Search results for: joint mediation learning
2798 Mini-Open Repair Using Ring Forceps Show Similar Results to Repair Using Achillon Device in Acute Achilles Tendon Rupture
Authors: Chul Hyun Park
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Background:Repair using the Achillon deviceis a representative mini-open repair technique;however, the limitations of this technique includethe need for special instruments and decreasedrepair strength.A modifiedmini-open repair using ring forcepsmight overcome these limitations. Purpose:This study was performed to compare the Achillon device with ring forceps in mini-open repairsof acute Achilles tendon rupture. Study Design:This was a retrospective cohort study, and the level of evidence was3. Methods:Fifty patients (41 men and 9 women), withacute Achilles tendon rupture on one foot, were consecutively treated using mini-open repair techniques. The first 20 patients were treated using the Achillon device (Achillon group) and the subsequent 30 patients were treated using a ring forceps (Forcep group). Clinical, functional, and isokinetic results,and postoperative complications were compared between the two groups at the last follow-up. Clinical evaluations wereperformed using the American Orthopedic Foot and Ankle Society (AOFAS) score, Achilles tendon Total Rupture Score (ATRS), length of incision, and operation time. Functional evaluationsincludedactive range of motion (ROM) of the ankle joint, maximum calf circumference (MCC), hopping test, and single limb heel-rise (SLHR) test. Isokinetic evaluations were performed using the isokinetic test for ankle plantar flexion. Results:The AOFAS score (p=0.669), ATRS (p=0.753), and length of incision (p=0.305) were not significantly different between the groups. Operative times in the Achillon group were significantly shorter than that in the Forcep group (p<0.001).The maximum height of SLHR (p=0.023) and number of SLHRs (p=0.045) in the Forcep group were significantly greater than that in the Achillon group. No significant differences in the mean peak torques for plantar flexion at angular speeds of 30°/s (p=0.219) and 120°/s (p=0.656) were detected between the groups. There was no significant difference in the occurrence of postoperative complications between the groups (p=0.093). Conclusion:The ring forceps technique is comparable with the Achillon technique with respect to clinical, functional, and isokinetic results and the postoperative complications. Given that no special instrument is required, the ring forceps technique could be a better option for acute Achilles tendon rupture repair.Keywords: achilles tendon, acute rupture, repair, mini-open
Procedia PDF Downloads 892797 Quasi-Photon Monte Carlo on Radiative Heat Transfer: An Importance Sampling and Learning Approach
Authors: Utkarsh A. Mishra, Ankit Bansal
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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks
Procedia PDF Downloads 2282796 A Challenge of the 3ʳᵈ Millenium: The Emotional Intelligence Development
Authors: Florentina Hahaianu, Mihaela Negrescu
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The analysis of the positive and negative effects of technology use and abuse in Generation Z comes as a necessity in order to understand their ever-changing emotional development needs. The article quantitatively analyzes the findings of a sociological questionnaire on a group of students in social sciences. It aimed to identify the changes generated by the use of digital resources in the emotional intelligence development. Among the outcomes of our study we include a predilection for IT related activities – be they social, learning, entertainment, etc. which undermines the manifestation of emotional intelligence, especially the reluctance to face-to-face interaction. In this context, the issue of emotional intelligence development comes into focus as a solution to compensate for the undesirable effects that contact with technology has on this generation.Keywords: digital resources, emotional intelligence, generation Z, students
Procedia PDF Downloads 2152795 Depth Estimation in DNN Using Stereo Thermal Image Pairs
Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge
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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation
Procedia PDF Downloads 2852794 The Impact of Critical Thinking on Educational Management for the Professional Development of English Language Teachers
Authors: Simin Baneshi
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Critical thinking, as one of the essential skills of the 21st century, plays a fundamental role in improving teaching and learning processes. In the field of educational management, strengthening this skill among teachers can contribute to designing more effective educational programs, enhancing teaching quality, and improving learning outcomes. English language teachers, by utilizing critical thinking, can analyze educational challenges and find innovative solutions for them. The aim of this research is to examine the role of critical thinking in educational management and its impact on the professional development of English language teachers. Additionally, identifying optimal methods to enhance this skill among teachers and educational managers is another objective of this study. This research was conducted using a mixed-methods approach with a sample population of 200 teachers and 20 educational managers from schools and English language teaching institutions across three provinces in Iran. Sampling was carried out through stratified random sampling for teachers and purposive sampling for managers. In the quantitative section, a standardized critical thinking questionnaire with 30 closed-ended questions and a Likert scale was employed, and the data were analyzed using independent t-tests, multivariate analysis of variance (MANOVA), and regression analysis. In the qualitative section, semi-structured interviews were conducted with 15 managers and 10 experienced teachers. Qualitative data were analyzed using thematic analysis. The validity of the instruments was confirmed by five experts in the field of education, and the reliability of the questionnaire was evaluated with a Cronbach’s alpha coefficient of 0.89. The findings revealed that teachers with high critical thinking skills are more successful in designing innovative educational programs, managing classrooms, and solving educational issues. Additionally, managers who adopt critical management approaches create a more dynamic educational environment for fostering these skills. Regular training programs and critical thinking workshops had a positive impact on the professional development of teachers. Critical thinking is a key element in educational management and the professional development of English language teachers. Providing targeted educational opportunities, specialized workshops, and constructive feedback can strengthen this skill among teachers and lead to improved teaching quality. The results of this study can assist educational policymakers in designing professional development programs for teachers and serve as a model for other educational domains.Keywords: critical thinking, educational management, professional development, teachers
Procedia PDF Downloads 72793 Neurocognitive and Executive Function in Cocaine Addicted Females
Authors: Gwendolyn Royal-Smith
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Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function
Procedia PDF Downloads 4042792 Artificial Intelligence for All: Artificial Intelligence Education for K-12
Authors: Yiqiao Yin
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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.Keywords: K12 education, AI4ALL, pre-college education, pre-college AI
Procedia PDF Downloads 1372791 Understand and Redefine Lean Product Development
Authors: Alemu Moges Belay, Torgeir Welo, Jan Ola Strandhagen
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Lean has long been linked with manufacturing, but its application claimed also by other functions such as product development and services. However, there is a challenge on understanding and defining lean in each function context. This paper aims to investigate the literature that focus mainly on PD process improvement, obtain better understanding and redefine LPD in systematic way. In addition to that, the paper attempts to summarize various proposed transformation strategies, definitions, identifying features of manufacturing and product development that would help to redefining lean in product development context. Finally we redefine LPD in organized way that encompasses different steps such as stage gate, communication and information, events, learning, innovation, knowledge and value creation.Keywords: lean, lean manufacturing, lean product development, transformation, strategies
Procedia PDF Downloads 4782790 The Analysis of Movement Pattern during Reach and Grasp in Stroke Patients: A Kinematic Approach
Authors: Hyo Seon Choi, Ju Sun Kim, DY Kim
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Introduction: This study was aimed to evaluate temporo-spatial patterns during the reach and grasp task in hemiplegic stroke patients and to identify movement pattern according to severity of motor impairment. Method: 29 subacute post-stroke patients were enrolled in this study. The temporo-spatial and kinematic data were obtained during reach and grasp task through 3D motion analysis (VICON). The reach and grasp task was composed of four sub-tasks: reach (T1), transport to mouth (T2), transport back to table (T3) and return (T4). The movement time, joint angle and sum of deviation angles from normative data were compared between affected side and unaffected side. They were also compared between two groups (mild to moderate group: 28~66, severe group: 0~27) divided by upper-Fugl-Meyer Assessment (FMA) scale. Result: In affected side, total time and durations of all four tasks were significantly longer than those in unaffected side (p < 0.001). The affected side demonstrated significant larger shoulder abduction, shoulder internal rotation, wrist flexion, wrist pronation, thoracic external rotation and smaller shoulder flexion during reach and grasp task (p < 0.05). The significant differences between mild to moderate group and severe group were observed in total duration, durations of T1, T2, and T3 in reach and grasp task (p < 0.01). The severe group showed significant larger shoulder internal rotation during T2 (p < 0.05) and wrist flexion during T2, T3 (p < 0.05) than mild to moderate group. In range of motion during each task, shoulder abduction-adduction during T2 and T3, shoulder internal-external rotation during T2, elbow flexion-extension during T1 showed significant difference between two groups (p < 0.05). The severe group had significant larger total deviation angles in shoulder internal-external rotation and wrist extension-flexion during reach and grasp task (p < 0.05). Conclusion: This study suggests that post-stroke hemiplegic patients have an unique temporo-spatial and kinematic patterns during reach and grasp task, and the movement pattern may be related to affected upper limb severity. These results may be useful to interpret the motion of upper extremity in stroke patients.Keywords: Fugl-Meyer Assessment (FMA), motion analysis, reach and grasp, stroke
Procedia PDF Downloads 2422789 Intensive Neurophysiological Rehabilitation System: New Approach for Treatment of Children with Autism
Authors: V. I. Kozyavkin, L. F. Shestopalova, T. B. Voloshyn
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Introduction: Rehabilitation of children with Autism is the issue of the day in psychiatry and neurology. It is attributed to constantly increasing quantity of autistic children - Autistic Spectrum Disorders (ASD) Existing rehabilitation approaches in treatment of children with Autism improve their medico- social and social- psychological adjustment. Experience of treatment for different kinds of Autistic disorders in International Clinic of Rehabilitation (ICR) reveals the necessity of complex intensive approach for healing this malady and wider implementation of a Kozyavkin method for treatment of children with ASD. Methods: 19 children aged from 3 to 14 years were examined. They were diagnosed ‘Autism’ (F84.0) with comorbid neurological pathology (from pyramidal insufficiency to para- and tetraplegia). All patients underwent rehabilitation in ICR during two weeks, where INRS approach was used. INRS included methods like biomechanical correction of the spine, massage, physical therapy, joint mobilization, wax-paraffin applications. They were supplemented by art- therapy, ergotherapy, rhythmical group exercises, computer game therapy, team Olympic games and other methods for improvement of motivation and social integration of the child. Estimation of efficacy was conducted using parent’s questioning and done twice- on the onset of INRS rehabilitation course and two weeks afterward. For efficacy assessment of rehabilitation of autistic children in ICR standardized tool was used, namely Autism Treatment Evaluation Checklist (ATEC). This scale was selected because any rehabilitation approaches for the child with Autism can be assessed using it. Results: Before the onset of INRS treatment mean score according to ATEC scale was 64,75±9,23, it reveals occurrence in examined children severe communication, speech, socialization and behavioral impairments. After the end of the rehabilitation course, the mean score was 56,5±6,7, what indicates positive dynamics in comparison to the onset of rehabilitation. Generally, improvement of psychoemotional state occurred in 90% of cases. Most significant changes occurred in the scope of speech (16,5 before and 14,5 after the treatment), socialization (15.1 before and 12,5 after) and behavior (20,1 before and 17.4 after). Conclusion: As a result of INRS rehabilitation course reduction of autistic symptoms was noted. Particularly improvements in speech were observed (children began to spell out new syllables, words), there was some decrease in signs of destructiveness, quality of contact with the surrounding people improved, new skills of self-service appeared. The prospect of the study is further, according to evidence- based medicine standards, deeper examination of INRS and assessment of its usefulness in treatment for Autism and ASD.Keywords: intensive neurophysiological rehabilitation system (INRS), international clinic od rehabilitation, ASD, rehabilitation
Procedia PDF Downloads 1722788 Supports for Student Learning Program: Exploring the Educational Terrain of Newcomer and Refugee Students in Canada
Authors: Edward Shizha, Edward Makwarimba
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This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness
Procedia PDF Downloads 702787 Challenges of School Leadership
Authors: Stefan Ninković
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The main purpose of this paper is to examine the different theoretical approaches and relevant empirical evidence and thus, recognize some of the most pressing challenges faced by school leaders. This paper starts from the fact that the new mission of the school is characterized by the need for stronger coordination among students' academic, social and emotional learning. In this sense, school leaders need to focus their commitment, vision and leadership on the issues of students' attitudes, language, cultural and social background, and sexual orientation. More specifically, they should know what a good teaching is for student’s at-risk, students whose first language is not dominant in school, those who’s learning styles are not in accordance with usual teaching styles, or who are stigmatized. There is a rather wide consensus around the fact that the traditionally popular concept of instructional leadership of the school principal is no longer sufficient. However, in a number of "pro-leadership" circles, including certain groups of academic researchers, consultants and practitioners, there is an established tendency of attributing school principal an extraordinary influence towards school achievements. On the other hand, the situation in which all employees in the school are leaders is a utopia par excellence. Although leadership obviously can be efficiently distributed across the school, there are few findings that speak about sources of this distribution and factors making it sustainable. Another idea that is not particularly new, but has only recently gained in importance is related to the fact that the collective capacity of the school is an important resource that often remains under-cultivated. To understand the nature and power of collaborative school cultures, it is necessary to know that these operate in a way that they make their all collective members' tacit knowledge explicit. In this sense, the question is how leaders in schools can shape collaborative culture and create social capital in the school. Pressure exerted on schools to systematically collect and use the data has been accompanied by the need for school leaders to develop new competencies. The role of school leaders is critical in the process of assessing what data are needed and for what purpose. Different types of data are important: test results, data on student’s absenteeism, satisfaction with school, teacher motivation, etc. One of the most important tasks of school leaders are data-driven decision making as well as ensuring transparency of the decision-making process. Finally, the question arises whether the existing models of school leadership are compatible with the current social and economic trends. It is necessary to examine whether and under what conditions schools are in need for forms of leadership that are different from those that currently prevail. Closely related to this issue is also to analyze the adequacy of different approaches to leadership development in the school.Keywords: educational changes, leaders, leadership, school
Procedia PDF Downloads 3392786 The Use of Artificial Intelligence to Identify Ore-Prospective Territories in East Kazakhstan
Authors: O. D. Gavrilenko, N. M Temirbekov, Z. A. Mustafina
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This article discusses the possibility of using machine learning algorithms to analyze and synthesize historical geological data with mathematical geophysics and geochemistry data, as well as Earth remote sensing (ERS) results. Creating geoinformation systems for such Big Data with their subsequent processing using artificial intelligence methods provides unique opportunities for more accurate minerogenic zoning of territories, which significantly increases the efficiency of geological exploration. This will improve the accuracy of geological exploration and forecast zones with potential mineral resources.Keywords: methods of remote sensing of the earth, geographic information systems, artificial intelligence, geological geophysical geochemical and minerogenic data, minerogenic model
Procedia PDF Downloads 52785 Application of Vector Representation for Revealing the Richness of Meaning of Facial Expressions
Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan
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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec
Procedia PDF Downloads 1812784 Music Listening in Dementia: Current Developments and the Potential for Automated Systems in the Home: Scoping Review and Discussion
Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda
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Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.Keywords: music listening, dementia, agitation, scoping review, technology
Procedia PDF Downloads 1182783 An Analytical Review of Tourism Management in India with Special Reference to Maharashtra State
Authors: Anilkumar L. Rathod
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This paper examines event tourism as a field of study and area of professional practice updating the previous review article published in 2015. In this substantially extended review, a deeper analysis of the field's evolution and development is presented, charting the growth of the literature, focusing both chronologically and thematically. A framework for understanding and creating knowledge about events and tourism is presented, forming the basis which signposts established research themes and concepts and outlines future directions for research. In addition, the review article focuses on constraining and propelling forces, ontological advances, contributions from key journals, and emerging themes and issues. It also presents a roadmap for research activity in event tourism. Published scholarly studies within this period are examined through content analysis, using such keywords as knowledge management, organizational learning, hospitality, tourism, tourist destinations, travel industry, hotels, lodging, motels, hotel industry, gaming, casino hotel and convention to search scholarly research journals. All contributions found are then screened for a hospitality and tourism theme. Researchers mostly discuss knowledge management approach in improving information technology, marketing and strategic planning in order to gain competitive advantage. Overall, knowledge management research is still limited. Planned events in tourism are created for a purpose, and what was once the realm of individual and community initiatives has largely become the realm of professionals and entrepreneurs provides a typology of the four main categories of planned events within an event-tourism context, including the main venues associated with each. It also assesses whether differences exist between socio-demographic groupings. An analysis using primarily descriptive statistics indicated both sub-samples had similar viewpoints although Maharashtra residents tended to have higher scores pertaining to the consequences of gambling. It is suggested that the differences arise due to the greater exposure of Maharashtra residents to the influences of casino development.Keywords: organizational learning, hospitality, tourism, tourist destinations, travel industry, hotels, lodging, motels, hotel industry, gaming, casino hotel and convention to search scholarly research journals
Procedia PDF Downloads 2412782 HTML5 Online Learning Application with Offline Web, Location Based, Animated Web, Multithread, and Real-Time Features
Authors: Sheetal R. Jadhwani, Daisy Sang, Chang-Shyh Peng
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Web applications are an integral part of modem life. They are mostly based upon the HyperText Markup Language (HTML). While HTML meets the basic needs, there are some shortcomings. For example, applications can cease to work once user goes offline, real-time updates may be lagging, and user interface can freeze on computationally intensive tasks. The latest language specification HTML5 attempts to rectify the situation with new tools and protocols. This paper studies the new Web Storage, Geolocation, Web Worker, Canvas, and Web Socket APIs, and presents applications to test their features and efficiencies.Keywords: HTML5, web worker, canvas, web socket
Procedia PDF Downloads 3092781 Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection
Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi
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In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection
Procedia PDF Downloads 2362780 “Japan’s New Security Outlook: Implications for the US-Japan Alliance”
Authors: Agustin Maciel-Padilla
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This paper explores the most significant change to Japan’s security strategy since the end of World War II, in particular Prime Minister Fumio Kishida’s government publication, in late 2022, of 3 policy documents (the National Security Strategy [NSS], the National Defense Strategy and the Defense Buildup Program) that basically propose to expand the country’s military capabilities and to increase military spending over a 5-year period. These policies represent a remarkable transformation of Japan’s defense-oriented policy followed since 1946. These proposals have been under analysis and debate since they were announced, as it was also Japan’s historic ambition to strengthening its deterrence capabilities in the context of a more complex regional security environment. Even though this new defense posture has attracted significant international attention, it is far from representing a done deal because of the fact that there is still a long way to go to implement this vision because of a wide variety of political and economic issues. Japan is currently experiencing the most dangerous security environment since the end of World War II, and this situation led Japan to intensify its dialogue with the United States to reflect a re-evaluation of deterrence in the face of a rapidly worsening security environment, a changing balance of power in East Asia, and the arrival of a new era of “great power competition”. Japan’s new documents, for instance, identify China and North Korea’s as posing, respectively, a strategic challenge and an imminent threat. Japan has also noted that Russia’s invasion of Ukraine has contributed to erode the foundation of the international order. It is considered that Russia’s aggression was possible because Ukraine’s defense capability was not enough for effective deterrence. Moreover, Japan’s call for “counterstrike capabilities” results from a recognition that China and North Korea’s ballistic and cruise missiles could overwhelm Japan’s air and missile defense systems, and therefore there is an urgent need to strengthen deterrence and resilience. In this context, this paper will focus on the impact of these changes on the US-Japan alliance. Adapting this alliance to Tokyo’s new ambitions and capabilities could be critical in terms of updating their traditional protection/access to bases arrangement, interoperability and joint command and control issues, as well as regarding the security–economy nexus. While China is Japan’s largest trading partner, and trade between the two has been growing, US-Japan economic relationship has been slower, notwithstanding the fact that US-Japan security cooperation has strengthened significantly in recent years.Keywords: us-japan alliance, japan security, great power competition, interoperability
Procedia PDF Downloads 682779 Creativity and Innovation in Postgraduate Supervision
Authors: Rajendra Chetty
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The paper aims to address two aspects of postgraduate studies: interdisciplinary research and creative models of supervision. Interdisciplinary research can be viewed as a key imperative to solve complex problems. While excellent research requires a context of disciplinary strength, the cutting edge is often found at the intersection between disciplines. Interdisciplinary research foregrounds a team approach and information, methodologies, designs, and theories from different disciplines are integrated to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline. Our aim should also be to generate research that transcends the original disciplines i.e. transdisciplinary research. Complexity is characteristic of the knowledge economy, hence, postgraduate research and engaged scholarship should be viewed by universities as primary vehicles through which knowledge can be generated to have a meaningful impact on society. There are far too many ‘ordinary’ studies that fall into the realm of credentialism and certification as opposed to significant studies that generate new knowledge and provide a trajectory for further academic discourse. Secondly, the paper will look at models of supervision that are different to the dominant ‘apprentice’ or individual approach. A reflective practitioner approach would be used to discuss a range of supervision models that resonate well with the principles of interdisciplinarity, growth in the postgraduate sector and a commitment to engaged scholarship. The global demand for postgraduate education has resulted in increased intake and new demands to limited supervision capacity at institutions. Team supervision lodged within large-scale research projects, working with a cohort of students within a research theme, the journal article route of doctoral studies and the professional PhD are some of the models that provide an alternative to the traditional approach. International cooperation should be encouraged in the production of high-impact research and institutions should be committed to stimulating international linkages which would result in co-supervision and mobility of postgraduate students and global significance of postgraduate research. International linkages are also valuable in increasing the capacity for supervision at new and developing universities. Innovative co-supervision and joint-degree options with global partners should be explored within strategic planning for innovative postgraduate programmes. Co-supervision of PhD students is probably the strongest driver (besides funding) for collaborative research as it provides the glue of shared interest, advantage and commitment between supervisors. The students’ field serves and informs the co-supervisors own research agendas and helps to shape over-arching research themes through shared research findings.Keywords: interdisciplinarity, internationalisation, postgraduate, supervision
Procedia PDF Downloads 2422778 Integrating a Six Thinking Hats Approach Into the Prewriting Stage of Argumentative Writing In English as a Foreign Language: A Chinese Case Study of Generating Ideas in Action
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Argumentative writing is the most prevalent genre in diverse writing tests. How to construct academic arguments is often regarded as a difficult task by most English as a foreign language (EFL) learners. A failure to generate enough ideas and organise them coherently and logically as well as a lack of competence in supporting their arguments with relevant evidence are frequent problems faced by EFL learners when approaching an English argumentative writing task. Overall, these problems are closely related to planning, and planning an argumentative writing at pre-writing stage plays a vital role in a good academic essay. However, how teachers can effectively guide students to generate ideas is rarely discussed in planning English argumentative writing, apart from brainstorming. Brainstorming has been a common practice used by teachers to help students generate ideas. However, some limitations of brainstorming suggest that it can help students generate many ideas, but ideas might not necessarily be coherent and logic, and could sometimes impede production. It calls for a need to explore effective instructional strategies at pre-writing stage of English argumentative writing. This paper will first examine how a Six Thinking Hats approach can be used to provide a dialogic space for EFL learners to experience and collaboratively generate ideas from multiple perspectives at pre-writing stage. Part of the findings of the impact of a twelve-week intervention (from March to July 2021) on students learning to generate ideas through engaging in group discussions of using Six Thinking Hats will then be reported. The research design is based on the sociocultural theory. The findings present evidence from a mixed-methods approach and fifty-nine participants from two first-year undergraduate natural classes in a Chinese university. Analysis of pre- and post- questionnaires suggests that participants had a positive attitude toward the Six Thinking Hats approach. It fosters their understanding of prewriting and argumentative writing, helps them to generate more ideas not only from multiple perspectives but also in a systematic way. A comparison of participants writing plans confirms an improvement in generating counterarguments and rebuttals to support their arguments. Above all, visual and transcripts data of group discussion collected from different weeks throughout the intervention enable teachers and researchers to ‘see’ the hidden process of learning to generate ideas in action.Keywords: argumentative writing, innovative pedagogy, six thinking hats, dialogic space, prewriting, higher education
Procedia PDF Downloads 922777 Proposed Anticipating Learning Classifier System for Cloud Intrusion Detection (ALCS-CID)
Authors: Wafa' Slaibi Alsharafat
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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection
Procedia PDF Downloads 4762776 People Management, Knowledge Sharing and Intermediary Variables
Authors: Nizar Mansour, Chiha Gaha, Emna Gara
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The present research investigates the relationship among HRM practices, knowledge sharing behavior and a certain number of intermediary variables in the context of Tunisian knowledge-intensive firms. Results suggest that five HR practices influence either directly or indirectly the knowledge sharing behavior through enhancing the value of human capital and fostering a learning-oriented organizational climate. Results have strong theoretical implications for both the fields of knowledge management and strategic human resource management. Managerial implications are also derived.Keywords: human capital, knowledge intensive firms, knowledge sharing, organizational climate, Tunisia
Procedia PDF Downloads 3382775 A Case Study on Experiences of Clinical Preceptors in the Undergraduate Nursing Program
Authors: Jacqueline M. Dias, Amina A Khowaja
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Clinical education is one of the most important components of a nursing curriculum as it develops the students’ cognitive, psychomotor and affective skills. Clinical teaching ensures the integration of knowledge into practice. As the numbers of students increase in the field of nursing coupled with the faculty shortage, clinical preceptors are the best choice to ensure student learning in the clinical settings. The clinical preceptor role has been introduced in the undergraduate nursing programme. In Pakistan, this role emerged due to a faculty shortage. Initially, two clinical preceptors were hired. This study will explore clinical preceptors views and experiences of precepting Bachelor of Science in Nursing (BScN) students in an undergraduate program. A case study design was used. As case studies explore a single unit of study such as a person or very small number of subjects; the two clinical preceptors were fundamental to the study and served as a single case. Qualitative data were obtained through an iterative process using in depth interviews and written accounts from reflective journals that were kept by the clinical preceptors. The findings revealed that the clinical preceptors were dedicated to their roles and responsibilities. Another, key finding was that clinical preceptors’ prior knowledge and clinical experience were valuable assets to perform their role effectively. The clinical preceptors found their new role innovative and challenging; it was stressful at the same time. Findings also revealed that in the clinical agencies there were unclear expectations and role ambiguity. Furthermore, clinical preceptors had difficulty integrating theory into practice in the clinical area and they had difficulty in giving feedback to the students. Although this study is localized to one university, generalizations can be drawn from the results. The key findings indicate that the role of a clinical preceptor is demanding and stressful. Clinical preceptors need preparation prior to precepting students on clinicals. Also, institutional support is fundamental for their acceptance. This paper focuses on the views and experiences of clinical preceptors undertaking a newly established role and resonates with the literature. The following recommendations are drawn to strengthen the role of the clinical preceptors: A structured program for clinical preceptors is needed along with mentorship. Clinical preceptors should be provided with formal training in teaching and learning with emphasis on clinical teaching and giving feedback to students. Additionally, for improving integration of theory into practice, clinical modules should be provided ahead of the clinical. In spite of all the challenges, ten more clinical preceptors have been hired as the faculty shortage continues to persist.Keywords: baccalaureate nursing education, clinical education, clinical preceptors, nursing curriculum
Procedia PDF Downloads 1792774 High Resolution Satellite Imagery and Lidar Data for Object-Based Tree Species Classification in Quebec, Canada
Authors: Bilel Chalghaf, Mathieu Varin
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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR
Procedia PDF Downloads 1392773 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis
Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante
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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.Keywords: dynamic analysis, long short-term memory, prediction, sepsis
Procedia PDF Downloads 1292772 Building Exoskeletons for Seismic Retrofitting
Authors: Giuliana Scuderi, Patrick Teuffel
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The proven vulnerability of the existing social housing building heritage to natural or induced earthquakes requires the development of new design concepts and conceptual method to preserve materials and object, at the same time providing new performances. An integrate intervention between civil engineering, building physics and architecture can convert the social housing districts from a critical part of the city to a strategic resource of revitalization. Referring to bio-mimicry principles the present research proposes a taxonomy with the exoskeleton of the insect, an external, light and resistant armour whose role is to protect the internal organs from external potentially dangerous inputs. In the same way, a “building exoskeleton”, acting from the outside of the building as an enclosing cage, can restore, protect and support the existing building, assuming a complex set of roles, from the structural to the thermal, from the aesthetical to the functional. This study evaluates the structural efficiency of shape memory alloys devices (SMADs) connecting the “building exoskeleton” with the existing structure to rehabilitate, in order to prevent the out-of-plane collapse of walls and for the passive dissipation of the seismic energy, with a calibrated operability in relation to the intensity of the horizontal loads. The two case studies of a masonry structure and of a masonry structure with concrete frame are considered, and for each case, a theoretical social housing building is exposed to earthquake forces, to evaluate its structural response with or without SMADs. The two typologies are modelled with the finite element program SAP2000, and they are respectively defined through a “frame model” and a “diagonal strut model”. In the same software two types of SMADs, called the 00-10 SMAD and the 05-10 SMAD are defined, and non-linear static and dynamic analyses, namely push over analysis and time history analysis, are performed to evaluate the seismic response of the building. The effectiveness of the devices in limiting the control joint displacements resulted higher in one direction, leading to the consideration of a possible calibrated use of the devices in the different walls of the building. The results show also a higher efficiency of the 00-10 SMADs in controlling the interstory drift, but at the same time the necessity to improve the hysteretic behaviour, to maximise the passive dissipation of the seismic energy.Keywords: adaptive structure, biomimetic design, building exoskeleton, social housing, structural envelope, structural retrofitting
Procedia PDF Downloads 4272771 Makhraj Recognition Using Convolutional Neural Network
Authors: Zan Azma Nasruddin, Irwan Mazlin, Nor Aziah Daud, Fauziah Redzuan, Fariza Hanis Abdul Razak
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This paper focuses on a machine learning that learn the correct pronunciation of Makhraj Huroofs. Usually, people need to find an expert to pronounce the Huroof accurately. In this study, the researchers have developed a system that is able to learn the selected Huroofs which are ha, tsa, zho, and dza using the Convolutional Neural Network. The researchers present the chosen type of the CNN architecture to make the system that is able to learn the data (Huroofs) as quick as possible and produces high accuracy during the prediction. The researchers have experimented the system to measure the accuracy and the cross entropy in the training process.Keywords: convolutional neural network, Makhraj recognition, speech recognition, signal processing, tensorflow
Procedia PDF Downloads 3402770 CDIO-Based Teaching Reform for Software Project Management Course
Authors: Liping Li, Wenan Tan, Na Wang
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With the rapid development of information technology, project management has gained more and more attention recently. Based on CDIO, this paper proposes some teaching reform ideas for software project management curriculum. We first change from Teacher-centered classroom to Student-centered and adopt project-driven, scenario animation show, teaching rhythms, case study and team work practice to improve students' learning enthusiasm. Results showed these attempts have been well received and very effective; as well, students prefer to learn with this curriculum more than before the reform.Keywords: CDIO, teaching reform, engineering education, project-driven, scenario animation simulation
Procedia PDF Downloads 4332769 Approaches to Implementing and Financing Primary Health Care in Kenya
Authors: Helen Owino, Sharifa Hussein
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Background: Kenya has made significant strides in improving access to PHC services. However, challenges relating to equitable distribution of services, resource allocation, and financial sustainability must be addressed. Targeted policy interventions strengthened collaboration between public and private sectors, and innovative financing mechanisms are needed to bridge existing gaps and enhance the delivery of PHC services. A holistic and collaborative approach is essential to ensure PHC remains accessible, affordable, and of high quality for all its citizens. By addressing the identified issues and building on the existing strengths, Kenya can move towards a more resilient and inclusive health system. Study objectives: Inform scale-up of promising primary health care (PHC) approaches/models, Inform the development of PHC advocacy materials, and Contribute to country, regional, and global discourse on PHC financing. The methodology involved conducting a desk review of background literature and statistics on the current state of PHC and key informant interviews guided by a questionnaire based on the pillars or building blocks of Health Systems Strengthening (HSS). Summary of Key Findings: Strong support from leadership is key for the successful implementation of Primary Care Networks (PCNs), as seen in Kisumu and Nakuru, where County Health Management Teams (CHMTs) showed commitment to the success of PCNs even without partner support. Using already existing governance and human resources for health (HRH) mechanisms to implement PCNs is useful, especially where there are resource constraints and improve performance: An appointed PHC focal person/office is key to ensuring the planning and implementation of PCNs, e.g., Kisumu, Nakuru, and Garissa. Embracing joint planning and distribution of resources within PHC leads to more efficient use of resources coordination outcomes, for example, in Kisumu and Garissa. Subsequent prioritization and county funding have led to successful PCN implementation in Nakuru and Kisumu. Partner funding in Garissa has facilitated PCN functionality in Garissa and Nakuru. Intersectoral collaboration and public participation in the health sector lead to greater utilization of PHC services, e.g., in Kisumu, working with other ministries to improve infrastructure like road networks to facilities has improved access to PHC facilities.Keywords: PHC policy and programming, innovations and adaptations, scale up, UHC
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