Search results for: lack of support

Authors: Taik Kim

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Mathematics anxiety has an important consequence for teacher practices that influence students’ attitudes and achievement. Elementary prospective teachers have the highest levels of mathematics anxiety in comparison with other college majors. In his teaching practice, the researcher developed a highly successful teaching model to reduce pre-service teachers’ higher math anxiety and simultaneously to improve their pedagogical math content knowledge. There were eighty one participants from 2015 to 2018 who took the Mathematics for Elementary Teachers I and II. As the analysis data indicated, elementary prospective teachers’ math anxiety was greatly reduced with improving their math pedagogical knowledge. U.S encounters a critical shortage of well qualified educators. To solve the issue, it is essential to engage students in a long-term commitmentto shape better teachers, who will, in turn, produce k-12 school students that are better-prepared for college students. It is imperative that new instructional strategies are implemented to improve student learning and address declining interest, poor preparedness, a lack of diverse representation, and low persistence of students in mathematics. Many four year college students take math courses from the math department in the College of Arts& Science and then take methodology courses from the College of Education. Before taking pedagogy, many students struggle in learning mathematics and lose their confidence. Since the content course focus on college level math, instead of pre service teachers’ teaching area, per se elementary math, they do not have a chance to improve their teaching skills on topics which eventually they teach. The research, a joint appointment of math and math education, has been involved in teaching content and pedagogy. As the result indicated, participants were able to math content at the same time how to teach. In conclusion, the new initiative to use several teaching strategies was able not only to increase elementary prospective teachers’ mathematical skills and knowledge but also to improve their attitude toward mathematics. We need an innovative teaching strategy which implements evidence-based tactics in redesigning a education and math to improve pre service teachers’math skills and which can improve students’ attitude toward math and students’ logical and reasoning skills. Implementation of these best practices in the local school district is particularly important because K-8 teachers are not generally familiar with lab-based instruction. At the same time, local school teachers will learn a new way how to teach math. This study can be a vital teacher education model expanding throughout the State and nationwide. In summary, this study yields invaluable information how to improve teacher education in the elementary level and, eventually, how to enhance K-8 students’ math achievement.

Keywords: quality of education and improvement method, teacher education, innovative teaching and learning methodologies, math education

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Authors: Preeti Tiwari, Jay Wood, Duncan Babbage

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Family planning plays a role in saving lives across the globe by preventing unwanted pregnancies. The purpose of this multidisciplinary research was to determine the impact of mHealth tools have on psychosocial determinants of behaviour for family planning. The present study examines a topic that is very relevant in times where human-technology interaction is at its peak. It is probably one of the first studies that have investigated the impact of mobile phone technology on the underlying mechanisms of behaviour change for family planning using primary data. To examine the association between exposure to mHealth tools and predictors of behaviour, data was collected from mHealth intervention areas in India. A post-intervention quasi-experimental study with a 2x2 factorial design was conducted among 831 men and women from the state of Bihar. The quantitative data analysis evaluated the extent of influence that predictors of behaviour (beliefs, social norms, perceived behaviour control, and outcome behaviour) have on a woman’s decisions about family planning. The results indicated an association between exposure to mHealth tools and improved communication about family planning among various family members after receiving health information from a health worker (H1). A relationship between exposure to mHealth tools and increased support women received from their husbands and extended family (mothers-in-law specifically) and peers (H2) was also found. A further result showed that knowledge about family planning was greater among users of family planning (H4). mHealth tools empower women to communicate with family members. This has important implications for developing mobile phone-based tools, as they can be used as a crucial communication channel that can be an effective method of increasing communication among family members about contraceptives. Thus, it can be implied that where women feel nervous talking about contraception, the successful application of mHealth tools can strengthen the interactivity of the health communication and could increase the likelihood of using contraception. However, while it may improve health communication that can inform health decisions, it may be insufficient on its own to cause behaviour change.

Keywords: contraceptive, e-health, psycho-social, women

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: John M. Basey, Clinton D. Francis, Maxwell B. Joseph

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After gathering data from experimental procedures, inquiry-oriented-science labs often allow students the freedom to stay and complete the write up in class or leave lab early and complete the write up later. Teachers must decide whether to allow students this freedom to self-regulate this time. Student interviews have indicated four time-target strategies that may influence how students utilize this time: grade-target-A, grade-target-C, time-limited, and proficiency. The hypothesis tested was that variability in class composition relative to the four grade-target strategies has an impact on when students leave class, which in turn may influence their overall learning as exemplified by grades. Students were divided into the four indicated groups with a survey. Class composition and the GTA teaching the class had significant impacts on how long students stayed in class with class composition having the greatest impact. A factor analysis identified two factors. Factor 1 included classes with percentages of grade-target students opposite time-limited/proficiency students and explained 43% of the variance. Factor 2 included classes with percentages of grade-target-A/proficiency students opposite grade-target-C students and explained 33% of the variance. Students who stayed longer received significantly higher grades (P = 0.008) with no significant relationships between grade and Factor 1 or Factor 2 (P > 0.05). The time students stayed in class was significantly positively related to Factor 1 (P = 0.006) and significantly negatively related to Factor 2 (P = 0.008). These results support the hypothesis and indicate that teachers may want to know the composition of student-target strategies before deciding on how to have students allocate study time at the end of inquiry-oriented labs. According to these results, ideal classes for self-regulation have a high proportion of proficiency and time-limited students and a low proportion of grade-target students, or a high proportion of grade-target-A and proficiency students and a low proportion of grade-target-C students. Non-ideal classes for self-regulation were comprised of the inverse proportions.

Keywords: grades, inquiry lab design, synergism in student motivation, class composition

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Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: Phillipa Denise Peart

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Black Asian and Minority Ethnic (BAME) people are more at risk of developing mental health disorders because they are more exposed to unfavorable social, economic, and environmental circumstances. These include housing, education, employment, community development, stigma, and discrimination. However, the majority of BAME mental health intervention studies focus on treatment with therapeutically effective drugs and use basic economic methods to evaluate their effectiveness; as a result, little is invested in the economic assessment of psychosocial interventions in BAME mental health. The UK government’s austerity programme and reduced funds for mental health services, has increased the need for the evaluation and assessment of initiatives to focus on value for money. The No Health without Mental Health policy (2011) provides practice guidance to practitioners, but there is little or no mention of the need to provide mental health initiatives targeted at BAME communities that are effective in terms of their impact and the cost-effectiveness. This, therefore, appears to contradict with and is at odds with the wider political discourse, which suggests there should be an increasing focus on health economic evaluation. As a consequence, it could be argued that whilst such policies provide direction to organisations to provide mental health services to the BAME community, by not requesting effective governance, assurance, and evaluation processes, they are merely paying lip service to address these problems and not helping advance knowledge and practice through evidence-based approaches. As a result, BAME communities suffer due to lack of efficient resources that can aid in the recovery process. This research study explores the mental health initiatives targeted at BAME communities, and analyses the techniques used when examining the cost effectiveness of mental health initiatives for BAME mental health communities. Using critical discourse analysis as an approach and method, mental health services will be selected as case studies, and their evaluations will be examined, alongside the political drivers that frame, shape, and direct their work. In doing so, it will analyse what the mental health policies initiatives are, how the initiatives are directed and demonstrate how economic models of evaluation are used in mental health programmes and how the value for money impacts and outcomes are articulated by mental health programme staff. It is anticipated that this study will further our understanding in order to provide adequate mental health resources and will deliver creative, supportive research to ensure evaluation is effective for the government to provide and maintain high quality and efficient mental health initiatives targeted at BAME communities.

Keywords: black, Asian and ethnic minority, economic models, mental health, health policy

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Koo Ja-Choon, Seok Hyun-Deok, Park So-Hee

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Even though developed countries have supported aid projects for restoring degraded and deforested mountain, recent North Korean authorities announced that North Korean forest is still very serious. Last 12 years, more than 16 thousand ha of forest were destroyed. Most of previous researches concluded that food and fuel problems should be solved for preventing people from deforesting and degrading forest in North Korea. It means that mountain restoration projects such as A/R(afforestation/reforestation) and REDD(Reducing Emissions from Deforestation and Forest Degradation) project should be implemented with the agroforestry and the forest tending project. Because agroforestry and the forest tending can provide people in the project area with foods and fuels, respectively. Especially, Agroforestry has been operated well with the support of Swiss agency of Development and cooperation since 2003. This paper aims to find the priority sites for mountain restoration project where all types of projects including agroforesty can be implemented simultaneously. We tried to find the primary counties where the areas of these activities were distributed widely and evenly. Recent spatial data of 186 counties representing altitude, gradient and crown density were collected from World Forest Watch. These 3 attributes were used to determine the type of activities; A/R, REDD, Agroforestry and forest tending project. Finally, we calculated the size of 4 activities in 186 counties by using GIS technique. Result shows that Chongjin in Hamgyeongbuk-do, Hoeryong in Hamgyeongbuk-do and Tongchang in Pyeonganbuk-do are on the highest priority of counties. Most of feasible counties whose value of richness and uniformity were greater than the average were located near the eastern coast of North Korea. South Korean government has not supported any aid projects in North Korea since 2010. Recently, South Korea is trying to continue the aid projects for North Korea. Forest project which is not affected by the political situation between North- and South- Korea can be considered as a priority activities. This result can be used when South Korean government determine the priority sites for North Korean mountain restoration project in near future.

Keywords: agroforestry, forest restoration project, GIS, North Korea, priority

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Authors: Stephanie Watson, Fabrice Stephenson, Conrad Pilditch, Carolyn Lundquist

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Spatial data detailing both the distribution and density of functionally important marine species are needed to inform management decisions. Species distribution models (SDMs) have proven helpful in this regard; however, models often focus only on species occurrences derived from spatially expansive datasets and lack the resolution and detail required to inform regional management decisions. Boosted regression trees (BRT) were used to produce high-resolution SDMs (250 m) at two spatial scales predicting probability of occurrence, abundance (count per sample unit), density (count per km2) and uncertainty for seven coastal seafloor taxa that vary in habitat usage and distribution to examine prediction differences and implications for coastal management. We investigated if small scale regionally focussed models (82,000 km2) can provide improved predictions compared to data-rich national scale models (4.2 million km2). We explored the variability in predictions across model type (occurrence vs abundance) and model scale to determine if specific taxa models or model types are more robust to geographical variability. National scale occurrence models correlated well with broad-scale environmental predictors, resulting in higher AUC (Area under the receiver operating curve) and deviance explained scores; however, they tended to overpredict in the coastal environment and lacked spatially differentiated detail for some taxa. Regional models had lower overall performance, but for some taxa, spatial predictions were more differentiated at a localised ecological scale. National density models were often spatially refined and highlighted areas of ecological relevance producing more useful outputs than regional-scale models. The utility of a two-scale approach aids the selection of the most optimal combination of models to create a spatially informative density model, as results contrasted for specific taxa between model type and scale. However, it is vital that robust predictions of occurrence and abundance are generated as inputs for the combined density model as areas that do not spatially align between models can be discarded. This study demonstrates the variability in SDM outputs created over different geographical scales and highlights implications and opportunities for managers utilising these tools for regional conservation, particularly in data-limited environments.

Keywords: Benthic ecology, spatial modelling, multi-scalar modelling, marine conservation.

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Authors: Shah Awan, Fahad Sultan, Shahid Jan Kakakhel

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Higher education in the 21st century has been faced with game-changing developments impacting teaching and learning and also strengthening the academia and industry relationship. The academia and industry relationship plays a key role in economic development in developed, developing and emerging economies. The partnership not only explores innovation but also provide a real time experience of the theoretical knowledge. For this purpose, the paper assessing the role of HEC in the Pakistan and discusses the way in academia and industry contribute their role in improving Pakistani economy. Successive studies have reported the importance of innovation and technology , research development initiatives in public sector universities, and the significance of role of higher education commission in strengthening the academia and industrial relationship to improve performance and minimize failure. The paper presents the results of interviews conducted, using semi-structured interviews amongst 26 staff members of two public sector universities, higher education commission and managers from corporate sector.The study shows public sector universities face the several barriers in developing economy like Pakistan, to establish the successful collaboration between universities and industry. Of the participants interviewed, HEC provides an insufficient road map to improve organisational capabilities in facilitating and enhance the performance. The results of this study have demonstrated that HEC has to embrace and internalize support to industry and public sector universities to compete in the era of globalization. Publication of this research paper will help higher education sector to further strengthen research sector through industry and university collaboration. The research findings corroborate the findings of Dooley and Kirk who highlights the features of university-industry collaboration. Enhanced communication has implications for the quality of the product and human resource. Crucial for developing economies, feasible organisational design and framework is essential for the university-industry relationship.

Keywords: higher education commission, role, academia and industry relationship, Pakistan

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Authors: Samar Saadeldin Abdelmotalab Omer, Ikram Mohammed Eltayeb Elsiddig, Amna Beshir Medani Ahmed, Saad Mohammed Hussein Ayoub

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Many herbal medicinal products are considered as potential hypocholesterolemic agents with encouraging safety profiles, however, only a limited amount of clinical research exists to support their efficacy. The present study was designed to compare the antihypercholesterolaemic and antioxidant activities of the crude ethanolic extracts of Citrus reticulata peel, Zingiber officinale rhizome, and Sesamum indicum seeds. Forty-five rats were used throughout the experiment, which were divided into nine groups, five rats in each as follows; normal control group (normal rats fed with standard normal diet), rats fed hypercholesterolemic diet consisting of 1% cholesterol and 10% saturated animal fat, which were further divided into eight groups; hypercholesterolemic control group (rats only fed hypercholesterolemic diet), groups 3,4,5,6,7, and 8 were given Citrus reticulata, Zingiber officinale, and Sesamum indicum ethanolic extracts at doses of (250mg/kg and 500mg/kg, respectively) orally; and group 9 rats were given atorvastatin (0.18mg/kg) orally as a reference antihypercholesterolaemic drug. Blood samples were obtained four weeks following treatment from the retro-orbital venous plexus after fasting overnight from all groups and the lipid profile (serum total cholesterol (TC), high-density-lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and triglycerides levels) was measured and the risk ratio (TC/HDL-C) was assessed. The antioxidant activity of the three plant extracts was determined using DPPH free-radical assay. Results of in vivo and in vitro antihypercholesterolaemic and antioxidant assay, respectively, revealed that the three extracts possess comparable antioxidant and anti-hypercholesterolaemic activities.

Keywords: anti hypercholesterolemic effects, antioxidant activity, HDL, LDL, TC, TGs, citrus reticulata, sesamum indicum, zingiber officinale

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Authors: Murat Can Pehlivanoglu

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Historically, gender equality has been mainly defended in the legal arenas of constitutional law and employment law. However, social and economic progress has required corporate law to provide gender equality on corporate boards. Recently, following the trend in Europe, the State of California (United States) enacted a law requiring that every publicly traded corporation based in California should have women on its board of directors. Still, the legal, social and economic implications of this law are yet to be discovered. The contractarian view of corporate law is predominant in the U.S. jurisprudence. However, gender quota law may not be justified through contractarian theory grounds. Therefore, the conformity of gender quota law with the general principles of U.S. corporate law remains questionable, and the immunity of close corporations from the scope of gender quota legislation provides support for the discrepancy. The methodology employed in this paper in the discussion of the rule’s conformity with corporate law is doctrinal, and American case law and legal scholarship are the basis for this discussion. This paper uses the aforementioned California law as sample legislation to evaluate the gender quota laws’ conformity with the contractarian theory of corporate law. It chooses California law as the sample due to its newness and the presence of pending shareholder lawsuits against it. Also, since California is home to global companies, the effect of such law is expected to be wider. As alternative theories laid down by corporate law may already be activated to provide gender equality on boards of publicly traded corporations, enacting a specific gender quota law would not be justified by an allegedly present statutory deficiency based on contractarian theory. However, this theoretical reality would not enable shareholders to succeed in their lawsuits against such law on corporate law grounds, and investors will have limited options against its results. This will eventually harm the integrity of the marketplace. Through the analysis of the contractarian theory of corporate law and California gender quota law, the major finding of this paper is that the contractarian theory of corporate law does not permit mandating board room equality through corporate law. In conclusion, it expresses that the issue should be dealt with through separate legislation with a different remedial structure, to preserve the traditional rationale of corporate law in U.S. law.

Keywords: board of directors, gender equality, gender quota, publicly traded corporations

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: A. Pascual Ramsay

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Accounts of the management of the economic and euro crisis in Spain have been dominated by an emphasis on external constraints. However, this approach leaves unanswered important questions about the role of domestic political factors. Using systematic qualitative primary research and employing elite interviewing and process tracing, this paper aims to fill this gap for the period of the Partido Socialista Obrero Español (PSOE) administration. The paper shows that domestic politics played a crucial role in the management of the crisis, most importantly by determining the shape of the measures undertaken. In its three distinct stages – downplaying/inaction, reaction/stimulus, and austerity/reform – the PSOE's response was certainly constrained by external factors, most notably EMU membership and the actions of sovereign-bond investors, the ECB and Germany. Yet while these external constraints forced the government to act, domestic political factors fundamentally shaped the content of key measures: the fiscal stimulus, the labour, financial and pension reforms, the refusal to accept a bailout or the reform of the Constitution. Seven factors were particularly influential: i) electoral and political cost, ii) party and partisanship, iii) organised interests, iv) domestic institutions, v) ideological preferences, vi) ineffective decision-making, and vii) judgement and personal characteristics of decision-makers. In conclusion, domestic politics played an important role in the management of the crisis, a role that has been underestimated by dominant approaches focusing on external constraints and weak domestic policy autonomy. The findings provide empirical evidence to support research agendas that identify significant state discretion in the face of international economic integration and an important role for domestic political factors such as institutions, material interests, partisanship and ideology in shaping economic outcomes.

Keywords: economic crisis, Euro, PSOE, Spain

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Authors: Chulpan Gromova, Rezeda Khairutdinova, Dina Birman

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One of the most significant issues that schools all over the world face today is the ways teachers respond to increasing diversity. The study was informed by the tripartite model of multicultural competence, with awareness of personal biases a necessary component, together with knowledge of different cultures, and skills to work with students from diverse backgrounds. The paper presents the results of qualitative descriptive studies that help to understand how school teachers in Russia treat migrant children, how they solve the problems of adaptation of migrant children. The purpose of this study was to determine: a) educational practices used by primary school teachers when working with migrant children; b) relationship between practices and attitudes of teachers. Empirical data were collected through interviews. The participants were informed that a conversation was being recorded. They were also warned that the study was voluntary, absolutely anonymous, no personal data was disclosed. Consent was received from 20 teachers. The findings were analyzed using directive content analysis (Graneheim and Lundman, 2004). The analysis was deductive according to the categories of practices and attitudes identified in the literature review and enriched inductively to identify variation within these categories. Studying practices is an essential part of preparing future teachers for working in a multicultural classroom. For language and academic support, teachers mostly use individual work. In order to create a friendly classroom climate and environment teachers have productive conversations with students, organize multicultural events for the whole school or just for an individual class. The majority of teachers have positive attitudes toward migrant children. In most cases, positive attitudes lead to high expectations for their academic achievements. Conceptual orientation of teacher attitudes toward cultural diversity is mostly pluralistic. Positive attitudes, high academic expectations and conceptual orientation toward pluralism are favorably reflected in teachers’ practice.

Keywords: intercultural education, migrant children schooling, teachers attitudes, teaching practices

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Authors: Hemin Yuan, Yun Wang, Xiangchun Wang

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Gas hydrate is drawing attention due to the fact that it has an enormous amount all over the world, which is almost twice the conventional hydrocarbon reserves, making it a potential alternative source of energy. It is widely distributed in permafrost and continental ocean shelves, and many countries have launched national programs for investigating the gas hydrate. Gas hydrate is mainly explored through seismic methods, which include bottom simulating reflectors (BSR), amplitude blanking, and polarity reverse. These seismic methods are effective at finding the gas hydrate formations but usually contain large uncertainties when applying to invert the micro-scale petrophysical properties of the formations due to lack of constraints. Rock physics modeling links the micro-scale structures of the rocks to the macro-scale elastic properties and can work as effective constraints for the seismic methods. A number of rock physics models have been proposed for gas hydrate modeling, which addresses different mechanisms and applications. However, these models are generally not well classified, and it is confusing to determine the appropriate model for a specific study. Moreover, since the modeling usually involves multiple models and steps, it is difficult to determine the source of uncertainties. To solve these problems, we summarize the developed models/methods and make four classifications of the models according to the hydrate micro-scale morphology in sediments, the purpose of reservoir characterization, the stage of gas hydrate generation, and the lithology type of hosting sediments. Some sub-categories may overlap each other, but they have different priorities. Besides, we also analyze the priorities of different models, bring up the shortcomings, and explain the appropriate application scenarios. Moreover, by comparing the models, we summarize a general workflow of the modeling procedure, which includes rock matrix forming, dry rock frame generating, pore fluids mixing, and final fluid substitution in the rock frame. These procedures have been widely used in various gas hydrate modeling and have been confirmed to be effective. We also analyze the potential sources of uncertainties in each modeling step, which enables us to clearly recognize the potential uncertainties in the modeling. In the end, we explicate the general problems of the current models, including the influences of pressure and temperature, pore geometry, hydrate morphology, and rock structure change during gas hydrate dissociation and re-generation. We also point out that attenuation is also severely affected by gas hydrate in sediments and may work as an indicator to map gas hydrate concentration. Our work classifies rock physics models of gas hydrate into different categories, generalizes the modeling workflow, analyzes the modeling uncertainties and potential problems, which can facilitate the rock physics characterization of gas hydrate bearding sediments and provide hints for future studies.

Keywords: gas hydrate, rock physics model, modeling classification, hydrate morphology

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Authors: Sophie Oakes-Rogers, Di Bailey, Karen Slade

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Female offenders are a uniquely vulnerable group, who are at high risk of suicide. Whilst the prevention of self-harm and suicide remains a key global priority, we need to better understand the relationship between these challenging behaviours that constitute a pressing problem, particularly in environments designed to prioritise safety and security. Method choice is unlikely to be random, and is instead influenced by a range of cultural, social, psychological and environmental factors, which change over time and between countries. A key aspect of self-harm and suicide in women receiving forensic care is the lack of free access to methods. At a time where self-harm and suicide rates continue to rise internationally, understanding the role of these influencing factors and the impact of current suicide prevention strategies on the use of near-lethal methods is crucial. This poster presentation will present findings from 25 interviews and 3 focus groups, which enlisted a Participatory Action Research approach to explore the differences between self-harming and suicidal behavior. A key element of this research was using the lived experiences of women receiving forensic care from one forensic pathway in the UK, and the staffs who care for them, to discuss the role of near-lethal self-harm (NLSH). The findings and suggestions from the lived accounts of the women and staff will inform a draft assessment tool, which better assesses the risk of suicide based on the lethality of methods. This tool will be the first of its kind, which specifically captures the needs of women receiving forensic services. Preliminary findings indicate women engage in NLSH for two key reasons and is determined by their history of self-harm. Women who have a history of superficial non-life threatening self-harm appear to engage in NLSH in response to a significant life event such as family bereavement or sentencing. For these women, suicide appears to be a realistic option to overcome their distress. This, however, differs from women who appear to have a lifetime history of NLSH, who engage in such behavior in a bid to overcome the grief and shame associated with historical abuse. NLSH in these women reflects a lifetime of suicidality and indicates they pose the greatest risk of completed suicide. Findings also indicate differences in method selection between forensic provisions. Restriction of means appears to play a role in method selection, and findings suggest it causes method substitution. Implications will be discussed relating to the screening of female forensic patients and improvements to the current suicide prevention strategies.

Keywords: forensic mental health, method substitution, restriction of means, suicide

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Authors: N. Nalini, Bhanu Prakash Gopularam

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The term data security refers to the degree of resistance or protection given to information from unintended or unauthorized access. The core principles of information security are the confidentiality, integrity and availability, also referred as CIA triad. Cloud computing services are classified as SaaS, IaaS and PaaS services. With cloud adoption the confidential enterprise data are moved from organization premises to untrusted public network and due to this the attack surface has increased manifold. Several cloud computing platforms like OpenStack, Eucalyptus, Amazon EC2 offer users to build and configure public, hybrid and private clouds. While the traditional encryption based on PKI infrastructure still works in cloud scenario, the management of public-private keys and trust certificates is difficult. The Identity based Public Key Cryptography (also referred as ID-PKC) overcomes this problem by using publicly identifiable information for generating the keys and works well with decentralized systems. The users can exchange information securely without having to manage any trust information. Another advantage is that access control (role based access control policy) information can be embedded into data unlike in PKI where it is handled by separate component or system. In OpenStack cloud platform the keystone service acts as identity service for authentication and authorization and has support for public key infrastructure for auto services. In this paper, we explain OpenStack security architecture and evaluate the PKI infrastructure piece for data confidentiality. We provide method to integrate ID-PKC schemes for securing data while in transit and stored and explain the key measures for safe guarding data against security attacks. The proposed approach uses JPBC crypto library for key-pair generation based on IEEE P1636.3 standard and secure communication to other cloud services.

Keywords: data confidentiality, identity based cryptography, secure communication, open stack key stone, token scoping

Procedia PDF Downloads 365

Authors: Pushpa Debnath

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Buddhism implies the ultimate methodology to obtain the acknowledgment to get out from cycling existence applied by the sutras. The Buddha’s natural methodology is the highest way of cessation from suffering existence. To be out of it, one must know the suffering before having tentativeness. According to the Buddha’s methodology, one can observe every being suffer from chronologically grasping craving. It is because lack of knowledge that the Buddha finds the four noble truths which are the basic states. These are suffering, the origin of suffering, cessation of suffering, and the path leading to the cessation of suffering. The Buddha describes that birth is suffering, aging is suffering, sickness is suffering, death is suffering, association with the unexpected is suffering, separation from the pleasant is suffering, and not receiving what one desires is suffering, In brief, the five aggregates of clinging are suffering. As the five aggregates are form, feeling, perception, mental formation, and consciousness. These are known as the matter that we identify with “You, Me” or “He.” The second truth cause of suffering is craving which has three types: craving for sense pleasures, craving for existence, and craving for non-existence. The third truth is the obliteration of craving, suffering can be eliminated to attain the Nibbana. The fourth truth is the path of liberation is the noble eight-fold path consisting of the right view, right intention, right speech, right action, right livelihood, right effort, right mindfulness, and right concentration. The six senses are the media of the eye, ear, nose, tongue, body, and mind sense faculties relating with the five aggregates and the six senses objects visual objects, sounds, smells, tastes, touch, and mind-objects that are contained by every visible being. The first five internal sense bases are material while the mind is a non-material phenomenon. Contact with the external world maintains by receiving through the six senses; visual objects through the eye, sounds through the ear, smells through the nose, tastes through the tongue, touch through the body, and mind-objects through sense faculties. These are the six senses a living being experiences by craving. Everything is conglomerated with all senses faculties through the natural phenomenon which are earth, water, fire, and air element. In this analysis, it is believed that beings are well adapted to the natural phenomenon. Everybody has fear of life because we have hatred, delusion, and anger which are the primary resources of falling into (Samsara) continuously that is the continuity of the natural way. These are the reasons for the suffering that chronically self-diluting through the threefold way. These are the roots of the entire beings suffering so the Buddha finds the enlightenment to uproot from cycling existence and the understanding of the natural consequence. When one could uproot ignorance, one could able to realize the ultimate happiness of Nirvana. From the craving of ignorance, everything starts to be present to the future which gives us mental agonies in existence.

Keywords: purification, morality, natural phenomenon, analysis, development of mind, observatory, Nirvana

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Authors: Isaac Diaka, Matsui Kenichi

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Ghana’s rice production has increased mainly because of increased cultivated areas. On this point, scholars who promoted crop production increase for food security have overlooked the fact that its per-acre yield has not increased. Also, Ghana’s domestic rice production has not contributed much to domestic rice consumption especially in major cities where consumers tend to rely on imported rice from Asia. Considering these points, the paper seeks to understand why smallholder rice farmers have not been able to increase per acre rice yield. It also examines smallholder rice farmers’ rice yield improvement needs, and the relationship that exist between rice farmers’ socioeconomic factors and their yield levels by rice varieties. The study adopted a simple random sampling technique to select 154 rice farmers for a questionnaire survey between October and November 2020. The data was analyzed by performing a correlation analysis, an independent t-test, and Kendall’s coefficient of concordance. The results showed that 58.4% of the respondents cultivated popular high-yield varieties like AGRA and Jasmine. The rest used local varieties. Regarding respondents’ yield differentials, AGRA and Jasmine had an average yield of 2.6 mt/ha, which is higher than that of local varieties (1.6mt/ha). The study found untimely availability of improved seed varieties and high cost of inputs some of the major reasons affecting yield in the area. For respondents’ yield improvement needs, Kendall’s coefficient of concordance showed that access to improved varieties, irrigation infrastructure, and row planting were respondents’ major technological needs. As to their non-technological needs, the respondents needed timely information about rice production, access to credit support options, and extension services. The correlation analysis revealed that farm size and off-farm income exhibited a positive and negative association towards respondents’ yield level, respectively. This paper then discusses recommendations for providing with improved rice production technologies to farmers.

Keywords: Ghana, rice, smallholder farmers, yield improvement.

Procedia PDF Downloads 79

Authors: Rebecca Keyte, Helen Egan, Michail Mantzios

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It is well acknowledged that ongoing adherence is a major concern within CF. However recently literature has indicated that non-adherence should not be viewed just in terms of medical regimens. There are other damaging behaviours that some chronically ill patients engage in which can be viewed as a form of non-adherence, such as risky behaviours. Risky behaviours are a major concern within CF, as they can have adverse health effects on patients regardless of patients adherence to medical regimens. The risky behaviours this research is predominantly focusing on are smoking, excessive alcohol consumption, illicit drug use and risky sexual behaviour. This research investigates patient’s beliefs about their CF and the impact their CF has upon their life, exploring rationales for why some patients engage in risky behaviours. This research utilises qualitative semi-structured interviews taking an interpretive perspective. Twenty-four adult participants have been recruited (16 male, age range 19–66 yrs) from two UK regional CF centres, with a median FEV1 61.77% predicted. Participants were recruited via clinician guidance, with 13 participants identified by clinicians as partaking in risky behaviours. However, during the interviews 17 participants were identified as partaking in risky behaviours, illustrating that not all patients offer full disclosure of engagement in such behaviours to their clinicians. Preliminary findings illustrate a variety of reasons as to why some CF patients engage in risky behaviours, with many participants stating that one challenge in terms of living with CF is accepting their illness. Disclosure of illness was also an issue, the desire to be seen as ‘normal’ was important to many. It is often possible for CF patients to hide their illness as they do not always appear to be unwell. However, literature indicates a desire for normalcy can be accompanied with the engagement of normalised risky behaviours, enabling patients to retaliate against their illness identity. There was also evidence of a life-orientated perspective amongst participants, with some reporting that their desire for fun and enjoyment was the reason for why they were engaging in risky behaviours. Some participants did not acknowledge the impact their risky behaviours could have upon their CF, and others rationalised their continuation with the behaviours by suggesting that they were in fact beneficial to their health. There was an apparent lack of knowledge around the implications of risky behaviours, with participants indicating that they had not been informed of such potential consequences by their clinicians. Given the adverse health effects of risky behaviours within CF, more effective health promotion measures are needed to both reduce and more importantly prevent these behaviours. Due to the initiation of risky behaviours within the CF population commonly occurring during adolescence, the researcher now proposes to conduct semi-structured interviews with paediatric patients to investigate their awareness and beliefs towards risky behaviours. Overall, this research will highlight reasons why some CF patients engage in risky behaviours, in order to inform interventions aimed to prevent the initiation in risky behaviours by increasing patient awareness.

Keywords: cystic fibrosis, health beliefs, preliminary findings, risky health behaviours

Procedia PDF Downloads 278

Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

Procedia PDF Downloads 138

Authors: Paolo Grasso, Sai Kalyan Yelike, Federico Benzi, Mathieu Le Cam

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The cabin air quality (CAQ) in commercial aircraft is of prime interest, especially in the context of the COVID-19 pandemic. Current Environmental Control Systems (ECS) rely on a prescribed fresh airflow per passenger to dilute contaminants. An adaptive ECS strategy is proposed, leveraging air sensing and filtration technologies to ensure a better CAQ. This paper investigates the CAQ level achieved in commercial aircraft’s cabin during various flight scenarios. The modeling and simulation analysis is performed in a Modelica-based environment describing the dynamic behavior of the system. The model includes the following three main systems: cabin, recirculation loop and air-conditioning pack. The cabin model evaluates the thermo-hygrometric conditions and the air quality in the cabin depending on the number of passengers and crew members, the outdoor conditions and the conditions of the air supplied to the cabin. The recirculation loop includes models of the recirculation fan, ordinary and novel filtration technology, mixing chamber and outflow valve. The air-conditioning pack includes models of heat exchangers and turbomachinery needed to condition the hot pressurized air bled from the engine, as well as selected contaminants originated from the outside or bled from the engine. Different ventilation control strategies are modeled and simulated. Currently, a limited understanding of contaminant concentrations in the cabin and the lack of standardized and systematic methods to collect and record data constitute a challenge in establishing a causal relationship between CAQ and passengers' comfort. As a result, contaminants are neither measured nor filtered during flight, and the current sub-optimal way to avoid their accumulation is their dilution with the fresh air flow. However, the use of a prescribed amount of fresh air comes with a cost, making the ECS the most energy-demanding non-propulsive system within an aircraft. In such a context, this study shows that an ECS based on a reduced and adaptive fresh air flow, and relying on air sensing and filtration technologies, provides promising results in terms of CAQ control. The comparative simulation results demonstrate that the proposed adaptive ECS brings substantial improvements to the CAQ in terms of both controlling the asymptotic values of the concentration of the contaminant and in mitigating hazardous scenarios, such as fume events. Original architectures allowing for adaptive control of the inlet air flow rate based on monitored CAQ will change the requirements for filtration systems and redefine the ECS operation.

Keywords: cabin air quality, commercial aircraft, environmental control system, ventilation

Procedia PDF Downloads 86

Authors: Selamat Muliadi

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This study aimed to explain conceptual the role of Zakat on sustainable economic development by Rumah Zakat. Rumah Zakat is a philanthropic institution that manages zakat and other social funds through community empowerment programs. In running the program, including economic empowerment and socio health services are designed for these recipients. Rumah Zakat's connection with the establisment of Sustainable Development Goals (SDGs) which is to help impoverished recipients economically and socially. It’s an important agenda that the government input into national development, even the region. The primary goal of Zakat on sustainable economic development, not only limited to economic variables but based on Islamic principles, has comprehensive characteristics. The characteristics include moral, material, spiritual, and social aspects. In other words, sustainable economic development is closely related to improving people’s living standard (Mustahiq). The findings provide empiricial evidence regarding the positive contribution and effectiveness of zakat targeting in reducing poverty and improve the welfare of people related with the management of zakat. The purpose of this study was to identify the role of Zakat on sustainable economic development, which was applied by Rumah Zakat. This study used descriptive method and qualitative analysis. The data source was secondary data collected from documents and texts related to the research topic, be it books, articles, newspapers, journals, or others. The results showed that the role of zakat on sustainable economic development by Rumah Zakat has been quite good and in accordance with the principle of Islamic economics. Rumah Zakat programs are adapted to support intended development. The contribution of the productive program implementation has been aligned with four goals in the Sustainable Development Goals, i.e., Senyum Juara (Quality Education), Senyum Lestari (Clean Water and Sanitation), Senyum Mandiri (Entrepreneur Program) and Senyum Sehat (Free Maternity Clinic). The performance of zakat in the sustainable economic empowerment community at Rumah Zakat is taking into account dimensions such as input, process, output, and outcome.

Keywords: Zakat, social welfare, sustainable economic development, charity

Procedia PDF Downloads 123

Authors: Myriam Rousseau, Suzie McKinnon, Mathieu Mireault, Anaïs V. Berthiaume, Marie-Hélène Poulin, Jacinthe Bourassa, Louis-Simon Maltais

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The increasing presence of young people with autism is forcing schools to adapt to this new situation and to offer services that meet the needs of this clientele. However, school staff often feels unqualified to support these students, lacking the preparation, skills and training to meet their needs. Continuing education for these staff is therefore essential to ensure that they can meet the needs of these students. As a result, the Government of Quebec has developed a bilingual (French and English) online training on autism specific to the needs of school staff. Therefore, adequate training for all school staff is likely to provide quality learning opportunities for these students. The research project focuses on the participants' appreciation, contributions, and social validity of the training. More specifically, it aims to: 1) evaluate the knowledge and self-efficacy of the participants, 2) evaluate the social validity and 3) document the evaluation of the ergonomics of the platform hosting the training. The evaluation carried out as part of this descriptive study uses a quantitative method. Data are collected using questionnaires completed online. The analysis of preliminary data reveals that participants' knowledge of autism and their sense of self-efficacy increased significantly. They value the training positively and consider it to be acceptable, appropriate, and suitable. The participants find it important for school staff to take this training. Almost all the items measuring the ergonomics of the platform have averages above 4.57/5. In general, the study shows that the training allows participating of the trainee school staff to improve their knowledge of autism and their sense of self-efficacy with young people with autism. In addition, participants recognize that the training has good social validity and appreciate the online modality. However, these results should be interpreted with caution given the limited number of participants who completed the research project. It is therefore important to continue the research with a larger number of participants to allow an adequate and general representativeness of the social validity, the feeling of competence and the appreciation of the platform.

Keywords: autism, online training, school staff, social validity

Procedia PDF Downloads 22

Authors: Mireya Mateo Gomez

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The purpose of this study was to examine the perceptions first-generation Mexican origin mothers living in San Diego have on postpartum depression (PPD), with a special focus on social influences and cultural beliefs towards those meanings. This study also aimed to examine possible PPD help-seeking behaviors that first-generation Mexican origin mothers can perform. The Health Belief Model (HBM) and Social Ecological Model (SEM) were the guiding theoretical frameworks for this study. Data for this study were collected from three focus groups, four in-depth interviews, and the distribution of an acculturation survey (ARSMA II). There were a total of 15 participants, in which participant’s mean age was 45, and the mean age migrated to the United States being 22. Most participants identified as being married, born in Southern or Western Mexico, and with a strong Mexican identity in relation to the ARSMA survey. Participants identified four salient PPD perceptions corresponding to the interpersonal level of SEM. These four main perceptions were: 1) PPD affecting the identity of motherhood; 2) PPD being a natural part of a mother’s experience but mitigated by networks; 3) PPD being a U.S. phenomenon due to family and community breakdown; and 4) natural remedies as a preferred PPD treatment. In regard to themes relating to help seeking behaviors, participants identified seven being: 1) seeking help from immediate family members; 2) practicing home remedies; 3) seeking help from a medical professional; 4) obtaining help from a clinic or organization; 5) seeking help from God; 6) participating in PPD support groups; and 7) talking to a friend. It was evident in this study that postpartum depression is not a well discussed topic within the Mexican immigrant population. In relation to the role culture and social influences have on PPD perceptions, most participants shared hearing or learning about PPD from their family members or friends. Participants also stated seeking help from family members if diagnosed with PPD and seeking out home remedies. This study as well provides suggestions to increase the awareness of PPD among the Mexican immigrant community.

Keywords: cultural beliefs, health belief model, Mexican origin mothers, perceptions, postpartum depression social ecological model

Procedia PDF Downloads 135

Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: database, electricity sub-meters, energy anomaly detection, sensor

Procedia PDF Downloads 290

Authors: Alper Tolga Kumtepe, Erdem Erdogdu, M. Recep Okur, Eda Kaypak, Ozlem Kaya, Serap Ugur, Deniz Dincer, Hakan Yildirim

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Interaction is one of the most important components of open and distance learning. According to Moore, who proposed one of the keystones on interaction types, there are three basic types of interaction: learner-teacher, learner-content, and learner-learner. From these interaction types, learner-content interaction, without doubt, can be identified as the most fundamental one on which all education is based. Efficacy, efficiency, and attraction of open and distance learning systems can be achieved by the practice of effective learner-content interaction. With the development of new technologies, interactive e-learning materials have been commonly used as a resource in open and distance learning, along with the printed books. The intellectual engagement of the learners with the content that is course materials may also affect their satisfaction for the open and distance learning practices in general. Learner satisfaction holds an important place in open and distance learning since it will eventually contribute to the achievement of learning outcomes. Using the learner-content interaction activities in course materials, Anadolu University, by its Open Education system, tries to involve learners in deep and meaningful learning practices. Especially, during the e-learning material design and production processes, identifying appropriate learner-content interaction activities within the context of learning outcomes holds a big importance. Considering the lack of studies adopting this approach, as well as its being a study on the use of e-learning materials in Open Education system, this research holds a big value in open and distance learning literature. In this respect, the present study aimed to investigate a) which learner-content interaction activities included in interactive courses are the most effective in learners’ achievement of verbal information learning outcomes and b) to what extent distance learners are satisfied with these learner-content interaction activities. For this study, the quasi-experimental research design was adopted. The 120 participants of the study were from Anadolu University Open Education Faculty students living in Eskişehir. The students were divided into 6 groups randomly. While 5 of these groups received different learner-content interaction activities as a part of the experiment, the other group served as the control group. The data were collected mainly through two instruments: pre-test and post-test. In addition to those tests, learners’ perceived learning was assessed with an item at the end of the program. The data collected from pre-test and post-test were analyzed by ANOVA, and in the light of the findings of this approximately 24-month study, suggestions for the further design of e-learning materials within the context of learner-content interaction activities will be provided at the conference. The current study is planned to be an antecedent for the following studies that will examine the effects of activities on other learning domains.

Keywords: interaction, distance education, interactivity, online courses

Procedia PDF Downloads 178

Authors: Maria Botero-Uribe, Melissa Fitzgerald, Robert Gilbert, Kim Bryceson, Jocelyn Midgley

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French fry manufacturing involves a series of processes in which structural properties of potatoes are modified to produce crispy french fries which consumers enjoy. In addition to the traditional french fry manufacturing process, the industry is applying a relatively new process called pulsed electrical field (PEF) to the whole potatoes. There is a wealth of information on the technical treatment conditions of PEF, however, there is a lack of information about its effect on the structural properties that affect texture and its synergistic interactions with the other manufacturing steps of french fry production. The effect of PEF on starch gelatinisation properties of Russet Burbank potato was measured using a Differential Scanning Calorimeter. Cation content (K+, Ca2+ and Mg2+) was determined by inductively coupled plasma optical emission spectrophotometry. Firmness, and toughness of raw and blanched potatoes were determined in an uniaxial compression test. Moisture content was determined in a vacuum oven and oil content was measured using the soxhlet system with hexane. The final texture of the french fries – crispness - was determined using a three bend point test. Triangle tests were conducted to determine if consumers were able to perceive sensory differences between French fries that were PEF treated and those without treatment. The concentration of K+, Ca2+ and Mg2+ decreased significantly in the raw potatoes after the PEF treatment. The PEF treatment significantly increased modulus of elasticity, compression strain, compression force and toughness in the raw potato. The PEF-treated raw potato were firmer and stiffer, and its structure integrity held together longer, resisted higher force before fracture and stretched further than the untreated ones. The strain stress relationship exhibited by the PEF-treated raw potato could be due to an increase in the permeability of the plasmalema and tonoplasm allowing Ca2+ and Mg2+ cations to reach the cell wall and middle lamella, and be available for cross linking with the pectin molecule. The PEF-treated raw potato exhibited a slightly higher onset gelatinisation temperatures, similar peak temperatures and lower gelatinisation ranges than the untreated raw potatoes. The final moisture content of the french fries was not significantly affected by the PEF treatment. Oil content in the PEF- treated potatoes was lower than the untreated french fries, however, not statistically significant at 5 %. The PEF treatment did not have an overall significant effect on french fry crispness (modulus of elasticity), flexure stress or strain. The triangle tests show that most consumers could not detect a difference between French fries that received a PEF treatment from those that did not.

Keywords: french fries, mechanical properties, PEF, potatoes

Procedia PDF Downloads 227

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

Procedia PDF Downloads 91