Search results for: global innovation network

Authors: Feng Guolin, Gong Zhiqiang

Abstract:

In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

Procedia PDF Downloads 427

Authors: Raquel M. De sousa, Sofiane Labidi, Allan Kardec D. Barros, Alex O. Barradas Filho, Aldalea L. B. Marques

Abstract:

Several parameters are established in order to measure biodiesel quality. One of them is the iodine value, which is an important parameter that measures the total unsaturation within a mixture of fatty acids. Limitation of unsaturated fatty acids is necessary since warming of a higher quantity of these ones ends in either formation of deposits inside the motor or damage of lubricant. Determination of iodine value by official procedure tends to be very laborious, with high costs and toxicity of the reagents, this study uses an artificial neural network (ANN) in order to predict the iodine value property as an alternative to these problems. The methodology of development of networks used 13 esters of fatty acids in the input with convergence algorithms of backpropagation type were optimized in order to get an architecture of prediction of iodine value. This study allowed us to demonstrate the neural networks’ ability to learn the correlation between biodiesel quality properties, in this case iodine value, and the molecular structures that make it up. The model developed in the study reached a correlation coefficient (R) of 0.99 for both network validation and network simulation, with Levenberg-Maquardt algorithm.

Keywords: artificial neural networks, biodiesel, iodine value, prediction

Procedia PDF Downloads 588

Authors: A. D. Tayal

Abstract:

The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

Procedia PDF Downloads 349

Authors: Renu Satish Nair

Abstract:

Indian higher education system is the third largest in the world next to United States and China. India is experiencing a rapid growth in higher education in terms of student enrollment as well as establishment of new universities, colleges and institutes of national importance. Presently about 22 million students are being enrolled in higher education and more than 46 thousand institutions’ are functioning as centers of higher education. Indian government plays a 'command and control' role in higher education. The main governing body is University Grants Commission, which enforces its standards, advises the government, and helps coordinate between the centre and the state. Accreditation of higher learning is over seen by 12 autonomous institutions established by the University Grants Commission. The present paper is an effort to analyze the strength, weakness, opportunities and threat (SWOT Analysis) of Indian Higher education system. The higher education in India is progressing ahead by virtue of its strength which is being recognized at global level. Several institutions of India, such as Indian Institutes of Technology (IITs), Indian Institutes of Management (IIMs) and National Institutes of Technology (NITs) have been globally acclaimed for their standard of education. Three Indian universities were listed in the Times Higher Education list of the world’s top 200 universities i.e. Indian Institutes of Technology, Indian Institute of Management and Jawahar Lal Nehru University in 2005 and 2006. Six Indian Institutes of Technology and the Birla Institute of Technology and Science - Pilani were listed among the top 20 science and technology schools in Asia by the Asia Week. The school of Business situated in Hyderabad was ranked number 12 in Globe MBA ranking by the Financial Times of London in 2010 while the All India Institute of Medical Sciences has been recognized as a global leader in medical research and treatment. But at the same time, because of vast expansion, the system bears several weaknesses. The Indian higher education system in many parts of the country is in the state of disrepair. In almost half the districts in the country higher education enrollment are very low. Almost two third of total universities and 90% of colleges are rated below average on quality parameters. This can be attributed to the under prepared faculty, unwieldy governance and other obstacles to innovation and improvement that could prohibit India from meeting its national education goals. The opportunities in Indian higher education system are widely ranged. The national institutions are training their products to compete at global level and make them capable to grab opportunities worldwide. The state universities and colleges with their limited resources are giving the products that are capable enough to secure career opportunities and hold responsible positions in various government and private sectors with in the country. This is further creating opportunities for the weaker section of the society to join the main stream. There are several factors which can be defined as threats to Indian higher education system. It is a matter of great concern and needs proper attention. Some important factors are -Conservative society, particularly for women education; -Lack of transparency, -Taking higher education as a means of business

Keywords: Indian higher education system, SWOT analysis, university grants commission, Indian institutes of technology

Procedia PDF Downloads 874

Authors: M. A. Barros, M. V. Barros

Abstract:

The aim of this work is to analyze the discursive dynamics of preservice teachers during the implementation of a didactic sequence on topics of Quantum Mechanics for High School. Our research methodology was qualitative, case study type, in which we selected two prospective teachers on the Physics Teacher Training Course of the Sao Carlos Institute of Physics, at the University of Sao Paulo/Brazil. The set of modes of communication analyzed were the intentions and interventions of the teachers, the established communicative approach, the patterns and the contents of the interactions between teachers and students. Data were collected through video recording, interviews and questionnaires conducted before and after an 8 hour mini-course, which was offered to a group of 20 secondary students. As teaching strategy we used an active learning methodology, called: Peer Instruction. The episodes pointed out that both future teachers used interactive dialogic and authoritative communicative approaches to mediate the discussion between peers. In the interactive dialogic dimension the communication pattern was predominantly I-R-F (initiation-response-feedback), in which the future teachers assisted the students in the discussion by providing feedback to their initiations and contributing to the progress of the discussions between peers. Although the interactive dialogic dimension has been preferential during the use of the Peer Instruction method the authoritative communicative approach was also employed. In the authoritative dimension, future teachers used predominantly the type I-R-E (initiation-response-evaluation) communication pattern by asking the students several questions and leading them to the correct answer. Among the main implications the work contributes to the improvement of the practices of future teachers involved in applying active learning methodologies in classroom by identifying the types of communicative approaches and communication patterns used, as well as researches on curriculum innovation in physics in high school.

Keywords: curricular innovation, high school, physics teaching, discursive dynamics

Procedia PDF Downloads 162

Authors: Nirmal Kundu, Chandan Bhar, Visveswaran Pandurangan

Abstract:

Technology is the most valued possession for a country or an organization. The economic development depends not on stock of technology but on the capabilities how the technology is being exploited. The technology transfer is the best way how the developing countries have an access to state-of- the-art technology. Traditional technology transfer is a unidirectional phenomenon where technology is transferred from developed to developing countries. But now there is a change of wind. There is a general agreement that global shift of economic power is under way from west to east. As China and India are making the transition from users to producers, and producers to innovators, this has increasing important implications on economy, technology and policy of global trade. As a result, Reverse technology transfer has become a phenomenon and field of study in technology management. The term “Reverse Technology Transfer” is not well defined. Initially the concept of Reverse technology transfer was associated with the phenomenon of “Brain drain” from developing to developed countries. In the second phase, Reverse Technology Transfer was associated with the transfer of knowledge and technology from subsidiaries to multinationals. Finally, time has come now to extend the concept of reverse technology transfer to two different organizations or countries related or unrelated by traditional technology transfer but the transfer or has essentially received the technology through traditional mode of technology transfer. The objective of this paper is to study; 1) the present status of Reverse technology transfer, 2) the factors which are the enablers and barriers of Reverse technology transfer and 3) how the reverse technology transfer strategy can be integrated in the technology policy of a country which will give the countries an economic boost. The research methodology used in this study is a combination of literature review, case studies and key informant interviews. The literature review includes both published as well as unpublished sources of literature. In case study, attempt has been made to study the records of reverse technology transfer that have been occurred in developing countries. In case of key informant interviews, informal telephonic discussions have been carried out with the key executives of the organizations (industry, university and research institutions) who are actively engaged in the process of technology transfer- traditional as well as reverse. Reverse technology transfer is possible only by creating technological capabilities. Following four important enablers coupled with government active and aggressive action can help to build technology base to reach to the goal of Reverse technology transfer 1) Imitation to innovation, 2) Reverse engineering, 3) Collaborative R & D approach, and 4) Preventing reverse brain drain. The barriers that come in the way are the mindset of over dependence, over subordination and parent–child attitude (not adult attitude). Exploitation of these enablers and overcoming the barriers of reverse technology transfer, the developing countries like India and China can prove that going “reverse” is the best way to move forward and again establish themselves as leader of the future world.

Keywords: barriers of reverse technology transfer, enablers of reverse technology transfer, knowledge transfer, reverse technology transfer, technology transfer

Procedia PDF Downloads 386

Authors: Ajay Das, Sandip Basu

Abstract:

Introduction: There is increasing recognition that diverse streams of knowledge can often be recombined in novel ways to generate new knowledge. However, knowledge recombination theory has not been applied to examine the effects of collaborator diversity on the quality of knowledge such collaborators produce. This is surprising because one would expect that a collaborative team with certain aspects of diversity should be able to recombine process elements related to knowledge development, which are relatively tacit, but also complementary because of the collaborator’s varying backgrounds. Theory and Hypotheses: We propose to examine two aspects of diversity in the environments of collaborative teams to try and capture such potential recombinations of relatively tacit, process knowledge. The first aspect of diversity in team members’ environments is geographical. Collaborators with more geographical distance between them (perhaps working in different countries) often have more autonomy in the processes they adopt for knowledge development. In the absence of overt monitoring, such collaborators are likely to adopt differing approaches to knowledge development. The sharing of such varying approaches among collaborators is likely to result in greater quality of the common collaborative pursuit. The second aspect is diversity in the work backgrounds of team members. Such diversity can also increase the potential for knowledge recombination. For example, if one or more members are from a manufacturing center (versus all of them being from a purely R&D center), such members will provide unique perspectives on the implementation of innovative ideas. Again, knowledge that has been evaluated from these diverse perspectives is likely to be of a higher quality. In addition to the above aspects of environmental diversity among team members, we also plan to examine the extent to which individual collaborators are in different environments from the primary innovation center of their employing firms. Proposed Methods: We will test our model on a sample of firms in the semiconductor industry. Our level of analysis will be individual patents generated by these firms and the teams involved in the generation of these. Information on manufacturing activities of our sample firms will be obtained from SEMI, a proprietary database of the semiconductor industry, as well as company 10-K reports. Conclusion: We believe that our results will represent a preliminary attempt to understand how various forms of diversity in collaborative teams impact the knowledge development process. Our dependent variable of knowledge quality is important to study since higher values of this variable can not only drive firm performance but the broader development of regions and societies through spillover impacts on future innovation. The results of this study will, therefore, inform future research and practice in innovation, geographical location, and vertical integration.

Keywords: innovation, manufacturing strategy, knowledge, diversity

Procedia PDF Downloads 337

Authors: Moulfi Bouchra, Ferouani Souheyla, Ziani Kerarti Djalal, Moulessehoul Wassila

Abstract:

The wireless body network (WBAN) is the most interesting network these days and especially with the appearance of contagious illnesses such as covid 19, which require surveillance in the house. In this article, we have designed a circular microstrip antenna. Gold is the material used respectively for the patch and the ground plane and Gallium (εr=12.94) is chosen as the dielectric substrate. The dimensions of the antenna are 82.10*62.84 μm2 operating at a frequency of 3.85 THz. The proposed, designed antenna has a return loss of -46.046 dB and a gain of 3.74 dBi, and it can measure various physiological parameters and sensors that help in the overall monitoring of an individual's health condition.

Keywords: circular patch antenna, Terahertz transmission, WBAN applications, real-time monitoring

Procedia PDF Downloads 295

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi, Morvarid Lalenoor

Abstract:

Background: Plantar pressure distribution measurement has been used for a long time to assess foot disorders. Plantar pressure is an important component affecting the foot and ankle function and Changes in plantar pressure distribution could indicate various foot and ankle disorders. Morphologic and mechanical properties of the foot may be important factors affecting the plantar pressure distribution. Accurate and early measurement may help to reduce the prevalence of pes planus. With recent developments in technology, new techniques such as machine learning have been used to assist clinicians in predicting patients with foot disorders. Significance of the study: This study proposes a neural network learning-based flat foot classification methodology using static foot pressure distribution. Methodologies: Data were collected from 895 patients who were referred to a foot clinic due to foot disorders. Patients with pes planus were labeled by an experienced physician based on clinical examination. Then all subjects (with and without pes planus) were evaluated for static plantar pressures distribution. Patients who were diagnosed with the flat foot in both feet were included in the study. In the next step, the leg length was normalized and the network was trained for plantar pressure mapping images. Findings: From a total of 895 image data, 581 were labeled as pes planus. A computational neural network (CNN) ran to evaluate the performance of the proposed model. The prediction accuracy of the basic CNN-based model was performed and the prediction model was derived through the proposed methodology. In the basic CNN model, the training accuracy was 79.14%, and the test accuracy was 72.09%. Conclusion: This model can be easily and simply used by patients with pes planus and doctors to predict the classification of pes planus and prescreen for possible musculoskeletal disorders related to this condition. However, more models need to be considered and compared for higher accuracy.

Keywords: foot disorder, machine learning, neural network, pes planus

Procedia PDF Downloads 342

Authors: Khyamling Parane, B. M. Prabhu Prasad, Basavaraj Talawar

Abstract:

Fast simulations are critical in reducing time to market in CMPs and SoCs. Several simulators have been used to evaluate the performance and power consumed by Network-on-Chips. Researchers and designers rely upon these simulators for design space exploration of NoC architectures. Our experiments show that simulating large NoC topologies take hours to several days for completion. To speed up the simulations, it is necessary to investigate and optimize the hotspots in simulator source code. Among several simulators available, we choose Booksim2.0, as it is being extensively used in the NoC community. In this paper, we analyze the cache and memory system behaviour of Booksim2.0 to accurately monitor input dependent performance bottlenecks. Our measurements show that cache and memory usage patterns vary widely based on the input parameters given to Booksim2.0. Based on these measurements, the cache configuration having least misses has been identified. To further reduce the cache misses, we use software optimization techniques such as removal of unused functions, loop interchanging and replacing post-increment operator with pre-increment operator for non-primitive data types. The cache misses were reduced by 18.52%, 5.34% and 3.91% by employing above technology respectively. We also employ thread parallelization and vectorization to improve the overall performance of Booksim2.0. The OpenMP programming model and SIMD are used for parallelizing and vectorizing the more time-consuming portions of Booksim2.0. Speedups of 2.93x and 3.97x were observed for the Mesh topology with 30 × 30 network size by employing thread parallelization and vectorization respectively.

Keywords: cache behaviour, network-on-chip, performance profiling, vectorization

Procedia PDF Downloads 179

Authors: Niranjani Ruba Pandian

Abstract:

In today’s multicultural global business community, most of the businesses and industries are linked with various countries in which different nationalities have different roles and responsibilities throughout the project. The purpose of this research is to examine the cross-cultural challenges between Indian and French and the ways to minimize these challenges to manage effectively the cross-cultural aspect of human resources for the success of global business in an automotive industry. The conducted study utilized quantitative methodology to analyze the data on Indian and French employees' perceptions of 6 cultural dimensions such as power versus distance, individualism versus collectivism, masculinity versus femininity, uncertainty versus avoidance, pragmatic versus normative and indulgence versus restraint. Employees of 4 multinational companies filled in the questionnaire based on the 5-point Likert scale to present quantitative results. The data was analysed with the correlation and multiple regression statistical analyses. It was found that Indian and French have major gap in uncertainty versus avoidance followed by individualism versus collectivism. However, this article highlights the way to minimize these gaps by adopting certain sequenced methodologies.

Keywords: automotive industry, cross cultural challenges, globalization, global business

Procedia PDF Downloads 452

Authors: Sun Zhe, Ruggero Micheletto

Abstract:

The research of neural network is very important for the development of advanced next generation intelligent devices and the medical treatment. The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. For this reason, we made a model with only two coupled neurons and studied the influence of connection strength between them. To emulate the neuronal activity of realistic neurons, we prefer to use the Izhikevich neuron model. This model can simulate the neuron variables accurately and it’s simplicity is very suitable to implement on computers. In this research, the parameter ρ is used to estimate the correlation coefficient between spike train of two coupling neurons.We think the results is very important for figuring out the mechanism between synchronization of coupling neurons and synaptic plasticity. The result also presented the importance of the spike frequency adaptation in complex systems.

Keywords: neural networks, noise, stochastic processes, coupled neurons, correlation coefficient, synchronization, pacemaker, synaptic plasticity

Procedia PDF Downloads 266

Authors: Gete Umbrey, Saifur Rahman

Abstract:

Graphs are found to be most capable in computing, and its abstract structures have been applied in some specific computations and algorithms like in phase encoding controller, processor microcontroller, and synthesis of a CMOS switching network, etc. Being motivated by these works, we develop an independent approach to study semiring structures and various properties by defining the binary operations which in fact, seems analogous to an existing definition in some sense but with a different approach. This work emphasizes specifically on the construction of semigroup and semiring structures on the set of undirected graphs, and their properties are investigated therein. It is expected that the investigation done here may have some interesting applications in theoretical computer science, networking and decision making, and also on joining of two network systems.

Keywords: graphs, join and union of graphs, semiring, weighted graphs

Procedia PDF Downloads 130

Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

Abstract:

Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

Procedia PDF Downloads 276

Authors: Gopinath Ganapathy, Chellammal Surianarayanan

Abstract:

Services are growing rapidly and generally they are aggregated into a composite service to accomplish complex business processes. There may be several services that offer the same required function of a particular task in a composite service. Hence a choice has to be made for selecting suitable services from alternative functionally similar services. Quality of Service (QoS)plays as a discriminating factor in selecting which component services should be selected to satisfy the quality requirements of a user during service composition. There are two categories of approaches for QoS based service selection, namely global and local approaches. Global approaches are known to be Non-Polynomial (NP) hard in time and offer poor scalability in large scale composition. As an alternative to global methods, local selection methods which reduce the search space by breaking up the large/complex problem of selecting services for the workflow into independent sub problems of selecting services for individual tasks are coming up. In this paper, distributed architecture for selecting services based on QoS using local selection is presented with an overview of local selection methodology. The architecture describes the core components, namely, selection manager and QoS manager needed to implement the local approach and their functions. Selection manager consists of two components namely constraint decomposer which decomposes the given global or workflow level constraints in local or task level constraints and service selector which selects appropriate service for each task with maximum utility, satisfying the corresponding local constraints. QoS manager manages the QoS information at two levels namely, service class level and individual service level. The architecture serves as an implementation model for local selection.

Keywords: architecture of service selection, local method for service selection, QoS based service selection, approaches for QoS based service selection

Procedia PDF Downloads 413

Authors: Jui-Chen Huang

Abstract:

This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 198

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

Abstract:

This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 138

Authors: Ethan Nikookar, Yalda Boroushaki, Larissa Statsenko, Jorge Ochoa Paniagua

Abstract:

Given the serious impact that supply chain disruptions can have on a firm's bottom-line performance, both industry and academia are interested in supply chain resilience, a capability of the supply chain that enables it to cope with disruptions. To date, much of the research has focused on the antecedents of supply chain resilience. This line of research has suggested various firm-level capabilities that are associated with greater supply chain resilience. A consensus has emerged among researchers that supply chain flexibility holds the greatest potential to create resilience. Supply chain flexibility achieves resilience by creating readiness to respond to disruptions with little cost and time by means of reconfiguring supply chain resources to mitigate the impacts of the disruption. Decisions related to supply chain disruptions are made by supply chain managers; however, the role played by supply chain managers' reference networks has been overlooked in the supply chain resilience literature. This study aims to understand the impact of supply chain managers on their firms' supply chain resilience. Drawing on social capital theory and social network theory, this paper proposes a conceptual model to explore the role of supply chain managers in developing the resilience of supply chains. Our model posits that higher level of supply chain managers' embeddedness in their reference network is associated with increased resilience of their firms' supply chain. A reference network includes individuals from whom supply chain managers seek advice on supply chain related matters. The relationships between supply chain managers' embeddedness in reference network and supply chain resilience are mediated by supply chain flexibility.

Keywords: supply chain resilience, embeddedness, reference networks, social capitals

Procedia PDF Downloads 210

Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

Abstract:

This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine data set, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: artificial neural network, bees algorithm, feature selection, Holon

Procedia PDF Downloads 443

Authors: Prakash Chittoor

Abstract:

In the recent past, it is realised especially in third sector that employing social innovation is crucial for achieving viable and long lasting social transformation. In this context, education is one among many sectors that have opened up itself for such move where employing social innovation emerges as key for reaching out to the excluded sections who are often failed to get support from either policy or market interventions. In fact, education is being as a crucial factor for social development is well understood at both academic and policy level. In order to move forward to achieve better results, interventions from multiple sectors may be required as its reach cultivates capabilities and skill of the deprived in order to ensure both market and social participation in the long run. Despite state’s intervention, it is found that still millions of children are out of school due to lack of political will, lapses in policy implementation and neoliberal intervention of marketization. As a result, universalisation of elementary education became as an elusive goal to poor and marginalised sections where state obtain constant pressure by corporate sector to withdraw from education sector that led convince in providing quality education. At this juncture, the role of third sector organizations plays is quite remarkable. Especially, it has evolved as a key player in education sector to reach out to the poor and marginalised in the far-flung areas. These organisations work in resources constrain environment, yet, in order to achieve larger social impact they adopt various social innovations from time to time to reach out to the unreached. Their attempts not only limited to just approaching the unreached children but to retain them for long-time in the schooling system in order to ripe the results for their families and communities. There is a need to highlight various innovative ways adopted and practiced by the third sector organisations in India to achieve the elusive goal of universal access of primary education with quality. With this background, the paper primarily attempts to present an in-depth understanding about innovative practices employed by third sectors organisations like Isha Vidya through government schools adoption programme in India where it engages itself with government and build capabilities among the government teachers to promote state run schooling with quality and better infrastructure. Further, this paper assess whether such innovative attempts succeeded in to achieving universal quality education in the areas where it operates and draws implications for State policy.

Keywords: school education, third sector organisations, social innovation, market domination

Procedia PDF Downloads 248

Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

Abstract:

Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

Procedia PDF Downloads 487

Authors: Aena Iqbal

Abstract:

The lack of access to maternal and reproductive health in Pakistan poses a great threat to global public health. Obstetric issues, including vesicovaginal fistulas (VVF), are the most common in South Asian countries, leaving women in a more vulnerable state. Koohi Goth Women’s Hospital offers free VVF operations, which draws in women from all over Pakistan. Although reproductive health is being handled, mental health is often neglected in these scenarios. Using a series of questions inspired by the Warwick Edinburgh Model, this paper builds on the results from interviewing women who have received vesicovaginal fistula repair surgery on their mental health, a taboo topic in Pakistan.

Keywords: obstetrics, VVF, Pakistan, reproductive health

Procedia PDF Downloads 83

Authors: Hazel Pettifor, Charlie Wilson, David Mccollum, Oreane Edelenbosch

Abstract:

Vehicle purchase is a technology adoption decision that will strongly influence future energy and emission outcomes. Global integrated assessment models (IAMs) provide valuable insights into the medium and long terms effects of socio-economic development, technological change and climate policy. In this paper we present a unique and transparent approach for improving the behavioural representation of these models by incorporating social influence effects to more accurately represent consumer choice. This work draws together strong conceptual thinking and robust empirical evidence to introduce heterogeneous and interconnected consumers who vary in their aversion to new technologies. Focussing on vehicle choice, we conduct novel empirical research to parameterise consumer risk aversion and how this is shaped by social and cultural influences. We find robust evidence for social influence effects, and variation between countries as a function of cultural differences. We then formulate an approach to modelling social influence which is implementable in both simulation and optimisation-type models. We use two global integrated assessment models (IMAGE and MESSAGE) to analyse four scenarios that introduce social influence and cultural differences between regions. These scenarios allow us to explore the interactions between consumer preferences and social influence. We find that incorporating social influence effects into global models accelerates the early deployment of electric vehicles and stimulates more widespread deployment across adopter groups. Incorporating cultural variation leads to significant differences in deployment between culturally divergent regions such as the USA and China. Our analysis significantly extends the ability of global integrated assessment models to provide policy-relevant analysis grounded in real-world processes.

Keywords: behavioural realism, electric vehicles, social influence, vehicle choice

Procedia PDF Downloads 171

Authors: Pınar Yardımcı

Abstract:

This paper tries to answer to the questions whether or not trade openness cause economic growth and trade policy changes is good for Turkey as a developing country in global economy before and after 1980. We employ Johansen cointegration and Granger causality tests with error correction modelling based on vector autoregressive. Using WDI data from the pre-1980 and the post-1980, we find that trade openness and economic growth are cointegrated in the second term only. Also the results suggest a lack of long-run causality between our two variables. These findings may imply that trade policy of Turkey should concentrate more on extra complementary economic reforms.

Keywords: globalization, trade policy, economic growth, openness, cointegration, Turkey

Procedia PDF Downloads 342

Authors: Neil Erick Q. Madariaga, Noel B. Linsangan

Abstract:

Body Mass Index (BMI) is one of the different ways to monitor the health of a person. It is based on the height and weight of the person. This study aims to compute for the BMI using an Android tablet by obtaining the height of the person by using a camera and measuring the weight of the person by using a weighing scale or load cell. The height of the person was estimated by applying background subtraction to the image captured and applying different processes such as getting the vanishing point and applying Artificial Neural Network. The weight was measured by using Wheatstone bridge load cell configuration and sending the value to the computer by using Gizduino microcontroller and Bluetooth technology after the amplification using AD620 instrumentation amplifier. The application will process the images and read the measured values and show the BMI of the person. The study met all the objectives needed and further studies will be needed to improve the design project.

Keywords: body mass index, artificial neural network, vanishing point, bluetooth, wheatstone bridge load cell

Procedia PDF Downloads 307

Authors: Salman Naseer

Abstract:

One of the main challenges of operating a smart city (SC) is collecting the massive data generated from multiple data sources (DS) and to transmit them to the control units (CU) for further data processing and analysis. These ever-increasing data demands require not only more and more capacity of the transmission channels but also results in resource over-provision to meet the resilience requirements, thus the unavoidable waste because of the data fluctuations throughout the day. In addition, the high energy consumption (EC) and carbon discharges from these data transmissions posing serious issues to the environment we live in. Therefore, to overcome the issues of intensive EC and carbon emissions (CE) of massive data dissemination in Smart Cities, we propose an energy efficient and carbon reduction approach by utilizing the daily mobility of the existing vehicles as an alternative communications channel to accommodate the data dissemination in smart cities. To illustrate the effectiveness and efficiency of our approach, we take the Auckland City in New Zealand as an example, assuming massive data generated by various sources geographically scattered throughout the Auckland region to the control centres located in city centre. The numerical results show that our proposed approach can provide up to 5 times lower delay as transferring the large volume of data by utilizing the existing daily vehicles’ mobility than the conventional transmission network. Moreover, our proposed approach offers about 30% less EC and CE than that of conventional network transmission approach.

Keywords: smart city, delay tolerant network, infrastructure offloading, opportunistic network, vehicular mobility, energy consumption, carbon emission

Procedia PDF Downloads 126

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 68

Authors: Melake Kuflom

Abstract:

European power networks involve the use of multiple overhead transmission lines to construct a highly duplicated system that delivers reliable and stable electrical energy to the distribution level. The transmission line protection applied in the existing GB transmission network are normally independent unit differential and time stepped distance protection schemes, referred to as main-1 & main-2 respectively, with overcurrent protection as a backup. The increasing penetration of renewable energy sources, commonly referred as “weak sources,” into the power network resulted in the decline of fault level. Traditionally, the fault level of the GB transmission network has been strong; hence the fault current contribution is more than sufficient to ensure the correct operation of the protection schemes. However, numerous conventional coal and nuclear generators have been or about to shut down due to the societal requirement for CO2 emission reduction, and this has resulted in a reduction in the fault level on some transmission lines, and therefore an adaptive transmission line protection is required. Generally, greater utilization of renewable energy sources generated from wind or direct solar energy results in a reduction of CO2 carbon emission and can increase the system security and reliability but reduces the fault level, which has an adverse effect on protection. Consequently, the effectiveness of conventional protection schemes under low fault levels needs to be reviewed, particularly for future GB transmission network operating scenarios. The proposed paper will evaluate the transmission line challenges under high penetration of renewable energy sources andprovides alternative viable protection solutions based on the problem observed. The paper will consider the assessment ofrenewable energy sources (RES) based on a fully rated converter technology. The DIgSILENT Power Factory software tool will be used to model the network.

Keywords: fault level, protection schemes, relay settings, relay coordination, renewable energy sources

Procedia PDF Downloads 182

Authors: Muhammad Abdullah Arafat, Nahrin Nowrose

Abstract:

Wireless charging of electric vehicles is becoming more and more attractive as large amount of power can now be transferred to a reasonable distance using magnetic resonance coupling method. However, proper tuning of the compensation network is required to achieve maximum power transmission. Due to the variation of coil distance from the nominal value as a result of change in tire condition, change in weight or uneven road condition, the tuning of the compensation network has become challenging. In this paper, a tuning method has been described to determine the optimum values of the compensation network in order to maximize the average output power. The simulation results show that 5.2 percent increase in average output power is obtained for 10 percent variation in coupling coefficient using the optimum values without the need of additional space and electro-mechanical components. The proposed method is applicable to both static and dynamic charging of electric vehicles.

Keywords: coupling coefficient, electric vehicles, magnetic resonance coupling, tuning capacitor, wireless power transfer

Procedia PDF Downloads 170

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

Abstract:

Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

Procedia PDF Downloads 498