Search results for: hybrid learning

Authors: Digby Warren, Jiri Kropac

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While aspirations of social justice are often articulated by universities as a “feel good” mantra, what is meant by education for social justice deserves deeper consideration. Based on in-depth interviews with academics (voluntary participants in this research) in different disciplines and institutions in the UK, Czech Republic, and other EU countries, this comparative study presents thematic findings regarding lecturers’ conceptions of education for social justice -what it is, why it is important, why they are personally committed to it, how it connects with their own values- and their practice of it- how it is implemented through curriculum content, teaching and learning activities, and assessment tasks. It concludes by presenting an analysis of the challenges, constraints, and enabling factors in practising social justice education in different subject, institutional and national contexts.

Keywords: higher education, social justice, inclusivity, diversity

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Authors: Jian Wang

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Teachers’ lesson-based discussions presume central to their effective learning to teach. Whether and to what extent such discussions offer opportunities for teachers to learn to teach effectively is worth a careful empirical examination. This study examines this assumption by drawing on lesson-based discussions and relevant curriculum materials from Chinese teachers in three urban schools. Their lesson-based discussions consistently focused on pedagogical content knowledge and offered specific and reasoned suggestions for teachers to refine their teaching practices. The mandated curriculum and their working language-mediated their lesson-based discussions.

Keywords: Chinese teachers, curriculum materials, lesson discussion, mathematics instruction

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Authors: Mumtaz Mooncey, Alexander Jolly, Megan Fisher, Kerry Robinson, Robert Lloyd, Dave Fielding

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Introduction: The integration of the WingFactors in-situ simulation programme has transformed the education landscape at the Whittington Health NHS Trust. To date, there have been a total of 90 simulations - 19 aimed at Paediatric trainees, including 2 Child and Adolescent Mental Health (CAMHS) scenarios. The opportunity for joint debriefs provided by clinical faculty and airline pilots, has created a new exciting avenue to explore human factors within psychiatry. Through the use of real clinical environments and primed actors; the benefits of high fidelity simulation, interdisciplinary and interprofessional learning has been highlighted. The use of in-situ simulation within Psychiatry is a newly emerging concept and its success here has been recognised by unanimously positive feedback from participants and acknowledgement through nomination for the Health Service Journal (HSJ) Award (Best Education Programme 2021). Methodology: The first CAMHS simulation featured a collapsed patient in the toilet with a ligature tied around her neck, accompanied by a distressed parent. This required participants to consider:; emergency physical management of the case, alongside helping to contain the mother and maintaining situational awareness when transferring the patient to an appropriate clinical area. The second simulation was based on a 17- year- old girl attempting to leave the ward after presenting with an overdose, posing potential risk to herself. The safe learning environment enabled participants to explore techniques to engage the young person and understand their concerns, and consider the involvement of other members of the multidisciplinary team. The scenarios were followed by an immediate ‘hot’ debrief, combining technical feedback with Human Factors feedback from uniformed airline pilots and clinicians. The importance of psychological safety was paramount, encouraging open and honest contributions from all participants. Key learning points were summarized into written documents and circulated. Findings: The in-situ simulations demonstrated the need for practical changes both in the Emergency Department and on the Paediatric ward. The presence of airline pilots provided a novel way to debrief on Human Factors. The following key themes were identified: -Team-briefing (‘Golden 5 minutes’) - Taking a few moments to establish experience, initial roles and strategies amongst the team can reduce the need for conversations in front of a distressed patient or anxious relative. -Use of checklists / guidelines - Principles associated with checklist usage (control of pace, rigor, team situational awareness), instead of reliance on accurate memory recall when under pressure. -Read-back - Immediate repetition of safety critical instructions (e.g. drug / dosage) to mitigate the risks associated with miscommunication. -Distraction management - Balancing the risk of losing a team member to manage a distressed relative, versus it impacting on the care of the young person. -Task allocation - The value of the implementation of ‘The 5A’s’ (Availability, Address, Allocate, Ask, Advise), for effective task allocation. Conclusion: 100% of participants have requested more simulation training. Involvement of airline pilots has led to a shift in hospital culture, bringing to the forefront the value of Human Factors focused training and multidisciplinary simulation. This has been of significant value in not only physical health, but also mental health simulation.

Keywords: human factors, in-situ simulation, inter-professional, multidisciplinary

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Authors: Roya Morad, W. Eirik Heintz

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The identity of a neighborhood is inevitably shaped by the architecture and the people of that place. Conventionally the streets within each neighborhood served as a semi-public-private extension of the private living spaces. The street as a design element formed a hybrid condition that was neither totally public nor private, and it encouraged social interactions. Thus through creating a sense of community, one of the most basic human needs of belonging was achieved. Similar to major global cities, Tehran has undergone serious urbanization. Developing into a capital city of high rises has resulted in an increase in urban density. Although allocating more residential units in each neighborhood was a critical response to the population boom and the limited land area of the city, it also created a crisis in terms of social communication and place attachment. District 10 in Tehran is a neighborhood that has undergone the most urban transformation among the other 22 districts in the capital and currently has the highest population density. This paper will explore how the active streets in district 10 have changed into their current condition of high rises with a lack of meaningful social interactions amongst its inhabitants. A residential building can be thought of as a large group of people. One would think that as the number of people increases, the opportunities for social communications would increase as well. However, according to the survey, there is an indirect relationship between the two. As the number of people of a residential building increases, the quality of each acquaintance reduces, and the depth of relationships between people tends to decrease. This comes from the anonymity of being part of a crowd and the lack of social spaces characterized by most high-rise apartment buildings. Without a sense of community, the attachment to a neighborhood is decreased. This paper further explores how the neighborhood participates to fulfill ones need for social interaction and focuses on the qualitative aspects of alternative spaces that can redevelop the sense of place attachment within the community.

Keywords: high density, place attachment, social communication, street life, urban transformation

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Authors: Viktorya Sargsyan, Arax Hovhannesyan, Karine Abelyan

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Introduction: During the last decade, scientific studies have proven the importance of Early Childhood Development (ECD) interventions. These interventions are shown to create strong foundations for children’s intellectual, emotional and physical well-being, as well as the impact they have on learning and economic outcomes for children as they mature into adulthood. Many children in rural Armenia fail to reach their full development potential due to lack of early brain stimulation (playing, singing, reading, etc.) from their parents, and lack of community tools and services to follow-up children’s neurocognitive development. This is exacerbated by high rates of stunting and anemia among children under 3(CU3). This research study tested the effectiveness of an integrated ECD and Maternal, Newborn and Childhood Health (MNCH) model, called “Go Baby, Go!” (GBG), against the traditional (MNCH) strategy which focuses solely on preventive health and nutrition interventions. The hypothesis of this quasi-experimental study was: Children exposed to GBG will have better neurocognitive and nutrition outcomes compared to those receiving only the MNCH intervention. The secondary objective was to assess the effect of GBG on parental child care and nutrition practices. Methodology: The 14 month long study, targeted all 1,300 children aged 0 to 23 months, living in 43 study communities the in Gavar and Vardenis regions (Gegharkunik province, Armenia). Twenty-three intervention communities, 680 children, received GBG, and 20 control communities, 630 children, received MCHN interventions only. Baseline and evaluation data on child development, nutrition status and parental child care and nutrition practices were collected (caregiver interview, direct child assessment). In the intervention sites, in addition to MNCH (maternity schools, supportive supervision for Health Care Providers (HCP), the trained GBG facilitators conducted six interactive group sessions for mothers (key messages, information, group discussions, role playing, video-watching, toys/books preparation, according to GBG curriculum), and two sessions (condensed GBG) for adult family members (husbands, grandmothers). The trained HCPs received quality supervision for ECD counseling and screening. Findings: The GBG model proved to be effective in improving ECD outcomes. Children in the intervention sites had 83% higher odd of total ECD composite score (cognitive, language, motor) compared to children in the control sites (aOR 1.83; 95 percent CI: 1.08-3.09; p=0.025). Caregivers also demonstrated better child care and nutrition practices (minimum dietary diversity in intervention site is 55 percent higher compared to control (aOR=1.55, 95 percent CI 1.10-2.19, p =0.013); support for learning and disciplining practices (aOR=2.22, 95 percent CI 1.19-4.16, p=0.012)). However, there was no evidence of stunting reduction in either study arm. he effect of the integrated model was more prominent in Vardenis, a community which is characterised by high food insecurity and limited knowledge of positive parenting skills. Conclusion: The GBG model is effective and could be applied in target areas with the greatest economic disadvantages and parenting challenges to improve ECD, care practices and developmental outcomes. Longitudinal studies are needed to view the long-term effects of GBG on learning and school readiness.

Keywords: early childhood development, integrated interventions, parental practices, quasi-experimental study

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Authors: Mohamed dammak

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Great attention has been paid to the design and synthesis of novel organic-inorganic compounds in recent decades because of their structural variety and the large diversity of atomic arrangements. In this work, the structure for the novel dimethyl aminopyridine tetrachlorocobaltate (C₇H₁₁N₂)₂CoCl₄ prepared by the slow evaporation method at room temperature has been successfully discussed. The X-ray diffraction results indicate that the hybrid material has a triclinic structure with a P space group and features a 0D structure containing isolated distorted [CoCl₄]2- tetrahedra interposed between [C7H11N²⁻]+ cations forming planes perpendicular to the c axis at z = 0 and z = ½. The effect of the synthesis conditions and the reactants used, the interactions between the cationic planes, and the isolated [CoCl4]2- tetrahedra are employing N-H...Cl and C-H…Cl hydrogen bonding contacts. The inspection of the Hirshfeld surface analysis helps to discuss the strength of hydrogen bonds and to quantify the inter-contacts. A phase transition was discovered by thermal analysis at 390 K, and comprehensive dielectric research was reported, showing a good agreement with thermal data. Impedance spectroscopy measurements were used to study the electrical and dielectric characteristics over a wide range of frequencies and temperatures, 40 Hz–10 MHz and 313–483 K, respectively. The Nyquist plot (Z" versus Z') from the complex impedance spectrum revealed semicircular arcs described by a Cole-Cole model. An electrical circuit consisting of a link of grain and grain boundary elements is employed. The real and imaginary parts of dielectric permittivity, as well as tg(δ) of (C₇H₁₁N₂)₂CoCl₄ at different frequencies, reveal a distribution of relaxation times. The presence of grain and grain boundaries is confirmed by the modulus investigations. Electric and dielectric analyses highlight the good protonic conduction of this material.

Keywords: organic-inorganic, phase transitions, complex impedance, protonic conduction, dielectric analysis

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Authors: Ede Jairus Adagba

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The National Policy on Education has made elaborate and fascinating provisions for the education of the people with Special Needs. This category of people includes the physically challenged, the disadvantaged, the gifted and talented. However, the focus of this paper is people that are physically challenged. The paper reasons that in spite of the commendable provisions, the present curricular and learning conditions are not conducive enough to cater for the interest of the physically challenged persons. As a panacea, some curricular and physical condition reforms are proposed. These are hoped to facilitate access to inclusive education and equalization for opportunities of the physically challenged.

Keywords: curricular reforms, equalization, inclusive education, physically challenged persons

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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Authors: Alexandra Shipley

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Background: Undergraduate paediatric teaching must overcome two major challenges: 1) balancing patient safety with active student engagement and 2) exposing students to a comprehensive range of pathologies within a relatively short clinical placement. Whilst lectures and shadowing on paediatric wards constitute the mainstay of learning, Simulation and Virtual Reality (VR) are emerging as effective teaching tools, which - immune to the unpredictability and seasonal variation of hospital presentations - could expose students to the entire syllabus more reliably, efficiently, and independently. We aim to evaluate the potential utility of Simulation and VR in addressing gaps within the traditional paediatric curriculum from the perspective of medical students. Summary of Work: Exposure to and perceived utility of various learning opportunities within the Paediatric and Emergency Medicine courses were assessed through a questionnaire completed by 5th year medical students (n=23). Summary of Results: Students reported limited exposure to several common acute paediatric presentations, such as bronchiolitis (41%), croup (32%) or pneumonia (14%), and to clinical emergencies, including cardiac/respiratory arrests or trauma calls (27%). Across all conditions, average self-reported confidence in assessment and management to the level expected of an FY1 is greater amongst those who observed at least one case (e.g. 7.6/10 compared with 3.6/10 for croup). Students rated exposure through Simulation or VR to be of similar utility to witnessing a clinical scenario on the ward. In free text responses, students unanimously favoured being ‘challenged’ through ‘hands-on’ patient interaction over passive shadowing, where it is ‘easy to zone out.’ In recognition of the fact that such independence is only appropriate in certain clinical situations, many students reported wanting more Simulation and VR teaching. Importantly, students raised the necessity of ‘proper debriefs’ after these sessions to maximise educational value. Discussion and Conclusion: Our questionnaire elicited several student-perceived challenges in paediatric education, including incomplete exposure to common pathologies and limited opportunities for active involvement in patient care. Indeed, these experiences seem to be important predictors of confidence. Quantitative and qualitative feedback suggests that VR and Simulation satisfy students’ self-reported appetite for independent engagement with authentic clinical scenarios. Take-aways: Our findings endorse further development of VR and Simulation as high-yield adjuncts to paediatric education.

Keywords: paediatric emergency education, simulation, virtual reality, medical education

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: emotion recognition, facial recognition, signal processing, machine learning

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

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Authors: Siva Teja Golla, B. Venkatesham

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The recent technologies in hybrid and high-end cars have subsided the noise from major sources like engines and transmission systems. This resulted in the unmasking of the previously subdued noises. These noises are becoming noticeable to the passengers, causing annoyance to them and affecting the perceived quality of the vehicle. Sloshing in the fuel tank is one such source of noise. Sloshing occurs due to the excitations undergone by the fuel tank due to the vehicle's movement. Sloshing noise occurs due to the interaction of the fluid with the surrounding tank walls or with the fluid itself. The noise resulting from the interaction of the fluid with the structure is ‘Hit noise’, and the noise due to fluid-fluid interaction is ‘Splash noise’. The type of interactions the fluid undergoes inside the tank, and the type of noise generated depends on a variety of factors like the fill level of the tank, type of fluid, presence of objects like baffles inside the tank, type and strength of the excitation, etc. There have been studies done to understand the effect of each of these parameters on the generation of different types of sloshing noises. But little work is done in the psychoacoustic aspect of these sounds. The psychoacoustic study of the sloshing noises gives an understanding of the level of annoyance it can cause to the passengers and helps in taking necessary measures to address it. In view of this, the current paper focuses on the calculation of the psychoacoustic parameters like loudness, sharpness, roughness and fluctuation strength for the sloshing noise. As the noise generation mechanisms for the hit and splash noises are different, these parameters are calculated separately for them. For this, the fluid flow regimes that predominantly cause the hit-and-splash noises are to be separately emulated inside the tank. This is done through a reciprocating test rig, which imposes reciprocating excitation to a rectangular tank filled with the fluid. By varying the frequency of excitation, the fluid flow regimes with the predominant generation of hit-and-splash noises can be separately created inside the tank. These tests are done in a quiet room and the noise generated is captured using microphones and is used for the calculation of psychoacoustic parameters of the sloshing noise. This study also includes the effect of fill level and the presence of baffles inside the tank on these parameters.

Keywords: sloshing, hit noise, splash noise, sound quality

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Authors: Vadim Kulikov

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The classical Stroop effect is the phenomenon that it takes more time to name the ink color of a printed word if the word denotes a conflicting color than if it denotes the same color. Over the last 80 years, there have been many variations of the experiment revealing various mechanisms behind semantic, attentional, behavioral and perceptual processing. The Stroop task is known to exhibit asymmetry. Reading the words out loud is hardly dependent on the ink color, but naming the ink color is significantly influenced by the incongruent words. This asymmetry is reversed, if instead of naming the color, one has to point at a corresponding color patch. Another debated aspects are the notions of automaticity and how much of the effect is due to semantic and how much due to response stage interference. Is automaticity a continuous or an all-or-none phenomenon? There are many models and theories in the literature tackling these questions which will be discussed in the presentation. None of them, however, seems to capture all the findings at once. A computational model is proposed which is based on the philosophical idea developed by the author that the mind operates as a collection of different information processing modalities such as different sensory and descriptive modalities, which produce emergent phenomena through mutual interaction and coherence. This is the framework theory where ‘framework’ attempts to generalize the concepts of modality, perspective and ‘point of view’. The architecture of this computational model consists of blocks of neurons, each block corresponding to one framework. In the simplest case there are four: visual color processing, text reading, speech production and attention selection modalities. In experiments where button pressing or pointing is required, a corresponding block is added. In the beginning, the weights of the neural connections are mostly set to zero. The network is trained using Hebbian learning to establish connections (corresponding to ‘coherence’ in framework theory) between these different modalities. The amount of data fed into the network is supposed to mimic the amount of practice a human encounters, in particular it is assumed that converting written text into spoken words is a more practiced skill than converting visually perceived colors to spoken color-names. After the training, the network performs the Stroop task. The RT’s are measured in a canonical way, as these are continuous time recurrent neural networks (CTRNN). The above-described aspects of the Stroop phenomenon along with many others are replicated. The model is similar to some existing connectionist models but as will be discussed in the presentation, has many advantages: it predicts more data, the architecture is simpler and biologically more plausible.

Keywords: connectionism, Hebbian learning, artificial neural networks, philosophy of mind, Stroop

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Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

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Authors: Pui-Lai To, E-Ping Sung

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The purpose of this study is to investigate hedonic online shopping motivations. A qualitative analysis was conducted to explore the factors influencing online hedonic shopping motivations. The results of the study indicate that traditional hedonic values, consisting of social, role, self-gratification, learning trends, pleasure of bargaining, stimulation, diversion, status, and adventure, and dimensions of flow theory, consisting of control, curiosity, enjoyment, and telepresence, exist in the online shopping environment. Two hedonic motivations unique to Internet shopping, privacy and online shopping achievement, were found. It appears that the most important hedonic value to online shoppers is having the choice to interact or not interact with others while shopping on the Internet. This study serves as a basis for the future growth of Internet marketing.

Keywords: internet shopping, shopping motivation, hedonic motivation

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Authors: R. Mellah, R. Toumi

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This paper presents a new adaptive neuro-fuzzy controller equipped with compensatory fuzzy control (CNFI) in order to not only adjusts membership functions but also to optimize the adaptive reasoning by using a compensatory learning algorithm. The proposed control structure includes both CNFI controllers for which one is used to control in force the master robot and the second one for controlling in position the slave robot. The experimental results obtained, show a fairly high accuracy in terms of position and force tracking under free space motion and hard contact motion, what highlights the effectiveness of the proposed controllers.

Keywords: compensatory fuzzy, neuro-fuzzy, control adaptive, teleoperation

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Authors: Ukhtie Nantika Mena, Ahmad Juntika Nurihsan, Ilfiandra

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This study aims to explore perspective on Foreign Language Classroom Anxiety (FLCA) of an international student. Descriptive narrative is used to discover written and spoken responses from the student. An online survey was employed as a secondary data to identify the level of FLCA among six UPI international students. A student with the highest score volunteered to be interviewed. Several symptoms were found; lack of concentration, excessive worry, fear, unwanted thoughts, and sweating. The results showed that difficulties to understand lecturers' correction, presentation, and fear of getting left behind are three major causes of his anxiety.

Keywords: foreign language classroom anxiety, FLCA, international students, language anxiety

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Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

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Association rule learning is an approach for discovering interesting relationships in large databases. The analysis of relations, invisible at first glance, is a source of new knowledge which can be subsequently used for prediction. We used this data mining technique (which is an automatic and objective method) to learn about interesting affects associations in a corpus of emergency phone calls. We also made an attempt to match revealed rules with their possible situational context. The corpus was collected and subjectively annotated by two researchers. Each of 3306 recordings contains information on emotion: (1) type (sadness, weariness, anxiety, surprise, stress, anger, frustration, calm, relief, compassion, contentment, amusement, joy) (2) valence (negative, neutral, or positive) (3) intensity (low, typical, alternating, high). Also, additional information, that is a clue to speaker’s emotional state, was annotated: speech rate (slow, normal, fast), characteristic vocabulary (filled pauses, repeated words) and conversation style (normal, chaotic). Exponentially many rules can be extracted from a set of items (an item is a previously annotated single information). To generate the rules in the form of an implication X → Y (where X and Y are frequent k-itemsets) the Apriori algorithm was used - it avoids performing needless computations. Then, two basic measures (Support and Confidence) and several additional symmetric and asymmetric objective measures (e.g. Laplace, Conviction, Interest Factor, Cosine, correlation coefficient) were calculated for each rule. Each applied interestingness measure revealed different rules - we selected some top rules for each measure. Owing to the specificity of the corpus (emergency situations), most of the strong rules contain only negative emotions. There are though strong rules including neutral or even positive emotions. Three examples of the strongest rules are: {sadness} → {anxiety}; {sadness, weariness, stress, frustration} → {anger}; {compassion} → {sadness}. Association rule learning revealed the strongest configurations of affects (as well as configurations of affects with affect-related information) in our emergency phone calls corpus. The acquired knowledge can be used for prediction to fulfill the emotional profile of a new caller. Furthermore, a rule-related possible context analysis may be a clue to the situation a caller is in.

Keywords: data mining, emergency phone calls, emotional profiles, rules

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Authors: Wichuda Kunnu, Aungkana Sukwises

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Audio-lingual method (ALM) is a teaching approach that is claimed that ineffective for teaching second/foreign languages. Because some linguists and second/foreign language teachers believe that ALM is a rote learning style. However, this study is done on a belief that ALM will be able to solve Thais’ English speaking problem. This paper aims to report the findings on teaching English speaking to adult learners with an “adapted ALM”, one distinction of which is to use Thai as the medium language of instruction. The participants are consisted of 9 adult learners. They were allowed to speak English more freely using both the materials presented in the class and their background knowledge of English. At the end of the course, they spoke English more fluently, more confidently, to the extent that they applied what they learnt both in and outside the class.

Keywords: teaching English, audio lingual method, cognitive science, psychology

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Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

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Sponsored search is a multi-billion dollar industry and makes up a major source of revenue for search engines (SE). Click-through-rate (CTR) estimation plays a crucial role for ads selection, and greatly affects the SE revenue, advertiser traffic and user experience. We propose a novel architecture of solving CTR prediction problem by combining artificial neural networks (ANN) with decision trees. First, we compare ANN with respect to other popular machine learning models being used for this task. Then we go on to combine ANN with MatrixNet (proprietary implementation of boosted trees) and evaluate the performance of the system as a whole. The results show that our approach provides a significant improvement over existing models.

Keywords: neural networks, sponsored search, web advertisement, click prediction, click-through rate

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Authors: Fernandez liporace, Mercedes Uriel Fabiana

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Academic achievement in high school and college students is currently a matter of concern. National and international assessments show high schoolers as low achievers, and local statistics indicate alarming dropout percentages in this educational level. Even so, 80% of those students intend attending higher education. On the other hand, applications to Public National Universities are free and non-selective by examination procedures. Though initial registrations are massive (307.894 students), only 50% of freshmen pass their first year classes, and 23% achieves a degree. Low performances use to be a common problem. Hence, freshmen adaptation, their adjustment, dropout and low academic achievement arise as topics of agenda. Besides, the hinge between high school and college must be examined in depth, in order to get an integrated and successful path from one educational stratum to the other. Psychology aims at developing two main research lines to analyse the situation. One regarding psychometric scales, designing and/or adapting tests, examining their technical properties and their theoretical validity (e.g., academic motivation, learning strategies, learning styles, coping, perceived social support, parenting styles and parental consistency, paradoxical personality as correlated to creative skills, psychopathological symptomatology). The second research line emphasizes relationships within the variables measured by the former scales, facing the formulation and testing of predictive models of academic achievement, establishing differences by sex, age, educational level (high school vs college), and career. Pursuing these goals, several studies were carried out in recent years, reporting findings and producing assessment technology useful to detect students academically at risk as well as good achievers. Multiple samples were analysed totalizing more than 3500 participants (2500 from college and 1000 from high school), including descriptive, correlational, group differences and explicative designs. A brief on the most relevant results is presented. Providing information to design specific interventions according to every learner’s features and his/her educational environment comes up as a mid-term accomplishment. Furthermore, that information might be helpful to adapt curricula by career, as well as for implementing special didactic strategies differentiated by sex and personal characteristics.

Keywords: academic achievement, higher education, high school, psychological assessment

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Authors: Senthuran Manoharan, Rathesan Sivagananalingam

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One of the main issues in system security is Authentication. Authentication can be defined as the process of recognizing the user's identity and it is the most important step in the access control process to safeguard data/resources from being accessed by unauthorized users. The static method of authentication cannot ensure the genuineness of the user. Due to this reason, more innovative authentication mechanisms came into play. At first two factor authentication was introduced and later, multi-factor authentication was introduced to enhance the security of the system. It also had some issues and later, adaptive authentication was introduced. In this research paper, the design of an adaptive authentication engine was put forward. The user risk profile was calculated based on the user parameters and then the user was challenged with a suitable authentication method.

Keywords: authentication, adaptive authentication, machine learning, security

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Authors: Ruzanna Muradyan

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Medical data mining is a crucial field in contemporary healthcare that offers cutting-edge tactics with enormous potential to transform patient care. This abstract examines how sophisticated data mining techniques could transform the healthcare industry, with a special focus on how they might improve patient outcomes. Healthcare data repositories have dynamically evolved, producing a rich tapestry of different, multi-dimensional information that includes genetic profiles, lifestyle markers, electronic health records, and more. By utilizing data mining techniques inside this vast library, a variety of prospects for precision medicine, predictive analytics, and insight production become visible. Predictive modeling for illness prediction, risk stratification, and therapy efficacy evaluations are important points of focus. Healthcare providers may use this abundance of data to tailor treatment plans, identify high-risk patient populations, and forecast disease trajectories by applying machine learning algorithms and predictive analytics. Better patient outcomes, more efficient use of resources, and early treatments are made possible by this proactive strategy. Furthermore, data mining techniques act as catalysts to reveal complex relationships between apparently unrelated data pieces, providing enhanced insights into the cause of disease, genetic susceptibilities, and environmental factors. Healthcare practitioners can get practical insights that guide disease prevention, customized patient counseling, and focused therapies by analyzing these associations. The abstract explores the problems and ethical issues that come with using data mining techniques in the healthcare industry. In order to properly use these approaches, it is essential to find a balance between data privacy, security issues, and the interpretability of complex models. Finally, this abstract demonstrates the revolutionary power of modern data mining methodologies in transforming the healthcare sector. Healthcare practitioners and researchers can uncover unique insights, enhance clinical decision-making, and ultimately elevate patient care to unprecedented levels of precision and efficacy by employing cutting-edge methodologies.

Keywords: data mining, healthcare, patient care, predictive analytics, precision medicine, electronic health records, machine learning, predictive modeling, disease prognosis, risk stratification, treatment efficacy, genetic profiles, precision health

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Authors: Eeva Wallenius-Nareneva, Tuula Toivanen-Labiad

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Background: Oral health promotion event was organised for forty Afghanistan, Iraqi and Bangladeshi underage asylum seekers in Finland. The invitation to arrange this coaching occasion was accepted in the Degree Programme in Oral Hygiene in Metropolia. The personnel in the reception center found the need to improve oral health among the youngsters. The purpose was to strengthen the health literacy of the boys in their oral self-care and to reduce dental fears. The Finnish studies, especially the terminology of oral health was integrated to coaching with the help of interpreters. Cooperative learning was applied. Methods: Oral health was interactively discussed in four study group sessions: 1. The importance of healthy eating habits; - Good and bad diets, - Regular meals, - Acid attack o Xylitol. 2. Oral diseases − connection to general health; - Aetiology of gingivitis, periodontitis and caries, - Harmfulness of smoking 3. Tools and techniques for oral self-care; - Brushing and inter dental cleaning. 4. Sharing earlier dental care experiences; - Cultural differences, - Dental fear, - Regular check-ups. Results: During coaching deficiencies appeared in brushing and inter dental cleaning techniques. Some boys were used to wash their mouth with salt justifying it by salt’s antiseptic properties. Many brushed their teeth by vertical movements. The boys took feedback positively when a demonstration with model jaws revealed the inefficiency of the technique. The advantages of fluoride tooth paste were advised. Dental care procedures were new and frightening for many boys. Finnish dental care system was clarified. The safety and indolence of the treatments and informed consent were highlighted. Video presentations and the dialog lowered substantially the threshold to visit dental clinic. The occasion gave the students means for meeting patients from different cultural and language backgrounds. The information hidden behind the oral health problems of the asylum seekers was valuable. Conclusions: Learning dental care practices used in different cultures is essential for dental professionals. The project was a good start towards multicultural oral health care. More experiences are needed before graduation. Health education themes should be held simple regardless of the target group. The heterogeneity of the group does not pose a problem. Open discussion with questions leading to the theme works well in clarifying the target group’s knowledge level. Sharing own experiences strengthens the sense of equality among the participants and encourages them to express own opinions. Motivational interview method turned out to be successful. In the future coaching occasions must confirm active participation of everyone. This could be realized by dividing the participants to even smaller groups. The different languages impose challenges but they can be solved by using more interpreters. Their presence ensures that everyone understands the issues properly although the use of plain and sign languages are helpful. In further development, it would be crucial to arrange a rehearsal occasion to the same participants in two/three months’ time. This would strengthen the adaption of self-care practices and give the youngsters opportunity to pose more open questions. The students would gain valuable feedback regarding the effectiveness of their work.

Keywords: cooperative learning, interactive methods, motivational interviewing, oral health promotion, underage asylum seekers

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Authors: Davoud Ansari Kejal, Meysam Sabour

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For long, there has been a belief that a reader can easily comprehend a text if he is strong enough in vocabulary and grammatical knowledge but there was no account for the ability of understanding different subjects based on readers’ understanding of the surrounding world which is called world background knowledge. This paper attempts to investigate the reading comprehension process applying the schema theory as an influential factor in comprehending texts, in order to prove the important role of background knowledge in reading comprehension. Based on the discussion, some teaching methods are suggested for employing world background knowledge for an elaborated teaching of reading comprehension in an active learning environment in EFL classes.

Keywords: background knowledge, reading comprehension, schema theory, ELT classes

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Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

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Authors: Seada Hussen, Frie Ayalew

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Integrating different energy resources, like solar PV and hydro, is used to ensure reliable power to rural communities like Hara village in Ethiopia. Hybrid power system offers power supply for rural villages by providing an alternative supply for the intermittent nature of renewable energy resources. The intermittent nature of renewable energy resources is a challenge to electrifying rural communities in a sustainable manner with solar resources. Major rural villages in Ethiopia are suffering from a lack of electrification, that cause our people to suffer deforestation, travel for long distance to fetch water, and lack good services like clinic and school sufficiently. The main objective of this project is to provide a balanced, stable, reliable supply for Hara village, Ethiopia using solar power with a pumped hydro energy storage system. The design of this project starts by collecting data from villages and taking solar irradiance data from NASA. In addition to this, geographical arrangement and location are also taken into consideration. After collecting this, all data analysis and cost estimation or optimal sizing of the system and comparison of solar with pumped hydro and solar with battery storage system is done using Homer Software. And since solar power only works in the daytime and pumped hydro works at night time and also at night and morning, both load will share to cover the load demand; this need controller designed to control multiple switch and scheduling in this project fuzzy logic controller is used to control this scenario. The result of the simulation shows that solar with pumped hydro energy storage system achieves good results than with a battery storage system since the comparison is done considering storage reliability, cost, storage capacity, life span, and efficiency.

Keywords: pumped hydro storage, solar energy, solar PV, battery energy storage, fuzzy logic controller

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Authors: Louis Ngai Yuen Wong, Varun Maruvanchery

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The Bukit Timah Granite, which is a major rock formation in Singapore, encompasses different rock types such as granite, adamellite, and granodiorite with various hybrid rocks. The present study focuses on the Central Singapore Granite found in the Mandai area. Even within this small aerial extent, lithological variations with respect to the composition, texture as well as the grain size have been recognized in this igneous body. Over the years, the research effort on the Bukit Timah Granite has been focused on achieving a better understanding of its engineering properties in association with civil engineering projects. To our best understanding, a few types of research attempted to systematically investigate the influence of grain size, mineral composition, texture etc. on the strength of Bukit Timah Granite rocks in a comprehensive manner. In typical local industry practices, the different lithological varieties are not differentiated, but all are grouped under Bukit Timah Granite during core logging and the subsequent determination of engineering properties. To address such a major gap in the local engineering geological practice, a preliminary study is conducted on the variations of uniaxial compressive strength (UCS) in seven distinctly different lithological varieties found in the Bukit Timah Granite. Other physical properties including Young’s modulus, P-wave velocity and dry density determined from laboratory testing will also be discussed. The study is supplemented by a petrographical thin section examination. In addition, the specimen failure mode is classified and further correlated with the lithological varieties by carefully observing the details of crack initiation, propagation and coalescence processes in the specimens undergoing loading tests using a high-speed camera. The outcome of this research, which is the first of its type in Singapore, will have a direct implication on the sampling and design practices in the field of civil engineering and particularly underground space development in Singapore.

Keywords: Bukit Timah Granite, lithological variety, thin section study, high speed video, failure mode

Procedia PDF Downloads 322

Authors: Lucas A. Silva, Carla R. Aguiar

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This work presents a proposal to perform contextual sentiment analysis using a supervised learning algorithm and disregarding the extensive training of annotators. To achieve this goal, a web platform was developed to perform the entire procedure outlined in this paper. The main contribution of the pipeline described in this article is to simplify and automate the annotation process through a system of analysis of congruence between the notes. This ensured satisfactory results even without using specialized annotators in the context of the research, avoiding the generation of biased training data for the classifiers. For this, a case study was conducted in a blog of entrepreneurship. The experimental results were consistent with the literature related annotation using formalized process with experts.

Keywords: sentiment analysis, untrained annotators, naive bayes, entrepreneurship, contextualized classifier

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Authors: Kari Björn, Mikael Soini

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Higher Education system reforms, especially Finnish system of Universities of Applied Sciences in 2014 are discussed. The new steering model is based on major legislative changes, output-oriented funding and open information. The governmental steering reform, especially the financial model and the resulting institutional level responses, such as a curriculum reforms are discussed, focusing especially in engineering programs. The paper is motivated by management need to establish objective steering-related performance indicators and to apply them consistently across all educational programs. The close relationship to governmental steering and funding model imply that internally derived indicators can be directly applied. Metropolia University of Applied Sciences (MUAS) as a case institution is briefly introduced, focusing on engineering education in Information and Communications Technology (ICT), and its related programs. The reform forced consolidation of previously separate smaller programs into fewer units of student application. New curriculum ICT students have a common first year before they apply for a Major. A framework of parallel and longitudinal comparisons is introduced and used across Majors in two campuses. The new externally introduced performance criteria are applied internally on ICT Majors using data ex-ante and ex-post of program merger.  A comparative performance of the Majors after completion of joint first year is established, focusing on previously omitted Majors for completeness of analysis. Some new research questions resulting from transfer of Majors between campuses and quota setting are discussed. Practical orientation identifies best practices to share or targets needing most attention for improvement. This level of analysis is directly applicable at student group and teaching team level, where corrective actions are possible, when identified. The analysis is quantitative and the nature of the corrective actions are not discussed. Causal relationships and factor analysis are omitted, because campuses, their staff and various pedagogical implementation details contain still too many undetermined factors for our limited data. Such qualitative analysis is left for further research. Further study must, however, be guided by the relevance of the observations.

Keywords: engineering education, integrated curriculum, learning outcomes, performance measurement

Procedia PDF Downloads 241