Search results for: evolving learning

Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

Procedia PDF Downloads 139

Authors: Balram Bhushan

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The emergence of social entrepreneurship challenges the strict categorization of not-for-profit, for-profit and hybrid organizations. Although the blurring of boundaries helps social entrepreneurial organizations (SEOs) make better use of emerging opportunities, it poses a significant challenge while mobilizing money from different sources. Additionally, for monetary resources, the legal framework of the host country may further complicate the issue by imposing strict accounting standards. Under such circumstances, the resource providers fail to recognize the suitable engagement strategy with the SEO of their choice. Based on the process of value creation and value capture, this paper develops a guiding framework for resource providers to design an appropriate mix of engagement with the identified SEOs. Essentially, social entrepreneurship creates value at the societal level, but value capture is a characteristic of an organization. Additionally, SEOs prefer value creation over value capture. The paper argued that the nature of the relationship between value creation and value capture determines the extent of blurred boundaries of the organization. Accordingly, synergistic, antagonistic and sequential relationships were proposed between value capture and value creation. When value creation is synergistically associated with value creation, the preferred nature of such action falls within the nature of for-profit organizations within the strictest legal framework. Banks offering micro-loans are good examples of this category. Opposite to this, the antagonist relationship between value creation and value capture, where value capture opportunities are sacrificed for value creation, dictates non-profit organizational structure. Examples of this category include non-government organizations and charity organizations. Finally, the sequential relationship between value capture opportunities is followed for value creation opportunities and guides the action closer to the hybrid structure. Examples of this category include organizations where a non-for-profit unit controls for-profit units of the organization either legally or structurally. As an SEO may attempt to utilize multiple entrepreneurial opportunities falling across any of the three relationships between value creation and value capture, the resource providers need to evaluate an appropriate mix of these relationships before designing their engagement strategies. The paper suggests three guiding principles for the engagement strategy. First, the extent of investment should be proportional to the synergistic relationship between value capture and value creation. Second, the subsidized support should be proportional to the sequential relationship. Finally, the funding (charity contribution) should be proportional to the antagonistic relationship. Finally, the resource providers are needed to keep a close watch on the evolving relationship between value creation and value capture for introducing appropriate changes in their engagement strategy.

Keywords: social entrepreneurship, value creation, value capture, entrepreneurial opportunity

Procedia PDF Downloads 133

Authors: Malik Imtiaz Ahmad

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Human beings are the super organism granted the gift of consciousness of life by the Almighty God and endowed with an intrinsic legal value to their humanity that shall be guarded and protected respecting dignity regardless of your cultural, religious, race, or physical background; you want to be treated equally for a reason for being human. Islam graces the essential integrity of humanity and confirms the freedom and accountability impact on individuality and the open societal sphere, including the moral, economic, and political aspects. Human Rights allow people to live with dignity, equality, justice, freedom, and peace. The Kantian approach to morality expresses that ethical actions follow universal moral laws. Hence, human rights are based upon the normative approaches setting the international standards to promote, guard, and protect the fundamental rights of the people. Islam is a divine religion commanding human rights based upon the principles of social justice and regulates all facets of the moral and spiritual ethics of Muslims besides bringing balance abreast in the non-Muslims to respect their lives with safety and security and property. The Canon law manifests the faith and equality amongst Christianity, regulating the communal dignity to build and promote the sanctity of Holy life (can. 208 to 223). This concept of the community is developed after the insight of the Islamic 'canon law', which is the code of revelation itself and inseparable from the natural part of the salvation of mankind. The etymology and history of human rights is a polemical debate in a preview of Islamic and Western culture. On the other hand, international law is meticulous about the fundamental part of Conon law that focuses on the communal political, social and economic relationship. The evolving process of human rights is considered to be an exclusive universal thought regarding an open society that forms a legal base for the constituent of international instruments of the protection of Human Rights, viz. UDHR. On the other side, Muslim scholars emphasize that human rights are devolving around Islamic law. Both traditions need a dire explanation of contemporary openness for bringing the harmonious universal law acceptable and applicable to the international communities concerning the anthropology of political, economic, and social aspects of a human being.

Keywords: human rights-based approach (HRBA), human rights in Islam, evolution of universal human rights, conflict in western, Islamic human rights

Procedia PDF Downloads 89

Authors: María González Alriols, Itziar Egües, María A. Andrés, Mirari Antxustegi

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Several collaborative learning proposals were prepared to be applied in the laboratory sessions of chemistry in the first course of engineering studies. The aim was to engage the students from the beginning and to avoid absenteeism as well as to reach a more homogeneous level in the class. The students, divided into small groups of four or five mates, were asked to do an exercise before having the practical session in the lab. Precisely, each one of the groups was asked to study the theoretical fundamentals and the practical aspects of one lab session and to prepare a didactical video with this content, including the materials, equipment and reactants required, and the detailed experimental procedure. Furthermore, they should include the performance of the experiment step by step, indicating the faced difficulties and the obtained results and conclusions. After watching the video of this precise activity, the other groups of students would go to the lab to put into practice the session following the commands explained in the video. The evaluation of the video activity that is worth the 50% of the total mark of the laboratory sessions, is done depending on the success that the other groups of students had while doing the practical session that was explained in the video. This means that the successful transmission of knowledge to the rest of the mates in the class through the video was compulsory to pass the practical sessions and the subject. The other 50% of the mark depended on the understanding of the other students’ explanations and the success in the corresponding practical sessions. The experience was found to be very positive, as the engagement level was considerably higher, the absenteeism lower and the attitude in the laboratory much more responsible. The materials, reactants and equipment were used carefully, and no incidents were registered. Furthermore, the fact of having peer experts was useful to encourage critical thinking in a more relaxed way, with the teacher figure in a secondary position. Finally, the academic achievements were satisfactory as well, with a high percentage of students over the level required for passing the subject.

Keywords: collaborative learning, engineering instruction, chemistry, laboratory sessions

Procedia PDF Downloads 166

Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

Procedia PDF Downloads 177

Authors: Branislav Kovačević, Andrej Pilipović, Zoran Novčić, Marina Milović, Lazar Kesić, Milan Drekić, Saša Pekeč, Leopold Poljaković Pajnik, Saša Orlović

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Poplars present one of the most important tree species used for phytoremediation in the northern hemisphere. They can be used either as direct “cleaners” of the contaminated soils or as buffer zones preventing the contaminant plume to the surrounding environment. In order to produce appropriate planting material for this purpose, there is a long process of the breeding of the most favorable candidates. Although the development of the poplar propagation technology has been evolving for decades, white poplar nursery production, as well as the establishment of short-rotation coppice plantations, still considerably depends on the success of hardwood cuttings’ survival. This is why easy rooting is among the most desirable properties in white poplar breeding. On the other hand, there are many opportunities for the optimization of the technological procedures in order to meet the demands of particular genotype (clonal technology). In this study the effect of the term of hardwood cuttings’ preparation of four white poplar clones on their survival and further growth of rooted cuttings in nursery conditions were tested. There were three terms of cuttings’ preparation: the beginning of February (2nd Feb 2023), the beginning of March (3rd Mar 2023) and the end of March (21nd Mar 2023), which is regarded as the standard term. The cuttings were stored in cool chamber at 2±2°C. All cuttings were planted on the same date (11th Apr 2023), in soil prepared with rotary tillage, and then cultivated by usual nursey procedures. According to the results obtained after the bud set (29th Sept 2023) there were significant differences in the survival and growth of rooted cuttings between examined terms of cutting preparation. Also, there were significant differences in the reaction of examined clones on terms of cutting preparation. In total, the best results provided cuttings prepared at the first term (2nd Feb 2023) (survival rate of 39.4%), while performance after two later preparation terms was significantly poorer (20.5% after second and 16.5% after third term). These results stress the significance of dormancy preservation in cuttings of examined white poplar clones for their survival, which could be especially important in context of climate change. Differences in clones’ reaction to term of cutting preparation suggest necessity of adjustment of the technology to the needs of particular clone i.e. design of clone specific technology.

Keywords: rooting, Populus alba, nursery, clonal technology

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Authors: Mohammad Hassanzadeh

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As far as incidental vocabulary learning is concerned, the basic contention of the Involvement Load Hypothesis (ILH) is that retention of unfamiliar words is, generally, conditional upon the degree of involvement in processing them. This study examined input modality and incidental vocabulary uptake in a task-induced setting whereby three variously loaded task types (marginal glosses, fill-in-task, and sentence-writing) were alternately assigned to one group of students at Allameh Tabataba’i University (n=2l) during six classroom sessions. While one round of exposure was comprised of the audiovisual medium (TV talk shows), the second round consisted of textual materials with approximately similar subject matter (reading texts). In both conditions, however, the tasks were equivalent to one another. Taken together, the study pursued the dual objectives of establishing a litmus test for the ILH and its proposed values of ‘need’, ‘search’ and ‘evaluation’ in the first place. Secondly, it sought to bring to light the superiority issue of exposure to audiovisual input versus the written input as far as the incorporation of tasks is concerned. At the end of each treatment session, a vocabulary active recall test was administered to measure their incidental gains. Running a one-way analysis of variance revealed that the audiovisual intervention yielded higher gains than the written version even when differing tasks were included. Meanwhile, task 'three' (sentence-writing) turned out the most efficient in tapping learners' active recall of the target vocabulary items. In addition to shedding light on the superiority of audiovisual input over the written input when circumstances are relatively held constant, this study for the most part, did support the underlying tenets of ILH.

Keywords: Keywords— Evaluation, incidental vocabulary learning, input mode, Involvement Load Hypothesis, need, search.

Procedia PDF Downloads 279

Authors: Taiebe Shokri, Shahram Yazdani, Leila Afshar, Soleiman Ahmadi

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Introduction: The importance of professionalism in higher education not only determines the appropriate and inappropriate behaviors and guides faculty members in the implementation of professional responsibilities, but also guarantees faculty members' adherence to professional principles and values, ensures the quality of teaching and facilitator will be the teaching-learning process in universities and will increase the commitment to meet the needs of students as well as the development of an ethical culture based on ethics. Therefore, considering the important role of medical education teachers to prepare teachers and students in the future, the need to determine the concept of professional teacher and teacher, and the characteristics of teacher professionalism, we have explained the concept of professionalism in teachers in this study. Methods: The concept analysis method used in this study was Walker and Avant method which has eight steps. Walker and Avant state the purpose of concept analysis as follows: The process of distinguishing between the defining features of a concept and its unrelated features. The process of concept analysis includes selecting a concept, determining the purpose of the analysis, identifying the uses of the concept, determining the defining features of the concept, identifying a model, identifying boundary and adversarial items, identifying the precedents and consequences of the concept, and defining empirical references. is. Results: Professionalism in its general sense, requires deep knowledge, insight, creating a healthy and safe environment, honesty and trust, impartiality, commitment to the profession and continuous improvement, punctuality, criticism, professional competence, responsibility, and Individual accountability, especially in social interactions, is an effort for continuous improvement, the acquisition of these characteristics is not easily possible and requires education, especially continuous learning. Professionalism is a set of values, behaviors, and relationships that underpin public trust in teachers.

Keywords: concept analysis, medical education, professionalism, faculty members

Procedia PDF Downloads 154

Authors: Paul Lam, Kevin Wong, Chi Him Chan

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Constant practicing and accurate, immediate feedback are the keys to improving students’ speaking skills. However, traditional oral examination often fails to provide such opportunities to students. The traditional, face-to-face oral assessment is often time consuming – attending the oral needs of one student often leads to the negligence of others. Hence, teachers can only provide limited opportunities and feedback to students. Moreover, students’ incentive to practice is also reduced by their anxiety and shyness in speaking the new language. A mobile app was developed to use artificial intelligence (AI) to provide immediate feedback to students’ speaking performance as an attempt to solve the above-mentioned problems. Firstly, it was thought that online exercises would greatly increase the learning opportunities of students as they can now practice more without the needs of teachers’ presence. Secondly, the automatic feedback provided by the AI would enhance students’ motivation to practice as there is an instant evaluation of their performance. Lastly, students should feel less anxious and shy compared to directly practicing oral in front of teachers. Technically, the program made use of speech-to-text functions to generate feedback to students. To be specific, the software analyzes students’ oral input through certain speech-to-text AI engine and then cleans up the results further to the point that can be compared with the targeted text. The mobile app has invited English teachers for the pilot use and asked for their feedback. Preliminary trials indicated that the approach has limitations. Many of the users’ pronunciation were automatically corrected by the speech recognition function as wise guessing is already integrated into many of such systems. Nevertheless, teachers have confidence that the app can be further improved for accuracy. It has the potential to significantly improve oral drilling by giving students more chances to practice. Moreover, they believe that the success of this mobile app confirms the potential to extend the AI-assisted assessment to other language skills, such as writing, reading, and listening.

Keywords: artificial Intelligence, mobile learning, oral assessment, oral practice, speech-to-text function

Procedia PDF Downloads 103

Authors: Boubacar Niang, Denis Raulin

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This paper presents the design of a dedicated board for learning and programming with ATMEL AVR new generation micro controller’s family. This board designed as a "shield" for the Arduino Uno allows us to focus on the design and programming of basic micro controller functionalities in high level language with a considerable time saving because of dealing with additional components is not required.

Keywords: Arduino, microcontroller, programming, language

Procedia PDF Downloads 584

Authors: Sima Modirkhameneh, Mohammad Mohammadpanah

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In the process of EFL teachers’ development, self-led reflection (SLR) is thought to have an imperative role because it may help teachers analyze, evaluate, and contemplate what is happening in their classes. Such contemplations can not only enhance the quality of their instruction and provide better learning environments for learners but also improve the quality of their classroom management (CM). Accordingly, understanding the effect of teachers’ SLR practices may help us gain valuable insights into what possible modifications SLR may bring about in all aspects of EFL teachers' practitioners, especially their CM. The main purpose of this case study was, thus, to investigate the impact of SLR practices of 12 Iranian EFL teachers on their CM based on the universal classroom management checklist (UCMC). In addition, another objective of the current study was to have a clear image of EFL teachers’ perceptions of their own SLR practices and their possible outcomes. By conducting repeated reflective interviews, observations, and feedback of the participants over five teaching sessions, the researcher analyzed the outcomes qualitatively through the process of meaning categorization and data interpretation based on the principles of Grounded Theory. The results demonstrated that EFL teachers utilized SLR practices to improve different aspects of their language teaching skills and CM in different contexts. Almost all participants had positive comments and reactions about the effect of SLR on their CM procedures in different aspects (expectations and routines, behavior-specific praise, error corrections, prompts and precorrections, opportunity to respond, strengths and weaknesses of CM, teachers’ perception, CM ability, and learning process). Otherwise stated, results implied that familiarity with the UCMC criteria and reflective practices contributes to modifying teacher participants’ perceptions about their CM procedure and utilizing the reflective practices in their teaching styles. The results are thought to be valuably beneficial for teachers, teacher educators, and policymakers, who are recommended to pay special attention to the contributions as well as the complexity of reflective teaching. The study concludes with more detailed results and implications and useful directions for future research.

Keywords: classroom management, EFL teachers, reflective practices, self-led reflection

Procedia PDF Downloads 54

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

Procedia PDF Downloads 167

Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

Procedia PDF Downloads 134

Authors: Sara T. K. Li, Belinda H. J. Chung, Jeffery C. N. Yip, Janet H. Hsiao

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Music notation and text reading both involve statistical learning of music or linguistic structures. However, it remains unclear how music reading expertise influences text reading behavior. The present study examined this issue through an eye-tracking study. Chinese-English bilingual musicians and non-musicians read English sentences, Chinese sentences, musical phrases, and sentences in Tibetan, a language novel to the participants, with their eye movement recorded. Each set of stimuli consisted of two conditions in terms of structural regularity: syntactically correct and syntactically incorrect musical phrases/sentences. They then completed a sentence comprehension (for syntactically correct sentences) or a musical segment/word recognition task afterwards to test their comprehension/recognition abilities. The results showed that in reading musical phrases, as compared with non-musicians, musicians had a higher accuracy in the recognition task, and had shorter reading time, fewer fixations, and shorter fixation duration when reading syntactically correct (i.e., in diatonic key) than incorrect (i.e., in non-diatonic key/atonal) musical phrases. This result reflects their expertise in music reading. Interestingly, in reading Tibetan sentences, which was novel to both participant groups, while non-musicians did not show any behavior differences between reading syntactically correct or incorrect Tibetan sentences, musicians showed a shorter reading time and had marginally fewer fixations when reading syntactically correct sentences than syntactically incorrect ones. However, none of the musicians reported discovering any structural regularities in the Tibetan stimuli after the experiment when being asked explicitly, suggesting that they may have implicitly acquired the structural regularities in Tibetan sentences. This group difference was not observed when they read English or Chinese sentences. This result suggests that music reading expertise facilities reading texts in a novel language (i.e., Tibetan), but not in languages that the readers are already familiar with (i.e., English and Chinese). This phenomenon may be due to the similarities between reading music notations and reading texts in a novel language, as in both cases the stimuli follow particular statistical structures but do not involve semantic or lexical processing. Thus, musicians may transfer their statistical learning skills stemmed from music notation reading experience to implicitly discover structures of sentences in a novel language. This speculation is consistent with a recent finding showing that music reading expertise modulates the processing of English nonwords (i.e., words that do not follow morphological or orthographic rules) but not pseudo- or real words. These results suggest that the modulation of music reading expertise on language processing depends on the similarities in the cognitive processes involved. It also has important implications for the benefits of music education on language and cognitive development.

Keywords: eye movement behavior, eye-tracking, music reading expertise, sentence reading, structural regularity, visual processing

Procedia PDF Downloads 380

Authors: Lik Hang Gary Wong

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Background: Practice learning is crucial for preparing the healthcare profession to meet the real challenge upon graduation. Students are required to demonstrate their competence in managing interpersonal challenges, such as teamwork with other professionals and communicating well with the service users, during the placement. Such competence precedes clinical practice, and it may eventually affect students' actual performance in a clinical context. Unfortunately, there were limited studies investigating how such competence affects students' performance in practice learning. Objectives: The aim of this study is to investigate how self-rated interpersonal competence affects students' actual performance during clinical placement. Methods: 40 occupational therapy students from Hong Kong were recruited in this study. Prior to the clinical placement (level two or above), they completed an online survey that included the Interpersonal Communication Competence Scale (ICCS) measuring self-perceived competence in interpersonal communication. Near the end of their placement, the clinical educator rated students’ performance with the Student Practice Evaluation Form - Revised edition (SPEF-R). The SPEF-R measures the eight core competency domains required for an entry-level occupational therapist. This study adopted the cross-sectional observational design. Pearson correlation and multiple regression are conducted to examine the relationship between students' interpersonal communication competence and their actual performance in clinical placement. Results: The ICCS total scores were significantly correlated with all the SPEF-R domains, with correlation coefficient r ranging from 0.39 to 0.51. The strongest association was found with the co-worker communication domain (r = 0.51, p < 0.01), followed by the information gathering domain (r = 0.50, p < 0.01). Regarding the ICCS total scores as the independent variable and the rating in various SPEF-R domains as the dependent variables in the multiple regression analyses, the interpersonal competence measures were identified as a significant predictor of the co-worker communication (R² = 0.33, β = 0.014, SE = 0.006, p = 0.026), information gathering (R² = 0.27, β = 0.018, SE = 0.007, p = 0.011), and service provision (R² = 0.17, β = 0.017, SE = 0.007, p = 0.020). Moreover, some specific communication skills appeared to be especially important to clinical practice. For example, immediacy, which means whether the students were readily approachable on all social occasions, correlated with all the SPEF-R domains, with r-values ranging from 0.45 to 0.33. Other sub-skills, such as empathy, interaction management, and supportiveness, were also found to be significantly correlated to most of the SPEF-R domains. Meanwhile, the ICCS scores correlated differently with the co-worker communication domain (r = 0.51, p < 0.01) and the communication with the service user domain (r = 0.39, p < 0.05). It suggested that different communication skill sets would be required for different interpersonal contexts within the workplace. Conclusion: Students' self-perceived interpersonal communication competence could predict their actual performance during clinical placement. Moreover, some specific communication skills were more important to the co-worker communication but not to the daily interaction with the service users. There were implications on how to better prepare the students to meet the future challenge upon graduation.

Keywords: interpersonal competence, clinical education, healthcare professional education, occupational therapy, occupational therapy students

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Authors: Obasa Joshua Ifeoluwa

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Phonetics is the foundation and most important part of language learning. This article, through an acoustic experiment as well as using Praat software, uses Yoruba students’ Chinese consonants, vowels, and tones pronunciation to carry out a visual comparison with that of native Chinese speakers. This article is aimed at Yoruba native speakers learning Chinese phonetics; therefore, Yoruba students are selected. The students surveyed are required to be at an elementary level and have learned Chinese for less than six months. The students selected are all undergraduates majoring in Chinese Studies at the University of Lagos. These students have already learned Chinese Pinyin and are all familiar with the pinyin used in the provided questionnaire. The Chinese students selected are those that have passed the level two Mandarin proficiency examination, which serves as an assurance that their pronunciation is standard. It is discovered in this work that in terms of Mandarin’s consonants pronunciation, Yoruba students cannot distinguish between the voiced and voiceless as well as the aspirated and non-aspirated phonetics features. For instance, while pronouncing [ph] it is clearly shown in the spectrogram that the Voice Onset Time (VOT) of a Chinese speaker is higher than that of a Yoruba native speaker, which means that the Yoruba speaker is pronouncing the unaspirated counterpart [p]. Another difficulty is to pronounce some affricates like [tʂ]、[tʂʰ]、[ʂ]、[ʐ]、 [tɕ]、[tɕʰ]、[ɕ]. This is because these sounds are not in the phonetic system of the Yoruba language. In terms of vowels, some students find it difficult to pronounce some allophonic high vowels such as [ɿ] and [ʅ], therefore pronouncing them as their phoneme [i]; another pronunciation error is pronouncing [y] as [u], also as shown in the spectrogram, a student pronounced [y] as [iu]. In terms of tone, it is most difficult for students to differentiate between the second (rising) and third (falling and rising) tones because these tones’ emphasis is on the rising pitch. This work concludes that the major error made by Yoruba students while pronouncing Chinese sounds is caused by the interference of their first language (LI) and sometimes by their lingua franca.

Keywords: Chinese, Yoruba, error analysis, experimental phonetics, consonant, vowel, tone

Procedia PDF Downloads 111

Authors: Folasade R. Sulaiman

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Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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Authors: Joyce Joas Kahembe

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The implementation of education assessment reforms in developing countries has been claimed to be problematic and difficult. The socio-economic teaching and learning environment has pointed to constraints in the education reform process. Nevertheless, there are existing assessment practices that if enhanced, can have potential to foster formative assessment practices in those contexts. The present study used the sociocultural perspective to explore teachers’ assessment practices and factors influencing them in Tanzania. Specifically, the sociocultural perspective helped to trace social, economic and political histories imparted to teachers’ assessment practices. The ethnographic oriented methods like interviews, observations and document reviews was used in this exploration. Teachers used assessment practices, such as questioning and answering, tests, assignments and examinations, for evaluating, monitoring and diagnosing students’ understanding, achievement and performance and standards and quality of instruction practices. The obtained assessment information functioned as feedback for improving students’ understanding, performance, and the standard and quality of teaching instruction and materials. For example, teachers acknowledged, praised, approved, disapproved, denied, graded, or marked students’ responses to give students feedback and aid learning. Moreover, teachers clarified and corrected or repeated students’ responses with worded/added words to improve students’ mastery of the subject content. Teachers’ assessment practices were influenced by the high demands of passing marks in the high stakes examinations and the contexts of the social economic teaching environment. There is a need to ally education assessment reforms with existing socio-economic teaching environments and society and institutional demands of assessment to make assessment reforms meaningful and sustainable. This presentation ought to contribute on ongoing strategies for contextualizing assessment practices for formative uses.

Keywords: assessment, feedback, practices, formative assessment

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Authors: Madjid Karimirad

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Floating solar was not very well-known in the renewable energy field a decade ago; however, there has been tremendous growth internationally with a Compound Annual Growth Rate (CAGR) of nearly 30% in recent years. To reach the goal of global net-zero emission by 2050, all renewable energy sources including solar should be used. Considering that 40% of the world’s population lives within 100 kilometres of the coasts, floating solar in coastal waters is an obvious energy solution. However, this requires more robust floating solar solutions. This paper tries to enlighten the fundamental requirements in the design of floating solar for offshore installations from the hydrodynamic and offshore engineering points of view. In this regard, a closer look at dynamic characteristics, stochastic behaviour and nonlinear phenomena appearing in this kind of structure is a major focus of the current article. Floating solar structures are alternative and very attractive green energy installations with (a) Less strain on land usage for densely populated areas; (b) Natural cooling effect with efficiency gain; and (c) Increased irradiance from the reflectivity of water. Also, floating solar in conjunction with the hydroelectric plants can optimise energy efficiency and improve system reliability. The co-locating of floating solar units with other types such as offshore wind, wave energy, tidal turbines as well as aquaculture (fish farming) can result in better ocean space usage and increase the synergies. Floating solar technology has seen considerable developments in installed capacities in the past decade. Development of design standards and codes of practice for floating solar technologies deployed on both inland water-bodies and offshore is required to ensure robust and reliable systems that do not have detrimental impacts on the hosting water body. Floating solar will account for 17% of all PV energy produced worldwide by 2030. To enhance the development, further research in this area is needed. This paper aims to discuss the main critical design aspects in light of the load and load effects that the floating solar platforms are subjected to. The key considerations in hydrodynamics, aerodynamics and simultaneous effects from the wind and wave load actions will be discussed. The link of dynamic nonlinear loading, limit states and design space considering the environmental conditions is set to enable a better understanding of the design requirements of fast-evolving floating solar technology.

Keywords: floating solar, offshore renewable energy, wind and wave loading, design space

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Authors: Muneeb Ullah, Daishihan, Xiadong Young

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Deep learning plays a crucial role in identifying COVID-19 and preventing its spread. To improve the accuracy of COVID-19 diagnoses, it is important to have access to a sufficient number of training images of CXRs (chest X-rays) depicting the disease. However, there is currently a shortage of such images. To address this issue, this paper introduces COVID-19 GAN, a model that uses generative adversarial networks (GANs) to generate realistic CXR images of COVID-19, which can be used to train identification models. Initially, a generator model is created that uses digressive channels to generate images of CXR scans for COVID-19. To differentiate between real and fake disease images, an efficient discriminator is developed by combining the dense connectivity strategy and instance normalization. This approach makes use of their feature extraction capabilities on CXR hazy areas. Lastly, the deep regret gradient penalty technique is utilized to ensure stable training of the model. With the use of 4,062 grape leaf disease images, the Leaf GAN model successfully produces 8,124 COVID-19 CXR images. The COVID-19 GAN model produces COVID-19 CXR images that outperform DCGAN and WGAN in terms of the Fréchet inception distance. Experimental findings suggest that the COVID-19 GAN-generated CXR images possess noticeable haziness, offering a promising approach to address the limited training data available for COVID-19 model training. When the dataset was expanded, CNN-based classification models outperformed other models, yielding higher accuracy rates than those of the initial dataset and other augmentation techniques. Among these models, ImagNet exhibited the best recognition accuracy of 99.70% on the testing set. These findings suggest that the proposed augmentation method is a solution to address overfitting issues in disease identification and can enhance identification accuracy effectively.

Keywords: classification, deep learning, medical images, CXR, GAN.

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Authors: Talar Agopian

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Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: active learning, constructivism, learner engagement, student-centered strategies

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Łukasz Bis

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The author is going to discuss virtual reality and its importance for new didactic methods. It has been known for years that experience-based education gives much better results in terms of long-term memory than theoretical study. However, practice is expensive - virtual reality allows the use of an empirical approach to learning, with minimized production costs. The author defines what makes a given VR experience appropriate (adequate) for the didactic and cognitive process. The article is a kind of a list of guidelines and their importance for the VR experience under development.

Keywords: virtual reality, education, universal design, guideline

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Authors: Michael Amankwaa Adu

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Effective communication in the classroom plays a vital role in ensuring successful teaching and learning. In particular, the types of language and speech acts teachers use shape classroom interactions and influence student engagement. This study aims to analyze the speech acts employed by a Career Technology teacher in a junior high school. While much research has focused on speech acts in language classrooms, less attention has been given to how these acts operate in non-language subject areas like technical education. The study explores how different types of speech acts—directives, assertives, expressives, and commissives—are used during three classroom encounters: lesson introduction, content delivery, and classroom management. This research seeks to fill the gap in understanding how teachers of non-language subjects use speech acts to manage classroom dynamics and facilitate learning. The study employs a mixed-methods design, combining qualitative and quantitative approaches. Data was collected through direct classroom observation and audio recordings of a one-hour Career Technology lesson. The transcriptions of the lesson were analyzed using John Searle’s taxonomy of speech acts, classifying the teacher’s utterances into directives, assertives, expressives, and commissives. Results show that directives were the most frequently used speech act, accounting for 59.3% of the teacher's utterances. These speech acts were essential in guiding student behavior, giving instructions, and maintaining classroom control. Assertives made up 20.4% of the speech acts, primarily used for stating facts and reinforcing content. Expressives, at 14.2%, expressed emotions such as approval or frustration, helping to manage the emotional atmosphere of the classroom. Commissives were the least used, representing 6.2% of the speech acts, often used to set expectations or outline future actions. No declarations were observed during the lesson. The findings of this study reveal the critical role that speech acts play in managing classroom behavior and delivering content in technical subjects. Directives were crucial for ensuring students followed instructions and completed tasks, while assertives helped in reinforcing lesson objectives. Expressives contributed to motivating or disciplining students, and commissives, though less frequent, helped set clear expectations for students’ future actions. The absence of declarations suggests that the teacher prioritized guiding students over making formal pronouncements. These insights can inform teaching strategies across various subject areas, demonstrating that a diverse use of speech acts can create a balanced and interactive learning environment. This study contributes to the growing field of pragmatics in education and offers practical recommendations for educators, particularly in non-language classrooms, on how to utilize speech acts to enhance both classroom management and student engagement.

Keywords: classroom interaction, pragmatics, speech acts, teacher communication, career technology

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Authors: Ahlem Dhahri, Waleed Omri, Audrey Becuwe, Abdelwahed Omri

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In industrial processes, decision-making ranges across different scales, from process control to supply chain management. The purchasing decision-making process in the supply chain is presently gaining more attention as a critical contributor to the company's strategic success. Given the scarcity of thorough summaries in the prior studies, this bibliometric analysis aims to adopt a meticulous approach to achieve quantitative knowledge on the constantly evolving subject of purchasing decision-making in supply chain management. Through bibliometric analysis, we examine a sample of 358 peer-reviewed articles from the Scopus database. VOSviewer and Gephi software were employed to analyze, combine, and visualize the data. Data analytic techniques, including citation network, page-rank analysis, co-citation, and publication trends, have been used to identify influential works and outline the discipline's intellectual structure. The outcomes of this descriptive analysis highlight the most prominent articles, authors, journals, and countries based on their citations and publications. The findings from the research illustrate an increase in the number of publications, exhibiting a slightly growing trend in this field. Co-citation analysis coupled with content analysis of the most cited articles identified five research themes mentioned as follows integrating sustainability into the supplier selection process, supplier selection under disruption risks assessment and mitigation strategies, Fuzzy MCDM approaches for supplier evaluation and selection, purchasing decision in vendor problems, decision-making techniques in supplier selection and order lot sizing problems. With the help of a graphic timeline, this exhaustive map of the field illustrates a visual representation of the evolution of publications that demonstrate a gradual shift from research interest in vendor selection problems to integrating sustainability in the supplier selection process. These clusters offer insights into a wide variety of purchasing methods and conceptual frameworks that have emerged; however, they have not been validated empirically. The findings suggest that future research would emerge with a greater depth of practical and empirical analysis to enrich the theories. These outcomes provide a powerful road map for further study in this area.

Keywords: bibliometric analysis, citation analysis, co-citation, Gephi, network analysis, purchasing, SCM, VOSviewer

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Authors: Vangmayee V. Subban, Suzan Deelan. Pinto, Somashekara Haralakatta Shivananjappa, Shwetha Prabhu, Jayashree S. Bhat

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Introduction and Need: During early years of schooling, the instruction in the schools mainly focus on children’s word decoding abilities. However, the skilled readers should master all the components of reading such as word decoding, reading fluency and comprehension. Nevertheless, the relationship between each component during the process of learning to read is less clear. The studies conducted in alphabetical languages have mixed opinion on relative contribution of word decoding and reading fluency on reading comprehension. However, the scenarios in alphasyllabary languages are unexplored. Aim and Objectives: The aim of the study was to explore the role of word decoding, reading fluency on reading comprehension abilities in children learning to read Kannada between the age ranges of 5.6 to 8.6 years. Method: In this cross sectional study, a total of 60 typically developing children, 20 each from Grade I, Grade II, Grade III maintaining equal gender ratio between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. The reading fluency and reading comprehension abilities of the children were assessed using Grade level passages selected from the Kannada text book of children core curriculum. All the passages consist of five questions to assess reading comprehension. The pseudoword decoding skills were assessed using 40 pseudowords with varying syllable length and their Akshara composition. Pseudowords are formed by interchanging the syllables within the meaningful word while maintaining the phonotactic constraints of Kannada language. The assessment material was subjected to content validation and reliability measures before collecting the data on the study samples. The data were collected individually, and reading fluency was assessed for words correctly read per minute. Pseudoword decoding was scored for the accuracy of reading. Results: The descriptive statistics indicated that the mean pseudoword reading, reading comprehension, words accurately read per minute increased with the Grades. The performance of Grade III children found to be higher, Grade I lower and Grade II remained intermediate of Grade III and Grade I. The trend indicated that reading skills gradually improve with the Grades. Pearson’s correlation co-efficient showed moderate and highly significant (p=0.00) positive co-relation between the variables, indicating the interdependency of all the three components required for reading. The hierarchical regression analysis revealed 37% variance in reading comprehension was explained by pseudoword decoding and was highly significant. Subsequent entry of reading fluency measure, there was no significant change in R-square and was only change 3%. Therefore, pseudoword-decoding evolved as a single most significant predictor of reading comprehension during early Grades of reading acquisition. Conclusion: The present study concludes that the pseudoword decoding skills contribute significantly to reading comprehension than reading fluency during initial years of schooling in children learning to read Kannada language.

Keywords: alphasyllabary, pseudo-word decoding, reading comprehension, reading fluency

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Authors: Nuur Insan Tangkelangi

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Needs on academic writing competence as the primary focus in higher education encourage the university institutions around the world to provide academic writing courses to support their students dealing with their tasks pertaining to this competence. However, a pilot study conducted previously in one of the universities in Palopo, a city in South Sulawesi, revealed that even though the institution has provided academic writing courses, supported by some workshops related to academic writing and some supporting facilities at campus, the students still face difficulties in completing their assignments related to academic writing, particularly in writing their theses. The present study focuses on investigating the specific needs of the students in the same institution in terms of competences required in academic writing. It is also carried out to examine whether the syllabus exists and accommodates the students’ needs or not. Questionnaire and interview were used to collect data from sixty students of sixth semester and two lecturers of the academic courses. The results reveal that the students need to learn all aspects of linguistic competence (language features, lexical phrases, academic language and vocabulary, and proper language) and some aspects in discourse competence (how to write introduction, search for appropriate literature, design research method, write coherent paragraphs, refer to sources, summarize and display data, and link sentences smoothly). Regarding the syllabus, it is found that the academic writing courses provided in the institution, where this study takes place, do not have syllabus. This condition is different from other institutions which provide syllabi for all courses. However, at the commencement of the course, the students and the lecturers have negotiated their learning goals, topics discussed, learning activities, and assessment criteria for the course. Therefore, even though the syllabus does not exist, but the elements of the syllabus are there. The negotiation between the students and the lecturers contributes to the students’ attitude toward the courses. The students are contented with the course and they feel that their needs in academic writing have been accommodated. However, some suggestions for the next academic writing courses are stated by the students. Considering the results of this study, a syllabus is then proposed which is expected to accommodate the specific needs of students in that institution.

Keywords: Students' needs, academic writing, syllabus design for instruction, case study

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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