Search results for: model transformation

Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, D. Nahum Kabeya

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In this paper the bifurcation analysis of oilfield in Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km2, a central basin with an area of 800,000 km2, the western branch of the East African Rift in which there are 50,000 km2. The fractal characterization of complex hydro-dynamic fractures in oilfield is developed to facilitate oil production process based on reservoirs bifurcation model.

Keywords: reservoir bifurcation, fractal characterisation, permeability, conductivity, skin effect

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Authors: Tejush Badal, Sanaa Alwidian

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

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

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Authors: Lin Dong-Yih, Yang S. M., Huang B. W., Lian J. A.

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Super duplex stainless steel has excellent mechanical properties and corrosion resistance. It becomes important structural material as its application has been extended to the fields such as renewable energy and the chemical industry because of its excellent properties. As examples are offshore wind power, solar cell machinery, and pipes in the chemical industry. The mechanical properties and corrosion resistance of super duplex stainless steel can be eliminated by welding due to the precipitation of the hard and brittle σ phase, which is rich of chromium, and molybdenum elements. This paper studies the influence of carbon element on the phase transformation of -ferrite and σ phase in 2507 super duplex stainless steel. The 2507 will be under argon gas protection welded with 316 and 316L extra low carbon stainless steel separately. The microstructural phases of stainless steels before and after welding, in fusion, heat affected zones, and base material will be studied via X-ray, OM, SEM, EPMA i.e. their quantity, size, distribution, and morphology. The influences of diffusion by carbon element will be compared according to the microstructures, hardness, and corrosion tests.

Keywords: complex stainless steel, welding, phase formation, carbon element, sigma phase, delta ferrite

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Authors: Emily Cherono Sawe, Elisha Ondieki Makori

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Knowledge and digital economies have brought challenges and potential opportunities for universities to innovate and improve the quality of learning. Disruption technologies and information dynamics continue to transform and change the landscape in teaching, scholarship, and research activities across universities. Digital literacy is a fundamental and imperative element in higher education and training, as witnessed during the new norm. COVID-19 caused unprecedented disruption in universities, where teaching and learning depended on digital innovations and applications. Academic services and activities were provided online, including library information services. Information professionals were forced to adopt various digital platforms in order to provide information services to patrons. University libraries’ roles in fulfilling educational responsibilities continue to evolve in response to changes in pedagogy, technology, economy, society, policies, and strategies of parent institutions. Libraries are currently undergoing considerable transformational change as a result of the inclusion of a digital environment. Academic libraries have been at the forefront of providing online learning resources and online information services, as well as supporting students and staff to develop digital literacy skills via online courses, tutorials, and workshops. Digital literacy transformation and information staff are crucial elements reminiscent of the prioritization of skills and knowledge for lifelong learning. The purpose of this baseline research is to assess the implications of digital literacy transformation in institutions of higher learning in Kenya and share appropriate strategies to leverage and sustain teaching and research. Objectives include examining the leverage and preparedness of the digital literacy environment in streamlining learning in the universities, exploring and benchmarking imperative digital competence for information professionals, establishing the perception of information professionals towards digital literacy skills, and determining lessons, best practices, and strategies to accelerate digital literacy transformation for effective research and learning in the universities. The study will adopt a descriptive research design using questionnaires and document analysis as the instruments for data collection. The targeted population is librarians and information professionals, as well as academics in public and private universities teaching information literacy programmes. Data and information are to be collected through an online structured questionnaire and digital face-to-face interviews. Findings and results will provide promising lessons together with best practices and strategies to transform and change digital literacies in university libraries in Kenya.

Keywords: digital literacy, digital innovations, information professionals, librarians, higher education, university libraries, digital information literacy

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Authors: Malathi Balakrishnan, Gananthan M. Nadarajah, Noraini Abd Rahim, Amy Wong On Mei

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The purpose of the study is to investigate the level of intrinsic motivation of trainers after attending a Continuous Professional Development Course (CPD) organized by Institute of Teacher Training Malaysia titled, ‘Transformation of Teaching and Learning the Fun Way’. This study employed a survey whereby 96 teacher trainers were given Situational Intrinsic Motivational Scale (SIMS) Instruments. Confirmatory factor analysis was carried out to get validity of this instrument in local setting. Data were analyzed with SPSS for descriptive statistic. Semi structured interviews were also administrated to collect qualitative data on participants experiences after participating in the two-day fun-filled program. The findings showed that the participants’ level of intrinsic motivation showed higher mean than the amotivation. The results revealed that the intrinsic motivation mean is 19.0 followed by Identified regulation with a mean of 17.4, external regulation 9.7 and amotivation 6.9. The interview data also revealed that the participants were motivated after attending this training program. It can be concluded that this program, which was organized by Institute of Teacher Training Malaysia, was able to enhance participants’ level of motivation. Self-Determination Theory (SDT) as a multidimensional approach to motivation was utilized. Therefore, teacher trainers may have more success using the ‘The fun way approach’ in conducting training program in future.

Keywords: teaching and learning, motivation, teacher trainer, SDT

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Authors: D. Thawinkarn, S. Wongbutlee

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

Keywords: leadership, social change model, organization, administrators

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Authors: Leonard Mike McNelly Longwa, Divine Kusosa Musiku, Dieudonne Nahum Kabeya

Abstract:

In this paper, the bifurcation analysis of oilfields in the Democratic Republic of Congo is presented in order to enhance petroleum production in an intense tectonic evolution characterized by distinct compressive and extensive phases and the digenetic transformation in the reservoirs during burial geological configuration. The use of porous media in the Makelekese MS-25 field has been established to simulate the boundaries within 3 sedimentary basins open to exploration including the coastal basin with an area of 5992 km², a central basin with an area of 800,000 km², the western branch of the East African Rift in which there are 50,000 km². The fractal characterization of complex hydro-dynamic fractures in oilfields is developed to facilitate the oil production process based on the reservoirs bifurcation model.

Keywords: reservoir bifurcation, fractal characterization, permeability, conductivity, skin effect

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Authors: A. Lakrim, D. Tahri

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

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

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Authors: Funda Kul, İsmail Gür

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

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

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Authors: Piotr Fiszeder, Marcin Fałdziński, Peter Molnár

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

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

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Qiao Fan, Xiaobo Guo, Junxian Zhu, Xiaohu Ding, Ching-Yu Cheng, Tien-Yin Wong, Mingguang He, Heping Zhang, Xueqin Wang

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A systematic, simultaneous analysis of multiple phenotypes in genome-wide association studies (GWASs) draws a great attention to integrate the signals from single phenotypes with increased power. However, lacking an interpretable and efficient multivariate GWAS analysis impede the application of such approach. In this study, we propose to decompose the multivariate model into a series of simple univariate models. This transformation illuminates what exactly the individual trait contributes to the significant signals from the multivariate analyses. By employing our approach in the analysis of three myopia-related endophenotypes from the Singapore Malay Eye Study (SIMES), we identify novel candidate loci which were successfully validated in an independent Guangzhou Twin Eye Study (GTES).

Keywords: GWAS multivariate, multiple traits, myopia, association

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Authors: Felix Schumann, Giorgia Carratta, Tobias Dauth, Liv Jaeckel

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In the last few decades, the rapid growth of the use and disposal of plastic items has led to their overaccumulation in the environment. As a result, plastic pollution has become a subject of global concern. Today plastics are used as raw materials in almost every industry. While the recognition of the ecological, social, and economic impact of plastics in academic research is on the rise, the potential role of the ‘plastic industry’ in dealing with such issues is still largely underestimated. Therefore, the literature on sustainable plastic management is still nascent and fragmented. Working towards sustainability requires a fundamental shift in the way companies employ plastics in their day-to-day business. For that reason, the applicability of the business model concept has recently gained momentum in environmental research. Business model innovation is increasingly recognized as an important driver to re-conceptualize the purpose of the firm and to readily integrate sustainability in their business. It can serve as a starting point to investigate whether and how sustainability can be realized under industry- and firm-specific circumstances. Yet, there is no comprehensive view in the plastic industry on how firms start refining their business models to embed sustainability in their operations. Our study addresses this gap, looking primarily at the industrial sectors responsible for the production of the largest amount of plastic waste today: plastic packaging, consumer goods, construction, textile, and transport. Relying on the archetypes of sustainable business models and applying them to the aforementioned sectors, we try to identify companies’ current strategies to make their business models more sustainable. Based on the thematic clustering, we can develop an integrative framework for the plastic industry. The findings are underpinned and illustrated by a variety of relevant plastic management solutions that the authors have identified through a systematic literature review and analysis of existing, empirically grounded research in this field. Using the archetypes, we can promote options for business model innovations for the most important sectors in which plastics are used. Moreover, by linking the proposed business model archetypes to the plastic industry, our research approach guides firms in exploring sustainable business opportunities. Likewise, researchers and policymakers can utilize our classification to identify best practices. The authors believe that the study advances the current knowledge on sustainable plastic management through its broad empirical industry analyses. Hence, the application of business model archetypes in the plastic industry will be useful for shaping companies’ transformation to create and deliver more sustainability and provides avenues for future research endeavors.

Keywords: business models, environmental economics, plastic management, plastic pollution, sustainability

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Ishit Sheth, Chandrasekhar Jinendran, Chinmaya Ranjan Sahu

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A fourteen degree of freedom (DOF) ride and handling control mathematical model is developed for a car using generalized boltzmann hamel equation which will create a basis for design of ride and handling controller. Mathematical model developed yield equations of motion for non-holonomic constrained systems in quasi-coordinates. The governing differential equation developed integrates ride and handling control of car. Model-based systems engineering approach is implemented for simulation using matlab/simulink, vehicle’s response in different DOF is examined and later validated using commercial software (ADAMS). This manuscript involves detailed derivation of full car vehicle model which provides response in longitudinal, lateral and yaw motion to demonstrate the advantages of the developed model over the existing dynamic model. The dynamic behaviour of the developed ride and handling model is simulated for different road conditions.

Keywords: Full Vehicle Model, MBSE, Non Holonomic Constraints, Boltzmann Hamel Equation

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Authors: Jolanta Tamošaitienė

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The article focuses on a developed comprehensive model to be used in an agile environment for the risk assessment and selection based on multi-attribute methods. The model is based on a multi-attribute evaluation of risk in construction, and the determination of their optimality criterion values are calculated using complex Multiple Criteria Decision-Making methods. The model may be further applied to risk assessment in an agile construction environment. The attributes of risk in a construction project are selected by applying the risk assessment condition to the construction sector, and the construction process efficiency in the construction industry accounts for the agile environment. The paper presents the comprehensive risk assessment model in an agile construction environment. It provides a background and a description of the proposed model and the developed analysis of the comprehensive risk assessment model in an agile construction environment with the criteria.

Keywords: assessment, environment, agile, model, risk

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Authors: Guowei Hou, Lixin Yu, Wei Zhuang, Hui Qin, Xue Yang

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Formal verification is proposed to ensure the correctness of the design and make functional verification more efficient. As cache plays a vital role in the design of System on Chip (SoC), and cache with Memory Management Unit (MMU) and cache memory unit makes the state space too large for simulation to verify, then a formal verification is presented for such system design. In the paper, a formal model checking verification flow is suggested and a new cache memory model which is called “exhaustive search model” is proposed. Instead of using large size ram to denote the whole cache memory, exhaustive search model employs just two cache blocks. For cache system contains data cache (Dcache) and instruction cache (Icache), Dcache memory model and Icache memory model are established separately using the same mechanism. At last, the novel model is employed to the verification of a cache which is module of a custom-built SoC system that has been applied in practical, and the result shows that the cache system is verified correctly using the exhaustive search model, and it makes the verification much more manageable and flexible.

Keywords: cache system, formal verification, novel model, system on chip (SoC)

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Preetinder Kaur Randhawa

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The rural areas can be differentiated from urban areas in terms of their economic activities as rural areas are primarily involved in agricultural sector and provide natural resources whereas, urban areas are primarily involved in infrastructure sector and provide manufacturing services. Census of India defines a Census Town as an area which satisfies the following three criteria i.e. population exceeds 5000, at least 75 percent of male population engaged in non-agricultural sector and minimum population density of 400 persons per square kilometers. Urban areas can be attributed to the improvement of transport facilities, the massive decline in agricultural, especially male workers and workers shift to non-agricultural activities. This study examines the pattern, process of rural areas transformed into urban areas/ census town. The study has analyzed the various factors which are responsible for land transformation as well as the socio-economic transformation of the village population. Nilpur (CT) which belongs to Rajpura Tehsil in Patiala district, Punjab has been selected for the present study. The methodology adopted includes qualitative and quantitative research design, methods based on secondary data. Secondary data has been collected from unpublished revenue record office of Rajpura Tehsil and Primary Census Abstract of Patiala district, Census of India 2011. The results have showed that rate of transformation of a village to census town in Rajpura Tehsil has been one of highest among other villages. The census town has evolved through the evolutionary process of human settlement which grows in size, population and physical development. There must be a complete economic transformation and attainment of high level of technological development. Urban design and construction of buildings and infrastructure can be carried out better and faster and can be used to aid human habitation with the enhancement of quality of life. The study has concluded that in the selected area i.e Nilpur (CT) literacy rate has increased to 72.1 percent in year 2011 from 67.6 percent in year 2001. Similarly non-agricultural work force has increased to 95.2 percent in year 2011 from 81.1 percent in year 2001. It is very much clear that the increased literacy rate has put a positive impact on the involvement of non-agricultural workers have enhanced. The study has concluded that rural-urban linkages are important tools for understanding complexities of people livelihood and their strategies which involve mobility migration and the diversification of income sources and occupations.

Keywords: Census Town, India, Nilpur, Punjab

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.

Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element

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Authors: Rahimah Abdulrahman, A. Eardle, Wilfred Alan, Abdel Hamid Soliman

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With the rapid development in technology, and advances in learning technologies, m-learning has begun to occupy a great part of our lives. The pace of the life getting together with the need for learning started mobile learning (m-learning) concept. In 2008, Saudi Arabia requested a national plan for the adoption of information technology (IT) across the country. Part of the recommendations of this plan concerns the implementation of mobile learning (m-learning) as well as their prospective applications to higher education within the Kingdom of Saudi Arabia. The overall aim of the research is to explore the main issues that impact the deployment of m-learning in nursing institutes in Saudi Arabia, at the Armed Force Hospitals (AFH), Alhada. This is in order to be able to develop a generic model to enable and assist the educational policy makers and implementers of m-learning, to comprehend and treat those issues effectively. Specifically, the research will explore the concept of m-learning; identify and analyse the main organisational; technological and cultural issue, that relate to the adoption of m-learning; develop a model of m-learning; investigate the perception of the students of the Nursing Institutes to the use of m-learning technologies for their nursing diploma programmes based on their experiences; conduct a validation of the m-learning model with the use of the nursing Institute of the AFH, Alhada in Saudi Arabia, and evaluate the research project as a learning experience and as a contribution to the body of knowledge. Activity Theory (AT) will be adopted for the study due to the fact that it provides a conceptual framework that engenders an understanding of the structure, development and the context of computer-supported activities. The study will be adopt a set of data collection methods which engage nursing students in a quantitative survey, while nurse teachers are engaged through in depth qualitative studies to get first-hand information about the organisational, technological and cultural issues that impact on the deployment of m-learning. The original contribution will be a model for developing m-learning material for classroom-based learning in the nursing institute that can have a general application.

Keywords: activity theory (at), mobile learning (m-learning), nursing institute, Saudi Arabia (sa)

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Authors: T. Yasmin, M. A. Farrelly, B. C. Rogers

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Urban water governance in developing countries faces numerous challenges arising from uncontrolled urban population expansion, water pollution, greater economic push and more recently, climate change impact while undergoing transitioning towards a sustainable system. Sustainability transition requires developing adaptive capacities of the socio-ecological and socio-technical system to be able to deal with complexity. Adaptive capacities deliver strategies to connect individuals, organizations, agencies and institutions at multiple levels for dealing with such complexity. Understanding the level of adaptive capacities for sustainability transformation thus has gained significant research attention within developed countries, much less so in developing countries. Filling this gap, this article develops a conceptual framework for analysing the level of adaptive capacities (if any) within a developing context. This framework then applied to the chronological development of urban water governance strategies in Bangladesh for almost two centuries. The chronological analysis of governance interventions has revealed that crisis (public health, food and natural hazards) became the opportunities and thus opened the windows for experimentation and learning to occur as a deviation from traditional practices. Self-organization and networks thus created the platform for development or disruptions to occur for creating change. Leadership (internal or external) is important for nurturing and upscaling theses development or disruptions towards guiding policy vision and targets as well as championing ground implementation. In the case of Bangladesh, the leadership from the international and national aid organizations and targets have always lead the development whereas more often social capital tools (trust, power relations, cultural norms) act as disruptions. Historically, this has been evident in the development pathways of urban water governance in Bangladesh. Overall this research has shown some level of adaptive capacities is growing for sustainable urban growth in big cities, nevertheless unclear regarding the growth in medium and small cities context.

Keywords: adaptive capacity, Bangladesh, sustainability transformation, water governance

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Authors: Chui Ka Shing

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This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

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Authors: Jinlai Bian, Zailin Yang, Guanxixi Jiang, Xinzhu Li

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The problem of elastic wave propagation in inhomogeneous medium has always been a classic problem. Due to the frequent occurrence of earthquakes, many economic losses and casualties have been caused, therefore, to prevent earthquake damage to people and reduce damage, this paper studies the dynamic response around the circular inclusion in the whole space with inhomogeneous modulus, the inhomogeneity of the medium is reflected in the shear modulus of the medium with the spatial position, and the density is constant, this method can be used to solve the problem of the underground buried pipeline. Stress concentration phenomena are common in aerospace and earthquake engineering, and the dynamic stress concentration factor (DSCF) is one of the main factors leading to material damage, one of the important applications of the theory of elastic dynamics is to determine the stress concentration in the body with discontinuities such as cracks, holes, and inclusions. At present, the methods include wave function expansion method, integral transformation method, integral equation method and so on. Based on the complex function method, the Helmholtz equation with variable coefficients is standardized by using conformal transformation method and wave function expansion method, the displacement and stress fields in the whole space with circular inclusions are solved in the complex coordinate system, the unknown coefficients are solved by using boundary conditions, by comparing with the existing results, the correctness of this method is verified, based on the superiority of the complex variable function theory to the conformal transformation, this method can be extended to study the inclusion problem of arbitrary shapes. By solving the dynamic stress concentration factor around the inclusions, the influence of the inhomogeneous parameters of the medium and the wavenumber ratio of the inclusions to the matrix on the dynamic stress concentration factor is analyzed. The research results can provide some reference value for the evaluation of nondestructive testing (NDT), oil exploration, seismic monitoring, and soil-structure interaction.

Keywords: circular inclusions, complex variable function, dynamic stress concentration factor (DSCF), inhomogeneous medium

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents modeling of a Alternating Current (AC) Photovoltaic (PV) module using Matlab/Simulink. The proposed AC-PV module model is simple, realistic, and application oriented. The model is derived on module level as compared to cell level directly from the information provided by the manufacturer data sheet. DC-PV module, MPPT control, BC, VSI and LC filter, all were treated as a single unit. The model accounts for changes in variations of both irradiance and temperature. The AC-PV module proposed model is simulated and the results are compared with the datasheet projected numbers to validate model’s accuracy and effectiveness. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: PV modeling, AC PV Module, datasheet, VI curves irradiance, temperature, MPPT, Matlab/Simulink

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Authors: Christian Uchechukwu Gilbert

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Generativism in language design investigates the framework on which varying sentence structures are built in the English language. Propounded by Noam Chomsky in 1965, the theory transforms sentences from an active structure to a passive one by the application of established rules of the theory. Resident in the body of syntax, the rules include movement, insertion, substitution, and deletion rules. Using the movement rule, the analysis is armed with the qualitative research method, on which the works of scholars were duly consulted for more insight and in line with the academic practice in research activities. The investigation showed that the rules of competent grammar explain the formulation of sentences in a language and how transformation takes place among sentences from a deep structure to a surface structure with accurate results. The structural differences that could be got through dative movement and the deletion of the preposition; passivisation got from an active sentence by the insertion of the preposition “by” a “be verb” and the aspect tense marker “–en”, held as the creative aspect of language vocabulary and the subject-auxiliary inversion that exchanges the auxiliary of a sentence with the subject of the same sentence thereby transforming a kennel sentence to a polar question, viewed as an external argument under θ-theory. Generativism in language design, therefore, changes available types of sentences and relates one form of linguistic category with others in language design.

Keywords: language, generate, transformation, structure, design

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

Abstract:

Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 91

Authors: Catherine Maware, Olufemi Adetunji

Abstract:

The paper is aimed at developing a model to measure the impact of Lean manufacturing deployment on organizational performance. The model will help industry practitioners to assess the impact of implementing Lean constructs on organizational performance. It will also harmonize the measurement models of Lean performance with the house of Lean that seems to have become the industry standard. The sheer number of measurement models for impact assessment of Lean implementation makes it difficult for new adopters to select an appropriate assessment model or deployment methodology. A literature review is conducted to classify the Lean performance model. Pareto analysis is used to select the Lean constructs for the development of the model. The model is further formalized through the use of Structural Equation Modeling (SEM) in defining the underlying latent structure of a Lean system. An impact assessment measurement model developed can be used to measure Lean performance and can be adopted by different industries.

Keywords: impact measurement model, lean bundles, lean manufacturing, organizational performance

Procedia PDF Downloads 485

Authors: Nougrara Zineb

Abstract:

The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

Procedia PDF Downloads 266