Search results for: learning assessment

Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: Rasheed A. Saliu, Sunday E. Ogundipe, Oluwaseun A. Adefila

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Information and Communication Technology (ICT) in recent time has transformed the means by which we inform ourselves, with world events and areas of personal interests, and further our learning. Today, for many, books and journals are no longer the first or primary source of information or learning. We now regularly rely on images, video, animations and sound to acquire information and to learn. Increased and improved access to the internet has accelerated this phenomenon. We now acquire and access information in ways fundamentally different from the pre-ICT era. But to what extent is academic staff in colleges of education, having access to and the utilising of ICT devices in their lecture deliveries especially in School of Science and Vocational and Technical? The main focus of this paper is to proffer solution to this salient question. It is essentially an empirical study carried out in five colleges of education in south-west zone of Nigeria. The target population was the academic staff in the selected institution. A total number of 150 male and female lecturers were contacted for the study. The main instrument was questionnaire. The finding reveals that male lecturers are much more ICT inclined than women folk in the academics. Some recommendations were made to endear academics to utilizing ICT at their disposal to foster qualitative delivery in this digital era.

Keywords: education, gender, ICT, Nigeria

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Authors: Maria C. Proença, Maria T. Rebelo, Marília Antunes, Maria J. Alves, Hugo Osório, Sofia Cunha, João Casaca

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Using a geographic information system (GIS), the relations between a georeferenced data set of Culex pipiens sl. mosquitoes collected in Portugal mainland during seven years (2006-2012) and meteorological and physiographic parameters such as: air relative humidity, air temperature (minima, maxima and mean daily temperatures), daily total rainfall, altitude, land use/land cover and proximity to water bodies are evaluated. Focus is on the mosquito females; the characterization of its habitat is the key for the planning of chirurgical non-aggressive prophylactic countermeasures to avoid ambient degradation. The GIS allow for the spatial determination of the zones were the mosquito mean captures has been above average; using the meteorological values at these coordinates, the limits of each parameter are identified/computed. The meteorological parameters measured at the net of weather stations all over the country are averaged by month and interpolated to produce raster maps that can be segmented according to the thresholds obtained for each parameter. The intersection of the maps obtained for each month show the evolution of the area favorable to the species through the mosquito season, which is from May to October at these latitudes. In parallel, mean and above average captures were related to the physiographic parameters. Three levels of risk could be identified for each parameter, using above average captures as an index. The results were applied to the suitability meteorological maps of each month. The Culex pipiens critical niche is delimited, reflecting the critical areas and the level of risk for transmission of the pathogens to which they are competent vectors (West Nile virus, iridoviruses, rheoviruses and parvoviruses).

Keywords: Culex pipiens, ecological niche, risk assessment, risk management

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Kristina Johansen

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Participation is a universal right that all children and young people are entitled to, according to the Convention on the Rights of the Child. Social work and action research share participation as a core value. However, we have limited knowledge of how children and young people of refugee background experience taking part in participatory research. The point of departure of this presentation is a qualitative study involving young, unaccompanied refugees, addressing the issues of psychosocial health and participation. The research design included participatory methods and action research. The presentation highlights the perspectives of young, unaccompanied refugees on what made participating in the research process valuable, what created challenges for participation and what created challenges for the action part in the research process. Feedback from participants indicated that taking part in enjoyable experiences, being listened to, sharing experiences, and learning from each other contributed to making the participation valuable. At the same time, participants addressed challenges related to communication, sensitive topics, participation in decision-making and powerlessness. The presentation will end with implications for social work research and practice involving young refugees.

Keywords: participatory research, power, young unaccompanied refugeees, relationships, participation

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Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

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In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

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Authors: Rosemarie P. Ongoco, Rowena S. Badua, Kristine Joy S. Simpao, Ria L. Dizon

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Food Technology (FT) has become a very powerful field in dealing with the processing of food making it available, safe, tasty and convenient. Bataan Peninsula State University (BPSU) has been offering FT as a major of the Bachelor of Science in Industrial Technology, both in the Main and Orani campuses since the 1970s. With the different orientation of FT offered in state universities and colleges, whether it is skill or science-based, this study aims to assess the current FT situation in BPSU. Curriculum, faculty profile and facilities of FT in BPSU were assessed and compared to the other FT related program in three state universities in Region III; Nueva Ecija University of Science and Technology, Pampanga Agricultural College, and Central Luzon State University. Data were gathered through structured interview, ocular inspection for the facilities and questionnaires for the teacher and students’ personal interest. Results show that BPSU’s FT program is more likely similar to the one offered in NEUST. PAC is offering a similar course but is more business and management-oriented BS Home Economics while CLSU is offering a science and technology-related course, BS Home Economics while CLSU is offering a science and technology-related course, BS Food Technology. BPSU students more intercede in cooking and baking while doing sales report, dishwashing and food packaging are the activities faculty and students are least interested. Mechanized machines in cooking and baking are also suggested by the majority of the students in BPSU. In conclusion, BPSU’s program in BS IT major in Food Technology must be improved in the aspects of curriculum, faculty profile, and facilities. It is recommended for the department to consider the curriculum, faculty profile, and facilities. It is recommended for the department to consider the curriculum of NEUST in the BS IT major in Food Technology.

Keywords: food technology, curriculum, technology, assessment

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Authors: Mohamed H. Kosba, Heba A. Ibrahim, H. Rozita

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Statement of the Problem: The life expectancy for transfusion-dependent thalassemia patients has increased dramatically with iron-chelation therapy and other modern management modalities. In these patients, the most dominant maxillofacial manifestations are protrusion of zygomatic bones and premaxilla due to the hyperplasia of bone marrow. The purpose of this study is to determine the prevalence of malocclusion and orthodontic treatment needs according to the Dental Aesthetic Index (DAI) among Malay transfusion-dependent thalassemia patients. Orientation: This is a cross-sectional study consist of 43 Malay transfusion-dependent thalassemia patients, 22 males, and 19 females with the mean age of 15.9 years old (SD 3.58). The subjects were selected randomly from patients attending Paediatrics and Internal Medicine Clinic at Hospital USM and Hospital Sultana Bahiyah. The subjects were assessed for malocclusion according to Angle’s classification, and orthodontic treatment needs using DAI. The results show that 22 of the subjects (51.1%) have class II malocclusion, 12 subjects (28%) have class І, while 9 subjects (20.9%) have class Ⅲ. The assessment of orthodontic treatment needs to reveal 22 cases (51.1%) fall in the normal/minor needs category, 12 subjects (28%) fall in the severe and very severe category, while 9 subjects (20.9%) fall in the definite category. Conclusion & Significance: Half of Malay transfusion-dependent thalassemia patients have Class Ⅱmalocclusion. About 28% had malocclusion and required orthodontic treatment. This research shows that Malay transfusion-dependent thalassemia may require orthodontic management; earlier intervention to reduce the complexity of the treatment later, suggesting functional appliance as a suitable treatment option for them, a twin block appliance together with headgear to restrict maxillary growth suggested for management. The current protocol implemented by the Malaysian Ministry of Health for the management of these patients seems to be sufficient since the result shows that about 28% require orthodontic treatment need, according to DAI.

Keywords: prevalence, DAI, thalassaemia, angle classification

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Authors: Sishen Wang

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Chinese rural industry development is the major task currently during rapid urbanization. Development of potentiality assessment, evaluate the overall suitability of each village for further industrial development, could offer reference for policy makers, especially considering the limited data available in Chinese rural regions. The study focuses on 157 official villages in Fuliang County and evaluates their development potentiality by their topography, transportation condition, population, income of villagers, infrastructure and environmental conditions. Land cover changes for Fuliang county and surrounding areas of each village is also investigated for reference. The final development potentiality of each village was calculated by adding different weighted scores of different categories. Besides, inverse distance weighting (IDW) images for both final score of development potentiality and each factor were made and compared to help to understand the final result. The study found that village in the southern and northern regions have higher development potentiality than villages in the eastern and western regions, mainly because of higher income of villagers, good accessibilities and a large amount of population size. In addition, the Fuliang county was divided into five regions based on final result and policy reference for the development of each region were put forward individually. In addition, three suggestions were made for better local development potentiality: Firstly, the transportation accessibility needs to be improved in the northern regions by building more public transit system there. Secondly, the environmental conditions and infrastructure conditions in the eastern region of the county need some improvement. Thirdly, some encouragement and job opportunities should beset up in the western regions to attract labor force to move in and settle down.

Keywords: development potentiality, Fuliang GIS-Based, GIS, official village

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Authors: Hsin-Yi Lo, Chia-Yu Hsu

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This article is the nursing experience of a multiple trauma case using Swanson's theory of caring, the nursing period is from May 31 to June 4, 2021, collect data through observation, written talks, interviews, listening, direct care and physical assessment, established cases with health problems such as acute pain, impaired tissue integrity, and anxiety. Nursing process including, evaluate the pain index with the pain assessment scale, assist in acupoint massage, use a corset to fix the wound, and give the patient listening to favorite radio programs to divert attention and relieve pain problems; promote wound healing and avoid infection by assessing wound condition and exudation, changing dressings with aseptic technique, and providing appropriate dressings; encourage patients to express their feelings, provide companionship, and assist in self-care and participation in treatment plans, to enable the case to overcome the anxiety caused by being admitted to the intensive care unit for the first time and not knowing about the disease, and assist the case to overcome the injury caused by the accident and return to normal life. There is no video equipment in the intensive care unit during the nursing period. In response to the problem that family visits cannot be opened during the epidemic, it is a limitation this time. It is recommended that the hospital take this into consideration in the future. In the post-epidemic era, it can reduce the risk of various infections for patients and family members. Traveling between home and hospital, improving the quality of high-quality and technological care.

Keywords: swanson's theory of caring, multiple trauma, anxiety, nursing experience

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Authors: Mohammad Pervez Mughal, Huma Shazadi

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Pakistan became a full signatory to the Washington Accord in June 2017, with the expectation that undergraduate engineering programs will be recognized by other signatory countries. Pakistan's accrediting body, the Pakistan Engineering Council (PEC), has distributed 12 Program Learning Outcomes (PLOs) under Outcome Based Education (OBE) criteria for engineering institutions in Pakistan to follow. However, no research has been conducted to rank graduates' employability skills in relation to these PLOs from the perspective of potential employers. The current work makes a concerted effort to rank the skills required by employers, which include both technical and non-technical skill sets. A survey was conducted throughout Pakistan to validate the relative importance of employability skills. 198 HR personnel, 1554 graduating students, 1540 alumni, and 267 faculty members provided valid responses, which were analyzed. According to the findings, ethics, communication, and lifelong learning are the most important attributes of engineering graduates' employability in the eyes of employers. Graduating students, alumni, and faculty's differential prospects are also presented and compared to employers' perspectives.

Keywords: employability skills, employers' perspective, outcome-based education, engineering graduates, Pakistan

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Authors: Ebru Turgal, Beyza Doganay Erdogan

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Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Kritiyaporn Kunsook

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Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

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Authors: Christiana Gauci-Sciberras

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The first language (L1) could be used in foreign language teaching and learning as a pedagogical tool to scaffold new knowledge in the target language (TL) upon linguistic knowledge that the learner already has. In a bilingual context, code-switching between the two languages usually occurs in classrooms. One of the reasons for code-switching is because both languages are used for scaffolding new knowledge. This research paper aims to find out why both the L1 (Maltese) and the L2 (English) are used in the classroom of Mandarin Chinese as a foreign language (CFL) in the bilingual context of Malta. This research paper also aims to find out the learners’ perceptions of the use of a bilingual medium of instruction. Two research methods were used to collect qualitative data; semi-structured interviews with adult learners of Mandarin Chinese and lesson observations. These two research methods were used so that the data collected in the interviews would be triangulated with data collected in lesson observations. The L1 (Maltese) is the language of instruction mostly used. The teacher and the learners switch to the L2 (English) or to any other foreign language according to the need at a particular instance during the lesson.

Keywords: Chinese, bilingual, pedagogical purpose of L1 and L2, CFL acquisition

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Authors: Munawar Malik, Muntaha Ahmad, Khalil Ullah Khan

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Linguistic abilities in students with hearing impairment yet remain a concern for educationists. The emerging technological support and provisions in recent era vows to have addressed the situation and claims significant contribution in terms of linguistic repertoire. Being a descriptive and quantitative paradigm of study, the purpose of this research set forth was to assess linguistic competencies of students with hearing impairment in English language. The goals were further broken down to identify level of reading abilities in the subject population. The population involved students with HI studying at higher secondary level in Lahore. Simple random sampling technique was used to choose a sample of fifty students. A purposive curriculum-based assessment was designed in line with accelerated learning program by Punjab Government, to assess Linguistic competence among the sample. Further to it, an Informal Reading Inventory (IRI) corresponding to reading levels was also developed by researchers duly validated and piloted before the final use. Descriptive and inferential statistics were utilized to reach to the findings. Spearman’s correlation was used to find out relationship between degree of hearing loss, grade level, gender and type of amplification device. Independent sample t-test was used to compare means among groups. Major findings of the study revealed that students with hearing impairment exhibit significant deviation from the mean scores when compared in terms of grades, severity and amplification device. The study divulged that respective students with HI have yet failed to qualify an independent level of reading according to their grades as majority falls at frustration level of word recognition and passage comprehension. The poorer performance can be attributed to lower linguistic competence as it shows in the frustration levels of reading, writing and comprehension. The correlation analysis did reflect an improved performance grade wise, however scores could only correspond to frustration level and independent levels was never achieved. Reported achievements at instructional level of subject population may further to linguistic skills if practiced purposively.

Keywords: linguistic competence, hearing impairment, reading levels, educationist

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Authors: Cornelia-Eugenia Munteanu

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The goal of this paper is to present the diagnostic contribution that the screening instrument, Mini-Mental State Examination-2: Expanded Version (MMSE-2:EV), brings in detecting the cognitive impairment or in monitoring the progress of degenerative disorders. The diagnostic signification is underlined by the interpretation of the MMSE-2:EV scores, resulted from the test application to patients with mild and major neurocognitive disorders. The original MMSE is one of the most widely used screening tools for detecting the cognitive impairment, in clinical settings, but also in the field of neurocognitive research. Now, the practitioners and researchers are turning their attention to the MMSE-2. To enhance its clinical utility, the new instrument was enriched and reorganized in three versions (MMSE-2:BV, MMSE-2:SV and MMSE-2:EV), each with two forms: blue and red. The MMSE-2 was adapted and used successfully in Romania since 2013. The cases were selected from current practice, in order to cover vast and significant neurocognitive pathology: mild cognitive impairment, Alzheimer’s disease, vascular dementia, mixed dementia, Parkinson’s disease, conversion of the mild cognitive impairment into Alzheimer’s disease. The MMSE-2:EV version was used: it was applied one month after the initial assessment, three months after the first reevaluation and then every six months, alternating the blue and red forms. Correlated with age and educational level, the raw scores were converted in T scores and then, with the mean and the standard deviation, the z scores were calculated. The differences of raw scores between the evaluations were analyzed from the point of view of statistic signification, in order to establish the progression in time of the disease. The results indicated that the psycho-diagnostic approach for the evaluation of the cognitive impairment with MMSE-2:EV is safe and the application interval is optimal. The alternation of the forms prevents the learning phenomenon. The diagnostic accuracy and efficient therapeutic conduct derive from the usage of the national test norms. In clinical settings with a large flux of patients, the application of the MMSE-2:EV is a safe and fast psycho-diagnostic solution. The clinicians can draw objective decisions and for the patients: it doesn’t take too much time and energy, it doesn’t bother them and it doesn’t force them to travel frequently.

Keywords: MMSE-2, dementia, cognitive impairment, neuropsychology

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Authors: Benjamin D Reese Jr

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Implicit bias is understood as unconscious attitudes, stereotypes, or associations that can influence the cognitions, actions, decisions, and interactions of an individual without intentional control. These unconscious attitudes or stereotypes are often targeted toward specific groups of people based on their gender, race, age, perceived sexual orientation or other social categories. Since the late 1980s, there has been a proliferation of research that hypothesizes that the operation of implicit bias is the result of the brain needing to process millions of bits of information every second. Hence, one’s prior individual learning history provides ‘shortcuts’. As soon as one see someone of a certain race, one have immediate associations based on their past learning, and one might make assumptions about their competence, skill, or danger. These assumptions are outside of conscious awareness. In recent years, an alternative conceptualization has been proposed. The ‘bias of crowds’ theory hypothesizes that a given context or situation influences the degree of accessibility of particular biases. For example, in certain geographic communities in the United States, there is a long-standing and deeply ingrained history of structures, policies, and practices that contribute to racial inequities and bias toward African Americans. Hence, negative biases among groups of people towards African Americans are more accessible in such contexts or communities. This theory does not focus on individual brain functioning or cognitive ‘shortcuts.’ Therefore, attempts to modify individual perceptions or learning might have negligible impact on those embedded environmental systems or policies that are within certain contexts or communities. From the ‘bias of crowds’ perspective, high levels of racial bias in a community can be reduced by making fundamental changes in structures, policies, and practices to create a more equitable context or community rather than focusing on training or education aimed at reducing an individual’s biases. The current paper acknowledges and supports the foundational role of long-standing structures, policies, and practices that maintain racial inequities, as well as inequities related to other social categories, and highlights the critical need to continue organizational, community, and national efforts to eliminate those inequities. It also makes a case for providing individual leaders with a deep understanding of the dynamics of how implicit biases impact cognitions, actions, decisions, and interactions so that those leaders might more effectively develop structural changes in the processes and systems under their purview. This approach incorporates both the importance of an individual’s learning history as well as the important variables within the ‘bias of crowds’ theory. The paper also offers a model for leadership education, as well as examples of structural changes leaders might consider.

Keywords: implicit bias, unconscious bias, bias, inequities

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Authors: Andrew Fox, Qingping Yang, Yuanhong Zhao, Tao Zhang

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Furniture is a very significant subdivision of architecture and its inherent interior design activities. The furniture industry has developed from an artisan-driven craft industry, whose forerunners saw themselves manifested in their crafts and treasured a sense of pride in the creativity of their designs, these days largely reduced to an anonymous collective mass-produced output. Although a very conservative industry, there is great potential for the implementation of collaborative digital technologies allowing a reconfigured artisan experience to be reawakened in a new and exciting form. The furniture manufacturing industry, in general, has been slow to adopt new methodologies for a design using artificial and rule-based generative design. This tardiness has meant the loss of potential to enhance its capabilities in producing sustainable, flexible, and mass customizable ‘right first-time’ designs. This paper aims to demonstrate the concept methodology for the creation of alternative and inspiring aesthetic structures for robot-based additive manufacturing (RBAM). These technologies can enable the economic creation of previously unachievable structures, which traditionally would not have been commercially economic to manufacture. The integration of these technologies with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most accomplished traditional design teams. This paper aims to address the problem by introducing generative design methodologies employing the Autodesk Fusion 360 platform. Examination of the alternative methods for its use has the potential to significantly reduce the estimated 80% contribution to environmental impact at the initial design phase. Though predominantly a design methodology, generative design combined with RBAM has the potential to leverage many lean manufacturing and quality assurance benefits, enhancing the efficiency and agility of modern furniture manufacturing. Through a case study examination of a furniture artifact, the results will be compared to a traditionally designed and manufactured product employing the Ecochain Mobius product life cycle analysis (LCA) platform. This will highlight the benefits of both generative design and robot-based additive manufacturing from an environmental impact and manufacturing efficiency standpoint. These step changes in design methodology and environmental assessment have the potential to revolutionise the design to manufacturing workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing, with the global demand for a circular economy and bespoke sustainable design at its heart.

Keywords: robot, manufacturing, generative design, sustainability, circular econonmy, product life cycle assessment, furniture

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Authors: Junaid Asimiyu Mohammed, Olakunle Docas Tosin

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The housing environment in many developing countries is fraught with risks that have potential negative impacts on the lives of the residents. The study examined the risk factors in residential areas of two neighborhoods in Bosso Local Government Areas of Minna in Nigeria with a view to determining the level of their potential impacts. A sample of 378 households was drawn from the estimated population of 22,751 household heads. The questionnaire and direct observation were used as instruments for data collection. The data collected were analyzed using the Relative Importance Index (RII) rule to determine the level of the potential impact of the risk factors while ArcGIS was used for mapping the spatial distribution of the risks. The study established that the housing environment of Angwan Biri and El-Waziri areas of Bosso is poor and vulnerable as 26% of the houses were not habitable and 57% were only fairly habitable. The risks of epidemics, building collapse and rainstorms were evident in the area as 53% of the houses had poor ventilation; 20% of residents had no access to toilets; 47% practiced open waste dumping; 46% of the houses had cracked walls while 52% of the roofs were weak and sagging. The results of the analysis of the potential impact of the risk factors indicate a RII score of 0.528 for building collapse, 0.758 for rainstorms and 0.830 for epidemics, indicating a moderate to very high level of potential impacts. The mean RII score of 0.639 shows a significant potential impact of the risk factors. The study recommends the implementation of sanitation measures, provision of basic urban facilities and neighborhood revitalization through housing infrastructure retrofitting as measures to mitigate the risks of disasters and improve the living conditions of the residents of the study area.

Keywords: assessment, risk, residential, Nigeria

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: E. O. Egieyeh, N. Butler, R. Coetzee, M. Van Huyssteen, A. Bheekie

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Background: High rate of maternal and child mortality is a global concern. Nationally, it constitutes one of South Africa’s quadruple burdens of diseases. Pharmacists have a crucial role in maternal and child health care delivery and as such should be equipped with adequate knowledge and skill required to contribute to maternal and child well-being. The International Pharmaceutical Federation statement of policy (2013) outlines pharmacist-led interventions in accordance with the World Health Organisation’s interventions in maternal, new-born and child health care. The South African Pharmacy Council’s guideline on Good Pharmacy Practice (2010) also stipulates the minimum standards required to participate in reproductive, maternal and child care. Pharmacy schools are obliged to train pharmacy students to meet priority health needs of the population so that graduates are ‘fit for purpose’. The purpose of the study is to evaluate the knowledge and skill of final year pharmacy students at a university in South Africa to determine their preparedness to contribute effectively to maternal and child health care. Method: A quantitative, descriptive, non-randomized baseline study was conducted among the final year students at the School of Pharmacy. Data was collected using a questionnaire designed in sections to assess knowledge of contraception, maternal and child health directed at the primary care level and framed within the scope of practice required of an entry-level generalist pharmacist. Participants’ skill in infant growth assessment was assessed in a section of the questionnaire in a written format. Participants ticked the topics they had been exposed to on a curriculum content assessment tool which was not graded. A pilot study examined the clarity and suitability of question items, and duration to complete the questionnaire. A score of 50% in each section of the questionnaire indicated a pass. The questionnaire was delivered in campus lecture venue. Results: Of the 102 students in final year, 53 (52%) students consented to participate in the study. Only 13.2% of participants scored above 50% in each section. Forty five (85%) participants scored above 50% in the contraception section while 40 (75%) scored less than 50% in the skills assessment. Less than half (45.3%) of the participants had a total score above 50%. Being a parent or working part-time as pharmacist assistance did not have any influence on the performance of the participants. Evaluation of participants’ curriculum content exposure showed differences in exposure to the various topics. Exposure to contraception teaching received the most recognition. Conclusion: Maternal and child health curriculum content should be reviewed at the university to enhance the knowledge and skill of pharmacy graduates.

Keywords: final year pharmacy students, knowledge and skill, maternal and child health, South Africa

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Authors: Dalila Lino, Maria Joao Hortas, Carla Rocha, Clarisse Nunes, Natalia Vieira, Marina Fuertes, Kátia Sa

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The value of play is recognized worldwide and is considered a fundamental right of all children, as defined in Article 31 of the United Nations Children’s Rights. It is consensual among the scientific community that play, and toys are of vital importance for children’s learning and development. Play promotes the acquisition of language, enhances creativity and improves social, affective, emotional, cognitive and motor development of young children. Young children ages 0 to 6 who have had many opportunities to get involved in play show greater competence to adapt to new and unexpected situations and more easily overcome the pain and suffering caused by traumatic situations. The PlayTrain Project aims to understand the places/spaces of play in the education of children from 0 to 6 years and promoting the training of preschool teachers to become capable of developing practices that enhance children’s agency, experimentation in the physical and social world and the development of imagination and creativity. This project follows the Design-Based-Research (DBR) and has two dimensions: research and intervention. The participants are 120 students from the Master in Pre-school Education of the Higher School of Education, Polytechnic Institute of Lisbon enrolled in the academic year 2018/2019. The development of workshops focused on the role of play and toys for young children’s learning promotes the participants reflection and the development of skills and knowledge to construct developmentally appropriated practices in early childhood education. Data was collected through an online questionnaire and focal groups. Results show that the PlayTrain Project contribute to the development of a body of knowledge about the role of play for early childhood education. It was possible to identify the needs of preschool teacher education and to enhance the discussion among the scientific and academic community about the importance of deepening the role of play and toys in the study plans of the masters in pre-school education.

Keywords: children's learning, early childhood education, play, teacher education, toys

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Authors: Rohan Bhasin

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Agrammatism in non-fluent Aphasia Cases can be defined as a language disorder wherein a patient can only use content words ( nouns, verbs and adjectives ) for communication and their speech is devoid of functional word types like conjunctions and articles, generating speech of with extremely rudimentary grammar . Past approaches involve Speech Therapy of some order with conversation analysis used to analyse pre-therapy speech patterns and qualitative changes in conversational behaviour after therapy. We describe this approach as a novel method to generate functional words (prepositions, articles, ) around content words ( nouns, verbs and adjectives ) using a combination of Natural Language Processing and Deep Learning algorithms. The applications of this approach can be used to assist communication. The approach the paper investigates is : LSTMs or Seq2Seq: A sequence2sequence approach (seq2seq) or LSTM would take in a sequence of inputs and output sequence. This approach needs a significant amount of training data, with each training data containing pairs such as (content words, complete sentence). We generate such data by starting with complete sentences from a text source, removing functional words to get just the content words. However, this approach would require a lot of training data to get a coherent input. The assumptions of this approach is that the content words received in the inputs of both text models are to be preserved, i.e, won't alter after the functional grammar is slotted in. This is a potential limit to cases of severe Agrammatism where such order might not be inherently correct. The applications of this approach can be used to assist communication mild Agrammatism in non-fluent Aphasia Cases. Thus by generating these function words around the content words, we can provide meaningful sentence options to the patient for articulate conversations. Thus our project translates the use case of generating sentences from content-specific words into an assistive technology for non-Fluent Aphasia Patients.

Keywords: aphasia, expressive aphasia, assistive algorithms, neurology, machine learning, natural language processing, language disorder, behaviour disorder, sequence to sequence, LSTM

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Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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Authors: Amir Reza Heydari, Yaser Jenab

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Coronary artery disease, a common cardiovascular disease, is attributed to the accumulation of cholesterol-based plaques in the coronary arteries, leading to atherosclerosis. This disease is associated with risk factors such as smoking, hypertension, diabetes, and elevated cholesterol levels, contributing to severe clinical consequences, including acute coronary syndromes and myocardial infarction. Treatment approaches such as from lifestyle interventions to surgical procedures like percutaneous coronary intervention and coronary artery bypass surgery. These interventions often employ stents, including bare-metal stents (BMS), drug-eluting stents (DES), and bioresorbable vascular scaffolds (BVS), each with its advantages and limitations. Computational tools have emerged as critical in optimizing stent designs and assessing their performance. The aim of this study is to provide an overview of the computational methods of studies based on the finite element (FE) method in the field of coronary stenting and discuss the potential for development and clinical application of stent devices. Additionally, the importance of assessing the ability of computational models is emphasized to represent real-world phenomena, supported by recent guidelines from the American Society of Mechanical Engineers (ASME). Validation processes proposed include comparing model performance with in vivo, ex-vivo, or in vitro data, alongside uncertainty quantification and sensitivity analysis. These methods can enhance the credibility and reliability of in silico simulations, ultimately aiding in the assessment of coronary stent designs in various clinical contexts.

Keywords: atherosclerosis, materials, restenosis, review, validation

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Authors: Sara J. Mills, Sally Howell

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The field of special education has long struggled to bridge the research to practice gap. There is ample evidence from research of effective strategies for students with special needs, but these strategies are not routinely implemented in schools in ways that yield positive results for students. In recent years, the field of special education has turned its focus to implementation science. That is, discovering effective methods of implementing evidence-based practices in school settings. Teacher training is a critical factor in implementation. This study aimed to successfully implement Schema-Based Instruction (SBI) for math problem solving in four classrooms in a special primary school serving students with language deficits, including students with Autism Spectrum Disorders (ASD) and Intellectual Disabilities (ID). Using an action research design that allowed for adjustments and modification to be made over the year-long study, two cohorts of teachers across the school were trained and supported in six-week learning cycles to implement SBI in their classrooms. The learning cycles included a one-day training followed by six weeks of one-on-one or team coaching and three fortnightly cohort group meetings. After the first cohort of teachers completed the learning cycle, modifications and adjustments were made to lesson materials in an attempt to improve their effectiveness with the second cohort. Fourteen teachers participated in the study, including master special educators (n=3), special education instructors (n=5), and classroom assistants (n=6). Thirty-one students participated in the study (21 boys and 10 girls), ranging in age from 5 to 12 years (M = 9 years). Twenty-one students had a diagnosis of ASD, 20 had a diagnosis of mild or moderate ID, with 13 of these students having both ASD and ID. The remaining students had diagnosed language disorders. To evaluate the effectiveness of the implementation approach, both student and teacher data was collected. Student data included pre- and post-tests of math word problem solving. Teacher data included fidelity of treatment checklists and pre-post surveys of teacher attitudes and efficacy for teaching problem solving. Finally, artifacts were collected throughout the learning cycle. Results from cohort 1 and cohort 2 revealed similar outcomes. Students improved in the number of word problems they answered correctly and in the number of problem-solving steps completed independently. Fidelity of treatment data showed that teachers implemented SBI with acceptable levels of fidelity (M = 86%). Teachers also reported increases in the amount of time spent teaching problem solving, their confidence in teaching problem solving and their perception of students’ ability to solve math word problems. The artifacts collected during instruction indicated that teachers made modifications to allow their students to access the materials and to show what they knew. These findings are in line with research that shows student learning can improve when teacher professional development is provided over an extended period of time, actively involves teachers, and utilizes a variety of learning methods in classroom contexts. Further research is needed to evaluate whether these gains in teacher instruction and student achievement can be maintained over time once the professional development is completed.

Keywords: implementation science, mathematics problem solving, research-to-practice gap, schema based instruction

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Nyamela M. ‘Masekhohola, Khanare P. Fumane

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The Lesotho downward trend in mathematics attainment at all levels is compounded by the absence of innovative approaches to teaching and learning in Early Childhood. However, studies have shown that play pedagogy can be used to mitigate the challenges of mathematics education. Despite the benefits of play pedagogy to rural learners, its full potential has not been realized in early childhood care and education classrooms to improve children’s performance in mathematics because the adoption of play pedagogy depends on a strength-based approach. The study explores the potential of play pedagogy to improve mathematics education in early childhood care and education in Lesotho. Strength-based approach is known for its advocacy of recognizing and utilizing children’s strengths, capacities and interests. However, this approach and its promisingattributes is not well-known in Lesotho. In particular, little is known about the attributes of play pedagogy that are essential to improve mathematic education in ECCE programs in Lesotho. To identify such attributes and strengthen mathematics education, this systematic review examines evidence published on the strengths of play pedagogy that supports the teaching and learning of mathematics education in ECCE. The purpose of this review is, therefore, to identify and define the strengths of play pedagogy that supports mathematics education. Moreover, the study intends to understand the rural teachers’ perceived intention of using play in ECCE math classrooms through a strength-based approach. Eight key strengths were found (cues for reflection, edutainment, mathematics language development, creativity and imagination, cognitive promotion, exploration, classification, and skills development). This study is the first to identify and define the strength-based attributes of play pedagogy to improve the teaching and learning of mathematics in ECCE centers in Lesotho. The findings reveal which opportunities teachers find important for improving the teaching of mathematics as early as in ECCE programs. We conclude by discussing the implications of the literature for stimulating dialogues towards formulating strength-based approaches to teaching mathematics, as well as reflecting on the broader contributions of play pedagogy as an asset to improve mathematics in Lesotho and beyond.

Keywords: early childhood education, mathematics education, lesotho, play pedagogy, strength-based approach.

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Authors: Ali Al-Shehri, Abdulaziz Al-Qasim, Abdulkarim Sofi, Ali Yousef

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The oil and gas industry has played a major role in improving the prosperity of mankind and driving the world economy. According to the International Energy Agency (IEA) and Integrated Environmental Assessment (EIA) estimates, the world will continue to rely heavily on hydrocarbons for decades to come. This growing energy demand mandates taking sustainability measures to prolong the availability of reliable and affordable energy sources, and ensure lowering its environmental impact. Unlike any other industry, the oil and gas upstream operations are energy-intensive and scattered over large zonal areas. These challenging conditions require unique sustainability solutions. In recent years there has been a concerted effort by the oil and gas industry to develop and deploy innovative technologies to: maximize efficiency, reduce carbon footprint, reduce CO2 emissions, and optimize resources and material consumption. In the past, the main driver for research and development (R&D) in the exploration and production sector was primarily driven by maximizing profit through higher hydrocarbon recovery and new discoveries. Environmental-friendly and sustainable technologies are increasingly being deployed to balance sustainability and profitability. Analyzing technology and its sustainability impact is increasingly being used in corporate decision-making for improved portfolio management and allocating valuable resources toward technology R&D.This paper articulates and discusses a novel workflow to identify strategic sustainable technologies for improved portfolio management by addressing existing and future upstream challenges. It uses a systematic approach that relies on sustainability key performance indicators (KPI’s) including energy efficiency quotient, carbon footprint, and CO2 emissions. The paper provides examples of various technologies including CCS, reducing water cuts, automation, using renewables, energy efficiency, etc. The use of 4IR technologies such as Artificial Intelligence, Machine Learning, and Data Analytics are also discussed. Overlapping technologies, areas of collaboration and synergistic relationships are identified. The unique sustainability analyses provide improved decision-making on technology portfolio management.

Keywords: sustainability, oil& gas, technology portfolio, key performance indicator

Procedia PDF Downloads 188