Search results for: implicit data

Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Duong Thuy Nguyen, Giulia Bencini

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The present study examined structural and prosodic factors on the computation of antecedent-reflexive relationships and sentence comprehension in native English (L1) and Vietnamese-English bilinguals (L2). Participants read sentences presented on the computer screen in one of three presentation formats aimed at manipulating prosodic parsing: word-by-word (RSVP), phrase-segment (self-paced), or whole-sentence (self-paced), then completed a grammaticality rating and a comprehension task (following Pratt & Fernandez, 2016). The design crossed three factors: syntactic structure (simple; complex), grammaticality (target-match; target-mismatch) and presentation format. An example item is provided in (1): (1) The actress that (Mary/John) interviewed at the awards ceremony (about two years ago/organized outside the theater) described (herself/himself) as an extreme workaholic). Results showed that overall, both L1 and L2 speakers made use of a good-enough processing strategy at the expense of more detailed syntactic analyses. L1 and L2 speakers’ comprehension and grammaticality judgements were negatively affected by the most prosodically disrupting condition (word-by-word). However, the two groups demonstrated differences in their performance in the other two reading conditions. For L1 speakers, the whole-sentence and the phrase-segment formats were both facilitative in the grammaticality rating and comprehension tasks; for L2, compared with the whole-sentence condition, the phrase-segment paradigm did not significantly improve accuracy or comprehension. These findings are consistent with the findings of Pratt & Fernandez (2016), who found a similar pattern of results in the processing of subject-verb agreement relations using the same experimental paradigm and prosodic manipulation with English L1 and L2 English-Spanish speakers. The results provide further support for a Good-Enough cue model of sentence processing that integrates cue-based retrieval and implicit prosodic parsing (Pratt & Fernandez, 2016) and highlights similarities and differences between L1 and L2 sentence processing and comprehension.

Keywords: anaphora resolution, bilingualism, implicit prosody, sentence processing

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Authors: Prema Basargekar

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Facilitating the subject ‘Entrepreneurship Education’ in higher education, such as management studies, can be exhilarating as well as challenging. It is a multi-disciplinary and ever-evolving subject. Capturing entrepreneurship as a phenomenon in a holistic manner is a daunting task as it requires covering various dimensions such as new ideas generation, entrepreneurial traits, business opportunities scanning, the role of policymakers, value creation, etc., to name a few. Implicit entrepreneurship theory and effectuation are two different theories that focus on engaging the participants to create content by using their own experiences, perceptions, and belief systems. It helps in understanding the phenomenon holistically. The assumption here is that all of us are part of the entrepreneurial ecosystem, and effective learning can come through active engagement and peer learning by all the participants together. The present study is an attempt to use these theories in the class assignment given to the students at the beginning of the course to build the course content and understand entrepreneurship as a phenomenon in a better way through peer learning. The assignment was given to three batches of MBA post-graduate students doing the program in one of the private business schools in India. The subject of ‘Entrepreneurship Management’ is facilitated in the third trimester of the first year. At the beginning of the course, the students were given the assignment to submit a brief write-up/ collage/picture/poem or in any other format about “What entrepreneurship means to you?” They were asked to give their candid opinions about entrepreneurship as a phenomenon as they perceive it. Nearly 156 students doing post-graduate MBA submitted the assignment. These assignments were further used to find answers to two research questions. – 1) Are students able to use divergent and innovative forms to express their opinions, such as poetry, illustrations, videos, etc.? 2) What are various dimensions of entrepreneurship which are emerging to understand the phenomenon in a better way? The study uses the Brawn and Clark framework of reflective thematic analysis for qualitative analysis. The study finds that students responded to this assignment enthusiastically and expressed their thoughts in multiple ways, such as poetry, illustration, personal narrative, videos, etc. The content analysis revealed that there could be seven dimensions to looking at entrepreneurship as a phenomenon. They are 1) entrepreneurial traits, 2) entrepreneurship as a journey, 3) value creation by entrepreneurs in terms of economic and social value, 4) entrepreneurial role models, 5) new business ideas and innovations, 6) personal entrepreneurial experiences and aspirations, and 7) entrepreneurial ecosystem. The study concludes that an implicit approach to facilitate entrepreneurship education helps in understanding it as a live phenomenon. It also encourages students to apply divergent and convergent thinking. It also helps in triggering new business ideas or stimulating the entrepreneurial aspirations of the students. The significance of the study lies in the application of implicit theories in the classroom to make higher education more engaging and effective.

Keywords: co-creation of content, divergent thinking, entrepreneurship education, implicit theory

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Authors: Erindi Allaj

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This paper studies arbitrage pricing theory in financial markets with transaction costs. We extend the existing theory to include the more realistic possibility that the price at which the investors trade is dependent on the traded volume. The investors in the market always buy at the ask and sell at the bid price. Transaction costs are composed of two terms, one is able to capture the implicit transaction costs and the other the price impact. Moreover, a new definition of a self-financing portfolio is obtained. The self-financing condition suggests that continuous trading is possible, but is restricted to predictable trading strategies which have left and right limit and finite quadratic variation. That is, predictable trading strategies of infinite variation and of finite quadratic variation are allowed in our setting. Within this framework, the existence of an equivalent probability measure is equivalent to the absence of arbitrage opportunities, so that the first fundamental theorem of asset pricing (FFTAP) holds. It is also proved that, when this probability measure is unique, any contingent claim in the market is hedgeable in an L2-sense. The price of any contingent claim is equal to the risk-neutral price. To better understand how to apply the theory proposed we provide an example with linear transaction costs.

Keywords: arbitrage pricing theory,
transaction costs, fundamental theorems of arbitrage, financial markets

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Authors: Jessica Neri, Elena Faccio

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In Europe, except for Denmark and Malta, the legal gender change and the stages of the possible process of gender transition are bound to the diagnosis of a gender identity disorder. The requirement of the evaluation of a mental disorder might have many implications on trans people’s self-representations, interpersonal relations in different social contexts and the therapeutic relations with clinicians during the transition. Psychopathological language may contribute to define the individual’s reality from normative presuppositions with value implications related to the dominant cultural principles. In an effort to mark the boundaries between sanity and pathology, it concurs to the definition of the management procedures of the constructed diversities and deviances, legitimizing the operational practices of particular professional figures. The aim of this research concerns the analysis of the diagnostic category of gender dysphoria contained in the last edition of the Diagnostic and Statistical Manual of Mental Disorders. In particular, this study focuses on the relationship between the implicit and explicit assumptions related to the expressions of gender non-conformity, that sustain the language and the criteria characterizing the Manual, and the possible implications on people’s narratives of transition. In order to achieve this objective two main research methods were used: historical reconstruction of the diagnostic category in the different versions of the Manual and content analysis of that category in the present version. From the historical analysis, in the medical and psychiatric field gender non-conformity has been predominantly explicated by naturalistic perspectives, naming it ‘transsexualism’ and collocating it in the category of gender identity disorder. Currently, pathological judged experiences are represented by gender dysphoria, described in the DSM-5 as the distress that may accompany the incongruence between one's experienced or expressed gender and one's assigned gender, specifying that there must be ‘evidence’ of this. Implicit theories about gender binary, parallelism between gender identity, sex and sexuality and the understanding of the mental health and the subject’s agency as subordinated to the expert knowledge, can be found in the process of designation of the category. A lack of awareness of the historical, social and political aspects connected to the cultural and normative dimensions at the basis of these implicit theories, can be noticed and data given by culture and data given by supposed -biological or psychological- nature, are often confused. This reductionist interpretation of gender and its presumed diversities legitimize the clinician to assume the role of searching and orienting, in a correctional perspective, the biographical elements that correspond to him specific expectations, with no space for other possibilities and identity configurations for people in transition. This research may contribute to the current critical debate about the epistemological foundation of the psychodiagnosis, emphasizing the pragmatic effects on the individuals and on the psychological practice in its wider social context. This work also permits to underline the risks due to the lack of awareness of the processes of social construction of the diagnostic system and its essential role of defence of the values that hold up the symbolic universe of reference.

Keywords: diagnosis, gender dysphoria, narratives, social constructionism

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Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh

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The slamming impact problem has a very important engineering background. For seaplane landing, recycling for the satellite re-entry capsule, and the impact load of the bow in the adverse sea conditions, the slamming problem always plays the important role. Due to its strong nonlinear effect, however, it seems to be not easy to obtain the accurate simulation results. Combined with the strong interaction between the fluid field and the elastic structure, the difficulty for the simulation leads to a new level for challenging. This paper presents a fully Lagrangian coupled solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with two different materials such as aluminum and steel on water entry. The present simulation results are compared with analytical solution derived using the hydrodynamic Wagner model and linear theory by Wan.

Keywords: fluid-structure interaction, moving particle semi-implicit (MPS) method, elastic structure, incompressible flow, wedge slamming impact

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Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: surface flattening, strain energy, minimum energy, approximate implicit method, fashion design

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Authors: Iddy Iddy, Qin Jiang, Changkuan Zhang

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This paper addresses the hydraulic performance of curtain wall breakwaters as a coastal structure protection based on the particles method modelling. The hydraulic functions of curtain wall as wave barriers by reflecting large parts of incident waves through the vertical wall, a part transmitted and a particular part was dissipating the wave energies through the eddy flows formed beneath the lower end of the plate. As a Lagrangian particle, the Moving Particle Semi-implicit (MPS) method which has a robust capability for numerical representation has proven useful for design of structures application that concern free-surface hydrodynamic flow, such as wave breaking and overtopping. In this study, a vertical two-dimensional numerical model for the simulation of violent flow associated with the interaction between the curtain-wall breakwaters and progressive water waves is developed by MPS method in which a higher precision pressure gradient model and free surface particle recognition model were proposed. The wave transmission, reflection, and energy dissipation of the vertical wall were experimentally and theoretically examined. With the numerical wave flume by particle method, very detailed velocity and pressure fields around the curtain-walls under the action of waves can be computed in each calculation steps, and the effect of different wave and structural parameters on the hydrodynamic characteristics was investigated. Also, the simulated results of temporal profiles and distributions of velocity and pressure in the vicinity of curtain-wall breakwaters are compared with the experimental data. Herein, the numerical investigation of hydraulic performance of curtain wall breakwaters indicated that the incident wave is largely reflected from the structure, while the large eddies or turbulent flows occur beneath the curtain-wall resulting in big energy losses. The improved MPS method shows a good agreement between numerical results and analytical/experimental data which are compared to related researches. It is thus verified that the improved pressure gradient model and free surface particle recognition methods are useful for enhancement of stability and accuracy of MPS model for water waves and marine structures. Therefore, it is possible for particle method (MPS method) to achieve an appropriate level of correctness to be applied in engineering fields through further study.

Keywords: curtain wall breakwaters, free surface flow, hydraulic performance, improved MPS method

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Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.

Keywords: base-isolated structures, earthquake engineering, mixed time integration, nonlinear exponential model

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Authors: Andres Pinilla Palacios, Ricardo Tamayo

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Emotional contagion is characterized as an automatic tendency to synchronize behaviors that facilitate emotional convergence among humans. It might thus play a pivotal role to understand the dynamics of key social interactions. However, a few research has investigated its potential mechanisms. We suggest two complementary but independent processes that may underlie emotional contagion. The efficient contagion hypothesis, based on fast and implicit bottom-up processes, modulated by familiarity and spread of activation in the emotional associative networks of memory. Secondly, the emotional contrast hypothesis, based on slow and explicit top-down processes guided by deliberated appraisal and hypothesis-testing. In order to assess these two hypotheses, an experiment with 39 participants was conducted. In the first phase, participants were induced (between-groups) to an emotional state (positive, neutral or negative) using a standardized video taken from the FilmStim database. In the second phase, participants classified and rated (within-subject) the emotional state of 15 faces (5 for each emotional state) taken from the POFA database. In the third phase, all participants were returned to a baseline emotional state using the same neutral video used in the first phase. In a fourth phase, participants classified and rated a new set of 15 faces. The accuracy in the identification and rating of emotions was partially explained by the efficient contagion hypothesis, but the speed with which these judgments were made was partially explained by the emotional contrast hypothesis. However, results are ambiguous, so a follow-up experiment is proposed in which emotional expressions and activation of the sympathetic system will be measured using EMG and EDA respectively.

Keywords: electromyography, emotional contagion, emotional valence, identification of emotions, imitation

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Authors: Rihab Idoudi, Karim Saheb Ettabaa, Basel Solaiman, Kamel Hamrouni

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Medical association rules induction is used to discover useful correlations between pertinent concepts from large medical databases. Nevertheless, ARs algorithms produce huge amount of delivered rules and do not guarantee the usefulness and interestingness of the generated knowledge. To overcome this drawback, we propose an ontology based interestingness measure for ARs ranking. According to domain expert, the goal of the use of ARs is to discover implicit relationships between items of different categories such as ‘clinical features and disorders’, ‘clinical features and radiological observations’, etc. That’s to say, the itemsets which are composed of ‘similar’ items are uninteresting. Therefore, the dissimilarity between the rule’s items can be used to judge the interestingness of association rules; the more different are the items, the more interesting the rule is. In this paper, we design a distinct approach for ranking semantically interesting association rules involving the use of an ontology knowledge mining approach. The basic idea is to organize the ontology’s concepts into a hierarchical structure of conceptual clusters of targeted subjects, where each cluster encapsulates ‘similar’ concepts suggesting a specific category of the domain knowledge. The interestingness of association rules is, then, defined as the dissimilarity between corresponding clusters. That is to say, the further are the clusters of the items in the AR, the more interesting the rule is. We apply the method in our domain of interest – mammographic domain- using an existing mammographic ontology called Mammo with the goal of deriving interesting rules from past experiences, to discover implicit relationships between concepts modeling the domain.

Keywords: association rule, conceptual clusters, interestingness measures, ontology knowledge mining, ranking

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Authors: Raoul Ouambo Tobou, Alexis Kuitche, Marcel Edoun

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The FWM (Finite Window Method) is a new numerical meshfree technique for solving problems defined either in terms of PDEs (Partial Differential Equation) or by a set of conservation/equilibrium laws. The principle behind the FWM is that in such problem each element of the concerned domain is interacting with its neighbors and will always try to adapt to keep in equilibrium with respect to those neighbors. This leads to a very simple and robust problem solving scheme, well suited for transfer problems. In this work, we have applied the FWM to an unsteady scalar convection-diffusion equation. Despite its simplicity, it is well known that convection-diffusion problems can be challenging to be solved numerically, especially when convection is highly dominant. This has led researchers to set the scalar convection-diffusion equation as a benchmark one used to analyze and derive the required conditions or artifacts needed to numerically solve problems where convection and diffusion occur simultaneously. We have shown here that the standard FWM can be used to solve convection-diffusion equations in a robust manner as no adjustments (Upwinding or Artificial Diffusion addition) were required to obtain good results even for high Peclet numbers and coarse space and time steps. A comparison was performed between the FWM scheme and both a first order implicit Finite Volume Scheme (Upwind scheme) and a third order implicit Finite Volume Scheme (QUICK Scheme). The results of the comparison was that for equal space and time grid spacing, the FWM yields a much better precision than the used Finite Volume schemes, all having similar computational cost and conditioning number.

Keywords: Finite Window Method, Convection-Diffusion, Numerical Technique, Convergence

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Authors: Khalid Alasim

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The reading comprehension levels of students who are deaf or hard of hearing (DHH) are low compared to those of their hearing peers. One possible reason for this low reading levels is related to the students’ prior knowledge. This study investigated the potential factors that might affected DHH students’ prior knowledge, including their degree of hearing loss, the presence or absence of family members with a hearing loss, and educational stage (elementary–middle school). The study also examined the contribution of prior knowledge in predicting DHH students’ reading comprehension levels, and investigated the differences in the students’ scores based on the type of questions, including text-explicit (TE), text-implicit (TI), and script-implicit (SI) questions. Thirty-one elementary and middle-school students completed a demographic form and assessment, and descriptive statistics and multiple and simple linear regressions were used to answer the research questions. The findings indicated that the independent variables—degree of hearing loss, presence or absence of family members with hearing loss, and educational stage—explained little of the variance in DHH students’ prior knowledge. Further, the results showed that the DHH students’ prior knowledge affected their reading comprehension. Finally, the result demonstrated that the participants were able to answer more of the TI questions correctly than the TE and SI questions. The study concluded that prior knowledge is important in these students’ reading comprehension, and it is also important for teachers and parents of DHH children to use effective ways to increase their students’ and children’s prior knowledge.

Keywords: reading comprehension, prior knowledge, metacognition, elementary, self-contained classrooms

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Authors: Daria Lozovskaia

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This paper is focused on the news coverage of public opinion polls about Russian full-scale invasion of Ukraine in Russian state-controlled media. After the announcement of the start of the so-called “Special Military Operation” on February 24, 2022, the number of publications of the results of public opinion polls increased many times over, and the poll numbers began to be discussed on social media and in the Kremlin’s official informational agenda. Headlines like "72 Percent of Russian Citizens Support the Operation " or "Russians Believe in Victory in the Special Military Operation" have become prominent parts of Russian state propaganda news stories and newspapers. At the same time, public opinion in Russia, as a concept and model, differs from the generally accepted democratic concept and has its own specifics. As a result, public opinion polls and their results, especially after February 24, have a number of features in the form of the dominance of the discourse of political elites in the media, which leads to a decrease in public awareness, the prevalence of the effect of joining the majority and a high number of non-responses due to fear of reprisals. The aim of this study was to determine the role of public opinion polls in the system of Russian war propaganda in Ukraine. For this purpose, were selected publications of the Russian media, the agenda of which corresponds to the official information policy of the Russian authorities. First, using frame analysis for the categories "Explicit trust", "Implicit trust", "Implicit distrust" and "Explicit distrust", provided by Irina Dusakova, the broadcast level of trust in the data of public opinion polls was determined. The results of this phase of the study showed that the Russian media broadcast an absolute level of confidence in public opinion polls regarding support for the war in Ukraine. The second stage of the study was the content analysis of publications. The categories of this analysis were derived from Anna Morelli's 10 Principles of Military Propaganda and Haavard Koppang's Definition of Propaganda to determine the purposes of the use of public opinion polls by Russian propaganda. The results of the study not only confirmed the widespread hypothesis that public opinion polls in Russia are used as a tool of state propaganda, but also showed that their purpose is to demonstrate the consolidation of society in support of the war and President Vladimir Putin.

Keywords: propaganda, public opinion, public opinion polls, Russian studies

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Authors: Cristina Schreiner, Romeo Ciobanu, Marius Pislaru

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This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. The model proposed provides new perspective for environmental assessment, and it can be used as a practical instrument for decision-making.

Keywords: ecosystem model, environmental security, fuzzy logic, sustainability of habitable regions

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Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: cell-centered finite volume method, coupled solver, exponential differencing scheme (EDS), physical influence scheme (PIS), pressure weighted interpolation method (PWIM), skew upwind differencing scheme (SUDS)

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Authors: Lindy Van Vliet, Saloni Phadke, Anthea Nelson, Ann Gallant

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Holistic and patient-centred palliative care and support require an integrated system of care that includes health and social service providers working together to ensure that patients and families have access to the care they need. The objective of this study is to further explore and understand the benefits and challenges of mobilizing multidisciplinary care teams for health care professionals and social service providers. Drawing on an interpretivist, exploratory, qualitative design, our multidisciplinary research team (medicine, nursing and social work) conducted interviews with 15 health care and social service providers in the Ottawa region. Interview data was audio-recorded, transcribed, and analyzed using a reflexive thematic analysis approach. The data deepens our understandings of the facilitators and barriers posed by multidisciplinary care teams. Three main findings emerged: First, the data highlighted the benefits of multidisciplinary care teams for both patient outcomes and quality of life and provider mental health; second, the data showed that the lack of a system-wide integrated communication system reduces the quality of patient care and increases provider stress while working in multidisciplinary care teams; finally, the data demonstrated the existence of implicit hierarchies between disciplines, this coupled with different disciplinary perspectives of palliative care provision can lead to friction and challenges within care teams. These findings will have important implications for the future of palliative care as they will help to facilitate and build stronger person-centred/relationship-centred palliative care practices by naming the challenges faced by multidisciplinary palliative care teams and providing examples of best practices.

Keywords: public health palliative care, palliative care nursing, care networks, integrated health care, palliative care approach, public health, multidisciplinary work, care teams

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Ghazal Faraj, Andras Micsik

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The CIDOC Conceptual Reference Model (CRM) is an extensible ontology that provides integrated access to heterogeneous and digital datasets. The CIDOC-CRM offers a “semantic glue” intended to promote accessibility to several diverse and dispersed sources of cultural heritage data. That is achieved by providing a formal structure for the implicit and explicit concepts and their relationships in the cultural heritage field. The COURAGE (“Cultural Opposition – Understanding the CultuRal HeritAGE of Dissent in the Former Socialist Countries”) project aimed to explore methods about socialist-era cultural resistance during 1950-1990 and planned to serve as a basis for further narratives and digital humanities (DH) research. This project highlights the diversity of flourished alternative cultural scenes in Eastern Europe before 1989. Moreover, the dataset of COURAGE is an online RDF-based registry that consists of historical people, organizations, collections, and featured items. For increasing the inter-links between different datasets and retrieving more relevant data from various data silos, a shared federated ontology for reconciled data is needed. As a first step towards these goals, a full understanding of the CIDOC CRM ontology (target ontology), as well as the COURAGE dataset, was required to start the work. Subsequently, the queries toward the ontology were determined, and a table of equivalent properties from COURAGE and CIDOC CRM was created. The structural diagrams that clarify the mapping process and construct queries are on progress to map person, organization, and collection entities to the ontology. Through mapping the COURAGE dataset to CIDOC-CRM ontology, the dataset will have a common ontological foundation with several other datasets. Therefore, the expected results are: 1) retrieving more detailed data about existing entities, 2) retrieving new entities’ data, 3) aligning COURAGE dataset to a standard vocabulary, 4) running distributed SPARQL queries over several CIDOC-CRM datasets and testing the potentials of distributed query answering using SPARQL. The next plan is to map CIDOC-CRM to other upper-level ontologies or large datasets (e.g., DBpedia, Wikidata), and address similar questions on a wide variety of knowledge bases.

Keywords: CIDOC CRM, cultural heritage data, COURAGE dataset, ontology alignment

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Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

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This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: Tahsin A. H. Nishat, Raquib Ahsan

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Sensitivity analysis of design parameters of the optimization procedure can become a significant factor while designing any structural system. The objectives of the study are to analyze the sensitivity of deck slab thickness parameter obtained from both the conventional and optimum design methodology of pre-stressed post-tensioned I-girder and deck system and to compare the relative significance of slab thickness. For analysis on conventional method, the values of 14 design parameters obtained by the conventional iterative method of design of a real-life I-girder bridge project have been considered. On the other side for analysis on optimization method, cost optimization of this system has been done using global optimization methodology 'Evolutionary Operation (EVOP)'. The problem, by which optimum values of 14 design parameters have been obtained, contains 14 explicit constraints and 46 implicit constraints. For both types of design parameters, sensitivity analysis has been conducted on deck slab thickness parameter which can become too sensitive for the obtained optimum solution. Deviations of slab thickness on both the upper and lower side of its optimum value have been considered reflecting its realistic possible ranges of variations during construction. In this procedure, the remaining parameters have been kept unchanged. For small deviations from the optimum value, compliance with the explicit and implicit constraints has been examined. Variations in the cost have also been estimated. It is obtained that without violating any constraint deck slab thickness obtained by the conventional method can be increased up to 25 mm whereas slab thickness obtained by cost optimization can be increased only up to 0.3 mm. The obtained result suggests that slab thickness becomes less sensitive in case of conventional method of design. Therefore, for realistic design purpose sensitivity should be conducted for any of the design procedure of girder and deck system.

Keywords: sensitivity analysis, optimum design, evolutionary operations, PC I-girder, deck system

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Authors: Kanupriya Rawat, Aleksandra Błachnio, Paweł Izdebski

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Achievement motivation, which drives a person to strive for success, is an important construct in sports psychology. This systematic review aims to analyze the methods of measuring achievement motivation used in previous studies published over the past four decades and to find out which method of measuring achievement motivation is the most prevalent and the most effective by thoroughly examining measures of achievement motivation used in each study and by evaluating most highly cited achievement motivation measures in sport. In order to understand this latent construct, thorough measurement is necessary, hence a critical evaluation of measurement tools is required. The literature search was conducted in the following databases: EBSCO, MEDLINE, APA PsychARTICLES, Academic Search Ultimate, Open Dissertations, ERIC, Science direct, Web of Science, as well as Wiley Online Library. A total of 26 articles met the inclusion criteria and were selected. From this review, it was found that the Achievement Goal Questionnaire- Sport (AGQ-Sport) and the Task and Ego Orientation in Sport Questionnaire (TEOSQ) were used in most of the research, however, the average weighted impact factor of the Achievement Goal Questionnaire- Sport (AGQ-Sport) is the second highest and most relevant in terms of research articles related to the sport psychology discipline. Task and Ego Orientation in Sport Questionnaire (TEOSQ) is highly popular in cross-cultural adaptation but has the second last average IF among other scales due to the less impact factor of most of the publishing journals. All measures of achievement motivation have Cronbach’s alpha value of more than .70, which is acceptable. The advantages and limitations of each measurement tool are discussed, and the distinction between using implicit and explicit measures of achievement motivation is explained. Overall, both implicit and explicit measures of achievement motivation have different conceptualizations of achievement motivation and are applicable at either the contextual or situational level. The conceptualization and degree of applicability are perhaps the most crucial factors for researchers choosing a questionnaire, even though they differ in their development, reliability, and use.

Keywords: achievement motivation, task and ego orientation, sports psychology, measures of achievement motivation

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Authors: Nikat Parveen, M. Ananthi

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Big data is one of the emerging technology, which collects the data from various sensors and those data will be used in many fields. Data retrieval is one of the major issue where there is a need to extract the exact data as per the need. In this paper, large amount of data set is processed by using the feature selection. Feature selection helps to choose the data which are actually needed to process and execute the task. The key value is the one which helps to point out exact data available in the storage space. Here the available data is streamed and R-Center is proposed to achieve this task.

Keywords: big data, key value, feature selection, retrieval, performance

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Authors: E. Olmos-Raya, A. Cascales Martínez, N. Minto de Sousa, M. Alcañiz Raya

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The late detection and subjectivity of the assessment of Autism Spectrum Disorder (ASD) imposed a difficulty for the children’s clinical and familiar environment. The results showed in this paper, are part of a research project about the assessment and training of social skills in children with ASD, whose overall goal is the use of virtual environments together with physiological measures in order to find a new model of objective ASD assessment based on implicit brain processes measures. In particular, this work tries to contribute by studying the differences and changes in the Skin Conductance Response (SCR) and Eye Tracking (ET) between a typical development group (TD group) and an ASD group (ASD group) after several combined stimuli using a low cost Immersive Virtual Environment (IVE). Subjects were exposed to a virtual environment that showed natural scenes that stimulated visual, auditory and olfactory perceptual system. By exposing them to the IVE, subjects showed natural behaviors while measuring SCR and ET. This study compared measures of subjects diagnosed with ASD (N = 18) with a control group of subjects with typical development (N=10) when exposed to three different conditions: only visual (V), visual and auditory (VA) and visual, auditory and olfactory (VAO) stimulation. Correlations between SCR and ET measures were also correlated with the Autism Diagnostic Observation Schedule (ADOS) test. SCR measures showed significant differences among the experimental condition between groups. The ASD group presented higher level of SCR while we did not find significant differences between groups regarding DF. We found high significant correlations among all the experimental conditions in SCR measures and the subscale of ADOS test of imagination and symbolic thinking. Regarding the correlation between ET measures and ADOS test, the results showed significant relationship between VA condition and communication scores.

Keywords: autism, electrodermal activity, eye tracking, immersive virtual environment, virtual reality

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Authors: Ananta Kumar Das, Sujit Kumar Chakrabarti

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Architectural tactics such as heartbeat, ping-echo, encapsulate, encrypt data are techniques that are used to achieve quality attributes of a system. Detecting architectural tactics has several benefits: it can aid system comprehension (e.g., legacy systems) and in the estimation of quality attributes such as safety, security, maintainability, etc. Architectural tactics are typically spread over the source code and are implicit. For large codebases, manual detection is often not feasible. Therefore, there is a need for automated methods of detection of architectural tactics. This paper presents a formalization of the heartbeat architectural tactic and a program analytic approach to detect this tactic in source code. The experiment of the proposed method is done on a set of Java applications. The outcome of the experiment strongly suggests that the method compares well with a manual approach in terms of its sensitivity and specificity, and far supersedes a manual exercise in terms of its scalability.

Keywords: software architecture, architectural tactics, detecting architectural tactics, program analysis, AST, alias analysis

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Authors: Delna Shroff

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Merchant shipping is an occupation with a high rate of fatal injuries caused by organizational accidents and maritime disasters. In most accident investigations, the leader’s actions are under scrutiny and point out the necessity to investigate the leader’s decisions in critical conditions. While several leadership studies have been carried out in the past, there is a tendency for most research to focus on holders of formal positions. The unit of analysis in most studies has been the ‘individual.’ A need is, therefore, felt to adopt a practice-based perspective of leadership, understand how leadership emerges to affect maritime safety. This paper explores the phenomenon of distributed leadership among seafarers more holistically. It further examines the role of one form of distributed leadership, that is, planfully aligned leadership in the emergency response of the team. A mixed design will be applied. In the first phase, the data gathered by way of semi-structured interviews will be used to explore the seafarer’s implicit understanding of leadership. The data will be used to develop a conceptual framework of distributed leadership, specific to the maritime context. This framework will be used to develop a simulation. Experimental design will be used to examine the relationship between planfully aligned leadership and emergency response of the team members during navigation. Findings show that planfully aligned leadership significantly and positively predicts the emergency response of team members. Planfully aligned leadership leads to a better emergency response of the team members as compared to authoritarian leadership. In the third qualitative phase, additional data will be gathered through semi-structured interviews to further validate the findings to gain a more complete understanding of distributed leadership and its relation to emergency response. Above are the predictive results; the study expects to be a cornerstone of safety leadership research and has important implications for leadership development and training within the maritime industry.

Keywords: authoritarian leadership, distributed leadership, emergency response , planfully aligned leadership

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Authors: Jose Ramon Calvo-Ferrer

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Video games have been extensively employed in educational contexts to teach contents and skills, upon the premise that they engage students and provide instant feedback, which makes them adequate tools in the field of education and training. Term frequency, along with metacognition and implicit corrective feedback, has often been identified as powerful variables in the learning of vocabulary in a foreign language. This study analyses the learning of L2 mobile operating system terminology by a group of students and uses the data collected by the video game The Conference Interpreter to identify the predictive strength of term frequency (times a term is shown), positive metacognition (times a right answer is provided), and negative metacognition (times a term is shown as wrong) regarding L2 vocabulary learning and perceived learning outcomes. The regression analysis shows that the factor ‘positive metacognition’ is a positive predictor of both dependent variables, whereas the other factors seem to have no statistical effect on any of them.

Keywords: digital game-based learning, feedback, metacognition, frequency, video games

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Authors: M. H. Imam, Imran A. Tasadduq, Abdul-Rahim Ahmad, Fahd M. Aldosari

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Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.

Keywords: expert system, student outcomes, course learning outcomes, question attributes

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