Search results for: English as a foreign language (EFL) learning

Authors: Aleksandra Tomic

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According to reliable sources, 4% of all websites is devoted to pornographic material, yet these estimates are often reported to be much higher. The largest internet pornography streaming website reports 21.2 billion visits in 2015 only. Considering the ubiquity of online pornography and the frequency of use, it is necessary to examine its potential influence on the construal of the sexual act and the roles of participants. Apart from the verbal and physical interactions in the pornographic movies themselves, the language in the titles of movies has the power to frame the sexual intercourse. In this study, Critical Discourse Analysis and corpus linguistics approaches will be used to examine the way the sexual intercourse and the roles of the participants are ideologically construed and perpetuated in the Internet pornography discourse. To this end, the study will explore the association between the specific morphosyntactic aspects of the references to performers of both genders, the person and the thematic role, and the gender of referred performer in the corpus of online pornographic movie titles. Distinctive collexeme analysis will be conducted to uncover possible associations between for gender of the performer denoted by the linguistic expression, and the person and thematic role assigned to it in the titles of online pornography movies. Initial results of the chi-square procedure performed on a sample of 295 online pornography movie titles on the largest pornography streaming website ‘Pornhub’ yielded significant results. The use of the three person categories was not equally distributed between genders, X2 (2, N = 106) = 32.52, p < 0.001, with female performers being referred to in the third person in 71.7% of the instances, and speaking in the first person 20.8% of the time, whereas male performers spoke in the first person 68% of the time, and were referred to in the third person in 17% of the instances. Moreover, there was a gender disparity in the assignment of thematic roles, with linguistic expressions for women being assigned the Patient role and men the Agent role in 58.8% of the cases, whereas the roles were reversed in 41.2% of the instances, X2 (1, N = 262) = 8.07633, p < 0.005. The results are discussed in terms of the ideologies surrounding female and male sexuality in the pornography discourse. Potential patterns of power imbalance, objectification, and discrimination are highlighted. Finally, the evidence from psycholinguistic studies on the influence of the language structure on event construal is related to the results of the study.

Keywords: corpus linguistics, gender studies, pornography, thematic roles

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Authors: Lelika Lazarus, Reshma Sookrajh, Kapil S. Satyapal

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Reflecting on teaching is commonly cited as a fundamental practice for personal and professional development. Educational research into the scholarship of teaching and learning anatomy includes engaging in discipline specific literature on teaching, reflecting on individual teaching methods and communicating these findings to peers. The aim of this paper is to formally assess the opinions of senior anatomy instructors regarding the state of anatomical knowledge at their respective institutions. The context of the paper derives from ongoing debates about the perceived decline in standards of anatomical knowledge of medical students and postgraduate learners. An open ended questionnaire was devised consisting of eight direct questions seeking opinions on anatomy teaching, knowledge, and potential educational developments and general thoughts on the teaching of anatomy to medical students. These were distributed to senior anatomy Faculty (identified by the author by their affiliation with the Anatomical Society of Southern Africa) based at the eight national medical schools within the country. A number of key themes emerged. Most senior faculty felt that the standard of medical education at their respective institutions was ‘good.’. However, emphasis was also placed on the ‘quality of teaching’ incorporating clinical scenarios. There were also indications that staff are split into those that are keen to do research and those that are happy to provide teaching to medical students as their primary function. Several challenges were also highlighted such as time constraints within the medical curriculum, the lack of cadavers to reinforce knowledge and gain depth perception and lack of appropriately qualified staff. Recommendations included fostering partnerships with both clinicians and medical scientists into the anatomy curriculum thus improving teaching and research.

Keywords: anatomy, education, reflection, teaching

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Authors: Annisa D. Febryandini

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Annexation is a typical construction that commonly used in Arabic language. The use of the construction appears in Arabic speech such as the speech of Thariq bin Ziyad. The speech as one of the most famous speeches in the history of Islam uses many annexations. This qualitative research paper uses the secondary data by library method. Based on the data, this paper concludes that the speech has two basic structures with some variations and has some grammatical relationship. Different from the other researches that identify the speech in sociology field, the speech in this paper will be analyzed in linguistic field to take a look at the structure of its annexation as well as the grammatical relationship.

Keywords: annexation, Thariq bin Ziyad, grammatical relationship, Arabic syntax

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Authors: Rahm Sibylle

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The core element in most European teacher training concepts consists in practical periods where teacher students may review the chosen profession before going on to their theoretical studies. In Germany, teacher students learn in practical studies about everyday teaching and learning in schools. Teacher students appreciate opportunities to explore school practice and to feel responsible for students’ learning. In practical studies, teacher students often idealize their teacher mentors (and consequently tend to imitate their teaching style) or contrarily feel disappointed about school practice. Concepts of empowerment through practical experience in school-based academic teacher training have to be developed. Our Swiss-German research project COPRA (Coaching in practical periods; funded by the Swiss National Science Foundation (SNF) and the German Research Foundation (DFG), aims at gaining resilient results about the effectiveness of (peer) coaching in practical school periods. To explore innovative ways of accompanying novice teachers in practical periods we consider different cultures of teacher training institutions. School cultures, including teachers’ beliefs and teaching traditions involve different training cultures as starting positions for our intervention study. In our qualitative study, we describe typologies of teacher training institutions by analyzing group discussions with teacher students, mentor teachers and university lecturers concerning participation, cooperation, and relationships. In our paper, we present the design of our intervention study, our coaching concept as well as typologies of teacher training cultures. We discuss opportunities for teacher students to learn through domain-specific (peer) coaching on the background of these typologies.

Keywords: teacher training (practical periods), teacher students' coaching, training cultures (typologies), COPRA (coaching in practical periods)

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Authors: Headman Hebe, Arnold Taringa

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Background of the study: The benefits derived from Environmental and Sustainability Education (ESE) go beyond obtaining knowledge about the environment and the impact of human beings on the environment. Hence, it is sensible to expose learners to various resources that could enable meaningful environment-inclined pedagogy. The schoolgrounds, where they are utilised to promote ESE, benefit holistic learner development. However, empirical evidence, globally, suggests that young children’s contact with nature is declining due to urbanization, safety concerns by parents/guardians, and greater dependency on technology. Modern children spend much time on videogames and social media with very little time in the natural environment. Furthermore, national education departments in numerous countries have made tangible efforts to embed environmental and place-based learning to their school curricula. South Africa is one of those countries whose national school education curriculum advocates for ESE in pedagogy. Nevertheless, there is paucity of research conducted in South Africa on schoolgrounds as potential enablers of ESE and tools to foster a connection between youngsters and the natural environment. Accordingly, this study was essential as it seeks to determine the extent to which environmental learning is accommodated in pedagogy. Significantly, it investigates efforts made to use schoolgrounds for pedagogical purposes to connect children with the natural environment. Therefore, this study was conducted to investigate the accessibility and use of schoolgrounds for environment-inclined pedagogy in Natural and Social Sciences in two schools located in the Mpumalanga Province of South Africa. It tries to answer the question: To what extent are schoolgrounds used to promote environmental and sustainability education in the selected schools?The sub-questions: How do teachers and learners perceive the use of schoolgrounds for environmental and sustainability education activities? How does the organization of schoolgrounds offer opportunities for environmental education activities and accessibility for learners? Research method: This qualitative–interpretive case study used purposive and convenient sampling for participant selection. Forty-six respondents: 40 learners (twenty grade 7 learners per school), 2 school principals and 4 grade 7 participated in this study. Data collection tools were observations, interviews, audio-visual recordings and questionnaires while data analysis was done thematically. Major findings: The findings of the study point to: The lack of teacher training and infrastructure in the schoolgrounds and, no administrative support. Unclear curriculum guidelines on the use of schoolgrounds for ESE. The availability various elements in the schoolgrounds that could aid ESE activities. Learners denied access to certain parts of the schoolgrounds. Lack of time and curriculum demands constrain teachers from using schoolgrounds.

Keywords: affordances, environment and sustainability education, experiential learning, schoolgrounds

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Authors: Homa Parmoon, Narges Hamzeh

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Since today's urban spaces are disposed towards behavioral disorders and lack of security, both qualitative and quantitative aspects of security especially social and physical security are considered as basic necessities in urban planning. This research focused on the variable of place of living, examined social security in the old and new textures, and investigated the amount of residents’ social security in Shiraz including safety, financial, emotional and moral security. To this end, two neighborhoods in region 1 of Shiraz- Qasr-Al-Dasht (old texture) and Moalem (new texture)- were examined through a comparative study of 60 samples lived in two neighborhoods. Data were gathered through two-way ANOVA between the variables of residential context and internal and external security. This analysis represents the significance or insignificance of the model as well as the individual effects of each independent variable on the dependent variable. It was tested by ANCOVA and F-test. Research findings indicated place of living has a significant effect on families’ social security. The safety, financial, emotional, and moral security also represented a great impact on social security. As a result, it can be concluded that social security changes with the changing in place of living.

Keywords: social security, damaged area, two-way ANOVA, Shiraz

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Authors: Dinesh N. Kurup, Celine Perriera

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The economic development of any country is based on the policies adopted by the government from time to time. If these policies are framed by the opinion of the people of the country, there is need for having strong knowledge base, right from the school level. There should be emphasis to provide in education, an ability to take informed decisions regarding socio-scientific issues. It would be better to adopt this practice in high school classrooms to build capacity among future citizens. This study is an attempt to provide a different approach of teaching and learning in classrooms at the high school level in Indian schools for providing opportunity for informed decision making regarding nuclear power use. A unit of work based on the 5E instructional model about the use of nuclear energy is used to build knowledge base and find out the effectiveness in terms of its influence for taking decisions as a future citizen. A sample of 120 students from three high schools using different curricula and teaching and learning methods were chosen for this study. This research used a design based research method. A pre and post questionnaire based on the theory of reasoned action, structured observations, focus group interviews and opportunity for decision making were used during the intervention. The data analysed qualitatively and quantitatively, and the qualitative data were coded into categories based on responses. The results of the study show that students were able to make informed decisions and could give reasons for their decisions. They were enthusiastic in formulating policy making based on their knowledge base and have strong held views and reasoning for their choice.

Keywords: informed decision making, socio-scientific issues, nuclear energy use, policy making

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

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Authors: Ivan Kuzio

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The GIZ/TTC project is the first of its kind in the Middle East, which allows the development of a teaching training programme to degree level based on modern methodologies. The graduates from this college are part of the Saudization programme and will, over the next four years be part of and eventually run the new Colleges of Excellence. The new Colleges of Excellence are being developed to create a local vocationally trained workforce and will run initially alongside the current Colleges of Technology.

Keywords: blended learning, pedagogy, training, key competencies, social skills, cognitive development

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Authors: Anne E. Goodenough

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Students often learn best ‘on the job’ through holistic real-world projects. They need real-world experiences to make classroom learning applicable and to increase their employability. Academics typically value working on projects where new knowledge is created and have a genuine desire to help students engage with learning and develop new skills. They might also have institutional pressure to enhance student engagement, retention, and satisfaction. External organizations - especially non-governmental bodies, charities, and small enterprises - often have fundamental and pressing questions, but lack the manpower and academic expertise to answer them effectively. They might also be on the lookout for talented potential employees. This study examines ways in which these diverse requirements can be met simultaneously by creating three-way projects that provide excellent academic and real-world outcomes for all involved. It studied a range of innovative projects across natural sciences (biology, ecology, physical geography and social sciences (human geography, sociology, criminology, and community engagement) to establish how to best harness the potential of this powerful approach. Focal collaborations included: (1) development of practitioner-linked modules; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; and (4) immersive fieldwork projects in novel locations to allow students engage first-hand with contemporary issues as diverse as rhino poaching in South Africa, segregation in Ireland, and gun crime in Florida. Although there was no ‘magic formula’ for success, the approach was found to work best when small projects were developed that were achievable in a short time-frame, both to tie into modular curricula and meet the immediacy expectations of many link organizations. Bigger projects were found to work well in some cases, especially when they were essentially a series of linked smaller projects, either running concurrently or successively with each building on previous work. Opportunities were maximized when there were tangible benefits to the link organization as this generally increased organization investment in the project and motivated students too. The importance of finding the right approach for a given project was found to be key: it was vital to ensure that something that could work effectively as an independent research project for one student, for example, was not shoehorned into being a project for multiple students within a taught module. In general, students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. Several students have gone on to do further work with the link organization in a voluntary capacity or as paid staff, or used the experiences to help them break into the ever-more competitive job market in other ways. Although this approach involves a substantial time investment, especially from academics, the benefits can be profound. The approach has strong potential to engage students, help retention, improve student satisfaction, and teach new skills; keep the knowledge of academics fresh and current; and provide valuable tangible benefits for link organizations: a real triple win.

Keywords: authentic learning, curriculum development, effective education, employability, higher education, innovative pedagogy, link organizations, student experience

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Authors: Mostafa Jafari

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Religious tourism is the core strategy of shaping Iranian's life-style. Why and How? This paper answers to this question. Theoretical base: From strategic marketing point of view, Life style is pattern of believes values, interests and acts. Strategy can be defined as a set of continuous important decisions. Here, strategy is making decisions about the target place and vehicle of touristic travel due to reform and redefine the self-identity and shaping life style. Methodology: Target society of this research is the selected residents of three provinces at northwest of Iran. The data collection instrument is interview and questionnaire and the collected data analysis by SEM (structural Equation Modeling) and LISREL software. Results: The primary results show that variety of touristic travels play an important role on shaping new life style of Iranian people. The target places of touristic travel (Europe, USA. Japan and etc.) are at the second priority. The number of foreign friends is at the third position. The fourth criteria are the number of travels. Among all kind of touristic travels the religious tourism from competitive point of view plays the main role. Findings: The geometry of Iranian life style are shaping and reshaping through some domestic and international tourism strategies particular religious strategy. During the dynamic trend of identity redefine, so many Iranians put the quantity and quality of their touristic travel on the first priority.

Keywords: religious tourism, core strategy, shaping life style

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Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Mashaal Hooda

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The rationale for conducting this action research was to increase students' Academic Achievement (AA) contexts of studying/researching by employing the Goal Setting intervention (GS). The purposive sample consisted of 10 female undergraduate students at a university in Dubai. The intervention was introduced through workshop classes conducted online. The pre-intervention consisted of discussions concentrating on participants' research contexts amidst a pandemic. The GS moderators were implemented in the class, followed by scaffolding and mentoring interactions and self-reflective accounts of students' actions and feelings of using the intervention to better plan and structure their dissertation tasks. The research incorporated a Mixed Methods Methodology (MMM). Quantitative data collection took place through surveys, while qualitative data were collected using semi-structured interviews. Triangulation of the emergent themes showed a positive increase in students achievable GS, self-regulatory study skills, feedback-seeking behaviours, research organisation and synthesis, self-reflection and Academic Resilient (AR) attitudes amalgamate to enhance students' AA outcomes. Though, students' intrinsic motivational levels to study and research observed minor changes only. Nonetheless, the pebble in the shoe was removed as students AA contexts improved in undertaking better actionable steps for their research. Therefore, the GS intervention enabled students to set, balance, and achieve academic goals while catering to their academic anxieties, mental health concerns, and adaptability to the e-learning platforms amidst the COVID-19 pandemic. Despite the wide-scale changes the pandemic brought to the teaching and learning communities, the GS intervention served as a targeted intervention to help students maintain their achievement contexts in a goal-oriented way.

Keywords: academic achievement, acadeic resilience, COVID-19, goal setting

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Ju Shan Lin

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The challenges for traditional industries in Taiwan the past few years are the changes of overall domestic and foreign industry structure, the entrepreneurs not only need to keep on improving their profession skills but also continuously research and develop new products. It is also necessary for the all traditional industries to keep updating the business strategy, let the enterprises continue to progress, and won't be easily replaced by the other industries. The traditional industry in Taiwan attach great importance to the field of enterprises upgrading and innovation in recent years, by the enterprise innovation and transformation can enhance the overall business situation also enable them to obtain more additional profits than in the past. Except the original industry structure's need to transform and upgrade, the brand's business and marketing strategy are also essential. This study will take a certain plastic company as case analysis, for the brand promotion of traditional industries, brand values and business innovation model for further exploration. It will also be mentioned that the other traditional industries cases which were already achieved success on the enterprise's upgrading and innovation, at the same time, the difficulties which they faced with and the way they overcome will be explored as well. This study will use the case study method combined with expert interviews to discuss and analyze this certain plastic company's current business situation, the existing products and the possible trends in the future. Looking forward to providing an innovative business model that will enable this plastic company to upgrade its corporate image and the brand could transform successfully.

Keywords: brand marketing strategy, enterprise upgrade, industrial transformation, traditional industry

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Authors: Marco Frieslaar, Bing Chu, Eric Rogers

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Stroke is a devastating illness that is the second biggest cause of death in the world (after heart disease). Where it does not kill, it leaves survivors with debilitating sensory and physical impairments that not only seriously harm their quality of life, but also cause a high incidence of severe depression. It is widely accepted that early intervention is essential for recovery, but current rehabilitation techniques largely favor hospital-based therapies which have restricted access, expensive and specialist equipment and tend to side-step the emotional challenges. In addition, there is insufficient funding available to provide the long-term assistance that is required. As a consequence, recovery rates are poor. The relatively unexplored solution is to develop therapies that can be harnessed in the home and are formulated from technologies that already exist in everyday life. This would empower individuals to take control of their own improvement and provide choice in terms of when and where they feel best able to undertake their own healing. This research seeks to identify how effective post-stroke, rehabilitation therapy can be applied to upper limb mobility, within the physical context of a home rather than a hospital. This is being achieved through the design and construction of an automation scheme, based on iterative learning control and the Riener muscle model, that has the ability to adapt to the user and react to their level of fatigue and provide tangible physical recovery. It utilizes a SMART Phone and laptop to construct an iterative learning control (ILC) system, that monitors upper arm movement in three dimensions, as a series of exercises are undertaken. The equipment generates functional electrical stimulation to assist in muscle activation and thus improve directional accuracy. In addition, it monitors speed, accuracy, areas of motion weakness and similar parameters to create a performance index that can be compared over time and extrapolated to establish an independent and objective assessment scheme, plus an approximate estimation of predicted final outcome. To further extend its assessment capabilities, nerve conduction velocity readings are taken by the software, between the shoulder and hand muscles. This is utilized to measure the speed of response of neuron signal transfer along the arm and over time, an online indication of regeneration levels can be obtained. This will prove whether or not sufficient training intensity is being achieved even before perceivable movement dexterity is observed. The device also provides the option to connect to other users, via the internet, so that the patient can avoid feelings of isolation and can undertake movement exercises together with others in a similar position. This should create benefits not only for the encouragement of rehabilitation participation, but also an emotional support network potential. It is intended that this approach will extend the availability of stroke recovery options, enable ease of access at a low cost, reduce susceptibility to depression and through these endeavors, enhance the overall recovery success rate.

Keywords: home-based therapy, iterative learning control, Riener muscle model, SMART phone, stroke rehabilitation

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Bassem Nassar, Wessam Hussein, Medhat Mokhtar

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The crucial concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems in order to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important in order to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the aforementioned problem coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions and the results shows that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: space telemetry monitoring, multivariate analysis, PCA algorithm, space operations

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Wichai Srisud, Shunnawat Pungbangkradee, Sukanya Chaemchoy

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This research study aims to analyze and assess school management guidelines designed to enhance the level of Student School Engagement of students at Bangkok Christian College, according to three following primary objectives: 1) to evaluate the level of Student School Engagement among Bangkok Christian College students, 2) to examine the Priority Needs Index of school management for promoting an optimum level of Student School Engagement among Bangkok Christian College students, and 3) to develop additional guidelines for school management to further enhance the level of Student School Engagement of Bangkok Christian College students. The research was conducted using Explanatory Design research methodology, with data obtained from a sample comprised of 291 students and 6 administrative personnel. The research findings indicated that: 1) The overall level of Student School Engagement was high. Emotional engagement averaged at the highest level, followed by Behavioral Engagement and Cognitive Engagement, respectively. 2) The Priority Needs Index of school management for promoting Student School Engagement of Bangkok Christian College students was examined, revealing that Evaluation averaged at the highest PNI level, followed by Planning and Implementation, respectively. 3) Guidelines for school management to enhance Student School Engagement of Bangkok Christian College students should consist of four approaches: 3.1) A Cognitive Engagement Enhancing Approach, which must include (1) fostering students’ problem-solving flexibility, and their ability to devise solutions for overcoming potential challenges, and (2) encouraging students to deal effectively with academic setbacks, rather than becoming overwhelmed by what they may perceive as failures, 3.2) An Emotional Engagement Enhancing Approach, cultivating students’ interests, aspirations and goals in learning to maximize emotional investment in their academic pursuits, and 3.3) A Behavioral Engagement Enhancing Approach, for elevating students’ focus and attentiveness during learning, and improving their ability to avoid distractions during study time.

Keywords: school engagement, guidelines for school management

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Authors: Abdul Wakeel, Hafeez Ur Rehman, Muhammad Umair Mubarak

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Rice is the second most important staple food in Pakistan after wheat. It is not only a healthy food for the people of all age groups but also a source of foreign exchange for Pakistan. Instead of bright history for Basmati rice production, we are suffering from multiple problems reducing yield and quality as well. Rice lodging and water shortage for an-aerobic rice production system is among major glitches of it. Due to water shortage an-aerobic rice production system has to be supplemented or replaced by aerobic rice system. Aerobic rice system has been adopted for production of non-basmati rice in many parts of the world. Also for basmati rice, significant efforts have been made for aerobic rice production, however still has to be improved for effective recommendations. Among two major issues for aerobic rice, weed elimination has been solved to great extent by introducing suitable herbicides, however, low yield production due weak grains and panicle sterility is still elusive. It has been reported that potassium (K) has significant role to decrease panicle sterility in cereals. Potassium deficiency is obvious for rice under aerobic rice production system due to lack of K gradient coming with irrigation water and lowered indigenous K release from soils. Therefore it was hypothesized that K application under aerobic rice production system may improve the rice yield by decreasing panicle sterility. Results from pot and field experiments confirm that application of K fertilizer significantly increased the rice grain yield due to decreased panicle sterility and improving grain health. The quality of rice was also improved by K fertilization.

Keywords: DSR, Basmati rice, aerobic, potassium

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Authors: Ogunrinde Roseline Bosede

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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: differential equations, numerical, polynomial, initial value problem, differential equation

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Authors: York Neudel

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The phenomenon of tourism has been considered as tool to overcome cultural frontiers, to comprehend the other and to cope with mutual mistrust and suspicion. Well, that has been a myth, at least when it comes to mass-tourism. Other approaches, like community-based tourism, still are based on the idea of embracing the other in order to help or to understand the cultural difference. In 1997, two American NGOs incentivized a tourism-project in a community in the highlands of Ecuador, in order to protect the cloud forest from destructive exploitation of its own inhabitants. Nineteen years after that, I analyze in this investigation the interactions between the Ecuadorian hosts in the mestizo-community of Yunguilla and the foreign tourist in the quest for “authentic life” in the Ecuadorian cloud forest. As a sort of “contemporary pilgrim” the traveller tries to find authenticity in other times and places far away from their everyday life in Europe or North America. Therefore, tourists are guided by stereotypes and expectations that are produced by the touristic industry. The host, on the other hand, has to negotiate this pre-established imaginary. That generates a kind of theatre-play with front- and backstage in organic gardens, little fabrics and even private housing, since this alternative project offers to share the private space of the host with the tourist in the setting the community-based tourism. In order to protect their privacy, the community creates new hybrid spaces that oscillate between front- and backstages that culminates in a game of hide and seek – a phenomenon that promises interesting frictions for an anthropological case-study.

Keywords: Tourism, Authenticity, Community-based tourism, Ecuador, Yunguilla

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Authors: Yujiang Wu

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As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

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Authors: Sedigheh Abbasnasab Sardareh

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The current study investigates ESL teachers' voices in order to formulate further research on the effectiveness of the SBOA practices. It is an attempt to find out (1) what are ESL experienced teachers’ perceptions, experiences, attitudes, and beliefs of SBOA; (2) what teaching and learning aspects of SBOA needs focus to enhance its effectiveness; (3) external issues related to the implementation of SBOA; (4) internal issues related to the implementation of SBOA; and also (5) perceived recommendations on SBOA. The study utilized focus group discussion sessions. 9 experienced ESL (5 females and 4 males) teachers were selected based on the consent letters sent to them. These teachers had over 20 years experience in both traditional and SBOA-type assessment and the train-the-trainer experts recommended by the Ministry of Education. Respondents were guided with open-ended questions to extracts their perceived experiences implementing SBOA guided structurally by the author as the moderator. Data were first discussed with the respondents for further clarifications and then only analyzed and re-confirmed with some recommendations before the final presentation of this preliminary results were presented here. The focus group discussions yielded some important perceived views on the SBOA implementation. Some of the themes were discussed and some recommendations were proposed for further in-depth study by the Ministry of Education. Some of the future directions based on the results were also put forward. Some external and internal variables were important in order for successful implementation of SBOA. Mere implementing a policy should be taken into consideration because this might impede some of the teaching and learning processes both by the classroom stakeholders such as teachers and student. More research methods such as the use of questionnaires could be utilized to further investigate to large populations of teacher educators in Malaysia.

Keywords: school based oral assessment, Malaysia, ESL, focus group discussion

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Authors: Hasibul Kabir, Samin Shahriar Tokey, Md. Tofazzal Hossain

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One of the most necessary things in the present time is raising social awareness about global warming and climate change among the people. Though many types of mediums and techniques have been used to teach people about this global phenomenon, there are still more effective ways to reach people with useful information about global warming. As many traditional methods to teach people about global warming and climate change did not work well, video games were overdue. To learn how effective a video game can be in this regard, we developed a Video game, "Historia's Nightmare," that teaches people about Global warming and climate change. The game was designed to entertain people and give them an idea about the reasons and consequences of global warming and climate change while not being like traditional educational games. The game threw a mini quiz consisting of two MCQs based on the information shown in the game, where a gamer had to pass the quiz to reach the next level. We published the game on different platforms to let all types of people play and complete our experiment effectively. The game continuously communicated with our server to send data about gamers' performance. We observed the data, including the participants' performance, time spent, quiz score, and the in-game feedback on a regular basis, and finally came to a verdict. In our experiment, we have found that most participants positively accepted the game and learned something new. The participants who spent more on our game performed better in both quiz and the game. Our experiment's result demonstrates that video games can be a great way to teach people something, particularly to raise social awareness about global warming and climate change. It also demonstrates that the game can be a significant element in education and learning improvement.

Keywords: video game, global warming, social awareness, climate change, education, feedback

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Authors: Ese Urhie, Olabisi Popoola, Obindah Gershon, Olabanji Ewetan

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Modern agriculture involves the use of improved tools and equipment (instead of crude and ineffective tools) like tractors, hand operated planters, hand operated fertilizer drills and combined harvesters - which increase agricultural productivity. Farmers in Nigeria still have huge potentials to enhance their productivity. The study argues that the increase in agricultural output due to increased productivity, orchestrated by modern agriculture will promote forward linkages and opportunities in the processing sub-sector; both the manufacturing of machines and the processing of raw materials. Depending on existing incentives, foreign investment could be attracted to augment local investment in the sector. The availability of raw materials in large quantity – which prices are competitive – will attract investment in other industries. In addition, potentials for backward linkages will also be created. In a nutshell, adopting the unbalanced growth theory in favour of the agricultural sector could engender industrialization in a country with untapped potentials. The paper highlights the numerous potentials of modern agriculture that are yet to be tapped in Nigeria and also provides a theoretical analysis of how the realization of such potentials could promote industrialization in the country. The study adopts the Lewis’ theory of structural–change model and Hirschman’s theory of unbalanced growth in the design of the analytical framework. The framework will be useful in empirical studies that will guide policy formulation.

Keywords: modern agriculture, industrialization, structural change model, unbalanced growth

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