Search results for: learning outcomes framework

Authors: Suhani Srivastava

Abstract:

This research delves into the classification of orbital debris through machine learning (ML): it will categorize the intensity of the threat orbital debris poses through multiple ML models to gain an insight into effectively estimating the danger specific orbital debris can pose to future space missions. As the space industry expands, orbital debris becomes a growing concern in Low Earth Orbit (LEO) because it can potentially obfuscate space missions due to the increased orbital debris pollution. Moreover, detecting orbital debris and identifying its characteristics has become a major concern in Space Situational Awareness (SSA), and prior methods of solely utilizing physics can become inconvenient in the face of the growing issue. Thus, this research focuses on approaching orbital debris concerns through machine learning, an efficient and more convenient alternative, in detecting the potential threat certain orbital debris pose. Our findings found that the Logistic regression machine worked the best with a 98% accuracy and this research has provided insight into the accuracies of specific machine learning models when classifying orbital debris. Our work would help provide space shuttle manufacturers with guidelines about mitigating risks, and it would help in providing Aerospace Engineers facilities to identify the kinds of protection that should be incorporated into objects traveling in the LEO through the predictions our models provide.

Keywords: aerospace, orbital debris, machine learning, space, space situational awareness, nasa

Procedia PDF Downloads 23

Authors: Catherine Omole

Abstract:

Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.

Keywords: assessment, examination malpractice, learning, science classroom

Procedia PDF Downloads 260

Authors: Anne-Loes K. Warps, Rob A. E. M. Tollenaar, Pieter J. Tanis, Jan Willem T. Dekker

Abstract:

Anastomotic leakage after colorectal cancer surgery remains a severe complication. Early diagnosis and treatment are essential to prevent further adverse outcomes. In the literature, it has been suggested that earlier reintervention is associated with better survival, but anastomotic leakage can occur with a highly variable time interval to index surgery. This study aims to evaluate the time-interval between rectal cancer resection with primary anastomosis creation and reoperation, in relation to short-term outcomes, stratified for the use of a defunctioning stoma. Methods: Data of all primary rectal cancer patients that underwent elective resection with primary anastomosis during 2013-2019 were extracted from the Dutch ColoRectal Audit. Analyses were stratified for defunctioning stoma. Anastomotic leakage was defined as a defect of the intestinal wall or abscess at the site of the colorectal anastomosis for which a reintervention was required within 30 days. Primary outcomes were new stoma construction, mortality, ICU admission, prolonged hospital stay and readmission. The association between time to reoperation and outcome was evaluated in three ways: Per 2 days, before versus on or after postoperative day 5 and during primary versus readmission. Results: In total 10,772 rectal cancer patients underwent resection with primary anastomosis. A defunctioning stoma was made in 46.6% of patients. These patients had a lower anastomotic leakage rate (8.2% vs. 11.6%, p < 0.001) and less often underwent a reoperation (45.3% vs. 88.7%, p < 0.001). Early reoperations (< 5 days) had the highest complication and mortality rate. Thereafter the distribution of adverse outcomes was more spread over the 30-day postoperative period for patients with a defunctioning stoma. Median time-interval from primary resection to reoperation for defunctioning stoma patients was 7 days (IQR 4-14) versus 5 days (IQR 3-13 days) for no-defunctioning stoma patients. The mortality rate after primary resection and reoperation were comparable (resp. for defunctioning vs. no-defunctioning stoma 1.0% vs. 0.7%, P=0.106 and 5.0% vs. 2.3%, P=0.107). Conclusion: This study demonstrated that early reinterventions after anastomotic leakage are associated with worse outcomes (i.e. mortality). Maybe the combination of a physiological dip in the cellular immune response and release of cytokines following surgery, as well as a release of endotoxins caused by the bacteremia originating from the leakage, leads to a more profound sepsis. Another explanation might be that early leaks are not contained to the pelvis, leading to a more profound sepsis requiring early reoperations. Leakage with or without defunctioning stoma resulted in a different type of reinterventions and time-interval between surgery and reoperation.

Keywords: rectal cancer surgery, defunctioning stoma, anastomotic leakage, time-interval to reoperation

Procedia PDF Downloads 138

Authors: Maria Janet, Anita David, P. Vijayasamundeeswarimaria

Abstract:

Introduction: The main purpose of this study is to compare the effectiveness of web-based and blended learning on Paediatric Basic Life Support on competency among undergraduate nursing students in selected nursing colleges in Chennai. Materials and methods: A descriptive pre-test and post-test study design were used for this study. Samples of 100 Fourth year B.Sc., nursing students at Sri Ramachandra Faculty of Nursing SRIHER, Chennai, 100 Fourth year B.Sc., nursing students at Apollo College of Nursing, Chennai, were selected by purposive sampling technique. The instrument used for data collection was Knowledge Questionnaire on Paediatric Basic Life Support (PBLS). It consists of 29 questions on the general expansion of Basic Life Support and Cardiopulmonary Resuscitation, Prerequisites of Basic Life Support, and Knowledge on Paediatric Basic Life Support in which each question has four multiple choices answers, each right answer carrying one mark and no negative scoring. This questionnaire was formed with reference to AHA 2020 (American Heart Association) revised guidelines. Results: After the post-test, in the web-based learning group, 58.8% of the students had an inadequate level of objective performance score, while 41.1% of them had an adequate level of objective performance score. In the blended learning group, 26.5% of the students had an inadequate level of an objective performance score, and 73.4% of the students had an adequate level of an objective performance score. There was an association between the post-test level of knowledge and the demographic variables of undergraduate nursing students undergoing blended learning. The age was significant at a p-value of 0.01, and the performance of BLS before was significant at a p-value of 0.05. The results show that there was a significant positive correlation between knowledge and objective performance score of undergraduate nursing students undergoing web-based learning on paediatric basic life support.

Keywords: basic life support, paediatric basic life support, web-based learning, blended learning

Procedia PDF Downloads 69

Authors: Szymon Rutkowski, Tomasz Korbak

Abstract:

We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

Procedia PDF Downloads 128

Authors: Prathik Ranka, Sridhar K, Vasanth Daniel, Mithun Shankar

Abstract:

With growing global food needs and climate uncertainties, informed crop choices are critical for increasing agricultural productivity. Here we propose a machine learning-based crop recommendation system to help farmers in choosing the most proper crops according to their geographical regions and soil properties. We can deploy algorithms like Decision Trees, Random Forests and Support Vector Machines on a broad dataset that consists of climatic factors, soil characteristics and historical crop yields to predict the best choice of crops. The approach includes first preprocessing the data after assessing them for missing values, unlike in previous jobs where we used all the available information and then transformed because there was no way such a model could have worked with missing data, and normalizing as throughput that will be done over a network to get best results out of our machine learning division. The model effectiveness is measured through performance metrics like accuracy, precision and recall. The resultant app provides a farmer-friendly dashboard through which farmers can enter their local conditions and receive individualized crop suggestions.

Keywords: crop recommendation, precision agriculture, crop, machine learning

Procedia PDF Downloads 16

Authors: Gertrude Nkechi Okenwa

Abstract:

Higher institutions, especially the universities that are saddled with the responsibilities of teaching, learning, research, publications and social services for the production of graduates that are worthy in learning and character, and the creation of up-to-date knowledge and innovations for the total socio-economic and even political development of a given nation. Therefore, the purpose of the study was to identify the teaching, learning techniques used in the Enugu State University of Science and Technology to ensure or ascertain students’ perception on these techniques. To guide the study, survey research method was used. The population for the study was made up of second and final year students which summed up to one hundred and twenty-six students in the faculty of education. Stratified random sampling technique was adopted. A sample size of sixty (60) students was drawn for the study. The instrument used for data collection was questionnaire. To analyze the data, mean and standard deviation were used to answers the research questions. The findings revealed that direct instruction and construction techniques are used in the university. On the whole, it was observed that the students perceived constructivist techniques to be more useful and effective than direct instruction technique. Based on the findings recommendations were made to include diversification of teaching techniques among others.

Keywords: Strategies, Teaching and Learning, Constructive Technique, Direct Instructional Technique

Procedia PDF Downloads 541

Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

Abstract:

In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

Procedia PDF Downloads 133

Authors: Abbas Raza Ali

Abstract:

Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 175

Authors: Saneeya Qureshi

Abstract:

This paper reports doctoral research into the impact of Special Educational Needs Coordinators (SENCOs) on teachers in England, UK. Since 1994, it has been compulsory for all mainstream schools in the UK to have a SENCO who co-ordinates assessment and provision for supporting pupils with Special Educational Needs (SEN), helping teachers to develop and implement optimal SEN planning and resources. SENCOs’ roles have evolved as various policies continually redefined SEN provision, impacting their positioning within the school hierarchical structure. SENCOs in England are increasingly recognised as key members of school senior management teams. In this paper, It will be argued that despite issues around the transformative ‘professionalisation’ of their role, and subsequent conflict around boundaries and power relations, SENCOs enhance teachers’ abilities in terms of delivering optimal SEN provision. There is a significant international dimension to the issue: a similar role in respect of SEN management already exists in countries such as Ireland, Finland and Singapore, whilst in other countries, such as Italy and India, the introduction of a role similar to that of a SENCO is currently under discussion. The research question addressed is: do SENCOs enhance teachers’ abilities to be effective teachers of children with Special Educational Needs? The theoretical framework of the project is that of interpretivism, as it is acknowledged that there are contexts and realities are social constructions. The study applied a mixed method approach consisting of two phases. The first phase involved a purposive survey (n=42) of 223 primary school SENCOs, which enabled a deeper insight into SENCOs’ perceptions of their roles in relation to teachers. The second phase consisted of semi-structured interviews (n=36) of SENCOs, teachers and head teachers, in addition to school SEN-related documentation scrutiny. ‘Trustworthiness’ was accomplished through data and methodological triangulation, in addition to a rigorous process of coding and thematic analysis. The research was informed by an Ethical Code as per national guidelines. Research findings point to the evolutionary aspect of the SENCO role having engendered a culture of expectations amongst practitioners, as SENCOs transition from being ‘fixers’ to being ‘enablers’ of teachers. Outcomes indicate that SENCOs can empower teaching staff through the dissemination of specialist knowledge. However, there must be resources clearly identified for such dissemination to take place. It is imperative that both SENCOs and teachers alike address the issue of absolution of responsibility that arises when the ownership and accountability for the planning and implementation of SEN provision are not clarified so as to ensure the promotion of a positive school ethos around inclusive practices. Optimal outcomes through effective SEN interventions and teaching practices are positively correlated with the inclusion of teachers in the planning and execution of SEN provisions. An international audience can consider how the key findings are being manifest in a global context, with reference to their own educational settings. Research outcomes can aid the development of specific competencies needed to shape optimal inclusive educational settings in accordance with the official global priorities pertaining to inclusion.

Keywords: inclusion, school professionals, school leadership, special educational needs (SEN), special educational needs coordinators (SENCOs)

Procedia PDF Downloads 194

Authors: T. Mersmann, P. Nyhuis

Abstract:

In the current economic climate, for many businesses it is generally no longer sufficient to pursue exclusively economic interests. Instead, integrating ecological and social goals into the corporate targets is becoming ever more important. However, the holistic integration of these new goals is missing from current factory planning approaches. This article describes the conceptual framework for a planning methodology for sustainable factories. To this end, the description of the key areas for action is followed by a description of the principal components for the systematization of sustainability for factories and their stakeholders. Finally, a conceptual framework is presented which integrates the components formulated into an established factory planning procedure.

Keywords: factory planning, stakeholder, systematization, sustainability

Procedia PDF Downloads 453

Authors: Sotiria Tzivinikou, Dimitra Kagkara

Abstract:

Teacher’s sense of self-efficacy can affect significantly both teacher’s and student’s performance. More specific, self-efficacy is associated with the learning outcomes as well as student’s motivation and self-efficacy. For example, teachers with high sense of self-efficacy are more open to innovations and invest more effort in teaching. In addition to this, effective inclusive education is associated with higher levels of teacher’s self-efficacy. Pre-service teachers with high levels of self-efficacy could handle student’s behavior better and more effectively assist students with special educational needs. Teacher preparation programs are also important, because teacher’s efficacy beliefs are shaped early in learning, as a result the quality of teacher’s education programs can affect the sense of self-efficacy of pre-service teachers. Usually, a number of pre-service teachers do not consider themselves well prepared to work with students with special educational needs and do not have the appropriate sense of self-efficacy. This study aims to investigate the factors that contribute to the improvement of the sense of self-efficacy of pre-service special educators by using an academic practicum training program. The sample of this study is 159 pre-service special educators, who also participated in the academic practicum training program. For the purpose of this study were used quantitative methods for data collection and analysis. Teacher’s self-efficacy was assessed by the teachers themselves with the completion of a questionnaire which was based on the scale of Teacher’s Sense of Efficacy Scale. Pre and post measurements of teacher’s self-efficacy were taken. The results of the survey are consistent with those of the international literature. The results indicate that a significant number of pre-service special educators do not hold the appropriate sense of self-efficacy regarding teaching students with special educational needs. Moreover, a quality academic training program constitutes a crucial factor for the improvement of the sense of self-efficacy of pre-service special educators, as additional for the provision of high quality inclusive education.

Keywords: inclusive education, pre-service, self-efficacy, training program

Procedia PDF Downloads 252

Authors: Yi-Hsiang Pan, Chen-Hui Huang, Ching-Hsiang Chen, Wei-Ting Hsu

Abstract:

The purposes of the study were to explore the students' learning effect of physical education curriculum between merging Teaching Personal and Social Responsibility (TPSR) with sport education model and TPSR with traditional teaching model, which these learning effects included sport self-efficacy, sport enthusiastic, group cohesion, responsibility and game performance. The participants include 3 high school physical education teachers and 6 physical education classes, 133 participants with experience group 75 students and control group 58 students, and each teacher taught an experimental group and a control group for 16 weeks. The research methods used questionnaire investigation, interview, focus group meeting. The research instruments included personal and social responsibility questionnaire, sport enthusiastic scale, group cohesion scale, sport self-efficacy scale and game performance assessment instrument. Multivariate Analysis of covariance and Repeated measure ANOVA were used to test difference of students' learning effects between merging TPSR with sport education model and TPSR with traditional teaching model. The findings of research were: 1) The sport education model with TPSR could improve students' learning effects, including sport self-efficacy, game performance, sport enthusiastic, group cohesion and responsibility. 2) The traditional teaching model with TPSR could improve students' learning effect, including sport self-efficacy, responsibility and game performance. 3) the sport education model with TPSR could improve more learning effects than traditional teaching model with TPSR, including sport self-efficacy, sport enthusiastic,responsibility and game performance. 4) Based on qualitative data about learning experience of teachers and students, sport education model with TPSR significant improve learning motivation, group interaction and game sense. The conclusions indicated sport education model with TPSR could improve more learning effects in physical education curriculum. On other hand, the curricular projects of hybrid TPSR-Sport Education model and TPSR-Traditional Teaching model are both good curricular projects of moral character education, which may be applied in school physical education.

Keywords: character education, sport season, game performance, sport competence

Procedia PDF Downloads 452

Authors: Daniel A. Walzer

Abstract:

As the options for course delivery and development expand, plenty of misconceptions still exist concerning e-learning and online course delivery. Classroom instructors often discuss pedagogy, methodologies, and best practices regarding teaching from a singular, traditional in-class perspective. As more professors integrate online, blended, and hybrid courses into their dossier, a clearly defined rubric for gauging online course delivery is essential. The transition from a traditional learning structure towards an updated distance-based format requires careful planning, evaluation, and revision. This paper examines how new media stimulates reflective practice and guided inquiry to improve pedagogy, engage interdisciplinary collaboration, and supply rich qualitative data for future research projects in media arts disciplines.

Keywords: action research, inquiry, new media, reflection

Procedia PDF Downloads 307

Authors: Alaa Ashraf Khaleel Abdallah

Abstract:

Background: The global landscape has witnessed an alarming rise in armed conflicts, further devastating populations through enforced displacement, compromised infrastructure, and strained healthcare systems. In Sudan, the situation is particularly dire, with conflict exacerbating shortages in medical supplies and personnel, pushing the already fragile healthcare system into crisis, especially affecting surgical care. Initially, war impacts were significant in conflict zones like Khartoum, but since mid-April 2023, the entire country has descended into chaos. Weak monitoring and health information systems hinder accurate assessment of surgical care in conflict zones, leading to inadequate resource allocation, suboptimal care, and missed opportunities for global learning. This study investigates the impact of the Sudanese conflict on postoperative complications, exploring prevalence, types, outcomes, and psychological effects in conflict and safe areas. Methods: Conducted across 10 Sudanese states—5 in conflict zones such as Khartoum and West Darfur, and 5 in safer regions like River Nile and Kassala—this study analyzed data from 1,457 patients who underwent surgery post-April 2023. Data were collected using a pretested, mixed-mode questionnaire that incorporated elements from validated frameworks and tailored questions specific to the study's context. Hospital records and surgical logs were also used, with data analyzed via SPSS. Results: The overall prevalence of postoperative complications was 35.89%, with a higher rate in conflict zones (57.5%) compared to safe areas (26.4%). Surgical site infections predominated in conflict zones (24.7%) and higher than its prevalence in safe areas, and while fever was prevalent in safer regions even though much less compared to conflict areas, bleeding from surgical site was very frequent in conflict areas. Most patients recovered within two months at a rate higher in safe areas, but most of them required further medical or surgical management within the first month, but psychological impacts were more pronounced in conflict zones with 22.22% reported anxiety among injuries patients, and 20.6% experienced depression, 13.5% and 16.9% respectively, in those had surgeries for other medical conditions, compared to 0.22%anxiety rates and 8.1%for depression in safer regions. Risk factors included age, travel to conflict zones, access to care, delays, and comorbidities. Conclusion: Strengthening healthcare systems and ensuring accessible surgical care are critical in both conflict and safe areas. Specific attention must be given to addressing patient suffering and demographic shifts caused by armed conflict. Further research is needed to refine the predictive model for postoperative complications in conflict zones.

Keywords: postoperative complications, conflict zones, risk factors, surgical outcomes, Sudan

Procedia PDF Downloads 0

Authors: Abdullah Abu-Tineh, Hissa Sadiq, Fatma Al-Mutawah, Youmen Chabaan

Abstract:

The current study examined the experiences of educators in Qatar with the licensure process currently implemented at government schools. Using a survey study design, a total of 1,669 participants expressed their perceptions on the strengths and weaknesses of the licensure system, the professional standards, and the professional portfolio. Findings included participants’ beliefs on the importance of the licensure system in improving their performance, the necessity of using the professional standards as tools for professional growth and development, the importance of refining the professional portfolio for authenticity and reliability, and the inclusion of multiple sources of evidence, such as classroom observations, interviews, student learning outcomes, and surveys. Documenting teachers’ and school leaders’ voices was fundamental in finding ways to successfully drive future developments of the licensure system. The findings may also provide implications for other countries interested in developing or refining their own appraisal systems.

Keywords: licensure system, educator voice, professional standards, professional portfolio

Procedia PDF Downloads 203

Authors: Ruchika Malhotra, Megha Khanna

Abstract:

The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

Procedia PDF Downloads 418

Authors: Erich Gomes Schaitza, Antônio Francisco Savi, Glaucia Aparecida Prates

Abstract:

The penetration of renewable energy into the electricity supply in Brazil is high, one of the highest in the World. Centralized hydroelectric generation is the main source of energy, followed by biomass and wind. Surprisingly, mini and micro-generation are negligible, with less than 2,000 connections to the national grid. In 2015, a new regulatory framework was put in place to change this situation. In the agricultural sector, the framework was complemented by the offer of low interest rate loans to in-farm renewable generation. Brazil proposed to more than double its area of planted forests as part of its INDC- Intended Nationally Determined Contributions to the UNFCCC-U.N. Framework Convention on Climate Change (UNFCCC). This is an ambitious target which will be achieved only if forests are attractive to farmers. Therefore, this paper analyses whether planting forests for in-farm energy generation with a with a woodchip gasifier is economically viable for microgeneration under the new framework and at if they could be an economic driver for forest plantation. At first, a static case was analyzed with data from Eucalyptus plantations in five farms. Then, a broader analysis developed with the use of Monte Carlo technique. Planting short rotation forests to generate energy could be a viable alternative and the low interest loans contribute to that. There are some barriers to such systems such as the inexistence of a mature market for small scale equipment and of a reference network of good practices and examples.

Keywords: biomass, distribuited generation, small-scale, Monte Carlo

Procedia PDF Downloads 285

Authors: Katerina Florou

Abstract:

Two decades after coined the term "learner corpora" as collections of texts created by foreign or second language learners across various language contexts, and some years following suggestion to incorporate "focusing on form" within a Task-Based Learning framework, this study aims to explore how learner corpora, whether annotated with errors or not, can facilitate a focus on form in an educational setting. Argues that analyzing linguistic form serves the purpose of enabling students to delve into language and gain an understanding of different facets of the foreign language. This same objective is applicable when analyzing learner corpora marked with errors or in their raw state, but in this scenario, the emphasis lies on identifying incorrect forms. Teachers should aim to address errors or gaps in the students' second language knowledge while they engage in a task. Building on this recommendation, we compared the written output of two student groups: the first group (G1) employed the focusing on form phase by studying a specific aspect of the Italian language, namely the past participle, through examples from native speakers and grammar rules; the second group (G2) focused on form by scrutinizing their own errors and comparing them with analogous examples from a native speaker corpus. In order to test our hypothesis, we created four learner corpora. The initial two were generated during the task phase, with one representing each group of students, while the remaining two were produced as a follow-up activity at the end of the lesson. The results of the first comparison indicated that students' exposure to their own errors can enhance their grasp of a grammatical element. The study is in its second stage and more results are to be announced.

Keywords: Corpus interlanguage analysis, task based learning, Italian language as F1, learner corpora

Procedia PDF Downloads 53

Authors: Anam Gopi

Abstract:

The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.

Keywords: teaching learning based optimization, direct torque control, PI controller

Procedia PDF Downloads 585

Authors: Agis Andriani

Abstract:

To create an effective teaching condition, the teacher requests the students as the instruction to guide the them interactively in the learning activities in the classroom. This study involves 160 Indonesian students who study English in the university, as participants in the discourse completion test, and ten of them are interviewed. The result shows that when the students response the teacher’s request, it realizes assertives, directives, commisives, expressives, and declaratives. These indicate that the students are active, motivated, and responsive in the learning process, although in the certain condition these responses are to prevent their faces from the shyness of their silence in interaction. Therefore, it needs the teacher’s creativity to give the conducive atmosphere in order to support the students’ participation in learning English.

Keywords: discourse completion test, effective teaching, request, teacher’s creativity

Procedia PDF Downloads 437

Authors: Akshay S. Dalvi, Hazim El-Mounayri

Abstract:

The internal and the external interactions between the complex structural and behavioral characteristics of the complex energy system result in unpredictable emergent behaviors. These emergent behaviors are not well understood, especially when modeled using the traditional top-down systems engineering approach. The intrinsic nature of current complex energy systems has called for an elegant solution that provides an integrated framework in Model-Based Systems Engineering (MBSE). This paper mainly presents a MBSE driven approach to define and handle the complexity that arises due to emergent behaviors. The approach provides guidelines for developing system architecture that leverages in predicting the complexity index of the system at different levels of abstraction. A framework that integrates indefinite and definite modeling aspects is developed to determine the complexity that arises during the development phase of the system. This framework provides a workflow for modeling complex systems using Systems Modeling Language (SysML) that captures the system’s requirements, behavior, structure, and analytical aspects at both problem definition and solution levels. A system architecture for a district cooling plant is presented, which demonstrates the ability to predict the complexity index. The result suggests that complex energy systems like district cooling plant can be defined in an elegant manner using the unconventional modified MBSE driven approach that helps in estimating development time and cost.

Keywords: district cooling plant, energy systems, framework, MBSE

Procedia PDF Downloads 131

Authors: Ágoston Nagy

Abstract:

This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

Procedia PDF Downloads 354

Authors: Durhane Wong-Rieger, Kawaldip Sehmi, Nicola Bedlington, Nicole Boice, Tamás Bereczky

Abstract:

Patient-generated health data should be seen as the expression of the experience of patients, including the outcomes reflecting the impact a treatment or service had on their physical health and wellness. We discuss how the healthcare system can reach a place where digital is a determinant of health - where data is generated by patients and is respected and which acknowledges their contribution to science. We explore the biggest barriers facing this. The International Experience Exchange with Patient Organisation’s Position Paper is based on a global patient survey conducted in Q3 2021 that received 304 responses. Results were discussed and validated by the 15 patient experts and supplemented with literature research. Results are a subset of this. Our research showed patient communities want to influence how their data is generated, shared, and used. Our study concludes that a reasonable framework is needed to protect the integrity of patient data and minimise abuse, and build trust. Results also demonstrated a need for patient communities to have more influence and control over how health data is generated, shared, and used. The results clearly highlight that the community feels there is a lack of clear policies on sharing data.

Keywords: digital health, equitable access, humanise healthcare, patient data

Procedia PDF Downloads 82

Authors: Hee-Young Song

Abstract:

Background and objectives: In 2011, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations proposed a multidimensional assessment of patients’ conditions that included both functional parameters and patient-reported outcomes, with the aim to provide a comprehensive assessment of the disease, thus meeting both the needs of the patient and the role of the physician. However, few studies have evaluated patient-reported outcomes as well as objective functional assessments among individuals with chronic obstructive pulmonary disease (COPD) in clinical practice in Korea. This study was undertaken to explore the relationship between functional status assessed by the 6-minute walking distance (MWD) test and subjective health status reported by stable patients with COPD residing in community. Methods: A cross-sectional descriptive study was conducted with 118 stable COPD patients aged 69.4 years old and selected by a convenient sampling from an outpatient department of pulmonology in a tertiaryhospitals. The 6-MWD test was conducted according to standardized instructions. Participants also completed a constructed questionnaire including general characteristics, smoking history, dyspnea by modified medical research council (mMRC) scale, and health status by COPD assessment test (CAT). Anthropometric measurements were performed for body mass index (BMI). Medical records were reviewed to obtain disease-related characteristics including duration of the disease and forced expiratory volume in 1 second (FEV1). Data were analyzed using PASW statistics 20.0. Results: Mean FEV1% of participants was 63.51% and mean 6-MWD and CAT scores were 297.54m and 17.7, respectively. The 6-MWD and CAT showed significant negative correlations (r= -.280, p=.002); FEV1 and CAT did as well correlations (r= -.347, p < .001). Conclusions: Findings suggest that the better functional status an individual with COPD has, the better subjective health status is, and provide the support for using patient-reported outcomes along with functional parameters to facilitate comprehensive assessment of COPD patients in real clinical practices.

Keywords: chronic obstructive pulmonary disease, COPD assessment test, functional status, patient-reported outcomes

Procedia PDF Downloads 366

Authors: Akram Hashemi

Abstract:

This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.

Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy

Procedia PDF Downloads 335

Authors: Brian Fleischli, Shani Robins

Abstract:

In recent years, the implementation of wisdom skills, including emotional intelligence, mindfulness, empathy, compassion, gratitude, realism (Cognitive-Behavioral Therapy), and humility, within K-12 educational settings has demonstrated significant benefits in reducing stress, anxiety, anger, and conflict among students. This study summarizes the findings of research conducted over several years, showcasing the positive outcomes associated with teaching these skills to elementary and high school students. Additionally, this overview includes an updated synthesis of current literature concerning the application and effectiveness of training these skill sets in K-12 schools. The research outcomes highlight substantial improvements in student well-being and behavior. Demonstrated with treatment group students exhibiting notable reductions in anger, anxiety, depression, and disruptive behaviors compared to control groups. For instance, fourth-grade students showed enhanced empathy, responsibility, and attention, particularly benefiting those with lower initial scores on these measures. Specific interaction effects suggest that older students and males particularly benefit from these interventions, showcasing the nuanced impact of wisdom skill training across different demographics. Furthermore, this presentation emphasizes the critical role of Social and Emotional Learning (SEL) programs in addressing the multifaceted challenges faced by children and adolescents, including mental health issues, academic performance, and social behaviors. The integration of wisdom skills into school curricula not only fosters individual growth and emotional regulation but also enhances overall school climate and academic achievement. In conclusion, the findings contribute to the growing body of empirical evidence supporting the efficacy of teaching wisdom skills in educational settings. The success of these interventions underscores the potential for widespread implementation of evidence-based programs to promote emotional well-being and academic success among students nationwide.

Keywords: wisdom skills, CBT, cognitive behavioral training, mindfulness, empathy, anxiety

Procedia PDF Downloads 45

Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

Abstract:

Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

Procedia PDF Downloads 118

Authors: Malathi Balakrishnan, Cheng Lee Ooi, Chander Vengadasalam

Abstract:

The purpose of this study is to explore a case study of trainee teachers’ learning experience on innovating traditional games during the traditional game carnival. It explores issues arising from multiple case studies of trainee teachers learning experiences in innovating traditional games. A qualitative methodology was adopted through observations, semi-structured interviews and reflective journals’ content analysis of trainee teachers’ learning experiences creating and implementing innovative traditional games. Twelve groups of 36 trainee teachers who registered for Sports and Physical Education Management Course were the participants for this research during the traditional game carnival. Semi structured interviews were administrated after the trainee teachers learning experiences in creating innovative traditional games. Reflective journals were collected after carnival day and the content analyzed. Inductive data analysis was used to evaluate various data sources. All the collected data were then evaluated through the Nvivo data analysis process. Inductive reasoning was interpreted based on the Self Determination Theory (SDT). The findings showed that the trainee teachers had positive game participation experiences, game knowledge about traditional games and positive motivation to innovate the game. The data also revealed the influence of themes like cultural significance and creativity. It can be concluded from the findings that the organized game carnival, as a requirement of course work by the Institute of Teacher Training Malaysia, was able to enhance teacher trainers’ innovative thinking skills. The SDT, as a multidimensional approach to motivation, was utilized. Therefore, teacher trainers may have more learning experiences using the SDT.

Keywords: learning experiences, innovation, traditional games, trainee teachers

Procedia PDF Downloads 330

Authors: Katerina Kormusheva

Abstract:

Pricing plays a pivotal role in the marketing discipline as it directly influences consumer perceptions, purchase decisions, and overall market positioning of a product or service. This paper seeks to expand current knowledge in the area of discriminatory and differential pricing, a main area of marketing research. The methodology includes developing a framework and a model for determining how many price points to implement in differential pricing. We focus on choosing the levels of differentiation, derive a function form of the model framework proposed, and lastly, test it empirically with data from a large-scale marketing pricing experiment of services in telecommunications.

Keywords: marketing, differential pricing, price points, optimization

Procedia PDF Downloads 93