Search results for: mauri model decision-making framework

Authors: Ilaria Barletta, Mahesh Mani, Björn Johansson

Abstract:

The concept of sustainability encompasses economic, environmental, social and institutional considerations. Sustainable manufacturing (SM) is, therefore, a multi-faceted concept. It broadly implies the development and implementation of technologies, projects and initiatives that are concerned with the life cycle of products and services, and are able to bring positive impacts to the environment, company stakeholders and profitability. Because of this, achieving SM-related goals requires a holistic, life-cycle-thinking approach from manufacturing companies. Further, such an approach must rely on a logic of continuous improvement and ease of implementation in order to be effective. Currently, there exists in the academic literature no comprehensively structured frameworks that support manufacturing companies in the identification of the issues and the capabilities that can either hinder or foster sustainability. This scarcity of support extends to difficulties in obtaining quantifiable measurements in order to objectively evaluate solutions and programs and identify improvement areas within SM for standards conformance. To bridge this gap, this paper proposes the concept of a framework for assessing and continuously improving the sustainability of manufacturing companies. The framework addresses strategies and projects for SM and operates in three sequential phases: analysis of the issues, design of solutions and continuous improvement. A set of interviews, observations and questionnaires are the research methods to be used for the implementation of the framework. Different decision-support methods - either already-existing or novel ones - can be 'plugged into' each of the phases. These methods can assess anything from business capabilities to process maturity. In particular, the authors are working on the development of a sustainable manufacturing maturity model (SMMM) as decision support within the phase of 'continuous improvement'. The SMMM, inspired by previous maturity models, is made up of four maturity levels stemming from 'non-existing' to 'thriving'. Aggregate findings from the use of the framework should ultimately reveal to managers and CEOs the roadmap for achieving SM goals and identify the maturity of their companies’ processes and capabilities. Two cases from two manufacturing companies in Australia are currently being employed to develop and test the framework. The use of this framework will bring two main benefits: enable visual, intuitive internal sustainability benchmarking and raise awareness of improvement areas that lead companies towards an increasingly developed SM.

Keywords: life cycle management, continuous improvement, maturity model, sustainable manufacturing

Procedia PDF Downloads 228

Authors: Alpana Goel, Kawalpreet Kalra

Abstract:

The study of level structures of deformed nuclei is the most complex topic in nuclear physics. For the description of level structure, a simple model is good enough to bring out the basic features which may then be further refined. The low lying level structures of these nuclei can, therefore, be understood in terms of Two Quasiparticle plus axially symmetric Rotor Model (TQPRM). The formulation of TQPRM for deformed nuclei has been presented. The analysis of available experimental data on two quasiparticle rotational bands of deformed nuclei present unusual features like signature dependence, odd-even staggering, signature inversion and signature reversal in two quasiparticle rotational bands of deformed nuclei. These signature effects are well discussed within the framework of TQPRM. The model is well efficient in reproducing the large odd-even staggering and anomalous features observed in even-even and odd-odd deformed nuclei. The effect of particle-particle and the Coriolis coupling is well established from the model. Detailed description of the model with implications to deformed nuclei is presented in the paper.

Keywords: deformed nuclei, signature effects, signature inversion, signature reversal

Procedia PDF Downloads 143

Authors: Andrew Thayer, Courtney Rondeau, Paraskevi Papadopoulou

Abstract:

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) gene-editing technologies have generated considerable discussion about the applications and ethics of their use. However, no consistent guidelines for using CRISPR technologies have been developed -nor common legislation passed related to gene editing, especially as it is connected to genetically modified organisms (GMOs) in the European Union. The recent announcement that the first babies with CRISPR-edited genes were born, along with new studies exploring CRISPR’s applications in treating thalassemia, sickle-cell anemia, cancer, and certain forms of blindness, have demonstrated that the technology is developing faster than the policies needed to control it. Therefore, it can be seen that a reasonable and coherent regulatory framework for the use of CRISPR in human somatic and germline cells is necessary to ensure the ethical use of the technology in future years. The European Union serves as a unique region of interconnected countries without a standard set of regulations or legislation for CRISPR gene-editing. We posit that the EU would serve as a suitable model in comparing the legislations of its affiliated countries in order to understand the practicality and effectiveness of adopting majority-approved practices. Additionally, we present a proposed set of guidelines which could serve as a basis in developing a consistent regulatory framework for the EU countries to implement but also act as a good example for other countries to adhere to. Finally, an additional, multidimensional framework of smart solutions is proposed with which all stakeholders are engaged to become better-informed citizens.

Keywords: CRISPR, ethics, regulatory framework, European legislation

Procedia PDF Downloads 110

Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

Abstract:

Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

Procedia PDF Downloads 43

Authors: Rong-Yang Lai, Jia-Yu Wu, Chih-Han Chang, Yung-Chung Chen

Abstract:

The dental bridge is one of the clinical methods of the treatment for missing teeth. The dental bridge is generally designed for two layers, containing the inner layer of the framework(zirconia) and the outer layer of the porcelain-fused to framework restorations. The design of a conventional bridge is generally based on the antagonist tooth profile so that the framework evenly indented by an equal thickness from outer contour. All-ceramic dental bridge made of zirconia have well demonstrated remarkable potential to withstand a higher physiological occlusal load in posterior region, but it was found that there is still the risk of all-ceramic bridge failure in five years. Thus, how to reduce the incidence of failure is still a problem to be solved. Therefore, the objective of this study is to develop mechanical designs for all-ceramic dental bridges framework by reducing the stress and enhancing fracture resistance under given loading conditions by finite element method. In this study, dental design software is used to design dental bridge based on tooth CT images. After building model, Bi-directional Evolutionary Structural Optimization (BESO) Method algorithm implemented in finite element software was employed to analyze results of finite element software and determine the distribution of the materials in dental bridge; BESO searches the optimum distribution of two different materials, namely porcelain and zirconia. According to the previous calculation of the stress value of each element, when the element stress value is higher than the threshold value, the element would be replaced by the framework material; besides, the difference of maximum stress peak value is less than 0.1%, calculation is complete. After completing the design of dental bridge, the stress distribution of the whole structure is changed. BESO reduces the peak values of principle stress of 10% in outer-layer porcelain and avoids producing tensile stress failure.

Keywords: dental bridge, finite element analysis, framework, automatic program

Procedia PDF Downloads 265

Authors: Kyle De Freitas, Margaret Bernard

Abstract:

Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

Procedia PDF Downloads 298

Authors: Frezer Alem Kebede

Abstract:

The notion of viewing ICT as merely support for the business process has shifted towards viewing ICT as a critical business enabler. As such, the need for ICT devices has increased, contributing to high electronic equipment acquisition and disposal. Hence, its use and disposal must be seen in light of environmental sustainability, i.e., in terms of green use and disposal. However, there are limited studies on green Use and Disposal framework to be used as guiding lens by organizations in developing countries. And this study endeavors to address that need taking one of the largest multinational ICT intensive company in the country. The design and development of this framework passed through several stages, initially factors affecting green use and disposal were identified after quantitative and qualitative data analysis then there were multiple brainstorming sessions for the design enhancement as participative modelling was employed. Given the difference in scope and magnitude of the challenges identified, the proposed framework approaches green use and disposal in four imperatives; strategically, tactically, operationally and through continuous improvement.

Keywords: energy efficiency, green disposal, green ICT, green use, green use and disposal framework, sustainability

Procedia PDF Downloads 169

Authors: Muhammad Atif, Cang Yan

Abstract:

The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

Procedia PDF Downloads 36

Authors: Vaikunthan Rajaratnam

Abstract:

Intro: Motor imagery (MI) and mental practice (MP) can be an alternative to acquire mastery of surgical skills. One component of using this technique is the use of a mental script. The aim of this study was to design and develop a mental script for basic micro suturing training for skill acquisition using a low-fidelity rubber glove model and to describe the detailed methodology for this process. Methods: This study was based on a design and development research framework. The mental script was developed with 5 expert surgeons performing a cognitive walkthrough of the repair of a vertical opening in a rubber glove model using 8/0 nylon. This was followed by a hierarchal task analysis. A draft script was created, and face and content validity assessed with a checking-back process. The final script was validated with the recruitment of 28 participants, assessed using the Mental Imagery Questionnaire (MIQ). Results: The creation of the mental script is detailed in the full text. After assessment by the expert panel, the mental script had good face and content validity. The average overall MIQ score was 5.2 ± 1.1, demonstrating the validity of generating mental imagery from the mental script developed in this study for micro suturing in the rubber glove model. Conclusion: The methodological approach described in this study is based on an instructional design framework to teach surgical skills. This MP model is inexpensive and easily accessible, addressing the challenge of reduced opportunities to practice surgical skills. However, while motor skills are important, other non-technical expertise required by the surgeon is not addressed with this model. Thus, this model should act a surgical training augment, but not replace it.

Keywords: mental script, motor imagery, cognitive walkthrough, verbal protocol analysis, hierarchical task analysis

Procedia PDF Downloads 79

Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

Abstract:

The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 111

Authors: Seun Mayowa Sunday

Abstract:

Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

Procedia PDF Downloads 106

Authors: M. Vlahovic

Abstract:

This paper presents a model of public finances, which combines three concepts: participatory budgeting, crowdfunding and blockchain technology. Participatory budgeting is defined as a process in which community members decide how to spend a part of community’s budget. Crowdfunding is a practice of funding a project by collecting small monetary contributions from a large number of people via an Internet platform. Blockchain technology is a distributed ledger that enables efficient and reliable transactions that are secure and transparent. In this hypothetical model, the government or authorities on local/regional level would set up a platform where they would propose public projects to citizens. Citizens would browse through projects and support or vote for those which they consider justified and necessary. In return, they would be entitled to a tax relief in the amount of their monetary contribution. Since the blockchain technology enables tracking of transactions, it can be used to mitigate corruption, money laundering and lack of transparency in public finances. Models of its application have already been created for e-voting, health records or land registries. By presenting a model of application of blockchain technology in public finances, this paper takes into consideration the potential of blockchain technology to disrupt governments and make processes more democratic, secure, transparent and efficient. The framework for this paper consists of multiple streams of research, including key concepts of direct democracy, public finance (especially the voluntary theory of public finance), information and communication technology, especially blockchain technology and crowdfunding. The framework defines rules of the game, basic conditions for the implementation of the model, benefits, potential problems and development perspectives. As an oversimplified map of a new form of public finances, the proposed model identifies primary factors, that influence the possibility of implementation of the model, and that could be tracked, measured and controlled in case of experimentation with the model.

Keywords: blockchain technology, distributed ledger, participatory budgeting, crowdfunding, direct democracy, internet platform, e-government, public finance

Procedia PDF Downloads 128

Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

Abstract:

Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

Procedia PDF Downloads 420

Authors: Anli Du Preez, James Bekker

Abstract:

Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

Procedia PDF Downloads 144

Authors: Ayham Fattoum, Simos Chari, Duncan Shaw

Abstract:

Volatile, uncertain, complex, and ambiguous (VUCA) conditions threaten systems viability with emerging and novel events requiring immediate and localized responses. Such responsiveness is only possible through devolved freedom and emancipated decision-making. The Viable System Model (VSM) recognizes the need and suggests maximizing autonomy to localize decision-making and minimize residual complexity. However, exercising delegated autonomy in VUCA requires confidence and knowledge to use intuition and guidance to maintain systemic coherence. This paper explores the role of intuition as an enabler of emancipated decision-making and autonomy under VUCA. Intuition allows decision-makers to use their knowledge and experience to respond rapidly to novel events. This paper offers three contributions to VSM. First, it designs a system model that illustrates the role of intuitive decision-making in managing complexity and maintaining viability. Second, it takes a black-box approach to theory development in VSM to model the role of autonomy and intuition. Third, the study uses a multi-stage discovery-oriented approach (DOA) to develop theory, with each stage combining literature, data analysis, and model/theory development and identifying further questions for the subsequent stage. We synthesize literature (e.g., VSM, complexity management) with seven months of field-based insights (interviews, workshops, and observation of a live disaster exercise) to develop a framework of intuitive complexity management framework and VSM models. The results have practical implications for enhancing the resilience of organizations and communities.

Keywords: Intuition, complexity management, decision-making, viable system model

Procedia PDF Downloads 49

Authors: Abdullah Eqal Al Mazrooei

Abstract:

In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

Procedia PDF Downloads 663

Authors: Anne Klimesch, Alejandra Martinez, Martin HäRter, Isabelle Scholl, Paulina Bravo

Abstract:

Patient-centered care (PCC) is a key principle of high-quality healthcare. In Latin America, research on and promotion of PCC have taken place in the past. However, thorough implementation of PCC in practice is still missing. In Germany, an integrative model of patient-centeredness has been developed by synthesis of diverse concepts of PCC. The model could serve as a point of reference for further research on the implementation of PCC. However, it is predominantly based on research from Europe and North America. This scoping review, therefore, aims to accumulate research on PCC in Latin America in the past 15 years and analyse how PCC has been conceptualized. The resulting overview of PCC in Latin America will be a foundation for a subsequent study aiming at the adaptation of the integrative model of patient-centeredness to the Latin American health care context. Scientific databases (MEDLINE, EMBASE, PsycINFO, CINAHL, Scopus, Web of Science, SCIELO, Redalyc.) will be searched, and reference and citation tracking will be performed. Studies will be included if they were carried out in Latin America, investigated PCC in any clinical and community setting (public and private), and were published in English, Spanish, French, or Portuguese since 2006. Furthermore, any theoretical framework or conceptual model to guide how PCC is conceptualized in Latin America will be included. Two reviewers will be responsible for the identification of articles, screening of records, and full-text assessment. The results of the scoping review will be used in the development of a mixed-methods study with the aim to understand the needs for PCC, as well as barriers and facilitators in Latin America. Based on the outcomes, the integrative model of PCC will be translated to Spanish and adapted to the Latin American context. The integrative model will enable the dissemination of the concept of PCC in Latin America and will provide a common ground for further research on the topic. The project will thereby make an important contribution to an evidence-based implementation of PCC in Latin America.

Keywords: conceptual framework, integrative model of PCC, Latin America, patient-centered care

Procedia PDF Downloads 169

Authors: Deng Zengming, Wang Mingjiang

Abstract:

As 3D video is explored as a hot research topic in the last few decades, free-viewpoint TV (FTV) is no doubt a promising field for its better visual experience and incomparable interactivity. View synthesis is obviously a crucial technology for FTV; it enables to render images in unlimited numbers of virtual viewpoints with the information from limited numbers of reference view. In this paper, a novel hybrid synthesis framework is proposed and blending priority is explored. In contrast to the commonly used View Synthesis Reference Software (VSRS), the presented synthesis process is driven in consideration of the temporal correlation of image sequences. The temporal correlations will be exploited to produce fine synthesis results even near the foreground boundaries. As for the blending priority, this scheme proposed that one of the two reference views is selected to be the main reference view based on the distance between the reference views and virtual view, another view is chosen as the auxiliary viewpoint, just assist to fill the hole pixel with the help of background information. Significant improvement of the proposed approach over the state-of –the-art pixel-based virtual view synthesis method is presented, the results of the experiments show that subjective gains can be observed, and objective PSNR average gains range from 0.5 to 1.3 dB, while SSIM average gains range from 0.01 to 0.05.

Keywords: fusion method, Gaussian mixture model, hybrid framework, view synthesis

Procedia PDF Downloads 226

Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

Abstract:

Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

Procedia PDF Downloads 342

Authors: Redha Elhuni, M. Munir Ahmad

Abstract:

The main purpose of this research is to construct a generic model for successful implementation of Total Quality Management (TQM) in oil sector, and to find out the effects of this model on the organizational sustainability development (OSD) performance of Libyan oil and gas companies using the structured equation modeling (SEM) approach. The research approach covers both quantitative and qualitative methods. A questionnaire was developed in order to identify the quality factors that are seen by Libyan oil and gas companies to be critical to the success of TQM implementation. Hypotheses were developed to evaluate the impact of TQM implementation on O SD. Data analysis reveals that there is a significant positive effect of the TQM implementation on OSD. 24 quality factors are found to be critical and absolutely essential for successful TQM implementation. The results generated a structure of the TQMSD implementation framework based on the four major road map constructs (Top management commitment, employee involvement and participation, customer-driven processes, and continuous improvement culture).

Keywords: total quality management, critical success factors, oil and gas, organizational sustainability development (SD), Libya

Procedia PDF Downloads 255

Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

Abstract:

Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

Procedia PDF Downloads 368

Authors: Kamolrat Turner, Boontuan Wattanakul

Abstract:

Critical thinking and creativity are prerequisite skills for working professionals in the 21^st century. A survey conducted in 2014 at the Boromarajonani College of Nursing, Chon Buri, Thailand, revealed that these skills within students across all academic years was at a low to moderate level. An action research study was conducted to develop the EREC IF Model, a framework which includes the concepts of experience, reflection, engagement, culture and language, ICT, and flexibility and fun, to guide pedagogic activities for 75 sophomores of the undergraduate nursing science program at the college. The model was applied to all professional nursing courses. Prior to implementation, workshops were held to prepare lecturers and students. Both lecturers and students initially expressed their discomfort and pointed to the difficulties with the model. However, later they felt more comfortable, and by the end of the project they expressed their understanding and appreciation of the model. A survey conducted four and eight months after implementation found that the critical thinking and creativity skills of the sophomores were significantly higher than those recorded in the pretest. It could be concluded that the EREC IF model is efficient for fostering critical thinking and creativity skills in the undergraduate nursing science program. This model should be used for other levels of students.

Keywords: critical thinking, creativity, undergraduate nursing students, EREC IF model

Procedia PDF Downloads 301

Authors: Indre Brazauskaite, Vilte Auruskeviciene

Abstract:

The paper explores the Stage-Gate framework application for innovation maturity among small and medium-sized enterprises (SMEs). Innovation management becomes an essential business survival process for all sizes of organizations that can be evaluated and audited systemically. This research systemically defines and assesses the innovation process from the perspective of the company’s top management. Empirical research explores attitudes and existing practices of innovation management in SMEs in Baltic countries. It structurally investigates the current innovation management practices, level of standardization, and potential challenges in the area. Findings allow to structure of existing practices based on an institutionalized model and contribute to a more advanced understanding of the innovation process among SMEs. Practically, findings contribute to advanced decision-making and business planning in the process.

Keywords: innovation measure, innovation process, SMEs, stage-gate framework

Procedia PDF Downloads 76

Authors: Ishak Ramli, Mohamad Noorman Masrek, Muhamad Abdul Aziz Ab Gani

Abstract:

Islam places restrictions and limitation to the creation and ownership of visual art. Not all forms of visual arts are permissible in Islam. However, guidance on the creation and ownership of visual arts is not made plain and clear not only to the Islamic followers but also to the art community. Given this gap, this study attempts to develop a conceptual framework that will guide artist and art collectors on what constitute to valid and acceptable through the Islamic perspective. Based on this framework, several research checklist are proposed. It is highly useful especially for the researchers who are interested to study the topic. Qualitative research is the best choice to test run the paper work to attempt all the checklist which are formed.

Keywords: contemporary visual art, Shariah, conceptual framework, Islam

Procedia PDF Downloads 342

Authors: A. Amar

Abstract:

Analysis of the elastic scattering of protons on ¹⁰B nuclei has been done in the framework of the optical model and single folding model at the beam energies up to 17 MeV. We could enhance the optical potential parameters using Esis88 Code, as well as SPI GENOA Code. Linear relationship between volume real potential (V₀) and proton energy (E_p) has been obtained. Also, surface imaginary potential W_D is proportional to the proton energy (E_p) in the range 0.400 and 17 MeV. The radiative reaction ¹⁰B(p,γ)¹¹C has been analyzed using potential model. A comparison between ¹⁰B(p,γ)¹¹C and ⁶Li(p,γ)⁷Be has been made. Good agreement has been found between theoretical and experimental results in the whole range of energy. The radiative resonance reaction ⁷Li(p,γ)⁸Be has been studied.

Keywords: elastic scattering of protons on 10B nuclei, optical potential parameters, potential model, radiative reaction

Procedia PDF Downloads 187

Authors: P. Byrnes, F. A. DiazDelaO

Abstract:

The Support Vector Machine (SVM) has become widely recognised as one of the leading algorithms in machine learning for both regression and binary classification. It expresses predictions in terms of a linear combination of kernel functions, referred to as support vectors. Despite its popularity amongst practitioners, SVM has some limitations, with the most significant being the generation of point prediction as opposed to predictive distributions. Stemming from this issue, a probabilistic model namely, Probabilistic Classification Vector Machines (PCVM), has been proposed which respects the original functional form of SVM whilst also providing a predictive distribution. As physical system designs become more complex, an increasing number of classification tasks involving industrial applications consist of more than two classes. Consequently, this research proposes a framework which allows for the extension of PCVM to a multi class setting. Additionally, the original PCVM framework relies on the use of type II maximum likelihood to provide estimates for both the kernel hyperparameters and model evidence. In a high dimensional multi class setting, however, this approach has been shown to be ineffective due to bad scaling as the number of classes increases. Accordingly, we propose the application of Markov Chain Monte Carlo (MCMC) based methods to provide a posterior distribution over both parameters and hyperparameters. The proposed framework will be validated against current multi class classifiers through synthetic and real life implementations.

Keywords: probabilistic classification vector machines, multi class classification, MCMC, support vector machines

Procedia PDF Downloads 205

Authors: Luciano Batista, Sylvia Saes, Nuno Fouto, Liam Fassam

Abstract:

This paper introduces the theoretical and methodological basis of an analytical framework conceived with the purpose of bringing industrial ecology perspectives into the core of the underlying disciplines supporting analyses in studies concerned with environmental sustainability aspects beyond the product cycle in a supply chain. Given the pressing challenges faced by the food sector, the framework focuses upon waste minimization through industrial linkages in food supply chains. The combination of industrial ecology practice with basic LCA elements, the waste hierarchy model, and the spatial scale of industrial symbiosis allows the standardization of qualitative analyses and associated outcomes. Such standardization enables comparative analysis not only between different stages of a supply chain, but also between different supply chains. The analytical approach proposed contributes more coherently to the wider circular economy aspiration of optimizing the flow of goods to get the most out of raw materials and cuts wastes to a minimum.

Keywords: by-product synergy, food supply chain, industrial ecology, industrial symbiosis

Procedia PDF Downloads 392

Authors: Wan Noorul Hafilah Binti Wan Ariffin

Abstract:

Dam safety management is the crucial infrastructure as dam failure has a catastrophic effect on the community. Dam safety management is the effective framework of key actions and activities for the dam owner to manage the safety of the dam for its entire life cycle. However, maintaining dam safety is a challenging task as there are changes in current dam states. These changes introduce new risks to the dam's safety, which had not been considered when the dam was designed. A new framework has to be developed to adapt to the changes in the dam risk and make the dams resilient. This study proposes a risk-based decision-making adaptation framework for dam safety management. The research focuses on climate change's impact on hydrological situations as it causes floods and damages the dam structure. The risk analysis framework is adopted to improve the dam management strategies. The proposed study encompasses four phases. To start with, measuring the effect by assessing the impact of climate change on embankment dam, the second phase is to analyze the potential embankment dam failures. The third is analyzing the different components of risks related to the dam and, finally, developing a robust decision-making framework.

Keywords: climate change, embankment dam, failure, risk-informed decision making

Procedia PDF Downloads 120

Authors: Gyoomi Kim, Jiyoung Bae

Abstract:

In the field of language education research, there are not many tries to empirically examine learners’ acceptance behavior and related factors of mobile-assisted language learning (MALL). This study is one of the few attempts to propose an integrated theoretical framework that explains MALL users’ acceptance behavior and potential factors. Constructs from technology acceptance model (TAM) and MALL research are tested in the integrated framework. Based on previous studies, a hypothetical model was developed. Four external variables related to the MALL user’s acceptance behavior were selected: subjective norm, content reliability, interactivity, self-regulation. The model was also composed of four other constructs: two latent variables, perceived ease of use and perceived usefulness, were considered as cognitive constructs; attitude toward MALL as an affective construct; behavioral intention to use MALL as a behavioral construct. The participants were 438 undergraduate students who enrolled in an intensive English program at one university in Korea. This particular program was held in January 2018 using the vacation period. The students were given eight hours of English classes each day from Monday to Friday for four weeks and asked to complete MALL courses for practice outside the classroom. Therefore, all participants experienced blended MALL environment. The instrument was a self-response questionnaire, and each construct was measured by five questions. Once the questionnaire was developed, it was distributed to the participants at the final ceremony of the intensive program in order to collect the data from a large number of the participants at a time. The data showed significant evidence to support the hypothetical model. The results confirmed through structural equation modeling analysis are as follows: First, four external variables such as subjective norm, content reliability, interactivity, and self-regulation significantly affected perceived ease of use. Second, subjective norm, content reliability, self-regulation, perceived ease of use significantly affected perceived usefulness. Third, perceived usefulness and perceived ease of use significantly affected attitude toward MALL. Fourth, attitude toward MALL and perceived usefulness significantly affected behavioral intention to use MALL. These results implied that the integrated framework from TAM and MALL could be useful when adopting MALL environment to university students or adult English learners. Key constructs except interactivity showed significant relationships with one another and had direct and indirect impacts on MALL user’s acceptance behavior. Therefore, the constructs and validated metrics is valuable for language researchers and educators who are interested in MALL.

Keywords: blended MALL, learner factors/variables, mobile-assisted language learning, MALL, technology acceptance model, TAM, theoretical framework

Procedia PDF Downloads 205

Authors: Fatima-Zahra Eddoug, Jamal Benhra, Rajaa Benabbou

Abstract:

Several project management models exist in the literature and the most used ones are the hybrids for their multiple advantages. Our objective in this paper is to analyze the existing models, which are based on the Lean and Agile approaches and to propose a novel framework with the convenient tools that will allow efficient management of a general project. To create the desired framework, we were based essentially on 7 existing models. Only the Scrum tool among the agile tools was identified by several authors to be appropriate for project management. In contrast, multiple lean tools were proposed in different phases of the project.

Keywords: agility, hybrid project management, lean, scrum

Procedia PDF Downloads 112