Search results for: learning academic words

Authors: Şeyda Akçalı

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This study explores the concept of social sustainability and its characteristics in terms of neighborhood (mahalle) which is a social phenomenon in Turkish urban life. As social sustainability indicators that moving away traditional themes toward multi-dimensional measures, the solutions for urban strategies may be achieved through learning lessons from historical precedents. It considers the inherent values of traditional urban forms contribute to the evolution of the city as well as the social functions of it. The study aims to measure non-tangible issues in order to evaluate social sustainability in historic urban environments and how they could contribute to the current urban planning strategies. The concept of neighborhood (mahalle) refers to a way of living that represents the organization of Turkish social and communal life rather than defining an administrative unit for the city. The distinctive physical and social features of neighborhood illustrate the link between social sustainability and historic urban environment. Instead of having a nostalgic view of past, it identifies both the failures and successes and extract lessons of traditional urban environments and adopt them to modern context. First, the study determines the aspects of social sustainability which are issued as the key themes in the literature. Then, it develops a model by describing the social features of mahalle which show consistency within the social sustainability agenda. The model is used to analyze the performance of traditional housing area in the historical city center of Bursa, Turkey whether it meets the residents’ social needs and contribute collective functioning of the community. Through a questionnaire survey exercised in the historic neighborhoods, the residents are evaluated according to social sustainability criteria of neighborhood. The results derived from the factor analysis indicate that social aspects of neighborhood are social infrastructure, identity, attachment, neighborliness, safety and wellbeing. Qualitative evaluation shows the relationship between key aspects of social sustainability and demographic and socio-economic factors. The outcomes support that inherent values of neighborhood retain its importance for the sustainability of community although there must be some local arrangements for few factors with great attention not to compromise the others. The concept of neighborhood should be considered as a potential tool to support social sustainability in national political agenda and urban policies. The performance of underlying factors in historic urban environment proposes a basis for both examining and improving traditional urban areas and how it may contribute to the overall city.

Keywords: historical city center, mahalle, neighborhood, social sustainability, traditional urban environment, Turkey

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Authors: Helene Jacobson Pettersson, Linda Lill

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Demographic changes and globalization in society provide new opportunities for social work and social work education in Sweden. There has been an ambition to include these aspects into the Swedish social work education. However, the Swedish welfare state standard continued to be as affectionate as invisible starting point in discussions about people’s way of life and social problems. The aim of this study is to explore content given to ethnic relations in social work in the social work education in Sweden. Our standpoint is that the subject can be understood both from individual and structural levels, it changes over time, varies in different steering documents and differs from the perspectives of teachers and students. Our question is what content is given to ethnic relations in social work by the teachers in their strategies and teaching material. The study brings together research in the interface between education science, social work and research of international migration and ethnic relations. The presented narratives are from longer interviews with a total of 17 university teachers who teach in social work program at four different universities in Sweden. The universities have in different ways a curriculum that involves the theme of ethnic relations in social work, and the interviewed teachers are teaching and grading social workers on specific courses related to ethnic relations at undergraduate and graduate levels. Overall assesses these 17 teachers a large number of students during a semester. The questions were concerned on how the teachers handle ethnic relations in education in social work. The particular focus during the interviews has been the teacher's understanding of the documented learning objectives and content of literature and how this has implications for their teaching. What emerges is the teachers' own stories about the educational work and how they relate to the content of teaching, as well as the teaching strategies they use to promote the theme of ethnic relations in social work education. The analysis of this kind of pedagogy is that the teaching ends up at an individual level with a particular focus on the professional encounter with individuals. We can see the shortage of a critical analysis of the construction of social problems. The conclusion is that individual circumstance precedes theoretical perspective on social problems related to migration, transnational relations, globalization and social. This result has problematic implications from the perspective of sustainability in terms of ethnic diversity and integration in society. Thus these aspects have most relevance for social workers’ professional acting in social support and empowerment related activities, in supporting the social status and human rights and equality for immigrants.

Keywords: ethnic relations in Swedish social work education, teaching content, teaching strategies, educating for change, human rights and equality

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Doris F. Rabelo

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Introduction: Endotracheal Intubation (ETI) is a procedure for clinical management of patients with severe clinical presentation of COVID-19 disease. Realistic simulation (RS) is an active learning methodology utilized for clinical skill's improvement. To improve ETI skills of public health network's physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was planned and carried out. Training scenario included the Nasco Lifeform realistic simulator, and three actions were simulated: ETI procedure, sedative drugs management, and bougie guide utilization. Training intervention occurred between May and June 2020, as an interinstitutional cooperation between the Health's Department of Bahia State and the Federal University from Recôncavo da Bahia. Objective: The main objective is to report the effects on participants' self-confidence perception for ETI procedure after RS based training. Methods: This is a descriptive study, with secondary data extracted from questionnaires applied throughout RS training. Priority workplace, time from last intubation, and knowledge about bougie were reported on a preparticipation questionnaire. Additionally, participants completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding self-confidence perception in performing each of simulated actions. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's Exact Test. Results: 36 physicians participated of training, 25 (69%) from primary care setting, 25 (69%) performed ETI over a year ago, and only 4 (11%) had previous knowledge about the bougie guide utilization. There was an increase in self-confidence medians for all three simulated actions. Medians (variation) for self-confidence before and after training, for each simulated action were as follows: ETI [5 (1-9) vs. 8 (6-10) (p < 0.0001)]; Sedative drug management [5 (1-9) vs. 8 (4-10) (p < 0.0001)]; Bougie guide utilization [2.5 (1-7) vs. 8 (4-10) (p < 0.0001)]. Among those who performed ETI over a year ago (n = 25), an increase in self-confidence greater than 3 points for ETI was reported by 23 vs. 2 physicians (p = 0.0002), and by 21 vs. 4 (p = 0.03) for sedative drugs management. Conclusions: RS training contributed to self-confidence increase in performing ETI. Among participants who performed ETI over a year, there was a significant association between RS training and increase of more than 3 points in self-confidence, both for ETI and sedative drug management. Training with RS methodology is suitable for ETI confidence enhancement during COVID-19 outbreak.

Keywords: confidence, COVID-19, endotracheal intubation, realistic simulation

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Authors: Gaelle Candel, David Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embeddings. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n²) to O(n²=k), and the memory requirement from n² to 2(n=k)², which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution, and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Nizamuddin Zainuddin, Adam Mohd Saifudin, Ahmad Yusni Bahaudin, Mohd Hanizan Zalazilah, Roslan Jamaluddin

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Students’ enhanced experience through simulation is a crucial factor that brings reality to the classroom. The enhanced experience is all about developing, enriching and applications of a generic process flow in the field of logistics and transportations. As educational technology has improved, the effective use of simulations has greatly increased to the point where simulations should be considered a valuable, mainstream pedagogical tool. Additionally, in this era of ongoing (some say never-ending) assessment, simulations offer a rich resource for objective measurement and comparisons. Simulation is not just another in the long line of passing fads (or short-term opportunities) in educational technology. It is rather a real key to helping our students understand the world. It is a way for students to acquire experience about how things and systems in the world behave and react, without actually touching them. In short, it is about interactive pretending. Simulation is all about representing the real world which includes grasping the complex issues and solving intricate problems. Therefore, it is crucial before stimulate the real process of inbound and outbound logistics and transportation a generic process flow shall be developed. The paper will be focusing on the validization of the process flow by looking at the inputs gains from the sample. The sampling of the study focuses on multi-national and local manufacturing companies, third party companies (3PL) and government agency, which are selected in Peninsular Malaysia. A simulation flow chart was proposed in the study that will be the generic flow in logistics and transportation. A qualitative approach was mainly conducted to gather data in the study. It was found out from the study that the systems used in the process of outbound and inbound are System Application Products (SAP) and Material Requirement Planning (MRP). Furthermore there were some companies using Enterprises Resources Planning (ERP) and Electronic Data Interchange (EDI) as part of the Suppliers Own Inventories (SOI) networking as a result of globalized business between one countries to another. Computerized documentations and transactions were all mandatory requirement by the Royal Custom and Excise Department. The generic process flow will be the basis of developing a simulation program that shall be used in the classroom with the objective of further enhanced the students’ learning experience. Thus it will contributes to the body of knowledge on the enrichment of the student’s employability and also shall be one of the way to train new workers in the logistics and transportation filed.

Keywords: enhancement, simulation, process flow, logistics, transportation

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Authors: Chana Pavneet

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Background: In more recent years in dentistry, a greater emphasis has been placed on competency-based education (CBE) programmes. Undergraduate and postgraduate curriculums have been reformed to reflect these changes, and adopting a CBE approach has shown to be beneficial to trainees and places an emphasis on continuous lifelong learning. The literature is vast; however, very little work has been done specifically to the assessment of competence in dentistry and even less so in oral surgery. The majority of the literature tends to opinion pieces. Some small-scale studies have been undertaken in this area researching assessment tools which can be used to assess competence in oral surgery. However, there is a lack of general consensus on the preferable assessment methods. The aim of this review is to identify the assessment methods available and their usefulness. Methods: Electronic databases (Medline, Embase, and the Cochrane Database of systematic reviews) were searched. PRISMA guidelines were followed to identify relevant papers. Abstracts of studies were reviewed, and if they met the inclusion criteria, they were included in the review. Papers were reviewed against the critical appraisal skills programme (CASP) checklist and medical education research quality instrument (MERQSI) to assess their quality and identify any bias in a systematic manner. The validity and reliability of each assessment method or tool were assessed. Results: A number of assessment methods were identified, including self-assessment, peer assessment, and direct observation of skills by someone senior. Senior assessment tended to be the preferred method, followed by self-assessment and, finally, peer assessment. The level of training was shown to affect the preferred assessment method, with one study finding peer assessment more useful in postgraduate trainees as opposed to undergraduate trainees. Numerous tools for assessment were identified, including a checklist scale and a global rating scale. Both had their strengths and weaknesses, but the evidence was more favourable for global rating scales in terms of reliability, applicability to more clinical situations, and easier to use for examiners. Studies also looked into trainees’ opinions on assessment tools. Logbooks were not found to be significant in measuring the competence of trainees. Conclusion: There is limited literature exploring the methods and tools which assess the competence of oral surgery trainees. Current evidence shows that the most favourable assessment method and tool may differ depending on the stage of training. More research is required in this area to streamline assessment methods and tools.

Keywords: competence, oral surgery, assessment, trainees, education

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Authors: Păcurar Diana Istina

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The indissoluble link between aesthetics and semiotics, the harmonization and semiotic understanding of the interactions between the viewer and the object being looked at, are the basis of the practical demonstration of the importance of aesthetic perception within the theater performance. The design of a theater performance includes several structures, some considered from the beginning, art forms (i.e., the text), others being represented by simple, common objects (e.g., scenographic elements), which, if reunited, can trigger a certain aesthetic perception. The audience is delivered, by the team involved in the performance, a series of auditory and visual signs with which they interact. It is necessary to explain some notions about the physiological support of the transformation of different types of stimuli at the level of the cerebral hemispheres. The cortex considered the superior integration center of extransecal and entanged stimuli, permanently processes the information received, but even if it is delivered at a constant rate, the generated response is individualized and is conditioned by a number of factors. Each changing situation represents a new opportunity for the viewer to cope with, developing feelings of different intensities that influence the generation of meanings and, therefore, the management of interactions. In this sense, aesthetic perception depends on the detection of the “correctness” of signs, the forms of which are associated with an aesthetic property. Fairness and aesthetic properties can have positive or negative values. Evaluating the emotions that generate judgment and implicitly aesthetic perception, whether we refer to visual emotions or auditory emotions, involves the integration of three areas of interest: Valence, arousal and context control. In this context, superior human cognitive processes, memory, interpretation, learning, attribution of meanings, etc., help trigger the mechanism of anticipation and, no less important, the identification of error. This ability to locate a short circuit produced in a series of successive events is fundamental in the process of forming an aesthetic perception. Our main purpose in this research is to investigate the possible conditions under which aesthetic perception and its minimum content are generated by all these structures and, in particular, by interactions with forms that are not commonly considered aesthetic forms. In order to demonstrate the quantitative and qualitative importance of the categories of signs used to construct a code for reading a certain message, but also to emphasize the importance of the order of using these indices, we have structured a mathematical analysis that has at its core the analysis of the percentage of signs used in a theater performance.

Keywords: semiology, aesthetics, theatre semiotics, theatre performance, structure, aesthetic perception

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: N. Mahon, I. Crute, M. Di Bonito, E. Simmons, M. M. Islam

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Growing interest in the concept of the sustainable intensification (SI) of agriculture has been shown by, national governments, transnational agribusinesses, intergovernmental organizations and research institutes, amongst others. This interest may be because SI is seen as a ‘third way’ for agricultural development, between the seemingly disparate paradigms of ‘intensive’ agriculture and more ‘sustainable’ forms of agriculture. However, there is a lack of consensus as to what SI means in practice and how it should be measured using indicators of change. This has led to growing confusion, disagreement and skepticism regarding the concept, especially amongst civil society organizations, both in the UK and other countries. This has prompted the need for bottom-up, participatory approaches to identify indicators of SI. Our aim is to identify the views of British stakeholders regarding the areas of agreement and disagreement as to what SI is and how it should be measured in the UK using indicators of change. Data for this investigation came from 32 semi-structured interviews, conducted between 2015 and 2016, with stakeholders from throughout the UK food system. In total 110 indicators of SI were identified. These indicators covered a wide variety of subjects including biophysical, social and political considerations. A number of indicators appeared to be widely applicable and were similar to those suggested in the global literature. These include indicators related to the management of the natural resources on which agriculture relies e.g., ‘Soil organic matter’, ‘Number of pollinators per hectare’ and ‘Depth of water table’. As well as those related to agricultural externalities, e.g., ‘Greenhouse gas emissions’ and ‘Concentrations of agro-chemicals in waterways’. However, many of the indicators were much more specific to the context of the UK. These included, ‘Areas of high nature value farmland’, ‘Length of hedgerows per hectare’ and ‘Age of farmers’. Furthermore, tensions could be seen when participants considered the relative importance of agricultural mechanization versus levels of agricultural employment, the pros and cons of intensive, housed livestock systems and value of wild biodiversity versus the desire to increase agricultural yields. These areas of disagreement suggest the need to carefully consider the trade-offs inherent in the concept. Our findings indicate that in order to begin to resolve the confusions surrounding SI it needs to be considered in a context specific manner, rather than as a single uniform concept. Furthermore, both the environmental and the social parameters in which agriculture operates need to be considered in order to operationalize SI in a meaningful way. We suggest that participatory approaches are key to this process, facilitating dialogue and collaborative-learning between all the stakeholders, allowing them to reach a shared vision for the future of agricultural development.

Keywords: agriculture, indicators, participatory approach, sustainable intensification

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Authors: Victoria L. Nkosi, Parvaneh Farhangpour

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Often a Grade 12 certificate is perceived as a passport to tertiary education and the minimum requirement to enter the world of work. In spite of its importance, many students do not make this milestone in South Africa. It is important to find out why so many students still fail in spite of transformation in the education system in the post-apartheid era. Given the complexity of education and its context, this study adopted a case study design to examine one historically underperforming high school in Bushbuckridge, Mpumalanga Province, South Africa in 2013. The aim was to gain a understanding of the inner and outer school contextual factors associated with the high failure rate among Grade 12 students.  Government documents and reports were consulted to identify factors in the district and the village surrounding the school and a student survey was conducted to identify school, home and student factors. The randomly-sampled half of the population of Grade 12 students (53) participated in the survey and quantitative data are analyzed using descriptive statistical methods. The findings showed that a host of factors is at play. The school is located in a village within a municipality which has been one of the poorest three municipalities in South Africa and the lowest Grade 12 pass rate in the Mpumalanga province.   Moreover, over half of the families of the students are single parents, 43% are unemployed and the majority has a low level of education. In addition, most families (83%) do not have basic study materials such as a dictionary, books, tables, and chairs. A significant number of students (70%) are over-aged (+19 years old); close to half of them (49%) are grade repeaters. The school itself lacks essential resources, namely computers, science laboratories, library, and enough furniture and textbooks. Moreover, teaching and learning are negatively affected by the teachers’ occasional absenteeism, inadequate lesson preparation, and poor communication skills. Overall, the continuous low performance of students in this school mirrors the vicious circle of multiple negative conditions present within and outside of the school. The complexity of factors associated with the underperformance of Grade 12 students in this school calls for a multi-dimensional intervention from government and stakeholders. One important intervention should be the placement of over-aged students and grade-repeaters in suitable educational institutions for the benefit of other students.

Keywords: inner context, outer context, over-aged students, vicious cycle

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Authors: Henry Memczak, Marc Hovestaedt, Bernhard Ay, Sandra Saenger, Thorsten Wolff, Frank F. Bier

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The influenza viruses cause flu epidemics every year and serious pandemics in larger time intervals. The only cost-effective protection against influenza is vaccination. Due to rapid mutation continuously new subtypes appear, what requires annual reimmunization. For a correct vaccination recommendation, the circulating influenza strains had to be detected promptly and exactly and characterized due to their antigenic properties. During the flu season 2016/17, a wrong vaccination recommendation has been given because of the great time interval between identification of the relevant influenza vaccine strains and outbreak of the flu epidemic during the following winter. Due to such recurring incidents of vaccine mismatches, there is a great need to speed up the process chain from identifying the right vaccine strains to their administration. The monitoring of subtypes as part of this process chain is carried out by national reference laboratories within the WHO Global Influenza Surveillance and Response System (GISRS). To this end, thousands of viruses from patient samples (e.g., throat smears) are isolated and analyzed each year. Currently, this analysis involves complex and time-intensive (several weeks) animal experiments to produce specific hyperimmune sera in ferrets, which are necessary for the determination of the antigen profiles of circulating virus strains. These tests also bear difficulties in standardization and reproducibility, which restricts the significance of the results. To replace this test a peptide-based assay for influenza virus subtyping from corresponding virus samples was developed. The differentiation of the viruses takes place by a set of specifically designed peptidic recognition molecules which interact differently with the different influenza virus subtypes. The differentiation of influenza subtypes is performed by pattern recognition guided by machine learning algorithms, without any animal experiments. Synthetic peptides are immobilized in multiplex format on various platforms (e.g., 96-well microtiter plate, microarray). Afterwards, the viruses are incubated and analyzed comparing different signaling mechanisms and a variety of assay conditions. Differentiation of a range of influenza subtypes, including H1N1, H3N2, H5N1, as well as fine differentiation of single strains within these subtypes is possible using the peptide-based subtyping platform. Thereby, the platform could be capable of replacing the current antigenic characterization of influenza strains using ferret hyperimmune sera.

Keywords: antigenic characterization, influenza-binding peptides, influenza subtyping, influenza surveillance

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Authors: Tahamina Begum, Wan Nor Azlen Wan Mohamad, Faruque Reza, Wan Rosilawati Wan Rosli

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To assess auditory perception and cognitive function during pregnancy is necessary as the pregnant women need extra effort for attention mainly for their executive function to maintain their quality of life. This study aimed to investigate neural correlates of cognitive and behavioral processing during mid trimester pregnancy. Event-Related Potentials (ERPs) were studied by using 128-sensor net and PAS or COWA (controlled Oral Word Association), WCST (Wisconsin Card Sorting Test), RAVLTIM (Rey Auditory Verbal and Learning Test: immediate or interference recall, delayed recall (RAVLT DR) and total score (RAVLT TS) were tested for neuropsychology assessment. In total 18 subjects were recruited (n= 9 in each group; control and pregnant group). All participants of the pregnant group were within 16-27 (mid trimester) weeks gestation. Age and education matched control healthy subjects were recruited in the control group. Participants were given a standardized test of auditory cognitive function as auditory oddball paradigm during ERP study. In this paradigm, two different auditory stimuli (standard and target stimuli) were used where subjects counted silently only target stimuli with giving attention by ignoring standard stimuli. Mean differences between target and standard stimuli were compared across groups. N100 (auditory sensory ERP component) and P300 (auditory cognitive ERP component) were recorded at T3, T4, T5, T6, Cz and Pz electrode sites. An equal number of electrodes showed non-significantly shorter amplitude of N100 component (except significantly shorter at T3, P= 0.05) and non-significant longer latencies (except significantly longer latency at T5, P= 0.008) of N100 component in pregnant group comparing control. In case of P300 component, maximum electrode sites showed non-significantly higher amplitudes and equal number of sites showed non-significant shorter latencies in pregnant group comparing control. Neuropsychology results revealed the non-significant higher score of PAS, lower score of WCST, lower score of RAVLTIM and RAVLTDR in pregnant group comparing control. The results of N100 component and RAVLT scores concluded that auditory perception is mildly impaired and P300 component proved very mild cognitive dysfunction with good executive functions in second trimester of pregnancy.

Keywords: auditory perception, pregnancy, stimuli, trimester

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Authors: Mohkammad Nur Cahyadi, Hepi Hapsari Handayani, Agus Budi Raharjo, Ronny Mardianto, Daud Wahyu Imani, Arizal Bawazir, Luki Adi Triawan

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PDAM (local water company) determines customer charges by considering the customer's building or house. Charges determination significantly affects PDAM income and customer costs because the PDAM applies a subsidy policy for customers classified as small households. Periodic updates are needed so that pricing is in line with the target. A thorough customer survey in Surabaya is needed to update customer building data. However, the survey that has been carried out so far has been by deploying officers to conduct one-by-one surveys for each PDAM customer. Surveys with this method require a lot of effort and cost. For this reason, this research offers a technology called moblie mapping, a mapping method that is more efficient in terms of time and cost. The use of this tool is also quite simple, where the device will be installed in the car so that it can record the surrounding buildings while the car is running. Mobile mapping technology generally uses lidar sensors equipped with GNSS, but this technology requires high costs. In overcoming this problem, this research develops low-cost mobile mapping technology using a webcam camera sensor added to the GNSS and IMU sensors. The camera used has specifications of 3MP with a resolution of 720 and a diagonal field of view of 78⁰. The principle of this invention is to integrate four camera sensors, a GNSS webcam, and GPS to acquire photo data, which is equipped with location data (latitude, longitude) and IMU (roll, pitch, yaw). This device is also equipped with a tripod and a vacuum cleaner to attach to the car's roof so it doesn't fall off while running. The output data from this technology will be analyzed with artificial intelligence to reduce similar data (Cosine Similarity) and then classify building types. Data reduction is used to eliminate similar data and maintain the image that displays the complete house so that it can be processed for later classification of buildings. The AI method used is transfer learning by utilizing a trained model named VGG-16. From the analysis of similarity data, it was found that the data reduction reached 50%. Then georeferencing is done using the Google Maps API to get address information according to the coordinates in the data. After that, geographic join is done to link survey data with customer data already owned by PDAM Surya Sembada Surabaya.

Keywords: mobile mapping, GNSS, IMU, similarity, classification

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Authors: Yun Yu Stephanie Law

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Sociometer Theory is well tested among young adults in western population, however, limited research is found for other age groups, like adolescent and middle-adulthood in Asia population. Thus, one of the main purposes of this study is to verify the validity of Sociometer Theory in different age groups among Asian. To be specific, we hypothesized that an increase in one’s perceived social rejection is associated to a decrease in his/her state self-esteem among all age groups in Asian population. And we expected that this association can be found among all age groups including adolescent, young adults and middle-adults group in our first study. In this way, we can verify the validity of Sociometer Theory across different age groups as well as its significance in Asian population. Furthermore, those participants who received rejection about ‘mate-role’ would also receive some negative feedbacks regarding their current/future capacity of being a good mate. Results suggested that participants’ state self-esteem sensitivity for mating-capacity rejection is higher when comparing to that of friend-capacity rejection, i.e. greater drop in state self-esteem when receiving mating-capacity feedbacks then receiving friend-capacity feedbacks. These results, however, is just applicable on young adults. Thus, the main purpose of study two would be testing the state self-esteem sensitivity towards social rejection in different domains among three age groups. We hypothesized that group differences would be found for three age groups regarding state self-esteem sensitivity. Research question 1: perceived social rejection is associated to decrease in state self-esteem, is applicable among different age groups in Asia population. Research question 2: there are significant group differences for three age groups regarding state self-esteem sensitivity. Methods: 300 subjects are divided into three age groups, adolescents group, young adult group and middle-adult group, with 100 subjects in each group. Two questionnaires were used in testing this fundamental concept. Subjects were then asked to rate themselves on questionnaire in measuring their current state self-esteem in order to obtain the baseline measurements for later comparison. In order to avoid demand characteristics from subjects, other unrelated tasks like word matching were also given after the first test. Results: A positive correlation between scores in questionnaire 1 and questionnaire 2 among all age groups. Conclusion: State self-esteem decrease to both imagined social rejection (study1) and experienced social rejection (study2). Moreover, level of decrease in state self-esteem vary when receiving different domains of social rejection. Implications: a better understanding of self-esteem development for various age group might bring insights for education systems and policies for teaching approaches and learning methods among different age groups.

Keywords: state self-esteem, social rejection, stage theory, self-feelings

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Authors: Belbaly Nassim

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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.

Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination

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Authors: Jimoh Abiodun Alaba

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Context: In many traditional African societies, sex education is often considered a taboo topic. However, the importance of sex education is becoming increasingly evident. This study aims to investigate the challenges faced in teaching sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Research Aim: The aim of this study is to identify and examine the problems confronting the teaching of sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Methodology: The study utilized a multi-stage sampling method. The first stage involved a purposive selection of ten (10) secondary schools in the Akoko region of Ondo State, while the second stage was a random selection of twenty (20) students, each in the selected secondary schools of the study area. This makes a total of two (200) hundred students that were considered for the survey. Descriptive analysis using percentages was employed to analyze the collected data. Factor analysis was also used to identify the most significant problems. Findings: The study revealed that sex education has been neglected in the sampled secondary schools due to traditional African beliefs that do not support the teaching and learning of this subject. Furthermore, there was evidence to suggest that parents also displayed reluctance towards the teaching of sex education, fearing that it might expose students to inappropriate behavior. Consequently, students were deprived of this essential aspect of education necessary for self-awareness and development. Theoretical Importance: This study contributes to the understanding of the challenges faced in teaching sex education in traditional African societies, specifically in the selected secondary schools in the Akoko region of Ondo state, Nigeria. Data Collection: Data were collected through the administration of 200 questionnaires in ten selected secondary schools. Additionally, information was gathered from federal, state, and local government authorities. Analysis Procedures: The collected data were analyzed using descriptive analysis, employing percentage calculations for better interpretation. Furthermore, factor analysis was conducted to isolate the most significant problems identified. Conclusion: The study concludes that sex education in the sampled secondary schools in the Akoko region of Ondo state, Nigeria, has suffered neglect due to traditional African beliefs and parental concerns. Consequently, students are denied an important aspect of education necessary for their self-awareness and development. Recommendations are made to change the negative perception of sex education, enrich the curriculum, and employ qualified personnel for its teaching. Additionally, it is suggested that sex education should be integrated with moral instruction.

Keywords: African traditional belief, sex, sex education, sexual misdemeanor, morality

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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Authors: M. Joris, O. Agirdag

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For over two decades, calls for citizenship education (CE) have been rising to the top of educational policy agendas in Europe. The main motive for the current treatment of CE as a key topic is a sense of crisis: social and political threats that go beyond the reach of nations and require action at the international and European level. On the one hand, this context has triggered abundant attention to the promotion of citizenship through education. On the other hand, the ubiquity of citizenship and education in policy language is paired with a self-evident manner of using the concepts: the more we call for citizenship in and through education, the less the concepts seem to be made explicit or be defined. Research and reflection on the normativity of the concepts of citizenship and CE in Europe are scarce. Departing from the idea that policies are always normative, this study, therefore, investigates the normativity of the current concepts of citizenship and education, in ’key’ European CE policy texts. The study consists of a content analysis of these texts, based on a normative framework developed around the different dimensions of citizenship as status, identity, virtues and agency. The framework also describes the purposes of education and its learning processes, content and practices, based on the assumption that good education always includes, next to qualification and socialisation, a purpose of emancipation: of helping young people become autonomous and independent subjects. The analysis shows how contemporary European citizenship is conceptualised around the dimension of competences. This focus on competences is also visible in the normative framing of education and its relationship to citizenship in the texts: CE should help young people learn how to become good citizens by acquiring a toolkit of competences, consisting of knowledge, skills, values and attitudes that can be predetermined, measured and evaluated. This ideal of citizenship-as-competence entails a focus on the educational purposes of socialisation and qualification. Current policy texts thus seem to leave out the educational purpose of emancipating young people, allowing them to take on citizenship as something to which they can determine their own relation and position. It is, however, this purpose of CE that seems increasingly important in our current context. Young people are stepping out of school and onto the streets by the thousands in Belgium and throughout Europe, protesting for more and better environmental policies. They are making use of existing modes of citizenship, exactly to indicate to policymakers how these are falling short and are claiming their right and entitlement to a future that established practices of politics are putting at risk. The importance of citizenship education might then lie, now more than ever, not in the fact that it would prepare young people for competent citizenship, but in offering them a possibility, an emancipatory experience of being able to do something new. It seems that this is what we might want to expect from the school if we want it to educate our truly future citizens.

Keywords: citizenship education, normativity, policy, purposes of education

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Authors: Lorenzo Ciletti, Ed Baines, Matt Somerville

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Internationally, supporting staff with limited training (Teaching Assistants (TA)) has played a critical role in the education of children with special educational needs and/or disabilities (SEND). Researchers have notably illustrated that TAs support the children’s classroom tasks while teachers manage the whole class. Rarely have researchers investigated the TAs’ support for children’s participation in whole-class or peer-group talk, despite this type of “social support” playing a significant role in children’s whole-class integration and engagement with the classroom curriculum and learning. Social support seems particularly crucial for a large proportion of children with SEND, namely those with communication and interaction difficulties (e.g., autism spectrum conditions and speech impairments). This study explored TA practice and, particularly, TA social support in a rarely examined context (Italy). The Italian case was also selected as it provides TAs, known nationally as “support teachers,” with the most comprehensive training worldwide, thus potentially echoing (effective) nuanced practice internationally. Twelve hours of video recordings of a single TA and a child with communication and interaction difficulties (CID) were made. Video data was converted into frequencies of TA multidimensional support strategies, including TA social support and pedagogical assistance. TA-pupil talk oriented to children’s participation in classroom talk was also analysed into thematic patterns. These multi-method analyses were informed by social scaffolding principles: in particular, the extent to which the TA designs instruction contingently to the child’s communication and interaction difficulties and how their social support fosters the child’s highest responsibility in dealing with whole-class or peer-group talk by supplying the least help. The findings showed that the TA rarely supported the group or whole class participation of the child with CID. When doing so, the TA seemed to highly control the content and the timing of the child’s contributions to the classroom talk by a) interrupting the teacher’s whole class or group conversation to start an interaction between themselves and the child and b) reassuring the child about the correctness of their talk in private conversations and prompting them to raise their hand and intervene in the whole-class talk or c) stopping the child from contributing to the whole-class or peer-group talk when incorrect. The findings are interpreted in terms of their theoretical relation to scaffolding. They have significant implications for promoting social scaffolding in TA training in Italy and elsewhere.

Keywords: children with communication and interaction difficulties, children with special educational needs and/or disabilities, social scaffolding, teaching assistants, teaching practice, whole-class talk participation

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Authors: Cherry Yieng Siang Ling, Joong Hee Lee, Myung Hwan Yun

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The quality of a product to be usable has become the basic requirement in consumer’s perspective while failing the requirement ends up the customer from not using the product. Identifying usability issues from analyzing quantitative and qualitative data collected from usability testing and evaluation activities aids in the process of product design, yet the lack of studies and researches regarding analysis methodologies in qualitative text data of usability field inhibits the potential of these data for more useful applications. While the possibility of analyzing qualitative text data found with the rapid development of data analysis studies such as natural language processing field in understanding human language in computer, and machine learning field in providing predictive model and clustering tool. Therefore, this research aims to study the application capability of text processing algorithm in analysis of qualitative text data collected from usability activities. This research utilized datasets collected from LG neckband headset usability experiment in which the datasets consist of headset survey text data, subject’s data and product physical data. In the analysis procedure, which integrated with the text-processing algorithm, the process includes training of comments onto vector space, labeling them with the subject and product physical feature data, and clustering to validate the result of comment vector clustering. The result shows 'volume and music control button' as the usability feature that matches best with the cluster of comment vectors where centroid comments of a cluster emphasized more on button positions, while centroid comments of the other cluster emphasized more on button interface issues. When volume and music control buttons are designed separately, the participant experienced less confusion, and thus, the comments mentioned only about the buttons' positions. While in the situation where the volume and music control buttons are designed as a single button, the participants experienced interface issues regarding the buttons such as operating methods of functions and confusion of functions' buttons. The relevance of the cluster centroid comments with the extracted feature explained the capability of text processing algorithms in analyzing qualitative text data from usability testing and evaluations.

Keywords: usability, qualitative data, text-processing algorithm, natural language processing

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Pauline Cuenin, Marcelo Leles Romarco Oliveira

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Based on their localities and following their ecological rationality, family-based farmers have experimented, adapted and innovated to improve their production systems continuously for millennia. With the technological package transfer processes of the so-called Green Revolution for agricultural holdings, farmers have become increasingly dependent on ready-made "recipes" built from so-called "universal" and global knowledge to face the problems that emerge in the management of local agroecosystems, thus reducing their creative and experiential capacities. However, the production of novelties within farms is fundamental to the transition to more sustainable agro food systems. In fact, as the fruits of local knowledge and / or the contextualization of exogenous knowledge, novelties are seen as seeds of transition. By presenting new techniques, new organizational forms and epistemological approaches, agroecology was pointed out as a way to encourage and promote the creative capacity of farmers. From this perspective, this theoretical work aims to analyze how agroecology encourages the innovative capacity of farmers, and in general, the production of novelties. For this, an analysis was made of the theoretical and methodological bases of agroecology through a literature review, specifically looking for the way in which it articulates the local with the global, complemented by an analysis of agro ecological Brazilian experiences. It was emphasized that, based on the peasant way of doing agriculture, that is, on ecological / social co-evolution or still called co-production (interaction between human beings and living nature), agroecology recognizes and revalues peasant involves the deep interactions of the farmer with his site (bio-physical and social). As a "place science," practice and movement, it specifically takes into consideration the local and empirical knowledge of farmers, which allows questioning and modifying the paradigms that underpin the current agriculture that have disintegrated farmers' creative processes. In addition to upgrade the local, agroecology allows the dialogue of local knowledge with global knowledge, essential in the process of changes to get out of the dominant logic of thought and give shape to new experiences. In order to reach this articulation, agroecology involves new methodological focuses seeking participatory methods of study and intervention that express themselves in the form of horizontal spaces of socialization and collective learning that involve several actors with different knowledge. These processes promoted by agroecology favor the production of novelties at local levels for expansion at other levels, such as the global, through trans local agro ecological networks.

Keywords: agroecology, creativity, global, local, novelty

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Margo O'Sullivan, Xuefeng Chen, Qi Zhao, J. Jiang, Ning Fu

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Early childhood development, or ECD, is about the 'whole child' – the physical, social and emotional, cognitive thinking and language progression of each young individual. Overwhelming evidence is now available to support investment in Early Childhood Development internationally, attendance at ECD leads to: improved learning outcomes; improved completion and reduced less dropout rates; and most notably, Professor Heckman, Nobel Laureate’s, findings that for every dollar invested, there is an economic return of up to 17%. Notably, ECD has been included in the 2015-2030 Sustainable Development Goals. The Government of China (GOC) has embraced this research and in 2010, State Council, announced focus on ECD setting a target to provide access to ECD for 85% of 3-6 year olds by 2020; to date, the target has surpassed expectations and reached 70.4%. GoC is also increasingly focusing on the even more critical 0-3 age group, when the plasticity of the brain is at its peak and neurons form connections as fast as 1,000 per second. Key to ECD are parents and caregivers of young children, with parental education critical to fully exploiting the significant potential of the early years of children. In China, with such vast numbers, one in seven pre-school age children in the world live in China, the Ministry of Education (MoE) and the National Centre for Education Technology, explored how to best provide parental education and provide key child developmental related knowledge to parents and caregivers. In response, MoE and UNICEF created a resource for parenting information that began with a computer website in 2012, followed by piloting a kiosk service in 2013 for parents in remote areas without access to the internet, and then a mobile phone application in 2014. The resource includes 269 ECD messages and 200 micro-videos covering critical issues of early childhood development from birth to age 6 years: daily care, nutrition and feeding, disease prevention, immunization, development and education, and safety and protection. To date, there have been 397,599 unique views on the website, and data for the mobile app currently being analysed (Links: http://yuer.cbern.gov.cn/; App: https://appsto.re/cn/OiKPZ.i). This paper will explore the development of this resource, its use by parents and the public, efforts to assess the effectiveness in improving parenting and child development, and future plans to roll an updated version in 2016 to all parents.

Keywords: early childhood development, mobile apps for education, parental education, China

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Authors: Titilope F. Onaolapo, Christiana A. Breed, Maya Pasgaard, Kristine E. Jensen, Peta Brom

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In the face of fast-growing urbanization in most of the world's developing countries, there is a need to understand and address the risk and consequences involved in the indiscriminate use of urban green space. Tshwane city in South Africa has the potential to become one of the world's top biodiversity cities as South Africa is ranked one of the mega countries in biodiversity conservation, and Tshwane metropolitan municipality is the city with the wealthiest biodiversity with grassland biomes. In this study, we focus on the potentials and challenges of urban green transitioning from the Global South perspective with Tshwane city as the case study. We also address the issue of management conflicts that have resulted in informal and illegal activities in and around green spaces, with consequences such as land degradation, loss of livelihoods and biodiversity, and socio-ecological imbalances. A desk study review of eight policy frameworks related to green urban planning and development was done based on four GI principles: multifunctionality, connectivity, interdisciplinary and social inclusion. We interviewed 15 key informants in related departments in the city and administered 200 survey questionnaires among residents. We also had several workshops the other researchers and experts on biodiversity and ecosystem. We found out there is no specific document dedicated to green space management, and where green infrastructure was mentioned, it was focused on as an approach to climate mitigation and adaptation. Also, residents perceive green and open spaces as extra land that could be developed at will. We demonstrated the use of collaborative learning approaches in ecological and development research and the tying research to the existing frameworks, programs, and strategies. Based on this understanding. We outlined the need to incorporate principles of green infrastructure in policy frameworks on spatial planning and environmental development. Furthermore, we develop a model for co-management of green infrastructures by stakeholders, such as residents, developers, policymakers, and decision-makers, to maximize benefits. Our collaborative, interdisciplinary projects pursue SDG multifunctionality of goals 11 and 15 by simultaneously addressing issues around Sustainable Cities and Communities, Climate Action, Life on Land, and Strong Institutions, and halt and reverse land degradation and biodiversity.

Keywords: governance, green infrastructure, South Africa, sustainable development, urban planning, Tshwane

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Authors: Mona Rashidirad, Hamid Salimian

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Dynamic capabilities, as the most considerable capabilities of firms in the current fast-moving economy may not be sufficient for performance improvement, but their contribution to performance is undeniable. While much of the extant literature investigates the impact of dynamic capabilities on organisational performance, little attention has been devoted to understand whether and how dynamic capabilities create value. Dynamic capabilities as the mirror of competitive strategies should enable firms to search and seize new ideas, integrate and coordinate the firm’s resources and capabilities in order to create value. A careful investigation to the existing knowledge base remains us puzzled regarding the relationship among competitive strategies, dynamic capabilities and value creation. This study thus attempts to fill in this gap by empirically investigating the impact of dynamic capabilities on value creation and the mediating impact of competitive strategy on this relationship. We aim to contribute to dynamic capability view (DCV), in both theoretical and empirical senses, by exploring the impact of dynamic capabilities on firms’ value creation and whether competitive strategy can play any role in strengthening/weakening this relationship. Using a sample of 491 firms in the UK telecommunications market, the results demonstrate that dynamic sensing, learning, integrating and coordinating capabilities play a significant role in firm’s value creation, and competitive strategy mediates the impact of dynamic capabilities on value creation. Adopting DCV, this study investigates whether the value generating from dynamic capabilities depends on firms’ competitive strategy. This study argues a firm’s competitive strategy can mediate its ability to derive value from its dynamic capabilities and it explains the extent a firm’s competitive strategy may influence its value generation. The results of the dynamic capabilities-value relationships support our expectations and justify the non-financial value added of the four dynamic capability processes in a highly turbulent market, such as UK telecommunications. Our analytical findings of the relationship among dynamic capabilities, competitive strategy and value creation provide further evidence of the undeniable role of competitive strategy in deriving value from dynamic capabilities. The results reinforce the argument for the need to consider the mediating impact of organisational contextual factors, such as firm’s competitive strategy to examine how they interact with dynamic capabilities to deliver value. The findings of this study provide significant contributions to theory. Unlike some previous studies which conceptualise dynamic capabilities as a unidimensional construct, this study demonstrates the benefits of understanding the details of the link among the four types of dynamic capabilities, competitive strategy and value creation. In terms of contributions to managerial practices, this research draws attention to the importance of competitive strategy in conjunction with development and deployment of dynamic capabilities to create value. Managers are now equipped with solid empirical evidence which explains why DCV has become essential to firms in today’s business world.

Keywords: dynamic capabilities, resource based theory, value creation, competitive strategy

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Authors: Sajjad Hassanpour, Vicente A. González, Yang Zou, Jiamou Liu

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Earthquakes pose a significant threat to both structural and non-structural elements in buildings, putting human lives at risk. Effective post-earthquake evacuation is critical for ensuring the safety of building occupants. However, current design practices often neglect the integration of post-earthquake evacuation considerations into the early-stage architectural design process. To address this gap, this paper presents a novel automated internal architectural layout generation tool that optimizes post-earthquake evacuation performance. The tool takes an initial plain floor plan as input, along with specific requirements from the user/architect, such as minimum room dimensions, corridor width, and exit lengths. Based on these inputs, firstly, the tool randomly generates different architectural layouts. Secondly, the human post-earthquake evacuation behaviour will be thoroughly assessed for each generated layout using the advanced Agent-Based Building Earthquake Evacuation Simulation (AB2E2S) model. The AB2E2S prototype is a post-earthquake evacuation simulation tool that incorporates variables related to earthquake intensity, architectural layout, and human factors. It leverages a hierarchical agent-based simulation approach, incorporating reinforcement learning to mimic human behaviour during evacuation. The model evaluates different layout options and provides feedback on evacuation flow, time, and possible casualties due to earthquake non-structural damage. By integrating the AB2E2S model into the automated layout generation tool, architects and designers can obtain optimized architectural layouts that prioritize post-earthquake evacuation performance. Through the use of the tool, architects and designers can explore various design alternatives, considering different minimum room requirements, corridor widths, and exit lengths. This approach ensures that evacuation considerations are embedded in the early stages of the design process. In conclusion, this research presents an innovative automated internal architectural layout generation tool that integrates post-earthquake evacuation simulation. By incorporating evacuation considerations into the early-stage design process, architects and designers can optimize building layouts for improved post-earthquake evacuation performance. This tool empowers professionals to create resilient designs that prioritize the safety of building occupants in the face of seismic events.

Keywords: agent-based simulation, automation in design, architectural layout, post-earthquake evacuation behavior

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Authors: Yinghua Huang, Tsu-Hong Yen

Abstract:

The latest advance in leadership research has revealed that leadership is co-created through the combined action of leading and following. The role of followers is as important as leaders in the leadership process. However, the previous leadership studies often conceptualize leadership as a leader-centric process, while the role of followers is largely neglected in the literature. Until recently, followership studies receives more attention because the character and behavior of followers are as vital as the leader during the leadership process. Yet, there is a dearth of followership research in the context of tourism and hospitality industries. Therefore, this study seeks to fill in the gap of knowledge and investigate the followership styles in the U.S. hospitality workforce. In particular, the objectives of this study are to identify popular followership practices among hospitality employees and evaluate hospitality employees' followership styles using Kelley’s followership typology framework. This study also compared the generational differences in followership styles among hospitality employees. According to the U.S. Bureau of Labor Statistics, the workforce in the lodging and foodservice sectors consists of around 12% baby boomers, 29% Gen Xs, 23% Gen Ys, and 36% Gen Zs in 2019. The diversity of workforce demographics in the U.S. hospitality industry calls for more attention to understand the generational differences in followership styles and organizational performance. This study conducted an in-depth interview and a questionnaire survey to collect both qualitative and quantitative data. A snowball sampling method was used to recruit participants working in the hospitality industry in the San Francisco Bay Area, California, USA. A total of 120 hospitality employees participated in this study, including 22 baby boomers, 32 Gen Xs, 30 Gen Ys, and 36 Gen Zs. 45% of the participants were males, and 55% were female. The findings of this study identified good followership practices across the multi-generational participants. For example, a Gen Y participant said that 'followership involves learning and molding oneself after another person usually an expert in an area of interest. I think of followership as personal and professional development. I learn and get better by hands-on training and experience'. A Gen X participant said that 'I can excel by not being fearful of taking on unfamiliar tasks and accepting challenges.' Furthermore, this study identified five typologies of Kelley’s followership model among the participants: 45% exemplary followers, 13% pragmatist followers, 2% alienated followers, 18% passive followers, and 23% conformist followers. The generational differences in followership styles were also identified. The findings of this study contribute to the hospitality human resource literature by identifying the multi-generational perspectives of followership styles among hospitality employees. The findings provide valuable insights for hospitality leaders to understand their followers better. Hospitality leaders were suggested to adjust their leadership style and communication strategies based on employees' different followership styles.

Keywords: followership, hospitality workforce, generational diversity, Kelley’s followership topology

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