Search results for: affective computing

Authors: Ammara Mehmood, Aneela Zameer, Muhammad Asif Zahoor Raja, Muhammad Faisal Fateh

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In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by defining an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefficient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels.

Keywords: parameter estimation, bio-inspired computing, continuous differential evolution (CDE), periodic signals

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Naiara Ozamiz Etcebarria, Sonia Ruiz De Azua Garcia, Agurtzane Ortiz Jauregi, Virginia Guillen Cañas

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Introduction: The most relevant competencies of a health professional are an adequate communication capacity, which will influence the satisfaction of professionals and patients, therapeutic compliance, conflict prevention, clinical outcomes´ improvement and efficiency of health services. The ability of Active listening , empathy, assertiveness and social skills, are important abilities to develop in all professions in which there is a relationship with other people. In the field of health, it is even more important to have adequate qualities so that the treatment with the patient will be adequate and satisfactory. We conducted a research with students of third year in the Degree of Medicine with the objectives: - to know how the active listening, empathy, assertiveness and social skills of students are. - to know if there are differences according to different demographic variables, such as sex, language, age, number of siblings and interest in the subject. Material and Methods: The students of the Third year in the Degree of Medicine (N = 212) participated voluntarily. Sociodemographic data were collected. Descriptive and comparative analysis of the averages of the students with respect to active listening, empathy, assertiveness and social skills were performed. Once the questionnaires were collected, they were entered into the SPSS 21 database. Four communicational aspects were evaluated: The active listening questionnaire, the TECA empathy questionnaire, the ACDA questionnaire and the EHS questionnaire Social Skills Scale. The active listening questionnaire assesses these factors: Listening without interruption and less contradiction, Listening with 100% attention, Listening beyond words, Listening encouraging the other to go deeper. The TECA questionnaire of cognitive and affective empathy evaluates: Adoption of perspectives, Emotional Comprehension, Emphasizing stress, Empathic joy. The EHS questionnaire Social Skills Scale: Self-expression in social situations, Defending one's own rights as a consumer, Expressing anger or dissatisfaction, Refusing to do and cutting interactions off, Making requests, Initiating positive interactions with the other sex. The ACDA questionnaire Assertiveness Assessment Scale evaluates self-assertiveness and heteroaservitivity. Applicability: To train these skills is so important for clinical practice of medical students and these capabilities that can be measured in a longitudinal way time. Ethical-legal aspects: The data were anonymous. The study was approved by the Ethics Committee. Results: The students of the Third year in the Degree of Medicine (34.4% Basque speakers and 65.6% Spanish speakers) with average age 20.93, (27.8% men and 72.2% women). There are no differences in social skills between men and women. The Basque speaker students of are more heteroactive (ACDA) than Spanish students. Active listening has a high correlation with social skills, especially with self-expression in social situations. Listening without interruption has a high correlation with self-expression in social situations and initiating positive interactions with the opposite sex. Adoption of perspectives presents a high correlation with auto- assertiveness. Emotional understanding presents a high correlation with positive interactions with the opposite sex. Empathic joy correlates with self-assertiveness, self-expression in social situations, and initiating positive interactions with the opposite sex.

Keywords: active listening, assertiveness, communicational skills, empathy, students of medicine

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Authors: Marlone D. Severo

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A pre- and post-test quasi-experimental design was used to test the intervention of Trachtenberg Speed Math on the mathematical competency of sixty (60) matched-paired students with a poor performing grade in Mathematics from one of the biggest public national high school at the South of Metro Manila. Both control and experimental group were administered with the Attitude Towards Mathematics Inventory (ATMI) before the pretest were given and both group showed high dislike for Mathematics. Pretest showed a 53 percent accuracy for the control group and 51 percent for the experimental group using a 15-item long multiplication test without any aid of a computing device. The experimental group were taught how to use the Trachtenberg number-keys and techniques in multiplication between October 2014 to March 2015. Post-test showed an improvement in the experimental group with 96 percent accuracy for the control group and a dismal 57 percent for the control group in long-multiplication. Post-test ATMI were administered. The control group showed a great dislike towards Mathematics, while the experimental group showed a positive attitude towards the subject.

Keywords: attitude towards mathematics, mathematical competency, number-keys, trachtenberg speed math

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Authors: Pejman Hosseinioun, Abolghasem Ghasempour, Elham Gholami, Hamed Sarbazi

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Considering the development in global semiconductor technology, it is anticipated that gadgets such as diodes and resonant transistor tunnels (RTD/RTT), Single electron transistors (SET) and quantum cellular automata (QCA) will substitute CMOS (Complementary Metallic Oxide Semiconductor) gadgets in many applications. Unfortunately, these new technologies cannot disembark the common Boolean logic efficiently and are only appropriate for liminal logic. Therefor there is no doubt that with the development of these new gadgets it is necessary to find new MacDraw technologies which are compatible with them. Resonant transistor tunnels (RTD/RTT) and circuit MacDraw with enhanced computing abilities are candida for accumulating Nano criterion in the future. Quantum cellular automata (QCA) are also advent Nano technological gadgets for electrical circuits. Advantages of these gadgets such as higher speed, smaller dimensions, and lower consumption loss are of great consideration. QCA are basic gadgets in manufacturing gates, fuses and memories. Regarding the complex Nano criterion physical entity, circuit designers can focus on logical and constructional design to decrease complication in MacDraw. Moreover Single electron technology (SET) is another noteworthy gadget considered in Nano technology. This article is a survey in future of Nano technology in digital MacDraw.

Keywords: nano technology, resonant transistor tunnels, quantum cellular automata, semiconductor

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Authors: Ankur Bansal, Shashank Bishnoi

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Degradation of Sewage pipes, sewage pumping station and Sewage treatment plants(STP) is of major concern due to difficulty in their maintenance and the high cost of replacement. Most of these systems undergo degradation due to Biogenic sulphuric acid (BSA) attack. Since most of Waste water treatment system are underground, detection of this deterioration remains hidden. This paper presents a literature review, outlining the mechanism of this attack focusing on critical parameters of BSA attack, along with available models and software to predict the deterioration due to this attack. This paper critically examines the various steps and equation in various Models of BSA degradation, detail on assumptions and working of different softwares are also highlighted in this paper. The paper also focuses on the service life design technique available through various codes and method to integrate the servile life design with BSA degradation on concrete. In the end, various methods enhancing the resistance of concrete against Biogenic sulphuric acid attack are highlighted. It may be concluded that the effective modelling for degradation phenomena may bring positive economical and environmental impacts. With current computing capabilities integrated degradation models combining the various durability aspects can bring positive change for sustainable society.

Keywords: concrete degradation, modelling, service life, sulphuric acid attack

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Authors: Kwang Chun, John Kemeny

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Light detection and ranging (LiDAR) has been a prevalent remote-sensing technology applied in the geological fields due to its high precision and ease of use. One of the major applications is to use the detailed geometrical information of underground structures as a basis for the generation of a three-dimensional numerical model that can be used in a geotechnical stability analysis such as FEM or DEM. To date, however, straightforward techniques in reconstructing the numerical model from the scanned data of the underground structures have not been well established or tested. In this paper, we propose a comprehensive approach integrating all the various processes, from LiDAR scanning to finite element numerical analysis. The study focuses on converting LiDAR 3D point clouds of geologic structures containing complex surface geometries into a finite element model. This methodology has been applied to Kartchner Caverns in Arizona, where detailed underground and surface point clouds can be used for the analysis of underground stability. Numerical simulations were performed using the finite element code Abaqus and presented by 3D computing visualization solution, ParaView. The results are useful in studying the stability of all types of underground excavations including underground mining and tunneling.

Keywords: finite element analysis, LiDAR, remote-sensing, scientific visualization, underground stability

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Authors: Anna-Maria Ramezanzadeh

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Demand for Arabic language is growing worldwide, driven by increased interest in the multifarious purposes the language serves, both for the population of heritage learners and those studying Arabic as a foreign language. The diglossic, or indeed multiglossic nature of the language as used in Arabic speaking communities however, is seldom represented in the content of classroom courses. This disjoint between the nature of provision and students’ expectations can severely impact their engagement with course material, and their motivation to either commence or continue learning the language. The nature of motivation and its relationship to multiglossia is sparsely explored in current literature on Arabic. The theoretical framework here proposed aims to address this gap by presenting a model and instruments for the measurement of Arabic learners’ motivation in relation to the multiple strands of the language. It adopts and develops the Second Language Motivation Self-System model (L2MSS), originally proposed by Zoltan Dörnyei, which measures motivation as the desire to reduce the discrepancy between leaners’ current and future self-concepts in terms of the second language (L2). The tripartite structure incorporates measures of the Current L2 Self, Future L2 Self (consisting of an Ideal L2 Self, and an Ought-To Self), and the L2 Learning Experience. The strength of the self-concepts is measured across three different domains of Arabic: Classical, Modern Standard and Colloquial. The focus on learners’ self-concepts allows for an exploration of the effect of multiple factors on motivation towards Arabic, including religion. The relationship between Islam and Arabic is often given as a prominent reason behind some students’ desire to learn the language. Exactly how and why this factor features in learners’ L2 self-concepts has not yet been explored. Specifically designed surveys and interview protocols are proposed to facilitate the exploration of these constructs. The L2 Learning Experience component of the model is operationalized as learners’ task-based engagement. Engagement is conceptualised as multi-dimensional and malleable. In this model, situation-specific measures of cognitive, behavioural, and affective components of engagement are collected via specially designed repeated post-task self-report surveys on Personal Digital Assistant over multiple Arabic lessons. Tasks are categorised according to language learning skill. Given the domain-specific uses of the different varieties of Arabic, the relationship between learners’ engagement with different types of tasks and their overall motivational profiles will be examined to determine the extent of the interaction between the two constructs. A framework for this data analysis is proposed and hypotheses discussed. The unique combination of situation-specific measures of engagement and a person-oriented approach to measuring motivation allows for a macro- and micro-analysis of the interaction between learners and the Arabic learning process. By combining cross-sectional and longitudinal elements with a mixed-methods design, the model proposed offers the potential for capturing a comprehensive and detailed picture of the motivation and engagement of Arabic learners. The application of this framework offers a number of numerous potential pedagogical and research implications which will also be discussed.

Keywords: Arabic, diglossia, engagement, motivation, multiglossia, sociolinguistics

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Authors: Daidai Shen, Jean Claude Thill, Wenjia Zhang

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This study explores the dynamics of synergy and complementarity within city networks, specifically focusing on the headquarters-subsidiary relations of firms. We begin by defining these two types of networks and establishing their pivotal roles in shaping city network structures. Utilizing the mesoscale analytic approach of weighted stochastic block modeling, we discern relational patterns between city pairs and determine connection strengths through statistical inference. Furthermore, we introduce a community detection approach to uncover the underlying structure of these networks using advanced statistical methods. Our analysis, based on comprehensive network data up to 2017, reveals the coexistence of both complementarity and synergy networks within China’s technology-intensive manufacturing cities. Notably, firms in technology hardware and office & computing machinery predominantly contribute to the complementarity city networks. In contrast, a distinct synergy city network, underpinned by the cities of Suzhou and Dongguan, emerges amidst the expansive complementarity structures in technology hardware and equipment. These findings provide new insights into the relational dynamics and structural configurations of city networks in the context of technology-intensive manufacturing, highlighting the nuanced interplay between synergy and complementarity.

Keywords: city system, complementarity, synergy network, higher-order network

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: knowledge representation, pervasive computing, agent technology, ECA rules

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Apirak Sombat, Teerapol Saleewong, Poom Kumam, Parin Chaipunya, Wiyada Kumam, Anantachai Padcharoen, Yeol Je Cho, Thana Sutthibutpong

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This research is aimed to study a two-step iteration process defined over a finite family of σ-asymptotically quasi-nonexpansive nonself-mappings. The strong convergence is guaranteed under the framework of Banach spaces with some additional structural properties including strict and uniform convexity, reflexivity, and smoothness assumptions. With similar projection technique for nonself-mapping in Hilbert spaces, we hereby use the generalized projection to construct a point within the corresponding domain. Moreover, we have to introduce the use of duality mapping and its inverse to overcome the unavailability of duality representation that is exploit by Hilbert space theorists. We then apply our results for σ-asymptotically quasi-nonexpansive nonself-mappings to solve for ideal efficiency of vector optimization problems composed of finitely many objective functions. We also showed that the obtained solution from our process is the closest to the origin. Moreover, we also give an illustrative numerical example to support our results.

Keywords: asymptotically quasi-nonexpansive nonself-mapping, strong convergence, fixed point, uniformly convex and uniformly smooth Banach space

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

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Authors: Line Massé, Claire Baudry, Claudia Verret, Marie-France Nadeau, Anne Brault-Labbé

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Little research has been conducted on educational services adapted for twice exceptional students. Within an action research, a cluster grouping was set up in an elementary school in Quebec, bringing together gifted or doubly exceptional (2E) students (n = 11) and students not identified as gifted (n = 8) within a multilevel class (3ᵣ𝒹 and 4ₜₕ years). 2E students had either attention deficit hyperactivity disorder (n = 8, including 3 with specific learning disability) or autism spectrum disorder (n = 2). Differentiated instructions strategies were implemented, including the possibility of progressing at their own pace of learning, independent study or research projects, flexible accommodation, tutoring with older students and the development of socio-emotional learning. A specialized educator also supported the teacher in the class for behavioural and socio-affective aspects. Objectives: The study aimed to assess the impacts of the grouping on all students, their academic motivation, and their socio-emotional adaptation. Method: A mixed method was used, combining a qualitative approach with a quantitative approach. Semi-directed interviews were conducted with students (N = 18, 4 girls and 14 boys aged 8 to 9) and one of their parents (N = 18) at the end of the school year. Parents and students completed two questionnaires at the beginning and end of the school year: the Behavior Assessment System for Children-3, children or parents versions (BASC-3, Reynolds and Kampus, 2015) and the Academic Motivation in Education (Vallerand et al., 1993). Parents also completed the Multidimensional Student Life Satisfaction Scale (Huebner, 1994, adapted by Fenouillet et al., 2014) comprising three domains (school, friendships, and motivation). Mixed thematic analyzes were carried out on the data from the interviews using the N'Vivo software. Related-samples Wilcoxon rank-sums tests were conducted for the data from the questionnaires. Results: Different themes emerge from the students' comments, including a positive impact on school motivation or attitude toward school, improved school results, reduction of their behavioural difficulties and improvement of their social relations. These remarks were more frequent among 2E students. Most 2E students also noted an improvement in their academic performance. Most parents reported improvements in attitudes toward school and reductions in disruptive behaviours in the classroom. Some parents also observed changes in behaviours at home or in the socio-emotional well-being of their children, here again, particularly parents of 2E children. Analysis of questionnaires revealed significant differences at the end of the school year, more specifically pertaining to extrinsic motivation identified, problems of conduct, attention, emotional self-control, executive functioning, negative emotions, functional deficiencies, and satisfaction regarding friendships. These results indicate that this approach could benefit not only gifted and doubly exceptional students but also students not identified as gifted.

Keywords: Cluster grouping, elementary school, giftedness, mixed methods, twice exceptional students

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Authors: Meenu S. Babu, K. Jayasankara Reddy

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Depression is a serious mental health concern that leads to significant distress and dysfunction in an individual. Due to the high physical, psychological, social, and economic burden it causes, it is important to study various bio-psycho-social factors that influence the onset, course, duration, intensity of depressive symptoms. The study aims to explore relationship between autobiographical memory (AM) functions, perceived control over stressful events and depressive symptoms. AM functions and perceived control were both found to be protective factors for individuals against depression and were both modifiable to predict better behavioral and affective outcomes. An extensive review of literatur, with a systematic search on Google Scholar, JSTOR, Science Direct and Springer Journals database, was conducted for the purpose of this review paper. These were used for all the aforementioned databases. The time frame used for the search was 2010-2021. An additional search was conducted with no time bar to map the development of the theoretical concepts. The relevant studies with quantitative, qualitative, experimental, and quasi- experimental research designs were included for the review. Studies including a sample with a DSM- 5 or ICD-10 diagnosis of depressive disorders were excluded from the study to focus on the behavioral patterns in a non-clinical population. The synthesis of the findings that were obtained from the review indicates there is a significant relationship between cognitive variables of AM functions and perceived control and depressive symptoms. AM functions were found to be have significant effects on once sense of self, interpersonal relationships, decision making, self- continuity and were related to better emotion regulation and lower depressive symptoms. Not all the components of AM function were equally significant in their relationships with various depressive symptoms. While self and directive functions were more related to emotion regulation, anhedonia, motivation and hence mood and affect, the social function was related to perceived social support and social engagement. Perceived control was found to be another protective cognitive factor that provides individuals a sense of agency and control over one’s life outcomes which was found to be low in individuals with depression. This was also associated to the locus of control, competency beliefs, contingency beliefs and subjective well being in individuals and acted as protective factors against depressive symptoms. AM and perceived control over stressful events serve adaptive functions, hence it is imperative to study these variables more extensively. They can be imperative in planning and implementing therapeutic interventions to foster these cognitive protective factors to mitigate or alleviate depressive symptoms. Exploring AM as a determining factor in depressive symptoms along with perceived control over stress creates a bridge between biological and cognitive factors underlying depression and increases the scope of developing a more eclectic and effective treatment plan for individuals. As culture plays a crucial role in AM functions as well as certain aspects of control such as locus of control, it is necessary to study these variables keeping in mind the cultural context to tailor culture/community specific interventions for depression.

Keywords: autobiographical memories, autobiographical memory functions, perceived control, depressive symptoms, depression, young adults

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

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Authors: Leila Goosen

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The research problem reported on in this paper relates to improving success in Computer Science and Information Technology subjects where students are learning applications, especially when teaching occurs in a distance education context. An investigation was launched in order to address students’ struggles with applications, and improve their assessment in such subjects. Some of the main arguments presented centre on formulating and situating significant concepts within an appropriate conceptual framework. The paper explores the experiences and perceptions of computing instructors, teaching assistants, students and higher education institutions on how they are empowered by using technologies such as myITLab. They also share how they are working with the available features to successfully teach applications to their students. The data collection methodology used is then described. The paper includes discussions on how myITLab empowers instructors, teaching assistants, students and higher education institutions. Conclusions are presented on the way in which this paper could make an original and significant contribution to the promotion and development of knowledge in fields related to successfully teaching applications for student learning, including in a distance education context. The paper thus provides a forum for practitioners to highlight and discuss insights and successes, as well as identify new technical and organisational challenges, lessons and concerns regarding practical activities related to myITLab as an implementation instance of distance education technologies.

Keywords: distance, education, myITLab, technologies

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Authors: Hussein Moselhy, Islam Salam

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There have been some challenges and problems which hinder the implementation of the e-marketing systems such as the high cost of information systems infrastructure and maintenance as well as their unavailability within the institution. Also, there is no system which supports all programming languages and different platforms. Another problem is the lack of integration between these systems on one hand and the operating systems and different web browsers on the other hand. No system for customer relationship management is established which recognizes their desires and puts them in consideration while performing e-marketing functions is available. Therefore, the service-oriented architecture emerged as one of the most important techniques and methodologies to build systems that integrate with various operating systems and different platforms and other technologies. This technology allows realizing the data exchange among different applications. The service-oriented architecture represents distributed computing concepts to demonstrate its success in achieving the requirements of systems through web services. It also reflects the appropriate design for the services to use different web services in supporting the requirements of business processes and software users. In a service-oriented environment, web services are deployed on the web in the form of independent services to be accessed without knowledge of the nature of the programs and systems with in. This Paper presents a proposal for a new model which contributes to the application of methods and means of e-marketing with the integration of marketing mix elements to improve marketing efficiency (E-MSOA). And apply it in the educational city of one of the Egyptian sector.

Keywords: service-oriented architecture, electronic commerce, virtual retailing, unified modeling language

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Authors: Muhammad Waqar Aziz, Syed Abdul Baqi Shah

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The execution time analysis is fundamental to the successful design and execution of real-time embedded software. In such analysis, the Worst-Case Execution Time (WCET) of a program is a key measure, on the basis of which system tasks are scheduled. The WCET analysis of embedded software is also needed for system understanding and to guarantee its behavior. WCET analysis can be performed statically (without executing the program) or dynamically (through measurement). Traditionally, research on the WCET analysis assumes sequential code running on single-core platforms. However, as computation is steadily moving towards using a combination of parallel programs and multi-core hardware, new challenges in WCET analysis need to be addressed. In this article, we report our experiences of performing the WCET analysis of Parallel Embedded Software (PES) running on multi-core platform. The primary purpose was to investigate how WCET estimates of PES can be computed statically, and how they can be derived dynamically. Our experiences, as reported in this article, include the challenges we faced, possible suggestions to these challenges and the workarounds that were developed. This article also provides observations on the benefits and drawbacks of deriving the WCET estimates using the said methods and provides useful recommendations for further research in this area.

Keywords: embedded software, worst-case execution-time analysis, static flow analysis, measurement-based analysis, parallel computing

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

Procedia PDF Downloads 155

Authors: Arif Ahmed Mohammed Al-Ahdal

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Poetry, tales, and fables have always been a part of the L1 repertoire and one that takes the learners to another amazing and fascinating world of imagination. The storytelling class and the genre of poems are activities greatly enjoyed by all age groups. The very significant idea behind their inclusion in the language curriculum is to sensitize young minds to a wide range of human emotions that are believed to greatly contribute to building their social resilience, emotional stability, empathy towards fellow creatures, and literacy. Quite certainly, the learning objective at this stage is not language acquisition (though it happens as an automatic process) but getting the young learners to be acquainted with an entire spectrum of what may be called the ‘noble’ abilities of the human race. They enrich their very existence, inspiring them to unearth ‘selves’ that help them as adults and enable them to co-exist fruitfully and symbiotically with their fellow human beings. By extension, ‘higher’ training in these literature genres shows the universality of human emotions, sufferings, aspirations, and hopes. The current study is anchored on the Reader-Response-Theory in literature learning, which suggests that the reader reconstructs work and re-enacts the author's creative role. Reiteratingly, literary works provide clues or verbal symbols in a linguistic system, widely accepted by everyone who shares the language, but everyone reads their own life experiences and situations into them. The significance of words depends on the reader, even if they have a typical relationship. In every reading, there is an interaction between the reader and the text. The process of reading is an experience in which the reader tries to comprehend the literary work, which surpasses its full potential since it provides emotional and intellectual reactions that are not anticipated from the document but cannot be affirmed just by the reader as a part of the text. The idea is that the text forms the basis of a unifying experience. A reinterpretation of the literary text may transform it into a guiding principle to respond to actual experiences and personal memories. The impulses delivered to the reader vary according to poetry or texts; nevertheless, the readers differ considerably even with the same material. Previous studies confirm that poetry is a useful tool for learning a language. This present paper works on these hypotheses and proposes to study the impetus given to L2 learning as a factor of exposure to poetry and meaningful stories in L1. The driving force behind the choice of this topic is the first-hand experience that the researcher had while teaching a literary text to a group of BA students who, as a reaction to the text, initially burst into tears and ultimately turned the class into an interactive session. The study also intends to compare the performance of male and female students post intervention using pre and post-tests, apart from undertaking a detailed inquiry via interviews with college learners of English to understand how L1 literature plays a great role in the acquisition of L2.

Keywords: SLA, literary text, poetry, tales, affective factors

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: confidence interval, handwriting, kernel density estimator, KDE, logistic regression LoR, repeatability, reproducibility

Procedia PDF Downloads 100

Authors: Abdul Hakim Chikho

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Most international codes allow the use of an equivalent lateral load method for designing practical buildings to withstand earthquake actions. This method requires calculating an approximation to the fundamental mode period of vibrations of these buildings. Several empirical equations have been suggested to calculate approximations to the fundamental periods of different types of structures. Most of these equations are knowing to provide an only crude approximation to the required fundamental periods and repeating the calculation utilizing a more accurate formula is usually required. In this paper, a new formula to calculate a satisfactory approximation of the fundamental period of a practical building is proposed. This formula takes into account the mass and the stiffness of the building therefore, it is more logical than the conventional empirical equations. In order to verify the accuracy of the proposed formula, several examples have been solved. In these examples, calculating the fundamental mode periods of several farmed buildings utilizing the proposed formula and the conventional empirical equations has been accomplished. Comparing the obtained results with those obtained from a dynamic computer has shown that the proposed formula provides a more accurate estimation of the fundamental periods of practical buildings. Since the proposed method is still simple to use and requires only a minimum computing effort, it is believed to be ideally suited for design purposes.

Keywords: earthquake, fundamental mode period, design, building

Procedia PDF Downloads 262

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

Procedia PDF Downloads 132

Authors: Desere Kokt

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Hospitality establishments worldwide are bearing the brunt of the effects of Covid-19. As the hospitality industry is looking to recover, emphasis is placed on rejuvenating the industry. This is especially pertinent for economic development in areas of high unemployment, such as the Free State province of South Africa. The province is not a main tourist area and thus depends on the influx of tourists. The province has great scenic beauty with many accommodation establishments that provide job opportunities to the local population. The two main economic hubs of the Free State province namely Bloemfontein and Clarens, were the focus of the investigation. The emphasis was on graded accommodation establishments as they must adhere to the quality principles of the Tourism Grading Council of South Africa (TGCSA) to obtain star grading. The hospitality industry is known for being labour intensive, and employees need to be available to cater for the needs of paying customers. This is referred to as ‘emotional labour’ and implies that employees need to manage their feelings and emotions as part of performing their jobs. The focus of this study was thus on psychological factors related to working in the hospitality industry – specifically psychological contract and psychological capital and its impact on the commitment of employees in graded accommodation establishments. Employee commitment can be explained as a psychological state that binds the individual to the organisation and involves a set of psychological relationships that include affective (emotions), normative (perceived obligation) and continuance (staying with the organisation) dimensions. Psychological contract refers to the reciprocal beliefs and expectations between the employer and the employee and consists of transactional and rational contracts. Transactional contracts are associated with the economic exchange, and contractional issues related to the employment contract and rational contracts relate to the social exchange between the employee and the organisation. Psychological capital refers to an individual’s positive psychology state of development that is characterised by self-efficiency (having confidence in doing one’s job), optimism (being positive and persevering towards achieving one’s goals), hope (expectations for goals to succeed) and resilience (bouncing back to attain success when beset by problems and adversity). The study employed a quantitative research approach, and a structured questionnaire was used to gather data from respondents. The study was conducted during the Covid-19 pandemic, which hampered the data gathering efforts of the researchers. Many accommodation establishments were either closed or temporarily closed, which meant that data gathering was an intensive and laborious process. The main researcher travelled to the various establishments to collect the data. Nine hospitality establishments participated in the study, and around 150 employees were targeted for data collection. Ninety-two (92) questionnaires were completed, which represents a response rate of 61%. Data were analysed using descriptive and inferential statistics, and partial least squares structural equation modelling (PLS-SEM) was applied to examine the relationship between the variables.

Keywords: employee commitment, hospitality industry, psychological contract, psychological capital

Procedia PDF Downloads 84

Authors: Aleksandra Rajewska-Rager, Maria Skibinska, Monika Dmitrzak-Weglarz, Natalia Lepczynska, Pawel Kapelski, Joanna Pawlak, Joanna Hauser

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Introduction: Inflammation and cytokines have emerged as a promising target in mood disorders research; however there are still very limited numbers of study regarding inflammatory alterations among adolescents and young adults with mood disorders. The Macrophage Migration Inhibitory Factor (MIF) and Stem Cell Factor (SCF) are the pleiotropic cytokines which may play an important role in mood disorders pathophysiology. The aim of this study was to investigate levels of these factors in serum of adolescent and young adults with mood disorders compared to healthy controls. Subjects: We involved 79 patients aged 12-24 years in 2-year follow-up study with a primary diagnosis of mood disorders: bipolar disorder (BP) and unipolar disorder with BP spectrum. Study group includes 23 males (mean age 19.08, SD 3.3) and 56 females (18.39, SD 3.28). Control group consisted 35 persons: 7 males (20.43, SD 4.23) and 28 females (21.25, SD 2.11). Clinical diagnoses according to DSM-IV-TR criteria were assessed using Kiddie-Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version (K-SADS-PL) and Structured Clinical Interview for the Diagnostic and Statistical Manual (SCID) in young adults respectively. Clinical assessment includes evaluation of clinical factors and symptoms severity (rated using the Hamilton Depression Rating Scale and Young Mania Rating Scale). Clinical and biological evaluations were made at control visits respectively at baseline (week 0), euthymia (at month 3 or 6) and after 12 and 24 months. Methods: Serum protein concentration was determined by Enzyme-Linked Immunosorbent Assays (ELISA) method. Human MIF and SCF DuoSet ELISA kits were used. In the analyses non-parametric tests were used: Mann-Whitney U test, Kruskal-Wallis ANOVA, Friedman’s ANOVA, Wilcoxon signed rank test, Spearman correlation. We defined statistical significance as p < 0.05. Results: Comparing MIF and SCF levels between acute episode of depression/hypo/mania at baseline and euthymia (at month 3 or 6) we did not find any statistical differences. At baseline patients with age above 18 years old had decreased MIF level compared to patients younger than 18 years. MIF level at baseline positively correlated with age (p=0.004). Positive correlations of SCF level at month 3 and 6 with depression or mania occurrence at month 24 (p=0.03 and p=0.04, respectively) was detected. Strong correlations between MIF and SCF levels at baseline (p=0.0005) and month 3 (p=0.03) were observed. Discussion: Our results did not show any differences in MIF and SCF levels between acute episode of depression/hypo/mania and euthymia in young patients. Further studies on larger groups are recommended. Grant was founded by National Science Center in Poland no 2011/03/D/NZ5/06146.

Keywords: cytokines, MIF, mood disorders, SCF

Procedia PDF Downloads 181

Authors: Lukasz Grzegorz Broda, Taiwo Oseni, Andrew Stranieri, Rodrigo Marino, Ronelle Welton, Mark Yates

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The oral health of residents in aged care centres in Australia is poor, contributing to infections, hospital admissions, and increased suffering. Although the use of electric toothbrushes has been deployed in many centres, smartbrushes that record and transmit information about brushing patterns and duration are not routinely deployed. Yet, the use of smartbrushes for aged care residents promises better oral care. Thus, a study aimed at investigating the appropriateness and suitability of a smartbrush for aged care residents is currently underway. Due to the peculiarity of the aged care setting, the incorporation of smartbrushes into residents’ care does require careful planning and design considerations. This paper describes an initial design process undertaken through the use of an actor to understand the important elements to be incorporated whilst installing a smartbrush for use in aged care settings. The design covers the configuration settings of the brush and app, including ergonomic factors related to brush and smartphone placement. A design science approach led to an installation re-design and a revised protocol for the planned study, the ultimate aim being to design installations to enhance perceived usefulness, ease of use, and attitudes towards the incorporation of smartbrushes for improving oral health care for aged care residents.

Keywords: smartbrush, applied computing, life and medical sciences, health informatics

Procedia PDF Downloads 146