Search results for: impacting student learning outcomes

Authors: Zainab Olabisi Tairu

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Strategic partnerships are a core requirement in delivering sustainable tourism for development in developing nations like Papua New Guinea. This paper unveils the strategic partnerships for sustainable tourism development in Papua New Guinea. Much emphasis is made among tourism stakeholders, on the importance of strategic partnership and positioning in developing sustainable tourism development. This paper engages stakeholders’ ecotourism differentiation and power relations in the discussion of the paper through interviews and observations with tourism stakeholders in Papua New Guinea. Collaborative approaches in terms of sustaining the tourism industry, having a milestone of achieved plans, are needed for tourism growth and development. This paper adds a new insight to the body of knowledge on stakeholders’ identification, formation, power relations and an integrated approach to successful tourism development. In order to achieve responsible tourism planning and management outcomes, partnerships must be holistic in perspective and based on sustainable development principles.

Keywords: stakeholders, sustainable tourism, Papua New Guinea, partnerships

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Authors: Thomas Rockstuhl, Soon Ang, Kok Yee Ng, Linn Van Dyne

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Intercultural interactions are often challenging and fraught with conflicts. To shed light on how to interact effectively across cultures, academics and practitioners alike have advanced a plethora of intercultural competence models. However, the majority of this work has emphasized distal outcomes, such as job performance and cultural adjustment, rather than proximal outcomes, such as how individuals resolve inevitable intercultural conflicts. As a consequence, the processes by which individuals negotiate challenging intercultural conflicts are not well understood. The current study advances theorizing on intercultural conflict resolution by exploring antecedents of how people resolve intercultural conflicts. To this end, we examine creativity – the generation of novel and useful ideas – in the context of resolving cultural conflicts in intercultural interactions. Based on the dual-identity theory of creativity, we propose that individuals with greater international experience will display greater creativity and that the relationship is accentuated by individual’s cultural intelligence. Two studies test these hypotheses. The first study comprises 84 senior university students, drawn from an international organizational behavior course. The second study replicates findings from the first study in a sample of 89 executives from eleven countries. Participants in both studies provided protocols of their strategies for resolving two intercultural conflicts, as depicted in two multimedia-vignettes of challenging intercultural work-related interactions. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded all strategies for their novelty and usefulness following scoring procedures for creativity tasks. Participants also completed online surveys of demographic background information, including their international experience, and cultural intelligence. Hierarchical linear modeling showed that surprisingly, while international experience is positively associated with usefulness, it is unrelated to novelty. Further, a person’s cultural intelligence strengthens the positive effect of international experience on usefulness and mitigates the effect of international experience on novelty. Theoretically, our findings offer an important theoretical extension to the dual-identity theory of creativity by identifying cultural intelligence as an important individual difference moderator that qualifies the relationship between international experience and creative conflict resolution. In terms of novelty, individuals higher in cultural intelligence seem less susceptible to rigidity effects of international experiences. Perhaps they are more capable of assessing which aspects of culture are relevant and apply relevant experiences when they brainstorm novel ideas. For utility, individuals high in cultural intelligence are better able to leverage on their international experience to assess the viability of their ideas because their richer and more organized cultural knowledge structure allows them to assess possible options more efficiently and accurately. In sum, our findings suggest that cultural intelligence is an important and promising intercultural competence that fosters creative resolutions to intercultural conflicts. We hope that our findings stimulate future research on creativity and conflict resolution in intercultural contexts.

Keywords: cultural Intelligence, intercultural conflict, intercultural creativity, international experience

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Authors: Antti Lanki, Justiina Halonen, Juuso Punnonen, Emmi Rantavuo

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Marine oil spill response operation requires extensive vessel maneuvering and navigation skills. At-sea oil containment and recovery include both single vessel and multi-vessel operations. Towing long oil containment booms that are several hundreds of meters in length, is a challenge in itself. Boom deployment and towing in multi-vessel configurations is an added challenge that requires precise coordination and control of the vessels. Efficient communication, as a prerequisite for shared situational awareness, is needed in order to execute the response task effectively. To gain and maintain adequate maritime skills, practical training is needed. Field exercises are the most effective way of learning, but especially the related vessel operations are resource-intensive and costly. Field exercises may also be affected by environmental limitations such as high sea-state or other adverse weather conditions. In Finland, the seasonal ice-coverage also limits the training period to summer seasons only. In addition, environmental sensitiveness of the sea area restricts the use of real oil or other target substances. This paper examines, whether maritime simulator training can offer a complementary method to overcome the training challenges related to field exercises. The objective is to assess the efficiency and the learning impact of simulator training, and the specific skills that can be trained most effectively in simulators. This paper provides an overview of learning results from two oil spill response pilot courses, in which maritime navigational bridge simulators were used to train the oil spill response authorities. The simulators were equipped with an oil spill functionality module. The courses were targeted at coastal Fire and Rescue Services responsible for near shore oil spill response in Finland. The competence levels of the participants were surveyed before and after the course in order to measure potential shifts in competencies due to the simulator training. In addition to the quantitative analysis, the efficiency of the simulator training is evaluated qualitatively through feedback from the participants. The results indicate that simulator training is a valid and effective method for developing marine oil spill response competencies that complement traditional field exercises. Simulator training provides a safe environment for assessing various oil containment and recovery tactics. One of the main benefits of the simulator training was found to be the immediate feedback the spill modelling software provides on the oil spill behaviour as a reaction to response measures.

Keywords: maritime training, oil spill response, simulation, vessel manoeuvring

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Authors: Sushil Kumar Singh, Ashok Kumar, Ankit Ganeshpurkar, Ravi Singh, Devendra Kumar

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In spectrum of neurodegenerative diseases, Alzheimer’s disease (AD) is characterized by the presence of amyloid β plaques and neurofibrillary tangles in the brain. It results in cognitive and memory impairment due to loss of cholinergic neurons, which is considered to be one of the contributing factors. Donepezil, an acetylcholinesterase (AChE) inhibitor which also inhibits butyrylcholinesterase (BuChE) and improves the memory and brain’s cognitive functions, is the most successful and prescribed drug to treat the symptoms of AD. The present work is based on designing of the selective BuChE inhibitors using computational techniques. In this work, machine learning models were trained using classification algorithms followed by screening of diverse chemical library of compounds. The various molecular modelling and simulation techniques were used to obtain the virtual hits. The amide derivatives of 4-(phenylsulfonamido) benzoic acid were synthesized and characterized using 1H & 13C NMR, FTIR and mass spectrometry. The enzyme inhibition assays were performed on equine plasma BuChE and electric eel’s AChE by method developed by Ellman et al. Compounds 31, 34, 37, 42, 49, 52 and 54 were found to be active against equine BuChE. N-(2-chlorophenyl)-4-(phenylsulfonamido)benzamide and N-(2-bromophenyl)-4-(phenylsulfonamido)benzamide (compounds 34 and 37) displayed IC50 of 61.32 ± 7.21 and 42.64 ± 2.17 nM against equine plasma BuChE. Ortho-substituted derivatives were more active against BuChE. Further, the ortho-halogen and ortho-alkyl substituted derivatives were found to be most active among all with minimal AChE inhibition. The compounds were selective toward BuChE.

Keywords: Alzheimer disease, butyrylcholinesterase, machine learning, sulfonamides

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Authors: Miracle Ajah

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One of the biggest challenges facing Theological/Religious Education in Nigeria is access to quality learning materials. For instance at the Trinity (Union) Theological College, Umuahia, it was difficult for lecturers to access suitable and qualitative materials for instruction especially the ones that would suit the African context and stimulate a deep rooted interest among the students. Some textbooks written by foreign authors were readily available in the School Library, but were lacking in the College bookshops for students to own copies. Even when the College was able to order some of the books from abroad, it did not usher in the needed enthusiasm expected from the students because they were either very expensive or very difficult to understand during private studies. So it became necessary to develop contextual materials which were affordable and understandable, though with little success. The National Open University of Nigeria (NOUN)’s innovation in the development and sharing of learning resources through its Open Course ware is a welcome development and of great assistance to students. Apart from NOUN students who could easily access the materials, many others from various theological/religious institutes across the nation have benefited immensely. So, the thesis of this paper is that the promotion of open educational resources in theological/religious education in Nigeria would facilitate a better informed/equipped religious leadership, which would in turn impact its adherents for a healthier society and national development. Adopting a narrative and historical approach within the context of Nigeria’s educational system, the paper discusses: educational traditions in Nigeria; challenges facing theological/religious education in Nigeria; and benefits of open educational resources. The study goes further to making recommendations on how OER could positively influence theological/religious education in Nigeria. It is expected that theologians, religious educators, and ODL practitioners would find this work very useful.

Keywords: OER, theological education, religious education, Nigeria

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Authors: Laura N. Bolivar T.

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The tourism importance for regional development is mainly highlighted by the collaborative, cooperating and competitive relationships of the involved agents. The fostering of associativity processes, in particular, the cluster approach emphasizes the beneficial outcomes from the concentration of enterprises, where innovation and entrepreneurship flourish and shape the dynamics for tourism empowerment. Considering the department of Huila, it is located in the south-west of Colombia and holds the biggest coffee production in the country, although it barely contributes to the national GDP. Hence, its economic development strategy is looking for more dynamism and Huila could be consolidated as a leading destination for cultural, ecological and heritage tourism, if at least the public policy making processes for the tourism management of La Tatacoa Desert, San Agustin Park and Bambuco’s National Festival, were implemented in a more efficient manner. In this order of ideas, this study attempts to address the potential restrictions and beneficial factors for the consolidation of the tourism sector of Huila-Colombia as a cluster and how could it impact its regional development. Therefore, a set of theoretical frameworks such as the Tourism Routes Approach, the Tourism Breeding Environment, the Community-based Tourism Method, among others, but also a collection of international experiences describing tourism clustering processes and most outstanding problematics, is analyzed to draw up learning points, structure of proceedings and success-driven factors to be contrasted with the local characteristics in Huila, as the region under study. This characterization involves primary and secondary information collection methods and comprises the South American and Colombian context together with the identification of involved actors and their roles, main interactions among them, major tourism products and their infrastructure, the visitors’ perspective on the situation and a recap of the related needs and benefits regarding the host community. Considering the umbrella concepts, the theoretical and the empirical approaches, and their comparison with the local specificities of the tourism sector in Huila, an array of shortcomings is analytically constructed and a series of guidelines are proposed as a way to overcome them and simultaneously, raise economic development and positively impact Huila’s well-being. This non-exhaustive bundle of guidelines is focused on fostering cooperating linkages in the actors’ network, dealing with Information and Communication Technologies’ innovations, reinforcing the supporting infrastructure, promoting the destinations considering the less known places as well, designing an information system enabling the tourism network to assess the situation based on reliable data, increasing competitiveness, developing participative public policy-making processes and empowering the host community about the touristic richness. According to this, cluster dynamics would drive the tourism sector to meet articulation and joint effort, then involved agents and local particularities would be adequately assisted to cope with the current changing environment of globalization and competition.

Keywords: innovative strategy, local development, network of tourism actors, tourism cluster

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Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Abdulmjeid Aljerawi

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This study aimed to investigate the students' attitudes towards the use of social networking in education. Due to the nature of the study, and on the basis of its problem, objectives, and questions, the researcher used the descriptive approach. An appropriate questionnaire was prepared and validity and reliability were ensured. The questionnaire was then applied to the study sample of 434 students from King Saud University.

Keywords: social networks, education, learning, students

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Authors: Jenn Gallup, Onur Kocaoz, Onder Islek

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In their pursuit of postsecondary transitions, individuals with disabilities tend to experience, academic, behavioral, and emotional challenges to a greater extent than their typically developing peers. These challenges result in lower rates of graduation, employment, independent living, and participation in college than their peers without disabilities. The lack of friendships and support systems has had a negative impact on those with a disability transitioning to postsecondary settings to include, employment, independent living, and university settings. Establishing friendships and support systems early on is an indicator of potential success and persistence in postsecondary education, employment, and independent living for typically developing college students. It is evident that a deficit in friendships and supports is a key deficit also for individuals with disabilities. To address the specific needs of this group, a mentor program was developed for a transition program held at the university for youth aged 18-21. Pre-service teachers enrolled in the special education program engaged with youth in the transition program in a variety of activities on campus. The mentorship program had two purposes: to assist young adults with disabilities who were transitioning to a workforce setting to help increase social skills, self-advocacy, supports and friendships, and confidence; and to give their peers without disabilities who were enrolled in a secondary special education course as a pre-service teacher the experience of interacting with and forming friendships with peers who had a disability for the purposes of career development. Additionally, according to researchers mobile technology has created a virtual world of equality and opportunity for a large segment of the population that was once marginalized due to physical and cognitive impairments. All of the participants had access to smart phones; therefore, technology was explored during this study to determine if it could be used as a compensatory tool to allow the young adults with disabilities to do things that otherwise would have been difficult because of their disabilities. Additionally, all participants were asked to incorporate technology such as smart phones to communicate beyond the activities, collaborate using virtual platform games which would support and promote social skills, soft-skills, socialization, and relationships. The findings of this study confirmed that a peer mentorship program that harnessed the power of technology supported outcomes specific to young adults with and without disabilities. Mobile technology and virtual game-based platforms, were identified as a significant contributor to personal, academic, and career growth for both groups. The technology encouraged friendships, provided an avenue for rich social interactions, and increased soft-skills. Results will be shared along with the development of the program and potential implications to the field.

Keywords: career outcomes, mentorship, soft-skills, technology, transition

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Authors: Ajay Pinjani, Minha Khan, Ayesha Mehkeri, Anum Iftikhar

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There is much research available on the benefits of adopting mother tongue-based multilingual education (MTB MLE) in primary school classrooms, but there is limited guidance available on how to design such programs for low-resource and linguistically diverse contexts. This paper is an effort to bridge the gap between theory and practice by offering a practitioner’s perspective on designing an MTB MLE program for linguistically heterogeneous contexts. The research compounds findings from current academic literature on MTB MLE, the study of global MTB MLE programs, interviews with practitioners, policy-makers, and academics worldwide, and a socio-linguistic survey carried out in parts of Tharparkar, Pakistan, the area selected for envisioned pilot implementation. These findings enabled the creation of ‘guiding principles’ which provide structure for the development of a contextualized and holistic MTB-MLE program. The guiding principles direct the creation of teaching and learning materials, creating effective teaching and learning environment, community engagement, and program evaluation. Additionally, the paper demonstrates the development of a context-specific language ladder framework which outlines the language journey of a child’s education, beginning with the mother tongue/ most familiar language in the early years and then gradually transitioning into other languages. Both the guiding principles and language ladder can be adapted to any multilingual context. Thus, this research provides MTB MLE practitioners with assistance in developing an MTB MLE model, which is best suited for their context.

Keywords: mother tongue based multilingual education, education design, language ladder, language issues, heterogeneous contexts

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Authors: Klara Królewiak-Detsi, Anna Orylska, Anna Gorgolewska, Marta Boczkowska, Agata Graczykowska

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This study investigates the communication between students and teachers in inclusive education in Poland. Specifically, we examine the communication and interaction of students with special educational needs during online learning compared to traditional face-to-face instruction. Our research questions are (1) how children with special educational needs communicate with their teachers and peers during online learning, and (2) what strategies can improve their communication skills. We conducted five focus groups with: (1) 55 children with special educational needs, (2) 65 typically developing pupils, (3) 28 professionals (psychologists and special education therapists), (4) 16 teachers, and (5) 16 parents of children with special educational needs. Our analysis focused on primary schools and used thematic analysis according to the 6-step procedure of Braun and Clarke. Our findings reveal that children with disabilities faced more difficulties communicating and interacting with others online than in face-to-face lessons. The online tools used for education were not adapted to the needs of children with disabilities, and schools lacked clear guidelines on how to pursue inclusive education online. Based on the results, we offer recommendations for online communication training and tools that are dedicated to children with special educational needs. Additionally, our results demonstrate that typically developing pupils are better in interpersonal relations and more often and effectively use social support. Children with special educational needs had similar emotional and communication challenges compared to their typically developing peers. In conclusion, our study highlights the importance of providing adequate support for the online education of children with special educational needs in inclusive classrooms.

Keywords: Inclusive education, Special educational needs, Social skills development, Online communication

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Authors: Donald Kushon, Jyoti Pillai

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Psychogenic Non-epileptic Seizure Disorder (PNES) is a challenging clinical problem for the neurologist. This study explores the benefits of on-site collaboration between psychiatry and neurology in the management of PNES. A 3 month period at a university hospital seizure clinic is described detailing specific management approaches taken as a result of this collaboration. This study describes four areas of interest: (1. After the video EEG results confirm the diagnosis of PNES, the presentation of the diagnosis of PNES to the patient. (2. The identification of co-morbid psychiatric illness (3. Treatment with specific psychotherapeutic interventions (including Cognitive Behavioral Therapy) and psychopharmacologic interventions (primarily SSRIs) and (4. Preliminary treatment outcomes.

Keywords: cognitive behavioral therapy (CBT), psychogenic non-epileptic seizure disorder (PNES), selective serotonin reuptake inhibitors (SSRIs), video electroencephalogram (VEEG)

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Authors: Agbana Olaseinde Julius, Opadere Olaolu Stephen

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The concept of cross carpeting is as old as politics itself. Basically, it entails an individual leaving a political party/group, to join another. The reasons for which cross carpeting is embarked upon are diverse: ideological differences; ethnic and/or religious differences; access to actual or perceived better political opportunities; liberty of association; rancor; etc. The current democratic dispensation in Nigeria has experienced renewed and rather alarming rate of cross carpeting, for reasons including those enumerated above and others. Right to cross carpet is inherent in a democratic setting as well as the political stakeholder; so does it also comprise of the constitutional right of ‘freedom of association’. However, the current species of cross carpeting in Nigeria requires scrutiny, in view of some potential legal and moral challenges it poses for both the present and the future. Cross carpeting is considered both legal and constitutional, but the current spate raises the question of expediency, particularly in a nascent democracy. It is considered to have a propensity of negatively impacting political stability in a polity with fragile nerves. Importantly too, cross carpeting is considered a potential damage to the psyche of posterity with regards to a warped disposition to promises, honour and integrity. The perceived peculiar dimension of cross carpeting in Nigeria raises questions on the quality of leadership presently obtainable in the country, vis-à-vis greed, self-centeredness, disregard for the concern and interest of avowed followers/fans, entrenchment of distrust, etc. Thus, the study made use of primary and secondary sources of information. The primary sources included the Constitutions of the Federal Republic of Nigeria 1999 (as amended); judicial decisions; and the Electoral Act, 2010 (as Amended). The secondary sources comprised of information from books, journals, newspapers, magazines and Internet documents. Data obtained from these sources were subjected to content analysis. Findings of this study show that though the act of cross carpeting may not be in breach of any Statute or Law, it however, in most cases, breaches the morals of expediency. The morality thereof is far from justifiable, and should be condemned in the interest of the present and posterity. There is a great and urgent need to embark on a re-entrenchment of the culture of political ideology in the Nigerian polity, as obtainable in developed democracies. In conclusion, the need to exercise the right of cross carpeting with caution cannot be overemphasized. Membership of a political group/party should be backed by commitment to well defined ideologies and values. Commitment to them should be regarded akin to that found in the family, which is not easily or flippantly jettisoned.

Keywords: cross-carpeting, Nigeria, legal, moral issues, politics

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Authors: Saughmon Boujkian

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This study delves into the intricate interplay between semantics and emotional connotation in linguistic expression, focusing on the role of expressive adjectives (EAs). Through a blend of theoretical frameworks from linguistics and computational techniques from natural language processing, native speakers' judgments are curated to capture the nuanced interpretations elicited by EAs in diverse linguistic contexts. Leveraging mathematical tools like least squares analysis, the study translates qualitative linguistic phenomena into quantitative measures, unveiling the differential impact of EAs on sentence sentiment. The derived expressive vectors offer insights into the nature of expressive meaning, underscoring the complex dynamics inherent in linguistic expression. While the study's outcomes provide valuable insights, future research endeavors could explore more sophisticated linguistic models to enhance the accuracy and granularity of expressive vector representations.

Keywords: vectors, expressive meaning, multi-dimentionality, least squares regression

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Authors: Vanessa H. S. Zago, Ana Maria H. de Avila, Paula P. Costa, Welington Corozolla, Liriam S. Teixeira, Eliana C. de Faria

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Objectives: The outcome of cardiovascular disease is affected by environment and climate. This study evaluated the possible relationships between climatic and environmental changes and the occurrence of biological rhythms in serum lipids and lipoproteins in a large population sample in the city of Campinas, State of Sao Paulo, Brazil. In addition, it determined the temporal variations of death due to atherosclerotic events in Campinas during the time window examined. Methods: A large 8-year retrospective study was carried out to evaluate the lipid profiles of individuals attended at the University of Campinas (Unicamp). The study population comprised 27.543 individuals of both sexes and of all ages. Normolipidemic and dyslipidemic individuals classified according to Brazilian guidelines on dyslipidemias, participated in the study. For the same period, the temperature, relative humidity and daily brightness records were obtained from the Centro de Pesquisas Meteorologicas e Climaticas Aplicadas a Agricultura/Unicamp and frequencies of death due to atherosclerotic events in Campinas were acquired from the Brazilian official database DATASUS, according to the International Classification of Diseases. Statistical analyses were performed using both Cosinor and ARIMA temporal analysis methods. For cross-correlation analysis between climatic and lipid parameters, cross-correlation functions were used. Results: Preliminary results indicated that rhythmicity was significant for LDL-C and HDL-C in the cases of both normolipidemic and dyslipidemic subjects (n =respectively 11.892 and 15.651 both measures increasing in the winter and decreasing in the summer). On the other hand, for dyslipidemic subjects triglycerides increased in summer and decreased in winter, in contrast to normolipidemic ones, in which triglycerides did not show rhythmicity. The number of deaths due to atherosclerotic events showed significant rhythmicity, with maximum and minimum frequencies in winter and summer, respectively. Cross-correlation analyzes showed that low humidity and temperature, higher thermal amplitude and dark cycles are associated with increased levels of LDL-C and HDL-C during winter. In contrast, TG showed moderate cross-correlations with temperature and minimum humidity in an inverse way: maximum temperature and humidity increased TG during the summer. Conclusions: This study showed a coincident rhythmicity between low temperatures and high concentrations of LDL-C and HDL-C and the number of deaths due to atherosclerotic cardiovascular events in individuals from the city of Campinas. The opposite behavior of cholesterol and TG suggest different physiological mechanisms in their metabolic modulation by climate parameters change. Thus, new analyses are underway to better elucidate these mechanisms, as well as variations in lipid concentrations in relation to climatic variations and their associations with atherosclerotic disease and death outcomes in Campinas.

Keywords: atherosclerosis, climatic variations, lipids and lipoproteins, associations

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Authors: Jiashu Shen

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This study aims at exploring the characteristics of sexual knowledge, attitudes, and behaviors of Chinese college students from the 'one-child' families compared with those with siblings. This study utilized the data from the 'National College Student Survey on Sexual and Reproductive Health 2019'. Multiple logistic regression analyses were used to assess the association between the 'only-child' and their sexual knowledge, sexual attitudes, sexual behaviors, and risky sexual behaviors (RSB) stratified by sex and home regions, respectively. Compared with students with siblings, the 'only-child' students scored higher in sex-related knowledge (only-child students: 4.49 ± 2.28, students with siblings: 3.60 ± 2.27). Stronger associations between only-child and more liberal sexual attitudes were found in urban areas, including the approval of premarital sexual intercourse (OR: 1.51, 95% CI: 1.50-1.65) and multiple sexual partners (OR: 1.85, 95% CI: 1.72-1.99). For risky sexual behaviors, being only-child is more likely to use condoms in first sexual intercourse, especially among male students (OR: 0.68, 95% CI: 0.58-0.80). Only-child students are more likely to have more sexual knowledge, more liberal sexual attitude, and less risky sexual behavior. Further health policy and sex education should focus more on students with siblings.

Keywords: attitudes and behaviors, only-child students, sexual knowledge, students with siblings

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Authors: Zhe Wang

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The fashion week, as a critical international fashion event in shaping world fashion cities, is one of the most significant world events that serves as the core medium for designers to stage new collections. However, its role in bringing about and shaping design ideologies of major fashion cities have long been neglected from a fashion ecosystem perspective. With the expanding scale of international fashion weeks in terms of culture and commerce, the organizational structures of these fashion weeks are becoming more complex. In the emerging fashion city, typified by Shanghai, a newly-formed 'hodgepodge' transforming the current global fashion ecosystem. A city’s legitimate fashion institutions, typically the organizers of international fashion weeks, have cultivated various cultural characteristics via rules and regulations pertaining to international fashion weeks. Under these circumstances, designers’ participatory behaviors, specifically show design and production, are influenced by the cultural ideologies of official organizers and institutions. This research compares international based Chinese (IBC) independent designers’ participatory behavior in London and Shanghai Fashion Weeks: specifically, the way designers present their clothing and show production. both of which are found to be profoundly influenced by cultural and design ideologies of fashion weeks. They are, to a large degree, manipulated by domestic institutions and organizers. Shanghai fashion week has given rise to a multiple, mass-ended entertainment carnival design and cultural ideology in Shanghai, thereby impacting the explicit cultural codes or intangible rules that IBC designers must adhere to when designing and producing fashion shows. Therefore, influenced by various cultural characteristics in the two cities, IBC designers’ show design and productions, in turn, play an increasingly vital role in shaping the design characteristic of an international fashion week. Through researching the organizational systems and design preferences of organizers of London and Shanghai fashion weeks, this paper demonstrates the embeddedness of design systems in the forming of design ideologies under various cultural and institutional contexts. The core methodology utilized in this research is ethnography. As a crucial part of a Ph.D. project on innovations in fashion shows under a cross-cultural context run by Edinburgh College of Art, School of Design, the fashion week’s organizational culture in various cultural contexts is investigated in London and Shanghai for approximately six months respectively. Two IBC designers, Angel Chen and Xuzhi Chen were followed during their participation of London and Shanghai Fashion Weeks from September 2016 to June 2017, during which two consecutive seasons were researched in order to verify the consistency of design ideologies’ associations with organizational system and culture.

Keywords: institutional ideologies, international fashion weeks, IBC independent designers; fashion show

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Authors: Samuel Sii, David Homewood, Brendan Dittmer, Tony Nzembela, Jonathan O’Brien, Niall Corcoran, Dinesh Agarwal

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Introduction: Innovation is key to the advancement of medicine and improvement in patient care. This is particularly true in surgery, where pioneering techniques have transformed operative management from a historically highly risky peri-morbid and disfiguring to the contemporary low-risk, sterile and minimally invasive treatment modality. There is a delicate balance between enabling innovation and minimizing patient harm. Publication and discussion of novel surgical techniques allow for independent expert review. Recent journals have increasingly stringent requirements for publications and often require larger case volumes for novel techniques to be published. This potentially impairs the initial publication of novel techniques and slows innovation. The historical perspective provides a better understanding of how requirements for the publication of new techniques have evolved over time. This is essential in overcoming challenges in developing novel techniques. Aims and Objectives: We explore how novel techniques in Urology have been published over the past 200 years. Our objective is to describe the trend and publication requirements of novel urological techniques, both historical and present. Methods: We assessed all major urological operations using multipronged historical analysis. An initial literature search was carried out through PubMed and Google Scholar for original literature descriptions, followed by reference tracing. The first publication of each pioneering urological procedure was recorded. Data collected includes the year of publication, description of the procedure, number of cases and outcomes. Results: 65 papers describing pioneering techniques in Urology were identified. These comprised of 2 experimental studies, 17 case reports and 46 case series. These papers described various pioneering urological techniques in urological oncology, reconstructive urology and endourology. We found that, historically, techniques were published with smaller case numbers. Often, the surgical technique itself was a greater focus of the publication than patient outcome data. These techniques were often adopted prior to larger publications. In contrast, the risks and benefits of recent novel techniques are often well-defined prior to adoption. This historical perspective is important as recent journals have requirements for larger case series and data outcomes. This potentially impairs the initial publication of novel techniques and slows innovation. Conclusion: A better understanding of historical publications and their effect on the adoption of urological techniques into common practice could assist the current generation of Urologists in formulating a safe, efficacious process in promoting surgical innovation and the development of novel surgical techniques. We propose the reassessment of requirements for the publication of novel operative techniques by splitting technical perspectives and data-orientated case series. Existing frameworks such as IDEAL and ASERNIP-S should be integrated into current processes when investigating and developing new surgical techniques to ensure efficacious and safe innovation within surgery is encouraged.

Keywords: urology, surgical innovation, novel surgical techniques, publications

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: Joy Chadwick

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There is no doubt that classrooms of today are more complex and diverse than ever before. Preparing teacher candidates to meet these challenges is essential to ensure the retention of teachers within the profession and to ensure that graduates begin their teaching careers with the knowledge and understanding of how to effectively meet the diversity of students they will encounter. Creating inclusive classrooms requires teachers to have a repertoire of effective instructional skills and strategies. Teachers must also have the mindset to embrace diversity and value the uniqueness of individual students in their care. This qualitative study analyzed teacher candidates' experiences as they completed a fourteen-week teaching practicum while simultaneously completing a university course focused on inclusive pedagogy. The research investigated the challenges and successes teacher candidates had in navigating the translation of theory related to inclusive pedagogy into their teaching practice. Applying threshold concept theory as a framework, the research explored the troublesome concepts, liminal spaces, and transformative experiences as connected to inclusive practices. Threshold concept theory suggests that within all disciplinary fields, there exists particular threshold concepts that serve as gateways or portals into previously inaccessible ways of thinking and practicing. It is in these liminal spaces that conceptual shifts in thinking and understanding and deep learning can occur. The threshold concept framework provided a lens to examine teacher candidate struggles and successes with the inclusive education course content and the application of this content to their practicum experiences. A qualitative research approach was used, which included analyzing twenty-nine course reflective journals and six follow up one-to-one semi structured interviews. The journals and interview transcripts were coded and themed using NVivo software. Threshold concept theory was then applied to the data to uncover the liminal or stuck spaces of learning and the ways in which the teacher candidates navigated those challenging places of teaching. The research also sought to uncover potential transformative shifts in teacher candidate understanding as connected to teaching in an inclusive classroom. The findings suggested that teacher candidates experienced difficulties when they did not feel they had the knowledge, skill, or time to meet the needs of the students in the way they envisioned they should. To navigate the frustration of this thwarted vision, they relied on present and previous course content and experiences, collaborative work with other teacher candidates and their mentor teachers, and a proactive approach to planning for students. Transformational shifts were most evident in their ability to reframe their perceptions of children from a deficit or disability lens to a strength-based belief in the potential of students. It was evident that through their course work and practicum experiences, their beliefs regarding struggling students shifted as they saw the value of embracing neurodiversity, the importance of relationships, and planning for and teaching through a strength-based approach. Research findings have implications for teacher education programs and for understanding threshold concepts theory as connected to practice-based learning experiences.

Keywords: inclusion, inclusive education, liminal space, teacher education, threshold concepts, troublesome knowledge

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Authors: Marta Lisowska

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The growing trend of market specialization imposes upon translators the need for proficiency in the working knowledge of specialist discourse. The notion of specialization differs from a broad general category to a highly specialized narrow field. The specialised discourse is used in the channel of communication based upon distinctive features typical for communities of practice whose co-existence is codified and hermetically locked against outsiders. Consequently, any translator deprived of professional discourse competence and social skills is incapable of providing competent translation product from source language into target language. In this paper, we report on research that explores the pedagogical practices aiming to bridge the dichotomy between the professionals and the specialist translators, while accounting for the reality of the world of professional communities entered by undergraduates on two levels: the text-based generic, and the social one. Drawing from the functional social constructivist approach, seen here as situated learning, this paper reports on the case of English-Polish, Polish-English undergraduate BA Level LSP of law translation class run in line with the simulated classroom-based and the reality-based (apprenticeship) approach. This blended method serves the purpose of introducing the young trainees to the professional world. The research provides new insights into how the LSP translation undergraduates become legitimized through discursive and social participation and engagement. The undergraduates, situated peripherally at the outset, experience their own transformation towards becoming members of these professional groups. With subjective evaluation, the trainees take a stance on this dual mode class and development of their skills. Comparing and contrasting their own work done in line with two models of translation teaching: authentic and near-authentic, the undergraduates answer research questions devised by a questionnaire survey The responses take us closer to how students feel about their LSP translation competence development. The major findings show how the trainees perceive the benefits and hardships of their functional translation class. In terms of skills, they related to communication as the most enhanced one; they highly valued the fact of being ‘exposed’ to a variety of texts (cf. multi literalism), team work, learning how to schedule work, IT skills boost and the ability to learn how to work individually. Another finding indicates that students struggled most with specialized language, and co-working with other students. The short-term research shows the momentum when the undergraduate LSP translation trainees entered the path of transformation i.e. gained consciousness of ‘how it is’ to be a participant-translator of real-life communities of practice, gaining pragmatic dint of the social and linguistic skills understood here as discursive competence (text > genre > discourse > professional practice). The undergraduates need to be aware of the work they have to do and challenges they are to face before arriving at the expert level of professional translation competence.

Keywords: communities of practice in LSP translation teaching, learning LSP translation as situated experience, peripheral participation, professional discourse for LSP translation teaching, professional translation competence

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Authors: Hamed Khezrzadeh

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Many investigations on the micromechanical structure of materials indicate that there exist fractal patterns at the micro scale in some of the main construction and industrial materials. A recently presented micro-fractal theory brings together the well-known periodic homogenization and the fractal geometry to construct an appropriate model for determination of the mechanical properties of particle reinforced composite materials. The proposed multi-step homogenization scheme considers the mechanical properties of different constituent phases in the composite together with the interaction between these phases throughout a step-by-step homogenization technique. In the proposed model the interaction of different phases is also investigated. By using this method the effect of fibers grading on the mechanical properties also could be studied. The theory outcomes are compared to the experimental data for different types of particle-reinforced composites which very good agreement with the experimental data is observed.

Keywords: fractal geometry, homogenization, micromehcanics, particulate composites

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Ngoc Dao

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State Paid Leave Programs (PFL) complement the Federal Family and Medical Leave Act (FMLA) by offering workers time off to take care of their newborns or sick family members with supplemental income, and further job protection. Up to date, four states (California, New Jersey, Rhode Island, and New York) implemented paid leave policies. This study adds further understanding of how state PFL policies help working families with elder parents improve their work balance by examining the paid leave policies on labor outcomes. Early findings suggest State Paid Leave Policies reduced the likelihood to exit the labor market by 1.6 percentage points, with larger effects among paid leave policies with job protection feature. In addition, the results imply job protection in paid leave policies matters in helping employed caregivers attach to the labor market.

Keywords: family paid leave, working caregivers, employment, social welfare

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Tianqi Wu, Min Wang

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Research investigating language acquisition from a constructionist perspective has demonstrated that language is learned as constructions at various linguistic levels, which is related to factors of frequency, semantic prototypicality, and form-meaning contingency. However, previous research on construction learning tended to focus on clause-level constructions such as verb argument constructions but few attempts were made to study morpheme-level constructions such as the progressive construction, which is regarded as a source of acquisition problems for English learners from diverse L1 backgrounds, especially for those whose L1 do not have an equivalent construction such as German and Chinese. To trace the developmental trajectory of Chinese EFL learners’ use of the progressive with respect to verb frequency, verb-progressive contingency, and verbal prototypicality and generality, a learner corpus consisting of three sub-corpora representing three different English proficiency levels was extracted from the Chinese Learners of English Corpora (CLEC). As the reference point, a native speakers’ corpus extracted from the Louvain Corpus of Native English Essays was also established. All the texts were annotated with C7 tagset by part-of-speech tagging software. After annotation all valid progressive hits were retrieved with AntConc 3.4.3 followed by a manual check. Frequency-related data showed that from the lowest to the highest proficiency level, (1) the type token ratio increased steadily from 23.5% to 35.6%, getting closer to 36.4% in the native speakers’ corpus, indicating a wider use of verbs in the progressive; (2) the normalized entropy value rose from 0.776 to 0.876, working towards the target score of 0.886 in native speakers’ corpus, revealing that upper-intermediate learners exhibited a more even distribution and more productive use of verbs in the progressive; (3) activity verbs (i.e., verbs with prototypical progressive meanings like running and singing) dropped from 59% to 34% but non-prototypical verbs such as state verbs (e.g., being and living) and achievement verbs (e.g., dying and finishing) were increasingly used in the progressive. Apart from raw frequency analyses, collostructional analyses were conducted to quantify verb-progressive contingency and to determine what verbs were distinctively associated with the progressive construction. Results were in line with raw frequency findings, which showed that contingency between the progressive and non-prototypical verbs represented by light verbs (e.g., going, doing, making, and coming) increased as English proficiency proceeded. These findings altogether suggested that beginning Chinese EFL learners were less productive in using the progressive construction: they were constrained by a small set of verbs which had concrete and typical progressive meanings (e.g., the activity verbs). But with English proficiency increasing, their use of the progressive began to spread to marginal members such as the light verbs.

Keywords: Construction learning, Corpus-based, Progressives, Prototype

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Authors: Yi-Jiun Chou, Ying-Hsuan Li, Yi-Jung Liu, Hsin-Yu Chiang, Hsuan-Ching Wang

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Background: Patients received therapeutic hypothermia (TH) after resuscitation from cardiac arrest are more dependent on continue and intensive nursing care. It involves many difficult steps, especially achieving target body temperature. To our best knowledge, there is no consensus or recommended standards on nursing practice of TH. Aim: The aim of this study is to increase the completion rate of nursing care at therapeutic hypothermia. Methods: We took five measures: (1) Amendment of nursing standards of therapeutic hypothermia; (2) Amendment of TH checklist items to nursing records; (3) Establishment of monitor procedure; (4) Design each period of TH care reminder cards; (5) Providing in-service training sections of TH for ICU nursing staff. Outcomes: The completion rate of nursing care at therapeutic hypothermia increased from 78.1% to 89.3%. Conclusion: The project team not only increased the completion rate but also improved patient safety and quality of care.

Keywords: therapeutic hypothermia, nursing, critical care, quality of care

Procedia PDF Downloads 403