state of the two art and science in focused areas of inquiry. We used experimental method. The experimental method is a systematic scientific research method in which the researchers manipulate one or more variables to control and measure any changes in other variables. For this purpose, two experimental groups have been designed: one experimental and one groups consisting of 30 lower secondary students. The session is given to the first batch using a computer presentation program that uses video clips to be considered as experimental group, while the second group is assigned as the same class using traditional methods using dialogue and discussion techniques that are considered a control group. Both groups are subject to pre and post-trial in matters that are handled by the class. The findings show that the results of the pre-test analysis did not show statistically significant differences, which in turn proved the equality of the two groups. Meanwhile, post-test analysis results show that there was a statistically significant difference between the experimental group and the control group at an importance level of 0.05 for the benefit of the experimental group.

Keywords: Video clips, Learning and Facilitation, Achievement, Motivation

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Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

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Authors: G. T. Aigarinova

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This article considers the legal issues of food security as a major component of national security of the republic. The problem of food security is the top priority of the economic policy strategy of any state, the effectiveness of this solution influences social, political, and ethnic stability in society. Food security and nutrition is everyone’s business. Food security exists when all people, at all times, have physical, social and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life. By analyzing the existing legislation in the area of food security, the author identifies weaknesses and gaps, suggesting ways to improve it.

Keywords: food security, national security, agriculture, public resources, economic security

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: K. D. Chandrasekhar, H. C. Wu, D. J. Hsieh, B. J. Song, J. -Y. Lin, J. L. Her, L. Z. Deng, M. Gooch, C. W. Chu, H. D. Yang

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Stress-mediated coupling of electrical and magnetic dipoles in a single phase multiferroic is rare. Pb₂MnO₄ belong to multi-piezo crystal class with the space group P⁻42₁

Keywords: multiferroic, multipiezo, Pb₂MnO₄, spin-flip

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Authors: Karla Hrbackova, Irena Balaban Cakirpaloglu

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This paper is a report on self-regulation in socially rejected pupils. A certain form of social rejection can be found in almost every class within the school environment. Research shows that due to social rejection mechanisms supporting the individual´s effort of reintegration into the group are not triggered. Paradoxically the opposite tendency arises, i.e., an increase in selfish and defeating behaviour. The link between peer exposure and self-regulation is likely to vary as a function of a type and quality of peer interaction (e.g., rejection or acceptance). The paper aims to clarify the level of self-regulation related to interpersonal cognitive problem-solving within the process of social rejection in a school class. The research was done on a sample of 1,133 upper-primary school pupils using the Means-Ends Problem Solving technique (MEPS) and peer sociometric nomination. The results showed that the level of self-regulated skills is related to the status of social rejection. Socially rejected pupils achieve lower levels of self-regulation than other classmates. We found deficiency in the regulation of behaviour, emotions and the regulation of will in the peer rejected pupils with the exception of cognitive regulation in which no differences were detected between socially rejected pupils and other classmates. The results have implications for early prevention and intervention efforts to foster adaptive self-regulation and reduce the risk of later social rejection.

Keywords: interpersonal cognitive problem-solving, self-regulation, socially rejected pupils, upper-primary school pupils

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Authors: Tatiana Ivushkina

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The paper is aimed at studying the use of literary words of foreign origin in modern fiction from a sociolinguistic point of view, which presupposes establishing correlation between this category of words in a speech portrayal or narrative and a social status of the speaker, verifying that it bears social implications and serves as a social marker or index of socially privileged identity in the British literature of the 21-st century. To this end, there were selected literary words of foreign origin in context (60 contexts) and subjected to careful examination. The study is carried out on two novels by Jeffrey Archer – Not a Penny More, Not a Penny Less and A Prisoner of Birth – who, being a graduate from Oxford, represents socially privileged classes himself and gives a wide depiction of characters with different social backgrounds and statuses. The analysis of the novels enabled us to categorize the selected words into four relevant groups. The first represented by terms (commodity, debenture, recuperation, syringe, luminescence, umpire, etc.) serves to unambiguously indicate education, occupation, a field of knowledge in which a character is involved or a situation of communication. The second group is formed of words used in conjunction with their Germanic counterparts (perspiration – sweat, padre – priest, convivial – friendly) to contrast social position of the characters: literary words serving as social indices of upper class speakers whereas their synonyms of Germanic origin characterize middle or lower class speech portrayals. The third class of words comprises socially marked words (verbs, nouns, and adjectives), or U-words (the term first coined by Allan Ross and Nancy Mitford), the status acquired in the course of social history development (elegant, excellent, sophistication, authoritative, preposterous, etc.). The fourth includes words used in a humorous or ironic meaning to convey the narrator’s attitude to the characters or situation itself (ministrations, histrionic, etc.). Words of this group are perceived as 'alien', stylistically distant as they create incongruity between style and subject matter. Social implication of the selected words is enhanced by French words and phrases often accompanying them.

Keywords: British literature of the XXI century, literary words of foreign origin, social context, social meaning

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Authors: Fionnuala Tynan, Margaret Nohilly

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Wellbeing in not only a national priority in Ireland but in the international context. A review of the literature highlights the consistent efforts of researchers to define the concept of wellbeing. This study sought to explore the understating of Wellbeing in Irish primary schools. National Wellbeing Guidelines in the Irish context frame the concept of wellbeing through a mental health paradigm, which is but one aspect of wellbeing. This exploratory research sought the views of Irish primary-school teachers on their understanding of the concept of wellbeing and the practical application of strategies to promote wellbeing both in the classroom and across the school. Teacher participants from four counties in the West of Ireland were invited to participate in focus group discussion and workshops through the Education Centre Network. The purpose of this process was twofold; firstly to explore teachers’ understanding of wellbeing in the primary school context and, secondly, for teachers to be co-creators in the development of practical strategies for classroom and whole school implementation. The voice of the teacher participants was central to the research design. The findings of this study indicate that the definition of wellbeing in the Irish context is too abstract a definition for teachers and the focus on mental health dominates the discourse in relation to wellbeing. Few teachers felt that they were addressing wellbeing adequately in their classrooms and across the school. The findings from the focus groups highlighted that while teachers are incorporating a range of wellbeing strategies including mindfulness and positive psychology, there is a clear disconnect between the national definition and the implementation of national curricula which causes them concern. The teacher participants requested further practical strategies to promote wellbeing at whole school and classroom level within the framework of the Irish Primary School Curriculum and enable them to become professionally confident in developing a culture of wellbeing. In conclusion, considering wellbeing is a national priority in Ireland, this research promoted the timely discussion the wellbeing guidelines and the development of a conceptual framework to define wellbeing in concrete terms for practitioners. The centrality of teacher voices ensured the strategies proposed by this research is both practical and effective. The findings of this research have prompted the development of a national resource which will support the implementation of wellbeing in the primary school at both national and international level.

Keywords: primary education, shared understanding, teacher voice, wellbeing

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Authors: Jo Angouri, Charlotte Kennedy, Shawnea Ting, David Rawlinson, Matthew Booker, Nigel Rees

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Ambulance services need to balance the large volume of emergency (999 in the UK) calls they receive (e.g., West Midlands Ambulance Service reports per day about 4,000 999 calls; about 679,000 calls per year are received in Wales), with dispatching limited resource for on-site intervention to the most critical cases. The process by which Emergency Medical Dispatch (EMD) decisions are made is related to risk assessment and involves the caller and call-taker as well as clinical teams negotiating risk levels on a case-by-case basis. Medical Priority Dispatch System (MPDS – also referred to as Advanced Medical Priority Dispatch System AMPDS) are used in the UK by NHS Trusts (e.,g WAST) to process and prioritise 999 calls. MPDS / AMPDS provide structured protocols for call prioritisation and call management. Protocols/policy frameworks have not been examined before in the way we propose in our project. In more detail, the risk factors that play a role in the EMD negotiation between the caller and call-taker have been analysed in both medical and social science research. Research has focused on the structural, morphological and phonological aspects that could improve, and train, human-to-human interaction or automate risk detection, as well as the medical factors that need to be captured from the caller to inform the dispatch decision. There are two significant gaps in our knowledge that we address in our work: 1. the role of backstage clinical teams in translating the caller/call-taker interaction in their internal risk negotiation and, 2. the role of policy frameworks, protocols and regulations in the framing of institutional priorities and resource allocation. We take a multi method approach and combine the analysis of 999 calls with the analysis of policy documents. We draw on interaction analysis, corpus methodologies and thematic analysis. In this paper, we report on our preliminary findings and focus in particular on the risk factors we have identified and the relationship with the regulations that create the frame within which teams operate. We close the paper with implications of our study for providing evidence-based policy intervention and recommendations for further research.

Keywords: emergency (999) call, interaction analysis, discourse analysis, ambulance dispatch, medical discourse

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Authors: Asena Demirci, Gozen Guner Aktaş, Nur Ayalp

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Nature provides a living space for humans, also in contrast it is destroyed by humans for their personal needs and ambitions. For decreasing these damages against nature, solutions are started to generate and to develop. Moreover, precautions are implemented. After 1960s, especially when the ozone layer got harmed and got thinner by toxic substances coming from man made structures, environmental problems which effected human’s activities of daily living. Thus, this subject about environmental solutions and precautions is becoming a priority issue for scientists. Most of the environmental problems are caused by buildings and factories which are built without any concerns about protecting nature. This situation creates awareness about environmental issues and also the terms like sustainability, Renewable energy show up in building, Construction and architecture sectors to provide environmental protection. In this perspective, the design disciplines also should be respectful to nature and the sustainability. Designs which involve the features like sustainability, renewability and being ecologic have specialties to be less detrimental to the environment rather than the designs which do not involve. Furthermore, these designs produce their own energy for consuming, So they do not use the natural resources. They do not contain harmful substances and they are made of recyclable materials. Thus, they are becoming environmentally friendly structures. There is a common concern among designers about the issue of sustainable design. They believe that the idea of sustainability inhibits the creativity. All works of design resemble each other from the point of aesthetics and technological matters. In addition, there is a concern about design ethics which aesthetic designs cannot be accepted as a priority. For these reasons, there are few designs included the features of being eco-friendly and well-designed and also had design concerns around the world. Despite the other design disciplines, The concept of sustainability is getting more important each day in interior architecture and interior design. As it is known that human being spends 90 % of his life in interior spaces, The importance of that concept in interior spaces is obvious. Aesthetic is another vital concern in interior space design also. Most of the time sustainable materials and sustainable interior design applications conflicts with personal aesthetic parameters. This study aims to discuss the great paradox between the design aesthetic and the sustainable design. Does the sustainable approach in interior design disturbs the design aesthetic? This is one of the most popular questions that have been discussed for a while. With this paper this question will be evaluated with a case study which analyzes the aesthetic perceptions and preferences of the users and designers in sustainable interior spaces.

Keywords: aesthetics, interior design, sustainable design, sustainability

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Authors: Strahinja Kovačević, Lidija Jevrić, Miloš Kuzmanović, Sanja Podunavac-Kuzmanović

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In this paper, various derivatives of benzimidazole have been evaluated against Gram-negative bacteria Escherichia coli. For all investigated compounds the minimum inhibitory concentration (MIC) was determined. Quantitative structure-activity relationships (QSAR) attempts to find consistent relationships between the variations in the values of molecular properties and the biological activity for a series of compounds so that these rules can be used to evaluate new chemical entities. The correlation between MIC and some absorption, distribution, metabolism and excretion (ADME) parameters was investigated, and the mathematical models for predicting the antibacterial activity of this class of compounds were developed. The quality of the multiple linear regression (MLR) models was validated by the leave-one-out (LOO) technique, as well as by the calculation of the statistical parameters for the developed models and the results are discussed on the basis of the statistical data. The results of this study indicate that ADME parameters have a significant effect on the antibacterial activity of this class of compounds. Principal component analysis (PCA) and agglomerative hierarchical clustering algorithms (HCA) confirmed that the investigated molecules can be classified into groups on the basis of the ADME parameters: Madin-Darby Canine Kidney cell permeability (MDCK), Plasma protein binding (PPB%), human intestinal absorption (HIA%) and human colon carcinoma cell permeability (Caco-2).

Keywords: benzimidazoles, QSAR, ADME, in silico

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Authors: Yurdum Cokadar

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The United States is the country where the majority of highly skilled immigrants are hosted. Two-thirds of foreign-born migrants from Turkey - an underrepresented and understudied immigrant group in the United States - are highly skilled. Generated by the aim of filling this gap in the literature, the motivation of this research is to understand highly skilled Turkish immigrant women’s integration into the U.S. labor market, including barriers that they face and strategies they develop to rebuild their career after relocation. The in-depth interviews of 20 highly skilled Turkish women residing in the U.S. revealed that the majority of women participants are either not integrated into the labor market, occupy positions below their skill, or cannot reach the same upper segments of the labor market in the host country, arising from a range of structural and personal barriers interplaying in their career trajectories. Furthermore, many of them cannot transfer their social and cultural capital gained in their home country into the United States. The labor market participation process of these women is analyzed in the light of Bourdieu’s theory of capital and the intersectional approach of gender, class and ethnicity in order to understand the positions of highly skilled immigrant women in the host country labor market.

Keywords: deskilling, gender, class and ethnicity, highly skilled women immigrants, integration into the U.S. the labor market, labor market participation, skilled migration, theory of capital

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Authors: Erdem Meriç

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Measuring total temperature of air flow accurately is a very important requirement in the development phases of many industrial products, including gas turbines and rockets. Thermocouples are very practical devices to measure temperature in such cases, but in high speed and high temperature flows, the temperature of thermocouple junction may deviate considerably from real flow total temperature due to the effects of heat transfer mechanisms of convection, conduction, and radiation. To avoid errors in total temperature measurement, special probe designs which are experimentally characterized are used. In this study, a validation case which is an experimental characterization of a specific class of total temperature probes is selected from the literature to develop a numerical conjugate heat transfer analysis methodology to study the total temperature probe flow field and solid temperature distribution. Validated conjugate heat transfer methodology is used to investigate flow structures inside and around the probe and effects of probe design parameters like the ratio between inlet and outlet hole areas and prob tip geometry on measurement accuracy. Lastly, a thermal model is constructed to account for errors in total temperature measurement for a specific class of probes in different operating conditions. Outcomes of this work can guide experimentalists to design a very accurate total temperature probe and quantify the possible error for their specific case.

Keywords: conjugate heat transfer, recovery factor, thermocouples, total temperature probes

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Angélique Laurent, Marie-Josée Letarte, Jean-Pascal Lemelin, Marie-France Morin

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This study aims at exploring teacher-child interactions within learning contexts in public prekindergartens of the province of Québec (Canada). It is based on previous research showing that teacher-child interactions in preschools have direct and determining effects on the quality of early childhood education and could directly or indirectly influence child development. However, throughout a typical preschool day, children experience different learning contexts to promote their learning opportunities. Depending on these specific contexts, teacher-child interactions could vary, for example, between free play and shared book reading. Indeed, some studies have found that teacher-directed or child-directed contexts might lead to significant variations in teacher-child interactions. This study drew upon both the bioecological and the Teaching Through Interactions frameworks. It was conducted through a descriptive and correlational design. Fifteen teachers were recruited to participate in the study. At Time 1 in October, they completed a diary to report the learning contexts they proposed in their classroom during a typical week. At Time 2, seven months later (May), they were videotaped three times in the morning (two weeks’ time between each recording) during a typical morning class. The quality of teacher-child interactions was then coded with the Classroom Assessment Scoring System (CLASS) through the contexts identified. This tool measures three main domains of interactions: emotional support, classroom organization, and instruction support, and10 dimensions scored on a scale from 1 (low quality) to 7 (high quality). Based on the teachers’ reports, five learning contexts were identified: 1) shared book reading, 2) free play, 3) morning meeting, 4) teacher-directed activity (such as craft), and 5) snack. Based on preliminary statistical analyses, little variation was observed within the learning contexts for each domain of the CLASS. However, the instructional support domain showed lower scores during specific learning contexts, specifically free play and teacher-directed activity. Practical implications for how preschool teachers could foster specific domains of interactions depending on learning contexts to enhance children’s social and academic development will be discussed.

Keywords: teacher practices, teacher-child interactions, preschool education, learning contexts, child development

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Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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Authors: Hatice Yildirim

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This study is an investigation into ‘The role of teaching assistants (TAs) for deaf pupils in an English primary school’, in order not only to contribute to the education of deaf pupils but also contribute to the literature, in which there has been a lack of attention paid to the role of TAs for deaf pupils. With this in mind, the research design was planned based on using a case study as a qualitative research approach in order to have a deep and first-hand understanding of the case for ‘the role of TAs for deaf pupils’ in a real-life context. 12 semi-structured classroom observations and six semi-structured interviews were carried out with four TAs and two teachers in one English mainstream primary school. The data analysis followed a thematic analysis framework. The results indicated that TAs are utilised based on a one-on-one support model and are deployed under the class teacher in the classroom. Out of the classroom activities are carried out in small groups with the agreement of the TAs and the class teacher, as per the policy of the school. Due to the one-on-one TA support model, the study pointed out the seven different roles carried out by TAs in the education of deaf pupils in an English mainstream primary school. While supporting deaf pupils academically and socially are the main roles of TAs, they also support deaf pupils by recording their progress, communicating with their parents, taking on a pastoral care role, tutoring them in additional support lessons, and raising awareness of deaf pupils’ issues.

Keywords: deaf, mainstream, teaching assistant, teaching assistant's roles

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Chialing Chang

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Language and culture are critical foundations of international mobility. However, the students who are limited to the local environment may affect their learning outcome and global perspective. Video Conferencing has been proven an economical way for students as a medium to communicate with international students around the world. In Taiwan, the National Development Commission advocated the development of bilingual national policies in 2030 to enhance national competitiveness and foster English proficiency and fully launched bilingual activation of the education system. Globalization is closely related to the development of Taiwan's education. Therefore, the teacher conducted an integrated lesson through interdisciplinary learning. This study aims to investigate how the teacher helps develop students' global and language core competencies in the international education class. The methodology comprises four stages, which are lesson planning, class observation, learning data collection, and speech analysis. The Grice's Conversational Maxims are adopted to analyze the students' conversation in the video conferencing course. It is the action research from the teacher's reflection on approaches to developing students' language learning skills. The study lays the foundation for mastering the teacher's international education professional development and improving teachers' teaching quality and teaching effectiveness as a reference for teachers' future instruction.

Keywords: international education, language learning, Grice's conversational maxims, video conferencing course

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Authors: Kelly Jo Hollingsworth

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Conversational Solfege, a research-based, 12-step music literacy instructional method using the sound-before-sight approach, was used to teach rhythm-reading to 128-second grade students at a public school in the southeastern United States. For each step, multiple scripted techniques are supplied to teach each skill. Unit one was the focus of this study, which is quarter note and barred eighth note rhythms. During regular weekly music instruction, students completed method steps one through five, which includes aural discrimination, decoding familiar and unfamiliar rhythm patterns, and improvising rhythmic phrases using quarter notes and barred eighth notes. Intact classes were randomly assigned to two treatment groups for teaching steps six through eight, which was the visual presentation and identification of quarter notes and barred eighth notes, visually presenting and decoding familiar patterns, and visually presenting and decoding unfamiliar patterns using said notation. For three weeks, students practiced steps six through eight during regular weekly music class. One group spent five-minutes of class time on steps six through eight technique work, while the other group spends ten-minutes of class time practicing the same techniques. A pretest and posttest were administered, and ANOVA results reveal both the five-minute (p < .001) and ten-minute group (p < .001) reached statistical significance suggesting Conversational Solfege is an efficient, effective approach to teach rhythm-reading to second grade students. After two weeks of no instruction, students were retested to measure retention. Using a repeated-measures ANOVA, both groups reached statistical significance (p < .001) on the second posttest, suggesting both the five-minute and ten-minute group retained rhythm-reading skill after two weeks of no instruction. Statistical significance was not reached between groups (p=.252), suggesting five-minutes is equally as effective as ten-minutes of rhythm-reading practice using Conversational Solfege techniques. Future research includes replicating the study with other grades and units in the text.

Keywords: conversational solfege, length of instructional time, rhythm-reading, rhythm instruction

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Authors: Ozcan Yavas, Berrak Erol Nalbur, Sermin Gunarslan

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A materiality matrix is a tool that organizations use to prioritize their activities and adapt to the increasing sustainability requirements in recent years. For the materiality index to move from business models to the sustainability business model stage, it must be done with all partners in the raw material, supply, production, product, and end-of-life product stages. Within the scope of this study, the Materiality Matrix was used to transform the business model into a sustainability business model and to create a sustainability roadmap in a factory producing electric buses. This matrix determines the necessary roadmap for all stakeholders to participate in the process, especially in sectors that produce sustainable products, such as the electric vehicle sector, and to act together with the cradle-to-cradle approach of sustainability roadmaps. Global Reporting Initiative analysis was used in the study conducted with 1150 stakeholders within the scope of the study, and 43 questions were asked to the stakeholders under the main headings of 'Legal Compliance Level,' 'Environmental Strategies,' 'Risk Management Activities,' 'Impact of Sustainability Activities on Products and Services,' 'Corporate Culture,' 'Responsible and Profitable Business Model Practices' and 'Achievements in Leading the Sector' and Economic, Governance, Environment, Social and Other. The results of the study aimed to include five 1st priority issues and four 2nd priority issues in the sustainability strategies of the organization in the short and medium term. When the studies carried out in the short term are evaluated in terms of Sustainability and Environmental Risk Management, it is seen that the studies are still limited to the level of legal legislation (60%) and individual studies in line with the strategies (20%). At the same time, the stakeholders expect the company to integrate sustainability activities into its business model within five years (35%) and to carry out projects to become the first company that comes to mind with its success leading the sector (20%). Another result obtained within the study's scope is identifying barriers to implementation. It is seen that the most critical obstacles identified by stakeholders with climate change and environmental impacts are financial deficiency and lack of infrastructure in the dissemination of sustainable products. These studies are critical for transitioning to sustainable business models for the electric vehicle sector to achieve the EU Green Deal and CBAM targets.

Keywords: sustainability business model, materiality matrix, electricity bus, carbon neutrality, sustainability management

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Authors: Anjali Bansal

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Reproductive preferences mainly deal with two questions: when a couple wants children and how many they want. Questions related to these desires are often included in the fertility surveys as they can provide relevant information on the subsequent behavior. The aim of the study is to observe whether respondent’s response to these questions changed over time or not. We also tried to identify socio- economic and demographic factors associated with the stability (or instability) of fertility preferences. For this purpose, we used IHDS1 (2004-05) and follow up survey IHDS2 (2011-12) data and applied bivariate, multivariate and multilevel repeated measure analysis to it to find the consistency between responses. From the analysis, we found that preferences of women changes over the course of time as from the bivariate analysis we have found that 52% of women are not consistent in their desired family size and huge inconsistency are found in desire to continue childbearing. To get a better overlook of these inconsistencies, we have computed Intra Class Correlation (ICC) which tries to explain the consistency between individuals on their fertility responses at two time periods. We also explored that husband’s desire for additional child specifically male offspring contribute to these variations. Our findings lead us to a cessation that in India, individuals fertility preferences changed over a seven-year time period as the Intra Class correlation comes out to be very small which explains the variations among individuals. Concerted efforts should be made, therefore, to educate people, and conduct motivational programs to promote family planning for family welfare.

Keywords: change, consistency, preferences, over time

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Authors: Hangil Park, Hwayeon Song, Jingyung Sim

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In this study, a business ecosystem of a domestic space industry is comprehensively analyzed to derive the influence factors. The priority level of each element as well as the disparity between the ideal and reality are investigated through a literature review and an expert survey. The three major influence factors determined are: (a) investment scale and approach, (b) propulsion system, and (c) industrialization with overseas expansion. Related issues based on the current status are evaluated, followed by a proposed activation strategy. This research's findings offer a direction for R&D budget allocation and law system maintenance for the activation of the domestic space industry.

Keywords: space industry, activation, strategy, business ecosystem

Procedia PDF Downloads 350