Search results for: multivariate probit model

Authors: Jia-Jang Wu

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The objective of this research is to develop a general technique so that one may predict the dynamic behaviour of a three-dimensional scale crane model subjected to time-dependent moving point forces by means of conventional finite element computer packages. To this end, the whole scale crane model is divided into two parts: the stationary framework and the moving substructure. In such a case, the dynamic responses of a scale crane model can be predicted from the forced vibration responses of the stationary framework due to actions of the four time-dependent moving point forces induced by the moving substructure. Since the magnitudes and positions of the moving point forces are dependent on the relative positions between the trolley, moving substructure and the stationary framework, it can be found from the numerical results that the time histories for the moving speeds of the moving substructure and the trolley are the key factors affecting the dynamic responses of the scale crane model.

Keywords: moving load, moving substructure, dynamic responses, forced vibration responses

Procedia PDF Downloads 355

Authors: Wera Supa, Panita Wannapiroon

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This paper is a report on the designing of the social collaborative learning model based on proactive involvement to Promote the global merit principle in cultivating youths’ morality. The research procedures into two phases, the first phase is to design the social collaborative learning model based on proactive involvement to promote the global merit principle in cultivating youths’ morality, and the second is to evaluate the social collaborative learning model based on proactive involvement. The sample group in this study consists of 15 experts who are dominant in proactive participation, moral merit principle and youths’ morality cultivation from executive level, lecturers and the professionals in information and communication technology expertise selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. This study has explored that there are four significant factors in promoting the hands-on collaboration of global merit scheme in order to implant virtues to adolescences which are: 1) information and communication Technology Usage; 2) proactive involvement; 3) morality cultivation policy, and 4) global merit principle. The experts agree that the social collaborative learning model based on proactive involvement is highly appropriate.

Keywords: social collaborative learning, proactive involvement, global merit principle, morality

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Authors: T. Alghamdi, G. Alaghband

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In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.

Keywords: Convolution Neural Network, Edges, Face Recognition , Support Vector Machine.

Procedia PDF Downloads 157

Authors: N. Ibrahim-Rassoul, A. Kessi, E. K. Si-Ahmed, N. Djilali, J. Legrand

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The static and dynamic formation of liquid water bridges is analyzed using a combination of visualization experiments in a microchannel with a mathematical model. This paper presents experimental and theoretical findings of water plug/capillary bridge formation in a 250 μm squared microchannel. The approach combines mathematical and numerical modeling with experimental visualization and measurements. The generality of the model is also illustrated for flow conditions encountered in manipulation of polymeric materials and formation of liquid bridges between patterned surfaces. The predictions of the model agree favorably the observations as well as with the experimental recordings.

Keywords: green energy, mathematical modeling, fuel cell, water plug, gas diffusion layer, surface of revolution

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Ofira Zloto, Ofir Fogel, Eyal Klang

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Purpose: The aim is to develop an automated framework based on machine learning to diagnose malignant eyelid skin tumors. Methods: This study utilized eyelid lesion images from Sheba Medical Center, a large tertiary center in Israel. Before model training, we pre-trained our models on the ISIC 2019 dataset consisting of 25,332 images. The proprietary eyelid dataset was then used for fine-tuning. The dataset contained multiple images per patient, aiming to classify malignant lesions in comparison to benign counterparts. Results: The analyzed dataset consisted of images representing both benign and malignant eyelid lesions. For the benign category, a total of 373 images were sourced. In comparison, the malignant category has 186 images. Based on the accuracy values, the model with 3 epochs and a learning rate of 0.0001 exhibited the best performance, achieving an accuracy of 0.748 with a standard deviation of 0.034. At a sensitivity of 69%, the model has a corresponding specificity of 82%. To further understand the decision-making process of our model, we employed heatmap visualization techniques, specifically Gradient-weighted Class Activation Mapping. Discussion: This study introduces a dependable model-aided diagnostic technology for assessing eyelid skin lesions. The model demonstrated accuracy comparable to human evaluation, effectively determining whether a lesion raises a high suspicion of malignancy or is benign. Such a model has the potential to alleviate the burden on the healthcare system, particularly benefiting rural areas and enhancing the efficiency of clinicians and overall healthcare.

Keywords: machine learning;, eyelid skin tumors;, decision-making process;, heatmap visualization techniques

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Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima

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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.

Keywords: Box-Jenkins's problem, double-input rule module, fuzzy inference model, obstacle avoidance, single-input rule module

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Authors: Neneng Hayatul Milah

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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.

Keywords: reading comprehension skills, CIRC, Padlet, narrative text

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Authors: Gudakesh Yadav

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Uttar Pradesh is one of the poorest performing states of India in terms of child health. Using data from the three round of NFHS and two rounds of DLHS, this paper attempts to examine tempo-spatial change in child health and care practices in Uttar Pradesh and its regions. Rate-ratio, CI, multivariate, and decomposition analysis has been used for the study. Findings demonstrate that child health care practices have improved over the time in all regions of the state. However; western and southern region registered the lowest progress in child immunization. Nevertheless, there is no decline in prevalence of diarrhea and ARI over the period, and it remains critically high in the western and southern region. These regions also poorly performed in giving ORS, diarrhoea and ARI treatment. Public health services are least preferred for diarrhoea and ARI treatment. Results from decomposition analysis reveal that rural area, mother’s illiteracy and wealth contributed highest to the low utilization of the child health care practices consistently over the period of time. The study calls for targeted intervention for vulnerable children to accelerate child health care service utilization. Poor performing regions should be targeted and routinely monitored on poor child health indicators.

Keywords: Acute Respiratory Infection (ARI), decomposition, diarrhea, inequality, immunization

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Authors: Machimontorn Promtong, Sherman C. P. Cheung, Guan H. Yeoh, Sara Vahaji, Jiyuan Tu

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The wide range of industrial applications involved with boiling flows promotes the necessity of establishing fundamental knowledge in boiling flow phenomena. For this purpose, a number of experimental and numerical researches have been performed to elucidate the underlying physics of this flow. In this paper, the improved wall boiling models, implemented on ANSYS CFX 14.5, were introduced to study subcooled boiling flow at elevated pressure. At the heated wall boundary, the Fractal model, Force balance approach and Mechanistic frequency model are given for predicting the nucleation site density, bubble departure diameter, and bubble departure frequency. The presented wall heat flux partitioning closures were modified to consider the influence of bubble sliding along the wall before the lift-off, which usually happens in the flow boiling. The simulation was performed based on the Two-fluid model, where the standard k-ω SST model was selected for turbulence modelling. Existing experimental data at around 5 bars were chosen to evaluate the accuracy of the presented mechanistic approach. The void fraction and Interfacial Area Concentration (IAC) are in good agreement with the experimental data. However, the predicted bubble velocity and Sauter Mean Diameter (SMD) are over-predicted. This over-prediction may be caused by consideration of only dispersed and spherical bubbles in the simulations. In the future work, the important physical mechanisms of bubbles, such as merging and shrinking during sliding on the heated wall will be incorporated into this mechanistic model to enhance its capability for a wider range of flow prediction.

Keywords: subcooled boiling flow, computational fluid dynamics (CFD), mechanistic approach, two-fluid model

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Authors: Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri, Aida Kazempour, Reza Tavakkoli-Moghaddam, Maryam Irani

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All over the world, natural disasters (e.g., earthquakes, floods, volcanoes and hurricanes) causes a lot of deaths. Earthquakes are introduced as catastrophic events, which is accident by unusual phenomena leading to much loss around the world. Such could be replaced by disasters or any other synonyms strongly demand great long-term help and relief, which can be hard to be managed. Supplies and facilities are very important challenges after any earthquake which should be prepared for the disaster regions to satisfy the people's demands who are suffering from earthquake. This paper proposed disaster response facility allocation problem for disaster relief operations as a mathematical programming model. Not only damaged people in the earthquake victims, need the consumable commodities (e.g., food and water), but also they need non-consumable commodities (e.g., clothes) to protect themselves. Therefore, it is concluded that paying attention to disaster points and people's demands are very necessary. To deal with this objective, both commodities including consumable and need non-consumable commodities are considered in the presented model. This paper presented the multi-objective multi-period mathematical programming model regarding the minimizing the average of the weighted response times and minimizing the total operational cost and penalty costs of unmet demand and unused commodities simultaneously. Furthermore, a Chebycheff multi-objective solution procedure as a powerful solution algorithm is applied to solve the proposed model. Finally, to illustrate the model applicability, a case study of the Tehran earthquake is studied, also to show model validation a sensitivity analysis is carried out.

Keywords: facility location, multi-objective model, disaster response, commodity

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Susana Marques

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Research on how store environment cues influence consumers’ store choice decision criteria, such as store operations, product quality, monetary price, store image and sales promotion, is sparse. Especially absent research on the simultaneous impact of multiple store environment cues. The authors propose a comprehensive store choice model that includes: three types of store environment cues as exogenous constructs; various store choice criteria as possible mediating constructs, and store patronage intentions as an endogenous construct. On the basis of testing with a sample of 561 customers of hypermarkets, the model is partially supported. This study used structural equation modelling to test the proposed model.

Keywords: store choice, store patronage, structural equation modelling, retailing

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Authors: Sahra Setorg

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The purpose of this study was to determine the effect of meta-cognitive therapy on meta-cognitive defects and emotional regulation in industrial substance dependence patients. This quasi-experimental research was conducted with post-test and two-month follow-up design with control and experimental groups. The statistical population consisted of all industrial Substance dependence patients refer to addictive withdrawal clinics in Esfahan city, in Iran in 2013. 45 patients were selected from three clinics through the convenience sampling method and were randomly divided into two experimental groups (15 crack dependences, 15 amphetamine dependences) and one control group (n=15). The meta-cognitive questionnaire (MCQ) and difficulties in emotional regulation questionnaire (DERS) were used as pre-test measures and the experimental groups (crack and amphetamine) received 8 MC therapy sessions in groups. The data were analyzed via multivariate covariance statistic method by spss-18. The results showed that MCT had a significant effect in improving the meta-cognitive defects in crack and amphetamine dependences. Also, this therapy can increase the emotional regulation in both groups (p<0/05).The effect of this therapy is confirmed in two months followup. According to these findings, met-cognitive is as an interface and important variable in prevention, control, and treatment of the new industrial substance dependences.

Keywords: meta-cognitive therapy, meta-cognitive defects, emotional regulation, substance dependence disorder

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Authors: Cyril Hrncar, Jozef Bujko, Widya P. B. Putra

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The growth curve of poultry is important to evaluate the farming management system. This study was aimed to estimate the growth curve of body weight in goose. The growth curve in this study was estimated with non-linear Gompertz model through CurveExpert 1.4. software. Three Slovak mixed-sex goose breeds of Landes (L), Pomeranian (P) and Steinbacher (S) were used in this study. Total of 28 geese (10 L, 8 P and 10 S) were used to estimate the growth curve. Research showed that the asymptotic weight (A) in those geese were reached of 5332.51 g (L), 6186.14 g (P) and 5048.27 g (S). Thus, the maturing rate (k) in each breed were similar (0.05 g/day). The weight of inflection was reached of 1960.48 g (L), 2274.32 g (P) and 1855.98 g (S). The time of inflection (ti) was reached of 25.6 days (L), 26.2 days (P) and 27.80 days (S). The maximum growth rate (MGR) was reached of 98.02 g/day (L), 113.72 g/day (P) and 92.80 g/day (S). Hence, the coefficient of determination (R2) in Gompertz model was 0.99 for each breed. It can be concluded that Pomeranian geese had highest of growth trait than the other breeds.

Keywords: body weight, growth curve, inflection, Slovak geese, Gompertz model

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Authors: Seemal Mazhar Khan, Tahira Mubashar

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The present research aimed to investigate the relationship in perceived organizational justice, organizational trust and employee engagement in bank employees. It was hypothesized: there is likely to be a relationship in perceived organizational justices, organizational trust and employee engagement; perceived organizational justice and organizational trust are likely to predict employee engagement; there is likely to be effect of bank type and designation on perceived organizational justice, organizational trust and employee engagement. The sample consisted of 150 bank employees (50 from government, 50 from private and 50 from privatized banks) selected from different banks in Lahore, Pakistan. Correlational research design was used to conduct this study. Perceived Organizational Justices Questionnaire, Organizational Trust Questionnaire and Employee Engagement Scale were used for assessment. Pearson product moment correlation, hierarchical regression and multivariate analysis of covariance were applied. Results showed a positive significant relationship in perceived organizational justice and organizational engagement and there were also a positive significant relation between organizational trust and job and organizational engagement. Results showed that organizational trust predicts organizational engagement after controlling the effect of age, marital status and socio-economic status and there is a significant interaction effect of bank type and designation level on organizational trust in bank employees. The findings of the research can serve as a platform for the awareness of important antecedents of employee engagement and organizations can inculcate trust for better and improved engagement of its employees, thereby, enhancing the productivity of their employees.

Keywords: bank employees, organizational engagement, perceived organizational justice, trust

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Authors: Fariba Dortaj, H. Bashir Nejad, Akram Dortaj,

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Investigate the Effectiveness of Mindfulness Education on Emotional, Psychological, and Social Well-being in 12th grade students in Tehran city is the aim of present study. The research method is semi-experimental with pretest-posttest design with control group. The statistical population of the study includes all 12th grade students of the 12th district of Tehran city in the academic year of 2017 to 2018. From the mentioned population, 60 students had earned low scores in three dimensions of Subjective Well-Being Questionnaire of Keyes and Magyar-Moe (2003) by using random sampling method and they were selected and randomly assigned into 2 experimental and control groups. Then experimental groups were received a Mindfulness protocol in 8 sessions during 2 hours. After completion of the sessions, all subjects were re-evaluated. Data were analyzed by using multivariate analysis of covariance. The findings of this study showed that in the emotional well-being aspect with the components of positive emotional affection (P < 0.025, F = 17/80) and negative emotions (P <0.025, F = 5/41), in the psychological well-being of the components Self-esteem (P < 0.008, F = 25.26), life goal (P < 0.008, F = 38.19), environmental domination (P <0.008, F=82.82), relationships with others (P < 0.008, F = 19.12), personal development with (P < 0.008, F = 87.38), and in the social well-being aspect, the correlation coefficients with (P<0.01, F=12/21), admission and acceptability with (P <0.01, F =18.09) and realism with (P <0.01, F = 11.30), there was a significant difference between the experimental and control groups and it can be said that the education of mindfulness affects the improvement of components of psychological, social and emotional well-being in students.

Keywords: mindfulness, emotional well-being, psychological well-being, social well-being

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Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz

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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Keywords: community empowerment, food security, model, systemic approach

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Authors: Leila Trabelsi

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The urbanization of Information Systems (IS) is an effective approach to master the complexity of the organization. It strengthens the coherence of IS and aligns it with the business strategy. Moreover, this approach has significant advantages such as reducing Information Technologies (IT) costs, enhancing the IS position in a competitive environment and ensuring the scalability of the IS through the integration of technological innovations. Therefore, the urbanization is considered as a business strategic decision. Thus, its embedding becomes a necessity in order to improve the IS practice. However, there is a lack of experimental cases studying meta-modelling of Urbanized Information System (UIS). The aim of this paper addresses new urbanization content meta-model which permits modelling, testing and taking into consideration organizational aspects. This methodological framework is structured according to two main abstraction levels, a conceptual level and an operational level. For each of these levels, different models are proposed and presented. The proposed model for has been empirically tested on company. The findings of this paper present an experimental study of urbanization meta-model. The paper points out the significant relationships between dimensions and their evolution.

Keywords: urbanization, information systems, enterprise architecture, meta-model

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Authors: Yen-Ku Kuo, Chie-Bein Chen, Jyh-Yi Shih, Kuang-Yi Lin, Chien-Han Peng

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This study is primarily concerned with exploring what factors affect the consumer’s intention of using mobile phone e-book. In developing research structure, we adopted technology acceptance model (TAM) and Innovation Diffusion Theory (IDT) as a foundation. The analysis method of structural equation model (SEM) was used to carry out this study. Subjects were 261 users who are using or used the mobile phone e-book. The findings can be summed up as follows: (1) The subjective norm and job relevance has non-significant and positive influence to the perceived usefulness. This represents now the user are still in a small number and most of them used it in non-work related purpose. (2) The output quality, result demonstrability and perceived ease of use were confirmed to have positive and significant influence to the perceived usefulness. (3) The moderator “innovative diffusion” affects the relationship between the attitude and behavior intention. These findings could be a reference for the practice and future study to make further exploration.

Keywords: mobile phone e-book, technology acceptance model (TAM), innovation diffusion theory (IDT), structural equation model (SEM)

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Authors: Le Fu, Rui Wu, Gang Feng Liu, Jie Zhao

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Normally, impedance control methods are based on a model that connects a spring and damper in parallel. The series connection, namely the Maxwell model, has emerged as a counterpart and draw the attention of robotics researchers. In the theoretical analysis, it turns out that the two pattern are both equivalents to some extent, but notable differences of response characteristics exist, especially in the effect of damping viscosity. However, this novel impedance control design is lack of validation on realistic robot platforms. In this study, stability analysis and experimental evaluation are achieved using a 3-fingered Barrett® robotic hand BH8-282 endowed with tactile sensing, mounted on a torque-controlled lightweight and collaborative robot KUKA® LBR iiwa 14 R820. Object handover and incoming objects catching tasks are executed for validation and analysis. Experimental results show that the series connection pattern has much better performance in natural impact or shock absorption, which indicate promising applications in robots’ safe and physical interaction with humans and objects in various environments.

Keywords: impedance control, Maxwell model, force control, dexterous manipulation

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Authors: Peter O. Osifo, Hein W. J. P. Neomagus

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In this study, a predicted pH model was used to determine adsorption equilibrium properties of copper, lead, zinc and cadmium. Chitosan was prepared from the exoskeleton of Cape rock-lobsters, collected from the surroundings of Cape Town, South Africa. The beads were cross-linked with gluteraldehyde to restore its chemical stability in acid media. The chitosan beads were characterized; the beads water contents and pKa varied in the range of 90-96% and 4.3-6.0 respectively and the degree of crosslinking for the beads was 18%. A pH-model, which described the reversibility of the metal adsorbed onto the beads, was used to predict the equilibrium properties of copper, lead, zinc and cadmium adsorption onto the cross-linked beads. The model accounts for the effect of pH and the important model parameters; the equilibrium adsorption constant (Kads) and to a lesser extent the adsorbent adsorption capacity (qmax). The adsorption equilibrium constant for copper, lead, zinc and cadmium were found to be 2.58×10-3, 2.22×0-3, 9.55×0-3, and 4.79×0-3, respectively. The adsorbent maximum capacity was determined to be 4.2 mmol/g.

Keywords: chitosan beads, adsorption, heavy metals, waste water

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Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian

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In this research, the changes in bubbles diameter and number that may occur due to the change in heat flux of pure water during pool boiling process. For this purpose, test equipment was designed and developed to collect test data. The bubbles were graded using Caliper Screen software. To calculate the growth and nucleation rates of bubbles under different fluxes, population balance model was employed. The results show that the increase in heat flux from q=20 kw/m2 to q=102 kw/m2 raised the growth and nucleation rates of bubbles.

Keywords: heat flux, bubble growth, bubble nucleation, population balance model

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Authors: Tanzeel Ur Rehman Khan, Franz Josef Behr, Phillip Davis

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Open source geospatial certifications are needed in geospatial technology education and industry sector. In parallel with proprietary software, free and open source software solutions become important in geospatial technology research and play an important role for the growth of the geospatial industry. ESRI, GISCI (GIS Certification Institute), ASPRS (American Society of Photogrammetry and remote sensing), and Meta spatial are offering certifications on proprietary and open source software. These are portfolio and competency based certifications depending on GIS Body of Knowledge (Bok). The analysis of these certification approaches might lead to the discovery of some gaps in them and will open a new way to develop certifications related to the geospatial open source (OS). This new certification will investigate the different geospatial competencies according to open source tools that help to identify geospatial professionals and strengthen the geospatial academic content. The goal of this research is to introduce a geospatial certification model based on geospatial technology competency model (GTCM).The developed certification will not only incorporate the importance of geospatial education and production of the geospatial competency-based workforce in universities and companies (private or public) as well as describe open source solutions with tools and technology. Job analysis, market analysis, survey analysis of this certification opens a new horizon for business as well.

Keywords: geospatial certification, open source, geospatial technology competency model, geoscience

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: probability-based damage detection (PBDD), Kriging, surrogate modeling, uncertainty quantification, artificial intelligence, enhanced ideal gas molecular movement (EIGMM)

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Authors: Ahmed O. Babaleye, Rafet E. Kurt

Abstract:

The global oil and gas industry is beginning to witness an increase in the number of installations moving towards decommissioning. Decommissioning of offshore installations is a complex, costly and hazardous activity, making safety one of the major concerns. Among existing removal options, complete and partial removal options pose the highest risks. Therefore, a dynamic risk model of the accidents from the two options is important to assess the risks on an overall basis. In this study, a risk-based safety model is developed to conduct quantitative risk analysis (QRA) for jacket structure systems failure. Firstly, bow-tie (BT) technique is utilised to model the causal relationship between the system failure and potential accident scenarios. Subsequently, to relax the shortcomings of BT, Bayesian Belief Networks (BBNs) were established to dynamically assess associated uncertainties and conditional dependencies. The BBN is developed through a similitude mapping of the developed bow-tie. The BBN is used to update the failure probabilities of the contributing elements through diagnostic analysis, thus, providing a case-specific and realistic safety analysis method when compared to a bow-tie. This paper presents the application of dynamic safety analysis to guide the allocation of risk control measures and consequently, drive down the avoidable cost of remediation.

Keywords: Bayesian belief network, offshore decommissioning, dynamic safety model, quantitative risk analysis

Procedia PDF Downloads 281

Authors: Yuta Moriyama, Tsuyoshi Yamazaki, Etsuo Morishita

Abstract:

Several aerodynamic devices currently attract engineers and research students. The plasma actuator is one of them, and it is very effective to control the flow. The actuator recovers a separated flow to an attached one. The actuator is also inversely applied to a spoiler. The model aircraft might be controlled by this actuator. We develop a model aircraft with the plasma actuator. Another interesting device is the Wells turbine which rotates in one direction. The present authors propose a bicycle with the Wells turbine in the wheels. Power reduction is measured when the turbine is driven by an electric motor at the exit of a wind tunnel. Several Watts power reduction might be possible. This means that the torque of the bike can be augmented by the turbine in the cross wind. These devices are tested in the wind tunnel with a three-component balance and the aerodynamic forces and moment are obtained. In this paper, we introduce these devices and their aerodynamic characteristics. The control force and moment of the plasma actuator are clarified and the power reduction of the bicycle is quantified.

Keywords: aerodynamics, model aircraft, plasma actuator, Wells turbine

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Authors: J. R. Wang, H. T. Lin, Y. Chiang, H. C. Chen, C. Shih

Abstract:

Kuosheng Nuclear Power Plant (NPP) is located on the northern coast of Taiwan. Its nuclear steam supply system is a type of BWR/6 designed and built by General Electric on a twin unit concept. First, the methodology of Kuosheng NPP SPU (Stretch Power Uprate) safety analysis TRACE/SNAP model was developed in this research. Then, in order to estimate the safety of Kuosheng NPP under the more severe condition, the SBO (Station Blackout) + LOCA (Loss-of-Coolant Accident) transient analysis of Kuosheng NPP SPU TRACE/SNAP model was performed. Besides, the animation model of Kuosheng NPP was presented using the animation function of SNAP with TRACE/SNAP analysis results.

Keywords: TRACE, safety analysis, BWR/6, severe accident

Procedia PDF Downloads 717