Search results for: learning science

Authors: El Miloudi Djelloul

Abstract:

Technology nowadays enables the remote access to laboratory equipment and instruments via Internet. This is especially useful in engineering education, where students can conduct laboratory experiment remotely. Such remote laboratory access can enable student to use expensive laboratory equipment, which is not usually available to students. In this paper, we present a method of creating a Web-based Remote Laboratory Experimentation in the master degree course “Wireless Communications Systems” which is part of “ICS (Information and Communication Systems)” and “Investment Management in Telecommunications” curriculums. This is done within the RIPLECS Project and the NI2011 FF005 Research Project “Implementation of Project-Based Learning in an Interdisciplinary Master Program”.

Keywords: remote access, remote laboratory, wireless telecommunications, external antenna-switching controller board (EASCB)

Procedia PDF Downloads 499

Authors: Digby Warren, Jiri Kropac

Abstract:

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

Procedia PDF Downloads 103

Authors: Jian Wang

Abstract:

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

Procedia PDF Downloads 68

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

Abstract:

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

Procedia PDF Downloads 96

Authors: Shiva Ebrahimian Dehaghani, Afsaneh Doosti, Morteza Zare

Abstract:

Background: There is no consensus regarding the association between dysphagia and cognition. Purpose: The aim of this study was to quantitatively and qualitatively analyze the available evidence on the direction and strength of association between dysphagia and cognition. Methodology: PubMed, Scopus, Embase and Web of Science were searched about the association between dysphagia and cognition. A random-effects model was used to determine weighted odds ratios (OR) and 95% confidence intervals (CI). Sensitivity analysis was performed to determine the impact of each individual study on the pooled results. Results: A total of 1427 participants showed that some cognitive disorders were significantly associated with dysphagia (OR = 3.23; 95% CI, 2.33–4.48). Conclusion: The association between cognition and swallowing disorders suggests that multiple neuroanatomical systems are involved in these two functions.

Keywords: adult, association, cognitive impairment, dysphagia, systematic review

Procedia PDF Downloads 144

Authors: Viktorya Sargsyan, Arax Hovhannesyan, Karine Abelyan

Abstract:

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

Procedia PDF Downloads 160

Authors: Ede Jairus Adagba

Abstract:

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

Procedia PDF Downloads 286

Authors: Zheng Yuxun

Abstract:

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

Procedia PDF Downloads 22

Authors: Alexandra Shipley

Abstract:

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

Procedia PDF Downloads 61

Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

Abstract:

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

Procedia PDF Downloads 303

Authors: Vadim Kulikov

Abstract:

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

Procedia PDF Downloads 252

Authors: Chiahsu Yang, Peiling Wu, Ted Ho

Abstract:

From emphasizing economic development to stressing public happiness, the international community mainly hopes to be able to understand whether the quality of life for the public is becoming better. The Better Life Index (BLI) constructed by OECD uses living conditions and quality of life as starting points to cover 11 areas of life and to convey the state of the general public’s well-being. In light of the BLI framework, the Directorate General of Budget, Accounting and Statistics (DGBAS) of the Executive Yuan instituted the Gross National Happiness Index to understand the needs of the general public and to measure the progress of the aforementioned conditions in residents across the island. Whereas living conditions consist of income and wealth, jobs and earnings, and housing conditions, health status, work and life balance, education and skills, social connections, civic engagement and governance, environmental quality, personal security. The ICT area consists of health care, living environment, ICT-enabled communication, transportation, government, education, pleasure, purchasing, job & employment. In the wake of further science and technology development, rapid formation of information societies, and closer integration between lifestyles and information societies, the public’s well-being within information societies has indeed become a noteworthy topic. the Board of Science and Technology of the Executive Yuan use the OECD’s BLI as a reference in the establishment of the Taiwan-specific ICT-Enabled Better Life Index. Using this index, the government plans to examine whether the public’s quality of life is improving as well as measure the public’s satisfaction with current digital quality of life. This understanding will enable the government to gauge the degree of influence and impact that each dimension of digital services has on digital life happiness while also serving as an important reference for promoting digital service development. The content of the ICT Enabled Better Life Index. Information and communications technology (ICT) has been affecting people’s living styles, and further impact people’s quality of life (QoL). Even studies have shown that ICT access and usage have both positive and negative impact on life satisfaction and well-beings, many governments continue to invest in e-government programs to initiate their path to information society. This research is the few attempts to link the e-government benchmark to the subjective well-being perception, and further address the gap between user’s perception and existing hard data assessment, then propose a model to trace measurement results back to the original public policy in order for policy makers to justify their future proposals.

Keywords: information and communications technology, quality of life, satisfaction, well-being

Procedia PDF Downloads 334

Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

Abstract:

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

Procedia PDF Downloads 60

Authors: Angga S. Fajar, A. Aminullah, J. Kiyono, R. A. Safitri

Abstract:

This paper discusses about the application of ANN for optimizing of bridge structure design. ANN has been applied in various field of science concerning prediction and optimization. The structural optimization has several benefit including accelerate structural design process, saving the structural material, and minimize self-weight and mass of structure. In this paper, there are three types of bridge structure that being optimized including PSC I-girder superstructure, composite steel-concrete girder superstructure, and RC bridge pier. The different optimization strategy on each bridge structure implement back propagation method of ANN is conducted in this research. The optimal weight and easier design process of bridge structure with satisfied error are achieved.

Keywords: bridge structures, ANN, optimization, back propagation

Procedia PDF Downloads 359

Authors: Pui-Lai To, E-Ping Sung

Abstract:

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

Procedia PDF Downloads 459

Authors: R. Mellah, R. Toumi

Abstract:

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

Procedia PDF Downloads 308

Authors: Ukhtie Nantika Mena, Ahmad Juntika Nurihsan, Ilfiandra

Abstract:

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

Procedia PDF Downloads 124

Authors: Olga Kononova, Sergey Lyapin

Abstract:

Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

Procedia PDF Downloads 341

Authors: Slim Souissi, Mohamed Ben Amar, Nesrine Bouhamed, Pierre Marechal

Abstract:

The bio-composites development from biodegradable materials and natural fibers has a growing interest in the science of composite materials. The present work was conducted as part of a cooperation project between the Sfax University and the Havre University. This work consists in developing and monitoring the properties of a composite material of olive flour wood with a polymer matrix (urea formaldehyde). For this, ultrasonic non-destructive and destructive methods of characterization were used to optimize the mechanical and acoustic properties of the studied material based on the elaboration parameters.

Keywords: bio-composite, olive flour wood, polymer matrix, ultrasonic methods, mechanical properties

Procedia PDF Downloads 478

Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

Abstract:

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

Procedia PDF Downloads 396

Authors: A. Salemi Golezania, A. Sharifi Fateha

Abstract:

In this study a nano-composite catalyst was synthesized by incorporation of chromium into the framework of MCM-41 as a base catalyst. Mesoporous silica molecular sieves MCM-41 were synthesized under Hydrothermal Continues pH Adjusting Path Way. Then, MCM-41 was impregnated by chromium nitrate aqueous solution for several times under water aspiration. Raw powder was cured by heat treatment in vacuum furnace at 500°C. Phase formation, morphology and gas absorption properties of resulted materials were characterized by XRD, TEM and BET analysis, respectively. The results showed that high quality hexagonal meso structure as a matrix and Cr as a second phase has been formed with a narrow size pore diameter distribution and high surface area in Cr/MCM-41 nano-composite structure. The specific surface and total volume of porosity of the synthesized nanocomposite are obtained 931m^2/gr and 1.12 cm^3/gr, respectively.

Keywords: nano-catalyst, MCM-41, Cr/MCM-41, Marine Science and Engineering

Procedia PDF Downloads 372

Authors: Devleminck Steven, Debackere Boris

Abstract:

This research is about the ways artists and scientists deal with (and endure) new meaning and comprehend and construct the world. The project reflects on the intense connection between comprehension and construction and their place of creation – the ‘locus of action’. It seeks to define a liquid form of understanding and analysis capable of approaching our complex liquid world as discussed by Zygmunt Bauman. The aim is to establish a multi-viewpoint theoretical approach based on the dynamic concept of the Flâneur as introduced by Baudelaire, replacing single viewpoint categorization. This is coupled with the concept of thickening as proposed by Clifford Geertz with its implication of interaction between multi-layers of meaning. Here walking and looking is introduced as a method or strategy, a model or map, providing a framework of understanding in conditions of hybridity and change.

Keywords: action, art, liquid, locus, negotiation, place, science

Procedia PDF Downloads 267

Authors: Afroze Ibrahim Baqapuri, Ilya Trofimov

Abstract:

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

Procedia PDF Downloads 556

Authors: Tomi Lois Olatunji, Frances Siebert, Ademola Emmanuel Adetunji, Brian Harvey, Johane Gericke, Josias Hamman, Frank Van Der Kooy

Abstract:

Ethnopharmacological relevance: Sceletium tortuosum (L.) N.E.Br, the most sought after and widely researched species in the genus Sceletium is a succulent forb endemic to South Africa. Traditionally, this medicinal plant is mainly masticated or smoked and used for the relief of toothache, abdominal pain, and as a mood-elevator, analgesic, hypnotic, anxiolytic, thirst and hunger suppressant, and for its intoxicating/euphoric effects. Sceletium tortuosum is currently of widespread scientific interest due to its clinical potential in treating anxiety and depression, relieving stress in healthy individuals, and enhancing cognitive functions. These pharmacological actions are attributed to its phytochemical constituents referred to as mesembrine-type alkaloids. Aim of the review: The aim of this review was to comprehensively summarize and critically evaluate recent research advances on the phytochemistry, pharmacokinetics, biological and clinical activities of the medicinal plant S. tortuosum. Additionally, current ongoing research and future perspectives are also discussed. Methods: All relevant scientific articles, books, MSc and Ph.D. dissertations on botany, behavioral pharmacology, traditional uses, and phytochemistry of S. tortuosum were retrieved from different databases (including Science Direct, PubMed, Google Scholar, Scopus and Web of Science). For pharmacokinetics and pharmacological effects of S. tortuosum, the focus fell on relevant publications published between 2009 and 2021. Results: Twenty-five alkaloids belonging to four structural classes viz: mesembrine, Sceletium A4, joubertiamine, and tortuosamine, have been identified from S. tortuosum, of which the mesembrine class is predominant. The crude extracts and commercially available standardized extracts of S. tortuosum have displayed a wide spectrum of biological activities (e.g. antimalarial, anti-oxidant, immunomodulatory, anti-HIV, neuroprotection, enhancement of cognitive function) in in vitro or in vivo studies. This plant has not yet been studied in a clinical population, but has potential for enhancing cognitive function, and managing anxiety and depression. Conclusion: As an important South African medicinal plant, S. tortuosum has garnered many research advances on its phytochemistry and biological activities over the last decade. These scientific studies have shown that S. tortuosum has various bioactivities. The findings have further established the link between the phytochemistry and pharmacological application, and support the traditional use of S. tortuosum in the indigenous medicine of South Africa.

Keywords: Aizoaceae, Mesembrine, Serotonin, Sceletium tortuosum, Zembrin®, psychoactive, antidepressant

Procedia PDF Downloads 200

Authors: Fernandez liporace, Mercedes Uriel Fabiana

Abstract:

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

Procedia PDF Downloads 354

Authors: Mayuri Roy Choudhury

Abstract:

In recent times the concept of agrivoltaics has gained popularity due to the dual use of land and the added value provided by photovoltaics in terms of renewable energy and crop production on farms. However, the transition towards agrivoltaics has been slow, and our research tries to investigate the obstacles leading towards the slow progress of agrivoltaics. We applied data science decision tree algorithms to quantify qualitative perceptions of farmers in the United States for agrivoltaics. To date, there has not been much research that mentions farmers' perceptions, as most of the research focuses on the benefits of agrivoltaics. Our study adds value by putting forward the voices of farmers, which play a crucial towards the transition to agrivoltaics in the future. Our results show a mixture of responses in favor of agrivoltaics. Furthermore, it also portrays significant concerns of farmers, which is useful for decision-makers when it comes to formulating policies for agrivoltaics.

Keywords: agrivoltaics, decision-tree algorithms, farmers perception, transition

Procedia PDF Downloads 172

Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

Abstract:

Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

Procedia PDF Downloads 171

Authors: Senthuran Manoharan, Rathesan Sivagananalingam

Abstract:

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

Procedia PDF Downloads 223

Authors: Ruzanna Muradyan

Abstract:

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

Procedia PDF Downloads 40

Authors: Eeva Wallenius-Nareneva, Tuula Toivanen-Labiad

Abstract:

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

Procedia PDF Downloads 272