Search results for: cognitive model

Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Ioanna Taouki, Marie Lallier, David Soto

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Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: Natalia Kajka, Agnieszka Kulik

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The aim of the study is to present the results regarding differences in perception of cognitive progress of children with Attention Deficit Hyperactivity Disorder (ADHD) by adults and children themselves. The experiment was attended by 45 children with ADHD, their parents and teachers. The children attended the 3-month metacognitive training. Both children and adults were examined before and after joining this project. In order to show significant differences between the first and second measurement of the test, non-parametric Wilcoxon tests were performed. The analysis showed statistically significant differences in the change of cognitive functioning in children with ADHD participating in metacognitive training, this was also confirmed by the results of the parents' research. There were no significant differences in the teachers' assessment of these children.

Keywords: ADHD, executive function, Golem effect metacognitive training

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Authors: Muhammad Shafi'u Adamu

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This study examined the effects of two Group Cognitive Behavioural Therapies (Cognitive Restructuring and Rational Emotive Behavioural Therapy) on Psychological Distress of awaiting-trial Inmates in Correctional Centres in North-West, Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centres in North-west, Nigeria. 131 awaiting trial inmates from three intact Correctional Centres were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to pilot study using Cronbach's Alpha with reliability co-efficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean sores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicating the posttreatment reduction of psychological distress on the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference on those exposed to REBT. The research recommends that a standardized structured CBT counselling technique treatment should be designed for correctional centres across Nigeria, and CBT counselling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centres, group cognitive behavioural therapies, rational emotive behavioural therapy

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Authors: Alberti Pascal, Mustapha Mouloua

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Companies are confronted with complex and competitive markets. The dynamics of these markets are becoming more and more fluid, requiring companies to provide competitive, definite and technological responses within increasingly short timeframes. To meet this demand, companies must rely on the cognitive abilities of actors of creativity to provide tangible answers to current contextual problems. It therefore seems appropriate to provide instruments to support this particular stage of innovation. Various methods and tools can meet this requirement. For a number of years we have been conducting experiments on the use of mind maps in the context of innovation projects with teams of different nationalities. After presenting the main research carried out on this theme, we discuss the possible correlation between the different uses of iconic tools and certain types of innovation. We then provide a link with different cognitive logic. Finally, we conclude by putting our research into perspective.

Keywords: creativity, innovation, causal logic, effectual logic, mind mapping

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Authors: Coskun Serefoglu

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The study aims to analyse how a traditional sector such as agri-food could be mobilized through regional innovation strategies. A principal component analysis as well as qualitative information, such as in-depth interviews, focus group and surveys, were employed to find the priority sectors. An agri-food model was developed which includes both a linear model and interactive model. The model consists of two main components, one of which is technological integration and the other one is agricultural extension which is based on Land-grant university approach of U.S. which is not a common practice in Turkey.

Keywords: regional innovation strategy, interactive model, agri-food sector, local development, planning, regional development

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Authors: Sasiporn Rattanasupha, Settapat Chinviriyasit

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The treatment function adopts a continuous and differentiable function which can describe the effect of delayed treatment when the number of infected individuals increases and the medical condition is limited. In this paper, the SEIR epidemic model with treatment function is studied to investigate the dynamics of the model due to the effect of treatment. It is assumed that the treatment rate is proportional to the number of infective patients. The stability of the model is analyzed. The model is simulated to illustrate the analytical results and to investigate the effects of treatment on the spread of infection.

Keywords: basic reproduction number, local stability, SEIR epidemic model, treatment function

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Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

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Authors: Karoliina Nisula, Samuli Pekkola

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Business education has been criticized for being too theoretical and distant from business life. Different types of experiential learning environments ranging from manual role-play to computer simulations and enterprise resource planning (ERP) systems have been used to introduce the realistic and practical experience into business learning. Each of these learning environments approaches business learning from a different perspective. The implementations tend to be individual exercises supplementing the traditional courses. We suggest combining them into a business skills laboratory resembling an actual workplace. In this paper, we present a concrete implementation of an ERP-supported business learning environment that is used throughout the first year undergraduate business curriculum. We validate the implementation by evaluating the learning outcomes through the different domains of Bloom’s taxonomy. We use the role-play oriented practice enterprise model as a comparison group. Our findings indicate that using the ERP simulation improves the poor and average students’ lower-level cognitive learning. On the affective domain, the ERP-simulation appears to enhance motivation to learn as well as perceived acquisition of practical hands-on skills.

Keywords: business simulations, experiential learning, ERP systems, learning environments

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Authors: Celine Davis

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The novel coronavirus 2019 (COVID-19) is an infectious disease caused by the virus SARS-CoV-2, which has detrimental respiratory, cardiovascular, and neurological effects impacting over one million lives in the United States. New researches has emerged indicating long-term neurologic consequences in those who survive COVID-19 infections, including more than seven million Americans and another 27 million people worldwide. These consequences include attentional deficits, memory impairments, executive function deficits and aphasia-like symptoms which fall within the purview of speech-language pathology. The National Health Interview Survey (NHIS) is a comprehensive annual survey conducted by the National Center for Health Statistics (NCHS), a branch of the Centers for Disease Control and Prevention (CDC) in the United States. The NHIS is one of the most significant sources of health-related data in the country and has been conducted since 1957. The longitudinal nature of the study allows for analysis of trends in various variables over the years, which can be essential for understanding societal changes and making treatment recommendations. This current study will utilize NHIS data from 2020-2022 which contained interview questions specifically related to COVID-19. Adult cases of individuals between the ages of 18-50 diagnosed with COVID-19 in the United States during 2020-2022 will be identified using the National Health Interview Survey (NHIS). Multiple regression analysis of self-reported data confirming COVID-19 infection status and challenges with concentration, communication, and memory will be performed. Latent class analysis will be utilized to identify subgroups in the population to indicate whether certain demographic groups have higher susceptibility to cognitive-linguistic deficits associated with COVID-19. Completion of this study will reveal whether there is an association between confirmed COVID-19 diagnosis and heightened incidence of cognitive deficits and subsequent implications, if any, on activities of daily living. This study is distinct in its aim to utilize national survey data to explore the relationship between confirmed COVID-19 diagnosis and the prevalence of cognitive-communication deficits with a secondary focus on resulting activity limitations. To the best of the author’s knowledge, this will be the first large-scale epidemiological study investigating the associations between cognitive-linguistic deficits, COVID-19 and implications on activities of daily living in the United States population. These findings will highlight the need for targeted interventions and support services to address the cognitive-communication needs of individuals recovering from COVID-19, thereby enhancing their overall well-being and functional outcomes.

Keywords: cognition, COVID-19, language, limitations, memory, NHIS

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Authors: Rumeysa Gunduz, Dirk Koester, Thomas Schack

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Previous behavioral studies have shown that working memory (WM) and manual actions share limited capacity cognitive resources, which in turn results in execution costs of manual actions in WM. However, to the best of our knowledge, there is no study investigating the neurophysiology of execution costs. The current study aims to fill this research gap investigating the neurophysiology of execution costs of grasping in WM phases (encoding, maintenance, retrieval) considering verbal and visuospatial domains of WM. A WM-grasping dual task paradigm was implemented to examine execution costs. Baseline single task required performing verbal or visuospatial version of a WM task. Dual task required performing the WM task embedded in a high precision grasp to place task. 30 participants were tested in a 2 (single vs. dual task) x 2 (visuo-spatial vs. verbal WM) within subject design. Event related potentials (ERPs) were extracted for each WM phase separately in the single and dual tasks. Memory performance for visuospatial WM, but not for verbal WM, was significantly lower in the dual task compared to the single task. Encoding related ERPs in the single task revealed different ERPs of verbal WM and visuospatial WM at bilateral anterior sites and right posterior site. In the dual task, bilateral anterior difference disappeared due to bilaterally increased anterior negativities for visuospatial WM. Maintenance related ERPs in the dual task revealed different ERPs of verbal WM and visuospatial WM at bilateral posterior sites. There was also anterior negativity for visuospatial WM. Retrieval related ERPs in the single task revealed different ERPs of verbal WM and visuospatial WM at bilateral posterior sites. In the dual task, there was no difference between verbal WM and visuospatial WM. Behavioral and ERP findings suggest that execution of grasping shares cognitive resources only with visuospatial WM, which in turn results in domain specific execution costs. Moreover, ERP findings suggest unique patterns of costs in each WM phase, which supports the idea that each WM phase reflects a separate cognitive process. This study not only contributes to the understanding of cognitive principles of manual action control, but also contributes to the understanding of WM as an entity consisting of separate modalities and cognitive processes.

Keywords: dual task, grasping execution, neurophysiology, working memory domains, working memory phases

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Authors: Rakesh Kumar Mishra, Tarun Kumar Dan

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Lead-Lag based Internal Model Control method is proposed based on Internal Model Control (IMC) strategy. In this paper, we have designed the Lead-Lag based Internal Model Control for binary distillation column for SISO process (considering only bottom product). The transfer function has been taken from Wood and Berry model. We have find the composition control and disturbance rejection using Lead-Lag based IMC and comparing with the response of simple Internal Model Controller.

Keywords: SISO, lead-lag, internal model control, wood and berry, distillation column

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Authors: H. Namazi, H. T. N. Kuan

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It is known that in humans, the adaptation to a given odor occurs within a quite short span of time (typically one minute) after the odor is presented to the brain. Different models of human olfaction have been developed by scientists but none of these models consider the diffusion phenomenon in olfaction. A novel microscopic model of the human olfaction is presented in this paper. We develop this model by incorporating the transient diffusivity. In fact, the mathematical model is written based on diffusion of the odorant within the mucus layer. By the use of the model developed in this paper, it becomes possible to provide quantification of the objective strength of odor.

Keywords: diffusion, microscopic model, mucus layer, olfaction

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Authors: Yanshuang Zhang, Byungho Jeong

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There exists some time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in calculating efficiency of decision making units (DMU). Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. This problem can be resolved a super-efficiency model. However, a super efficiency model sometimes causes infeasibility problem. This paper suggests an output oriented super-efficiency model for efficiency evaluation under the consideration of time lag effect. A case example using a long term research project is given to compare the suggested model with the MpO model

Keywords: DEA, Super-efficiency, Time Lag, research activities

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Authors: Leema Jacob

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The concept of psychological well-being is complex and has familiar use not only in psychology but also in the area of lifespan development. Eudaimonic well-being is finding a purpose and meaning in life, and this depends on both the individual and society, especially during adolescence; the social-cognitive environment can be decisive. The social environment of adolescents, including family, school, and friends, is recognized as an essential context for successful human life. The development of mature social relationships is also undoubtedly important. Theory of Mind is an emerging domain in cognitive neuroscience that involves the ability to attribute mental states to oneself and others. ToM skills training constitutes a new aspect of the adolescent’s social development, including four domains: cognitive ToM, affective ToM, and an inter-intra-personal understanding of social norms. Still, little effort has been made to promote this training as a modality to foster their psychological well-being. This study aims to use the eudaimonic approach to evaluate psychological well-being with a quasi-experimental research design (pre-post-test). The major objective of the study was to identify the effect of ToM skills training on the eudaimonic well-being of adolescents with low social cognition. The data was analyzed to find their effect size from a sample of 74 adolescents from India between 17 and 19 years old. The result revealed that ToM skills training has a positive outcome on the well-being of adolescents post-training. The results are discussed based on the effect of ToM skills training on psychological well-being during adolescence, as well as on the importance of focusing on mental health as a developmental asset that can potentially influence mental well-being in the future.

Keywords: ToM training, adolescents, eudaimonic well-being, social cognition

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Authors: Zainab Magaji Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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The web services applications for digital reference service (WSDRS) of LIS model is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ needs in the reference section of libraries. The formal WSDRS model consists of the Z specifications of all the informal specifications of the model. This paper discusses the formal validation of the Z specifications of WSDRS model. The authors formally verify and thus validate the properties of the model using Z/EVES theorem prover.

Keywords: validation, verification, formal, theorem prover

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Authors: Seung Ah Lee, Sunghyun Cho, Kyong Mee Chung

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Rapid population aging became a worldwide demographic phenomenon due to rising life expectancy and declining fertility rates. Considering the current increasing rate of population aging, it is assumed that Korean society enters into a ‘super-aged’ society in 10 years, in which people aged 65 years or older account for more than 20% of entire population. In line with this trend, ICT services aimed to help elderly people to improve the quality of life have been suggested. However, existing ICT services mainly focus on supporting health or nursing care and are somewhat limited to meet a variety of specialized needs and challenges of this population. It is pointed out that the majority of services have been driven by technology-push policies. Given that the usage of ICT services greatly vary on individuals’ socio-economic status (SES), physical and psychosocial needs, this study systematically categorized elderly population into sub-groups and identified their needs and characteristics related to ICT usage in detail. First, three assessment criteria (demographic variables including SES, cognitive functioning level, and emotional functioning level) were identified based on previous literature, experts’ opinions, and focus group interview. Second, survey questions for needs assessment were developed based on the criteria and administered to 600 respondents from a national probability sample. The questionnaire consisted of 67 items concerning demographic information, experience on ICT services and information technology (IT) devices, quality of life and cognitive functioning, etc. As the result of survey, age (60s, 70s, 80s), education level (college graduates or more, middle and high school, less than primary school) and cognitive functioning level (above the cut-off, below the cut-off) were considered the most relevant factors for categorization and 18 sub-groups were identified. Finally, 18 sub-groups were clustered into 3 groups according to following similarities; computer usage rate, difficulties in using ICT, and familiarity with current or previous job. Group 1 (‘active users’) included those who with high cognitive function and educational level in their 60s and 70s. They showed favorable and familiar attitudes toward ICT services and used the services for ‘joyful life’, ‘intelligent living’ and ‘relationship management’. Group 2 (‘potential users’), ranged from age of 60s to 80s with high level of cognitive function and mostly middle to high school graduates, reported some difficulties in using ICT and their expectations were lower than in group 1 despite they were similar to group 1 in areas of needs. Group 3 (‘limited users’) consisted of people with the lowest education level or cognitive function, and 90% of group reported difficulties in using ICT. However, group 3 did not differ from group 2 regarding the level of expectation for ICT services and their main purpose of using ICT was ‘safe living’. This study developed a systematic needs assessment tool and identified three sub-groups of elderly ICT users based on multi-criteria. It is implied that current cognitive function plays an important role in using ICT and determining needs among the elderly population. Implications and limitations were further discussed.

Keywords: elderly population, ICT, needs assessment, population aging

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Ketwadee Madden

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Product or service image is among the vital factors that predict individuals’ choice of buying a product or services, goes to a place or attached to a person. Similarly, in the context of tourism, the destination image is a very important factor to which tourist considers before making their tour destination decisions. In light of this, the objective of this study is to conceptually investigate among French tourists, the determinants of Thailand’s tourism destination image. For this objective to be achieved, prior studies were reviewed, leading to the development of conceptual framework highlighting the determinants of destination image. In addition, this study develops some hypotheses that are to be empirically investigated. Aside these, based on the conceptual findings, suggestions on how to motivate European tourists to chose Thailand as their preferred tourism destination were made.

Keywords: cognitive destination image, affective destination image, motivations, risk perception, word of mouth

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Authors: Jianlun Zhang, Christine Lim

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Local food is one of the most attractive elements to tourists. The role of local cuisine in destination branding is very important because it is the distinctive identity that helps tourists remember the destination. The objectives of this study are: (1) Test the direct relation between the cognitive image of destination food and tourists’ intention to eat local food. (2) Examine the mediating effect of tourists’ desire to try destination food on the relationship between the cognitive image of local food and tourists’ intention to eat destination food. (3) Study the moderating effect of tourists’ perceived difficulties in finding local food on the relationship between tourists’ desire to try destination food and tourists’ intention to eat local food. To achieve the goals of this study, Macanese cuisine is selected as the destination food. Macau is located in Southeastern China and is a former colonial city of Portugal. The taste and texture of Macanese cuisine are unique because it is a fusion of cuisine from many countries and regions of mainland China. As people travel to seek authentically exotic experience, it is important to investigate if the food image of Macau leaves a good impression on tourists and motivate them to try local cuisine. A total of 449 Chinese tourists were involved in this study. To analyze the data collected, partial least square-structural equation modelling (PLS-SEM) technique is employed. Results suggest that the cognitive image of Macanese cuisine has a direct effect on tourists’ intention to eat Macanese cuisine. Tourists’ desire to try Macanese cuisine mediates the cognitive image-intention relationship. Tourists’ perceived difficulty of finding Macanese cuisine moderates the desire-intention relationship. The lower tourists’ perceived difficulty in finding Macanese cuisine is, the stronger the desire-intention relationship it will be. There are several practical implications of this study. First, the government tourism website can develop an authentic storyline about the evolvement of local cuisine, which provides an opportunity for tourists to taste the history of the destination and create a novel experience for them. Second, the government should consider the development of food events, restaurants, and hawker businesses. Third, to lower tourists’ perceived difficulty in finding local cuisine, there should be locations of restaurants and hawker stalls with clear instructions for finding them on the websites of the government tourism office, popular tourism sites, and public transportation stations in the destination. Fourth, in the post-COVID-19 era, travel risk will be a major concern for tourists. Therefore, when promoting local food, the government tourism website should post images that show food safety and hygiene.

Keywords: cognitive image of destination food, desire to try destination food, intention to eat food in the destination, perceived difficulties of finding local cuisine, PLS-SEM

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Authors: Tejush Badal, Sanaa Alwidian

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Class diagrams are useful tools within the Unified Modelling Language (UML) to model and visualize the relationships between, and properties of objects within a system. As a system evolves over time and space (e.g., products), a series of models with several commonalities and variabilities create what is known as a model family. In circumstances where there are several versions of a model, examining each model individually, becomes expensive in terms of computation resources. To avoid performing redundant operations, this paper proposes an approach for representing a family of class diagrams into Union Models to represent model families using a single generic model. The paper aims to analyze and reason about a family of class diagrams using union models as opposed to individual analysis of each member model in the family. The union algorithm provides a holistic view of the model family, where the latter cannot be otherwise obtained from an individual analysis approach, this in turn, enhances the analysis performed in terms of speeding up the time needed to analyze a family of models together as opposed to analyzing individual models, one model at a time.

Keywords: analysis, class diagram, model family, unified modeling language, union model

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

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Authors: Man Guo

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This paper delves into the intricate interplay between spatial morphology and spatial cognition in Lidukou Village, utilizing a combined approach of spatial syntax and field data. Through a comparative analysis of the gathered data, it emerges that the spatial integration level of Lidukou Village exhibits a direct positive correlation with the spatial cognitive preferences of its inhabitants. Specifically, the areas within the village that exhibit a higher degree of spatial cognition are predominantly distributed along the axis primarily defined by Shuxiang Road. However, the accessibility to historical relics remains limited, lacking a coherent systemic relationship. To address the morphological challenges faced by Lidukou Village, this study proposes optimization strategies that encompass diverse perspectives, including the refinement of spatial mechanisms and the shaping of strategic spatial nodes.

Keywords: traditional villages, spatial syntax, spatial integration degree, morphological problem

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Authors: D. Thawinkarn, S. Wongbutlee

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The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

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Authors: Samson Olasunkanmi Oluga, Teh Chee Send, Gerard Sagaya Raj Rajo

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It is ironical that the national anthems of many nations that are in the forefront of the global condemnation of violence of all forms have portions or expressions that propagate various forms of linguistic violence which advocate attacking opponents, going to war, shedding blood and sacrificing lives. These diametrically contradict contemporary yearnings for global tranquility and the ideals of the United Nations established for the maintenance of international peace and harmony aimed at making the world a safe haven for all and sundry. The linguistic violence of many national anthems is manipulatively constructed /presented via the instrumentality of the figurative or rhetorical language. This helps to linguistically embellish the violent ideas communicated and makes them sound somehow better or logical to the target audience with the intention of cognitively manipulating them to accept or rationalize such violent ideas. This paper, therefore, presents the outcome of a linguistic exploration/examination of national anthems which reveals elements or cases manipulative figurative linguistic violence in the anthems of twenty-one (21) nations. The paper details a Socio-Cognitive Critical Discourse Analysis of the manipulative figures of comparison, contrast, indirectness, association and sound used to convey the linguistic violence of the identified national anthems. Finally, the paper advocates the need for linguistic overhaul of affected anthems so that the language of anthems which epitomize nations can be pacific and in tandem with contemporary global trends.

Keywords: national anthems, linguistic violence, figurative language, cognitive, manipulation, CDA

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Authors: A. Lakrim, D. Tahri

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This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS diode, electro-thermal, SPICE model, behavioral macro-model

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Authors: Funda Kul, İsmail Gür

Abstract:

Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

Abstract:

The dynamic conditional correlation model of Engle (2002) is one of the most popular multivariate volatility models. However, this model is based solely on closing prices. It has been documented in the literature that the high and low price of the day can be used in an efficient volatility estimation. We, therefore, suggest a model which incorporates high and low prices into the dynamic conditional correlation framework. Empirical evaluation of this model is conducted on three datasets: currencies, stocks, and commodity exchange-traded funds. The utilisation of realized variances and covariances as proxies for true variances and covariances allows us to reach a strong conclusion that our model outperforms not only the standard dynamic conditional correlation model but also a competing range-based dynamic conditional correlation model.

Keywords: volatility, DCC model, high and low prices, range-based models, covariance forecasting

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Authors: Ekaterina Lukianchenko

Abstract:

This article sums up a six-year experience of teaching English as a foreign language to over 900 university students at MGIMO (Moscow University of International Relations, Russia), all of them native speakers of Russian aged 16 to 23. By combining modern communicative approach to teaching with cognitive linguistics theories, one can deal more effectively with deeply rooted mistakes which particular students have of which conventional methods have failed to eliminate. If language items are understood as concepts and frames, and classroom activities as meaningful parts of language competence development, this might help to solve such problems as incorrect use of words, unsuitable register, and confused tenses - as well as logical or structural mistakes, and even certain psychological issues concerning essay writing. Along with classic teaching methods, such classroom practice includes plenty of interaction between students - playing special classroom games aimed at eliminating particular mistakes, working in pairs and groups, integrating all skills in one class. The main conclusions that the author of the experiment makes consist in an assumption that academic essay writing classes demand a balanced plan. This should not only include writing as such, but additionally feature elements of listening, reading, speaking activities specifically chosen according to the skills and language students will need to write the particular type of essay.

Keywords: academic essay writing, creative teaching, cognitive linguistics, competency-based approach, communicative language teaching, frame, concept

Procedia PDF Downloads 297