Search results for: explicit

Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

Abstract:

Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Mark Shiu-kee Shum, Dan Shi

Abstract:

The paper aims to introduce the ‘Reading to Learn, Learning to Write’ (R2L) pedagogy and its application in teaching reading and writing to non-Chinese speaking (NCS) students in Hong Kong. Guided by the teaching and learning cycles accentuated in R2L pedagogy, sufficient scaffolding was provided for students with an explicit teaching method in literacy education. To understand the influence of using R2L pedagogy on students’ reading and writing abilities across different genres, quantitative data were collected by pre- and post-test of reading and writing tasks in the two different genres of narration and explanation. The pre-test and post-test were used to assess students’ writing performance based on the three textual components of context, discourse, and graphic features, while the reading abilities were assessed at the literal, inferred and interpretive levels of reading comprehension to measure the effectiveness of R2L pedagogy on their literacy improvement. The findings show the use of R2L pedagogy has been proven more effective in improving NCS students’ writing abilities than developing their reading capacity. It is hoped that the R2L-based pedagogic practices can serve as teaching references and pedagogic rationale for L1 language teachers and raise their metalinguistic awareness in teaching Chinese to non-Chinese speaking students in Hong Kong and beyond.

Keywords: pedagogical inclusiveness, literacy education, ethnic minority, reading and writing

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Authors: N. S. Yen, T. H. Yang, W. H. Huang, Y. F. Fang, H. W. Cho

Abstract:

Ultimatum game is an experimental paradigm to study human decision making. There are two players, a proposer and a responder, to split a fixed amount of money. According to the traditional economic theory on ultimatum game, proposer should propose the selfish offers to responder as much as possible to maximize proposer’s own outcomes. However, most evidences had showed that people chose more fair offers, hence two hypotheses – fairness favoring and strategic concern were proposed. In current study, we induced the motivation in participants to be either selfish or altruistic, and manipulated the task variables, the stake sizes (NT$100, 1000, 10000) and the share sizes (the 40%, 30%, 20%, 10% of the sum as selfish offers, and the 60%, 70%, 80%, 90% of the sum as altruistic offers), to examine the two hypotheses. The results showed that most proposers chose more fair offers with longer reaction times (RTs) no matter in choosing between the fair and selfish offers, or between the fair and altruistic offers. However, the proposers received explicit self-interest instruction chose more selfish offers accompanied with longer RTs in choosing between the fair and selfish offers. Therefore, the results supported the strategic concern hypothesis that previous proposers choosing the fair offers might be resulted from the fear of rejection by responders. Proposers would become more self-interest if the fear of being rejected is eliminated.

Keywords: ultimatum game, proposer, self-interest, fear of rejection

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Authors: Sylvia Villarreal, Edna Bravo

Abstract:

Knowledge management focuses on coordinating technologies, people, processes, and structures to generate a competitive advantage and considering that networks are perceived as mechanisms for knowledge creation and transfer, this research presents the stages and practices related to the creation of knowledge networks. The methodology started with a literature review adapted from the systematic literature review (SLR). The descriptive analysis includes variables such as approach (conceptual or practical), industry, knowledge management processes and mythologies (qualitative or quantitative), etc. The content analysis includes identification of reference cases. These cases were characterized based on variables as scope, creation goal, years, network approach, actors and creation methodology. It was possible to do a comparative analysis to determinate similarities and differences in these cases documented in knowledge network scientific literature. Consequently, it was shown that even the need and impact of knowledge networks in organizations, the initial guidelines for their creation are not documented, so there is not a guide of good practices and lessons learned. The reference cases are from industries as energy, education, creative, automotive and textile. Their common points are the human approach; it is oriented to interactions to facilitate the appropriation of knowledge, explicit and tacit. The stages of every case are analyzed to propose the main successful elements.

Keywords: creation, knowledge management, network, stages

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Authors: Mounir Kehal

Abstract:

The post-globalization epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behavior has come to provide the competitive and comparative edge. Enterprises have turned to explicit - and even conceptualizing on tacit - knowledge management to elaborate a systematic approach to develop and sustain the intellectual capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualized. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper, we present an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

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Authors: George Kamil Kamal Abdelnor

Abstract:

Every major educational institution has incorporated diversity, equity, and inclusion (DEI) principles into its administrative, hiring, and pedagogical practices. Yet these DEI principles rarely incorporate explicit language or critical thinking about disability. Despite the fact that according to the World Health Organization, one in five people worldwide is disabled, making disabled people the larger minority group in the world, disability remains the neglected stepchild of DEI. Drawing on disability studies and crip theory frameworks, the underlying causes of this exclusion of disability from DEI, such as stigma, shame, invisible disabilities, institutionalization/segregation/delineation from family, and competing models and definitions of disability are examined. This paper explores both the ideological and practical shifts necessary to include disability in university DEI initiatives. It offers positive examples as well as conceptual frameworks such as 'divers ability' for so doing. Using Georgetown University’s 2020-2022 DEI initiatives as a case study, this paper describes how curricular infusion, accessibility, identity, community, and diversity administration infused one university’s DEI initiatives with concrete disability-inclusive measures. It concludes with a consideration of how the very framework of DEI itself might be challenged and transformed if disability were to be included.

Keywords: cognitive disability, cognitive diversity, disability, higher education disability, Standardized Index of Diversity of Disability (SIDD), differential and diversity in disability, 60+ population diversity, equity, inclusion, crip theory, accessibility

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Authors: Sameh Ahmed, Khaled Galal

Abstract:

Fiber-reinforced polymer (FRP) sandwich panels are increasingly making their way into structural engineering applications. One of these applications is the blast mitigation. This is attributed to FRP ability of absorbing considerable amount of energy relative to their low density. In this study, FRP sandwich panels are numerically studied using an explicit finite element code ANSYS AUTODYN. The numerical model is then validated with the experimental field tests in the literature. The inner core configurations that have been studied in the experimental field tests were formed from different orientations of the honeycomb shape. On the other hand, the conducted numerical study has proposed a new core configuration. The new core configuration is formulated from a combination of woven and honeycomb shapes. Throughout this study, two performance parameters are considered; the amount of the energy absorbed by the panels and the peak deformation of the panels. Following, a parametric study has been conducted with more variations of the studied parameters to examine the enhancement of the panels' performance. It is found that the numerical results have shown a good agreement with the experimental measurements. Furthermore, the analyses have revealed that using the proposed core configuration obviously enhances the FRP panels’ behavior when subjected to blast loads.

Keywords: blast load, fiber reinforced polymers, finite element modeling, sandwich panels

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Authors: Katarina Lazarević, Mirjana Todosijević, Tijana Vulević, Natalija Momirović, Ranka Erić

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Due to increasing demand, climate change, and world population growth, natural resources are getting exploit fast. One of the most important natural resources is soil, which is susceptible to degradation. Erosion as one of the forms of land degradation is also one of the most global environmental problems. Ecosystem services are often defined as benefits that nature provides to humankind. Soil, as the foundation of basic ecosystem functions, provides benefits to people, erosion control, water infiltration, food, fuel, fibers… This research is using the ecosystem approach as a strategy for natural resources management for promoting sustainability and conservation. The research was done on the Topčiderska River basin (Belgrade, Serbia). The InVEST Sediment Delivery Ratio model was used, to quantify erosion intensity with a spatial distribution output map of overland sediment generation and delivery to the stream. InVEST SDR, a spatially explicit model, is using a method based on the concept of hydrological connectivity and (R) USLE model. This, combined with socio-economic and law and policy analysis, gives a full set of information to decision-makers helping them to successfully manage and deliver sustainable ecosystems.

Keywords: ecosystem services, InVEST model, soil erosion, sustainability

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Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

A class of implicit systems is known as a more generalized class of systems than a class of explicit systems. To establish a control method for such a generalized class of systems, we adopt model predictive control method which is a kind of optimal feedback control with a performance index that has a moving initial time and terminal time. However, model predictive control method is inapplicable to systems whose all state variables are not exactly known. In other words, model predictive control method is inapplicable to systems with limited measurable states. In fact, it is usual that the state variables of systems are measured through outputs, hence, only limited parts of them can be used directly. It is also usual that output signals are disturbed by process and sensor noises. Hence, it is important to establish a state estimation method for nonlinear implicit systems with taking the process noise and sensor noise into consideration. To this purpose, we apply the model predictive control method and unscented Kalman filter for solving the optimization and estimation problems of nonlinear implicit systems, respectively. The objective of this study is to establish a model predictive control with unscented Kalman filter for nonlinear implicit systems.

Keywords: optimal control, nonlinear systems, state estimation, Kalman filter

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Authors: Sumaira Saleem, Sajjad Hussain, Asma Kashif Shahzad, Hina Shaheen

Abstract:

This study aims at exploring the relationship between language and ideology and how such relationships are represented in the analysis of spoken texts, following Van Dijk’s Socio Cognitive Model (2002). In this study, it is tried to show that political Talk shows broadcast by Private TV channels are working apparatuses of ideology and store meanings which are not always obvious for readers. This analysis was about the situation created by Arslan Iftkhar, the son of ex-Chief Justice of Pakistan, Iftikhar Muhammad Chaudry and PTI Chief Imran Khan. Arslan Iftikhar submitted an application against Imran Khan that he is not able to become a member of parliament of Pakistan. In the application, he demanded the documents, which are submitted by Imran Khan at the time of Election to the Election Commission of Pakistan. Murad Ali from PTI also submitted an application against PM Nawaz Sharif to the Election Commission of Pakistan for providing the copies. It also suggests that these talk shows mystify the agency of processes by using various strategies. In other words, critical text analyses reveal how these choices enable speakers to manipulate the realizations of agency and power in the representation of action to produce particular meanings which are not always explicit for all readers.

Keywords: ECP, CDA, socio cognitive model, ideology, TV channels, power

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Authors: David Chung

Abstract:

The development of seventeenth-century French harpsichord music is enigmatic in several respects. Although little is known about the formation of this style before 1650 (we have names of composers, but no surviving music), the style has attained a high degree of refinement and sophistication in the music of the earliest known masters (e.g. Chambonnières, Louis Couperin and D’Anglebert). In fact, how the seventeenth-century musicians acquired the skills of their art remains largely steeped in mystery, as the earliest major treatise on French keyboard pedagogy was not published until 1702 by Saint Lambert. This study fills this lacuna by surveying some twenty recently-rediscovered manuscripts, which offer ample materials for revisiting key issues pertaining to seventeenth-century harpsichord pedagogy. By analyzing the musical contents, the verbal information and explicit notation (such as written-out ornaments and rhythmic effects), this study provides a rich picture of the process of learning at the time, with engaging details of performance nuances often lacking in tutors and treatises. Of even greater significance, that creative skills (such as continuo and ornamentation) were taught alongside fundamental knowledge (solfèges, note values, etc.) at the earliest stage of learning offers fresh challenge for modern pedagogues to rethink how harpsichord pedagogy can be revamped to cater for our own pedagogical and aesthetic needs.

Keywords: French, harpsichord, pedagogy, seventeenth century

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Authors: Martin Hewing, Katharina Hölzle

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Organizations increasingly use environmental stimuli and ideas from users within participatory innovation processes in order to tap new sources of knowledge. The research presented in this article focuses on users who shape the distant edges of markets and currently are not using products and services from a domain– so called potential users. Those users at the peripheries are perceived to contribute more novel information, by which they better reflect shifts in needs and behavior than current users in the core market. Their contributions in collaborative and creative problem-solving processes and how they generate ideas for discontinuous innovations are of particular interest. With an experimental design, we compare ideas from potential and current users and analyze the effects of cognitive distance in collaboration and the utilization of explicit and tacit knowledge. We find potential users to generate more original ideas, particularly when they collaborate with someone experienced within the domain. Their ideas are most obviously characterized by an increased level of surprise and unusualness compared to dominant designs, which is rooted in contexts and does not require technological leaps. Collaboration with potential users can therefore result in new ways to leverage technological competences. Furthermore, the cross-fertilization arising from cognitive distance between a potential and a current user is asymmetric due to differences in the nature of their utilized knowledge and personal objectives. This paper discusses implications for innovation research and the management of early innovation processes.

Keywords: user collaboration, co-creation, discontinuous innovation, innovation research

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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

Keywords: management, Globsl software development, global software engineering

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Authors: Sana Tahir, Haya Fatimah

Abstract:

Sexuality is a social construct which is considered as the most confidential affair among individuals where women tend to refrain themselves more from sexually explicit behavior than men. Patriarchy has an elevated influence on the expression of female sexuality. While women’s sexual experiences are suppressed men are entitled to pleasure themselves according to their desire. The purpose of this study is to explore how the internalization of patriarchy affects women’s sexuality. Similarly, it was investigated how women sexuality is associated with psychological distress. The sample consisted of 100(age 20-40) married women. Participants were selected through a combination of convenient and snowball sampling. Women were asked to provide data regarding patriarchal beliefs, sexual awareness and DAS (depression, anxiety, and stress). Pearson Product Moment Correlation Analyze was conducted to examine the nature of the relationship between patriarchal beliefs, sexual awareness and psychological distress in married women. There is a significant negative relation between sexual awareness and patriarchal beliefs (r=-.391, p<.001). There also lies a significant negative relation between sexual awareness and depression, anxiety, stress (r=-.359, p<.001) (r=.301, p=.002) (r=-.221, p=.027). The results reveal that women with strong patriarchal beliefs have less sexual awareness in terms of sexual consciousness, sexual monitoring, sexual assertiveness and sexual appeal consciousness. Similarly, women with strong patriarchal beliefs and less sexual awareness have high levels of depression, anxiety, and stress.

Keywords: female sexuality, patriarchy, psychological distress, sexual awareness

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Authors: Saima Noreen, Malcolm D. MacLeod

Abstract:

Different types of forgiveness (emotional and decisional) have been shown to have differential effects on incidental forgetting of information related to a prior transgression. The present study explored the extent to which emotional and decisional forgiveness also influenced intentional forgetting; that is, the extent to which forgetting occurs following an explicit instruction to forget. Using the List-Method Directed Forgetting (LMDF) paradigm, 236 participants were presented with a hypothetical transgression and then assigned to an emotional forgiveness, a decisional forgiveness, or a no-forgiveness manipulation. Participants were then presented with two-word lists each comprising transgression-relevant and transgression-irrelevant words. Following the presentation of the first list, participants were told to either remember or forget the previously learned list of words. Participants in the emotional forgiveness condition were found to remember fewer relevant and more irrelevant transgression-related words, while the opposite was true for both decisional forgiveness and no-forgiveness conditions. Furthermore, when directed to forget words in List 1, participants in the decisional and no-forgiveness conditions were less able to forget relevant transgression-related words in comparison to participants in the emotional forgiveness condition. This study suggests that emotional forgiveness plays a pivotal role in the intentional forgetting of transgression-related information. The potential implications of these findings for coping with unpleasant incidents will be considered.

Keywords: decisional forgiveness, directed forgetting, emotional forgiveness, executive control, forgiveness

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Authors: Rachida Ouysse

Abstract:

This paper proposes a constrained principal components (CnPC) estimator for efficient estimation of large-dimensional factor models when errors are cross sectionally correlated and the number of cross-sections (N) may be larger than the number of observations (T). Although principal components (PC) method is consistent for any path of the panel dimensions, it is inefficient as the errors are treated to be homoskedastic and uncorrelated. The new CnPC exploits the assumption of bounded cross-sectional dependence, which defines Chamberlain and Rothschild’s (1983) approximate factor structure, as an explicit constraint and solves a constrained PC problem. The CnPC method is computationally equivalent to the PC method applied to a regularized form of the data covariance matrix. Unlike maximum likelihood type methods, the CnPC method does not require inverting a large covariance matrix and thus is valid for panels with N ≥ T. The paper derives a convergence rate and an asymptotic normality result for the CnPC estimators of the common factors. We provide feasible estimators and show in a simulation study that they are more accurate than the PC estimator, especially for panels with N larger than T, and the generalized PC type estimators, especially for panels with N almost as large as T.

Keywords: high dimensionality, unknown factors, principal components, cross-sectional correlation, shrinkage regression, regularization, pseudo-out-of-sample forecasting

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

Abstract:

Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper, we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies especially those that have not yet defined an explicit technology strategy. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to direct monitoring activities. Current as well as planned product, production and material technologies as well as existing skills, capabilities and resources form the basis of the described derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: monitoring radar, search field, technology intelligence, technology monitoring

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Authors: Aicha Majda, Abdelhamid El Hassani

Abstract:

Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: graph cuts, lung CT scan, lung parenchyma segmentation, patch-based similarity metric

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Authors: Oday Al-Mamoori, J. Enrique Martinez-Rueda

Abstract:

'C' shape yielding devices (C-devices) are effective tools for introducing supplemental sources of energy dissipation by hysteresis. Studies have shown that C-devices made of mild steel can be successfully applied as integral parts of seismic retrofitting schemes. However, explicit modelling of these devices can become cumbersome, expensive and time consuming. The device under study in this article has been previously used in non-invasive dissipative bracing for seismic retrofitting. The device is cut from a mild steel plate and has an overall shape that resembles that of a rectangular portal frame with circular interior corner transitions to avoid stress concentration and to control the extension of the dissipative region of the device. A number of inelastic finite element (FE) analyses using either inelastic 2D plane stress elements or inelastic fibre frame elements are reported and used to calibrate a 1D equivalent inelastic spring model that effectively reproduces the cyclic response of the device. The more elaborate FE model accounts for the frictional forces developed between the steel plate and the bolts used to connect the C-device to structural members. FE results also allow the visualization of the inelastic regions of the device where energy dissipation is expected to occur. FE analysis results are in a good agreement with experimental observations.

Keywords: C-device, equivalent nonlinear spring, FE analyses, reversed cyclic tests

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Authors: Nguyen Quang Kim, Nguyen Thu Hien, Nguyen Thien Dung

Abstract:

Flood disasters are increasing worldwide in both frequency and magnitude. Every year in Vietnam, flood causes great damage to people, property, and environmental degradation. The flood risk management policy in Vietnam is currently updated. The planning of flood mitigation strategies is reviewed to make a decision how to reach sustainable flood risk reduction. This paper discusses the basic approach where the measures of flood protection are chosen based on minimizing the present value of expected monetary expenses, total residual risk and costs of flood control measures. This approach will be proposed and demonstrated in a case study for flood risk management in Vinh Phuc province of Vietnam. Research also proposed the framework to find a solution of optimal protection level and optimal measures of the flood. It provides an explicit economic basis for flood risk management plans and interactive effects of options for flood damage reduction. The results of the case study are demonstrated and discussed which would provide the processing of actions helped decision makers to choose flood risk reduction investment options.

Keywords: drainage plan, flood planning, flood risk, residual risk, risk optimization

Procedia PDF Downloads 195

Authors: Mounir Kehal, Adel Al Araifi

Abstract:

The post-globalisation epoch has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources (i.e. Autocart). In this paper we present likewise an empirical research study conducted previously to try and explore knowledge diffusion in a specialist knowledge domain.

Keywords: knowledge management, knowledge maps, knowledge diffusion, organizational cartography

Procedia PDF Downloads 390

Authors: Vivienne Langhorne, Helen Sharpe

Abstract:

Body dissatisfaction begins developing in middle childhood, with wide-ranging implications for mental health and well-being. Previous research on parent behavior has focused on the role of explicit parent behaviors in adolescent and young adult body dissatisfaction, leaving a gap in understanding how implicit parent behaviors relate to body dissatisfaction in childhood. The current study investigated how implicit parent behavior (such as modeling own body dissatisfaction and dieting) relates to parent and child body dissatisfaction. It was hypothesized that implicit behavior would be directly related to parent and child body dissatisfaction and mediate the relationship between the two. Furthermore, this study aimed to examine child gender as a potential moderator in this mediation, as research shows that boys and girls experience body dissatisfaction differently. This study analyzed survey responses on parent body dissatisfaction, implicit behavior, and child body dissatisfaction measures from a sample of 166 parent-child dyads with children between the ages of 6 to 9 years old. Regression analyses revealed that parent body dissatisfaction is related to both parent-implicit behavior and child body dissatisfaction. However, implicit behavior did not mediate the relationship between the two body dissatisfaction variables. Additionally, the results of moderated mediation indicated there were no child gender differences in the strength of the association between parental implicit behaviors and child body dissatisfaction. These findings highlight the need for further research into the mechanisms behind parent and child body dissatisfaction to better understand the process through which intergenerational transmission occurs.

Keywords: body dissatisfaction, implicit behaviour, middle childhood, parenting

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Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: Xueying Li

Abstract:

Different from English, it is common to observe Chinese clauses logically related in an implicit way without any conjunctions. This typological difference has posed a great challenge for Chinese-English translators, as 1) translators may interpret logical meaning in different ways when there are no conjunctions in Chinese Source Text (ST); 2) translators may have questions whether to make Chinese implicit logical meaning explicit or to remain implicit in Target Text (TT), and whether other dimensions of logical meaning (e.g., type of logical meaning) should be shifted or not. Against this background, this study examines a comprehensive arrange of Chinese-English translation choices of logical meaning to deal with this challenge in a systematic way. It compiles several ST-TT passages from a set of translation textbooks in a corpus, namely Ying Yu Bi Yi Shi Wu (Er Ji)) [Translation Practice between Chinese and English: Intermediate Level] and its supportive training book, analyzes how logical meaning in ST are translated in TT in texts across different text types with Systemic Functional Linguistics (SFL) as the theoretical framework, and finally draws a system network of translation choices of logical meaning from Chinese into English. Since translators may probably think about semantic meaning rather than lexico-grammatical resources in translation, this study goes away from traditional lexico-grammatical choices, but rather describing translation choices from the semantic level. The findings in this study can provide some help and support for translation practitioners so that they can understand that besides explicitation, there are a variety of possible linguistic choices available for making informed decisions when translating Chinese logical meaning into English.

Keywords: Chinese-English translation, logical meaning, systemic functional linguistics, translation choices

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Authors: Chaohong Pan

Abstract:

Through public diplomacy on social media, governments have attempted to influence foreign public opinion. What is the impact of digital public diplomacy? Public diplomacy research often relies on content analysis to study the strategies employed by communicators but has rarely examined its actual impact on the audience. In addition, we do not know if giving a communicator an explicit label, as Twitter does with “government account”, would change the effects of the messages. Can the government label reduce the percussiveness of public diplomacy messages by sending a warning signal? Using a 2 × 2 survey experiment, the present paper contributes to the study of public diplomacy by randomly exposing American participants to four types of tweets from Chinese diplomats. The stimulus materials vary in terms of the tweets’ content (“positive-china” vs. “negative-US) and Twitter government labels (with vs. without the labels). I found that positive tweets about China have a significant positive effect on Americans’ attitudes toward China, whereas negative tweets about the US have little effect on their opinions. Furthermore, positive-China tweets are effective only on China-related issues, which indicates that Chinese diplomats’ tweets have limited effects on shaping a foreign audience’s attitudes toward their own country. Lastly, I find that labels largely have no impact on a diplomatic tweet’s effect. These results contribute to our understanding of the effects of public diplomacy in the digital age.

Keywords: public diplomacy, china, foreign public opinion, twitter

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Authors: Racholsan Raj Nirmal, B. S. V. Patnaik, R. Jayaganthan

Abstract:

The deformation behaviour of additively manufactured AlSi10Mg alloy under low strains, high strain rates and elevated temperature conditions is essential to analyse and predict its response against dynamic loading such as impact and thermomechanical fatigue. The constitutive relation of Johnson-Cook is used to capture the strain rate sensitivity and thermal softening effect in AlSi10Mg alloy. Johnson-Cook failure model is widely used for exploring damage mechanics and predicting the fracture in many materials. In this present work, Johnson-Cook material and damage model parameters for additively manufactured AlSi10Mg alloy have been determined numerically from four types of uniaxial tensile test. Three different uniaxial tensile tests with dynamic strain rates (0.1, 1, 10, 50, and 100 s^-1) and elevated temperature tensile test with three different temperature conditions (450 K, 500 K and 550 K) were performed on 3D printed AlSi10Mg alloy in ABAQUS/Explicit. Hexahedral elements are used to discretize tensile specimens and fracture energy value of 43.6 kN/m was used for damage initiation. Levenberg Marquardt optimization method was used for the evaluation of Johnson-Cook model parameters. It was observed that additively manufactured AlSi10Mg alloy has shown relatively higher strain rate sensitivity and lower thermal stability as compared to the other Al alloys.

Keywords: ABAQUS, additive manufacturing, AlSi10Mg, Johnson-Cook model

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

Abstract:

Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Cory Callahan

Abstract:

Here the author synthesizes findings and implications from two research studies that comprise a continuing line of inquiry into the potential of an innovative professional development program to help in-service teachers understand and implement a complex model of social studies instruction. The paper specifically explores the question: To what degree can a collaborative professional development program centered around innovative curriculum materials help social studies teachers understand and implement a powerful social studies approach? Findings suggest the teachers increasingly incorporated substantive thinking (i.e., second-order historical domain knowledge) into their respective practice and they facilitated students’ use of historical photographs as evidence to begin to answer a compelling question. The teachers also began to effectively support students’ abilities to make claims about the past. Implications include the foregrounding of high-quality questions during planning and the need for explicit guidance in the form of structures and procedures (i.e., scaffolds) to help teachers systematically review students’ work products. The work shared here may contribute to scholarship that posits explanations for why teacher-support is routinely ineffectual and suggests ways to provide substantive collaborative support for in-service social studies teachers.

Keywords: educative curriculum, social studies, professional development, lesson study

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Authors: Hendrik Bernard Van Der Walt, Frik Van Niekerk

Abstract:

Heterogeneous thorium-based fuels have been proposed as an alternative for conventional reactor fuels and many studies have shown promising results. Fuel cycle characteristics still have to be explored in detail. This study investigates the use of a novel thorium-based fuel design aimed at increasing fuel cycle length of a typical PWR with an explicit focus on thorium- uranium content, neutron spectrum, flux considerations and neutron economy.As nuclear reactions are highly dependent on reactor flux and material matrix, analytical and numerical calculations have been completed to predict the behaviour of the proposed nuclear fuel. The proposed design utilizes various ratios of thorium oxide and uranium oxide pellets within fuel pins, divided into heterogeneous sections of specified length. This design renders multiple regions with unique characteristics. The goal of this study is to determine and optimally utilize these characteristics. Proliferation considerations result in the need for denaturing of heterogeneous regions, which renders more unique characteristics, these aspects were examined in this study. Finally, the use of fertile thorium to emulate a burnable poison for managing excess BOL reactivity has been investigated, as well as an option for flux shaping in a typical PWR.

Keywords: nuclear fuel, nuclear characteristics, nuclear fuel cycle, thorium-based fuel, heterogeneous design

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Authors: Getachew T. Sedebo, Stephan V. Joubert, Michael Y. Shatalov

Abstract:

Conventional configuration of the vibratory disc gyroscope is based on in-plane non-axisymmetric vibrations of the disc with a prescribed circumferential wave number. Due to the Bryan's effect, the vibrating pattern of the disc becomes sensitive to the axial component of inertial rotation of the disc. Rotation of the vibrating pattern relative to the disc is proportional to the inertial angular rate and is measured by sensors. In the present paper, the authors investigate a possibility of making a 3D sensor on the basis of both in-plane and bending vibrations of the disc resonator. We derive equations of motion for the disc vibratory gyroscope, where both in-plane and bending vibrations are considered. Hamiltonian variational principle is used in setting up equations of motion and the corresponding boundary conditions. The theory of thin shells with the linear elasticity principles is used in formulating the problem and also the disc is assumed to be isotropic and obeys Hooke's Law. The governing equation for a specific mode is converted to an ODE to determine the eigenfunction. The resulting ODE has exact solution as a linear combination of Bessel and Neumann functions. We demonstrate how to obtain an explicit solution and hence the eigenvalues and corresponding eigenfunctions for annular disc with fixed inner boundary and free outer boundary. Finally, the characteristics equations are obtained and the corresponding eigenvalues are calculated. The eigenvalues are used for the calculation of tuning conditions of the 3D disc vibratory gyroscope.

Keywords: Bryan’s effect, bending vibrations, disc gyroscope, eigenfunctions, eigenvalues, tuning conditions

Procedia PDF Downloads 291