Search results for: augmented reality framework

Authors: Michael A. Ifarajimi

Abstract:

The transition from being a graduate teacher to a highly accomplished teacher has been widely portrayed in literature as challenging. Pre-service teachers are troubled with complex issues such as implementing, assessment, meeting prescribed learning outcomes, taking risks, supporting eco sustainability, etc. This list is not exhaustive as they are further complicated when the concerns extend beyond the classroom into the broader school setting and community. Meanwhile, the pre-service teacher education programme as is currently run in Nigeria, cannot adequately prepare newly trained teachers for the realities of classroom teaching. And there appears to be no formal structure in place for mentoring such teachers by the more seasoned teachers in schools. The central research question of the study, therefore, is which institutional framework can be distinguished for enactment in mentoring practices in teacher education? The study was conducted in five colleges of education in South-West Nigeria, and a sample of 1000 pre-service teachers on their final year practicum was randomly selected from the colleges of education. A pre-service teacher mentorship programme (PTMP) framework was designed and implemented, with a focus on the impact of transformative inquiry on the pre-service teacher support system. The study discovered a significant impact of mentoring on pre-service teacher’s professional transformation. The study concluded that institutionalizing mentorship through transformative inquiry is a means to sustainable teacher education, professional growth, and effective classroom practice. The study recommended that the government should enact policies that will promote mentoring in teacher education and establish a framework for the implementation of mentoring practices in the colleges of education in Nigeria.

Keywords: institutionalization, mentoring, pre-service teachers teacher education, transformative inquiry

Procedia PDF Downloads 129

Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

Procedia PDF Downloads 272

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 122

Authors: Sarbjit Singh

Abstract:

This framework development explored the status of GSCM in manufacturing SMEs and concluded that there was a significant gap w.r.t carbon emissions measurement in the supply chain activities. The measurement of carbon emissions within supply chains is important green initiative toward its reduction. The majority of the SMEs were facing the problem to quantify the green house gas emissions in its supply chain & to make it a low carbon supply chain or GSCM. Thus, the carbon management initiatives were amalgamated with the supply chain activities in order to measure and reduce the carbon emissions, confirming the GHG protocol scopes. Henceforth, it covers the development of carbon management software (CMS) tool to quantify carbon emissions for effective carbon management. This tool is cheap and easy to use for the industries for the management of their carbon emissions within the supply chain.

Keywords: w.r.t carbon emissions, carbon management software, supply chain management, Indian Industry

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Authors: Tim Wollert, Fabian Behrendt

Abstract:

Value Stream Management (VSM) is a widely used methodology in the context of Lean Management for improving end-to-end material and information flows from a supplier to a customer from a company’s perspective. Whereas the design principles, e.g. Pull, value-adding, customer-orientation and further ones are still valid against the background of an increasing digitalized and dynamic environment, the methodology itself for mapping a value stream is characterized as time- and resource-intensive due to the high degree of manual activities. The digitalization of processes in the context of Industry 4.0 enables new opportunities to reduce these manual efforts and make the VSM approach more agile. The paper at hand aims at providing a modular data and calculation framework, utilizing the available business data, provided by information and communication technologies for automizing the value stream mapping process with focus on the manufacturing process.

Keywords: lean management 4.0, value stream management (VSM) 4.0, dynamic value stream mapping, enterprise resource planning (ERP)

Procedia PDF Downloads 146

Authors: Modestus Queen

Abstract:

As we know, diplomatic languages carry the political ideology and cultural stance of the country. Knowing that China's diplomatic discourse is complicated and is heavily flavored with Chinese characteristics, one of the core goals of President Xi's administration is to properly tell the story of China. This cannot be done without proper translation or interpretation of major Chinese diplomatic concepts. Therefore, this research seeks to interpret the relevance of "Yi" as used in "Zhèngquè Yì Lì Guān". The author argues that it is not enough to translate a document but that it must be properly interpreted to portray it as political, economic, cultural and diplomatic relevant to the target audience, in this case, African people. The first finding in the current study indicates that literal translation is a bad strategy, especially in Chinese diplomatic discourses. The second finding indicates that "Yi" can be used as a framework to analyze Sino-Africa relations from economic, social and political perspectives, and the third finding indicates that "Yi" is the guiding principle of China's foreign policy towards Africa.

Keywords: Yi, justice, China-Africa, interpretation, diplomatic discourse, discourse reconstruction

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Authors: Taha Anjamrooz, Sareh Rajabi, Salwa Bheiry

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Selection between the available projects in bidding processes for the contractor is one of the essential areas to concentrate on. It is important for the contractor to choose the right projects within its portfolio during the tendering stage based on certain criteria. It should align the bidding process with its origination strategies and goals as a screening process to have the right portfolio pool to start with. Secondly, it should set the proper framework and use a suitable technique in order to optimize its selection process for concertation purpose and higher efforts during the tender stage with goals of success and winning. In this research paper, a two steps framework proposed to increase the efficiency of the contractor’s bidding process and the winning chance of getting the new projects awarded. In this framework, initially, all the projects pass through the first stage screening process, in which the portfolio basket will be evaluated and adjusted in accordance with the organization strategies to the reduced version of the portfolio pool, which is in line with organization activities. In the second stage, the contractor uses linear programming to optimize the portfolio pool based on available resources such as manpower, light equipment, heavy equipment, financial capability, return on investment, and success rate of winning the bid. Therefore, this optimization model will assist the contractor in utilizing its internal resource to its maximum and increase its winning chance for the new project considering past experience with clients, built-relation between two parties, and complexity in the exertion of the projects. The objective of this research will be to increase the contractor's winning chance in the bidding process based on the success rate and expected return on investment.

Keywords: bidding process, internal resources, optimization, contracting portfolio management

Procedia PDF Downloads 140

Authors: Raja Asad Zaheer, Aisha Tanveer, Hafza Mehreen Fatima

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Global Software Development (GSD) is becoming a common norm in software industry, despite of the fact that global distribution of the teams presents special issues for effective communication and coordination of the teams. Now trends are changing and project management for distributed teams is no longer in a limbo. GSD can be effectively established using agile and project managers can use different agile techniques/tools for solving the problems associated with distributed teams. Agile methodologies like scrum and XP have been successfully used with distributed teams. We have employed exploratory research method to analyze different recent studies related to challenges of GSD and their proposed solutions. In our study, we had deep insight in six commonly faced challenges: communication and coordination, temporal differences, cultural differences, knowledge sharing/group awareness, speed and communication tools. We have established that each of these challenges cannot be neglected for distributed teams of any kind. They are interlinked and as an aggregated whole can cause the failure of projects. In this paper we have focused on creating a scalable framework for detecting and overcoming these commonly faced challenges. In the proposed solution, our objective is to suggest agile techniques/tools relevant to a particular problem faced by the organizations related to the management of distributed teams. We focused mainly on scrum and XP techniques/tools because they are widely accepted and used in the industry. Our solution identifies the problem and suggests an appropriate technique/tool to help solve the problem based on globally shared knowledgebase. We can establish a cause and effect relationship using a fishbone diagram based on the inputs provided for issues commonly faced by organizations. Based on the identified cause, suitable tool is suggested, our framework suggests a suitable tool. Hence, a scalable, extensible, self-learning, intelligent framework proposed will help implement and assess GSD to achieve maximum out of it. Globally shared knowledgebase will help new organizations to easily adapt best practices set forth by the practicing organizations.

Keywords: agile project management, agile tools/techniques, distributed teams, global software development

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Authors: Maulana Ayoub Ali, Pradeep Kulshrestha

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Laws of any given secular state have a huge contribution in the growth of the Islamic banking system because the system uses conventional laws to govern its activities. Therefore, the former should be ready to accommodate the latter in order to make the Islamic banking system work properly without affecting the current conventional banking system and therefore without affecting its system. Islamic financial rules have been practiced since the birth of Islam. Following the recent world economic challenges in the financial sector, a quick rebirth of the contemporary Islamic ethical banking system took place. The coming of the Islamic banking system is due to various reasons including but not limited to the failure of the interest based economy in solving financial problems around the globe. Therefore, the Islamic banking system has been adopted as an alternative banking system in order to recover the highly damaged global financial sector. But the Islamic banking system has been facing a number of challenges which hinder its smooth operation in different parts of the world. It has not been the aim of this paper to discuss other challenges rather than the legal ones, but the same was partly discussed when it was justified that it was proper to do so. Generally, there are so many things which have been discovered in the course of writing this paper. The most important part is the issue of the regulatory and supervisory framework for the Islamic banking system in Tanzania and in other nations is considered to be a crucial part for the development of the Islamic banking industry. This paper analyses what has been observed in the study on that area and recommends for necessary actions to be taken on board in a bid to make Islamic banking system reach its climax of serving the larger community by providing ethical, equitable, affordable, interest-free and society cantered banking system around the globe.

Keywords: Islamic banking, interest free banking, ethical banking, legal framework

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Authors: Mohammed Saif Al-Saidi, John P. T. Mo

Abstract:

Modern engineering assets are complex and very high in value. They are expected to function for years to come, with ability to handle the change in technology and ageing modification. The aging of an engineering asset and continues increase of vendors and contractors numbers forces the asset operation management (or Owner) to design an asset system which can capture these changes. Furthermore, an accurate performance measurement and risk evaluation processes are highly needed. Therefore, this paper explores the nature of the asset management system performance evaluation for an engineering asset based on the System Support Engineering (SSE) principles. The research work explores the asset support system from a range of perspectives, interviewing managers from across a refinery organisation. The factors contributing to complexity of an asset management system are described in context which clusters them into several key areas. It is proposed that SSE framework may then be used as a tool for analysis and management of asset. The paper will conclude with discussion of potential application of the framework and opportunities for future research.

Keywords: asset management, performance, evaluation, modern engineering, System Support Engineering (SSE)

Procedia PDF Downloads 674

Authors: Avrokomi Zavitsanou, Spiros Papadopoulos, Theofanis Alexandridis

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This paper presents the research project ‘Colour & Travel’, which is co-funded by the European Union and national resources through the Operational Programme “Competitiveness, Entrepreneurship and Innovation” 2014-2020, under the Single RTDI State Aid Action "RESEARCH - CREATE - INNOVATE". The research project proposes the design of an innovative, playful framework for exploring a variety of travel destinations and creating personalised travel narratives, aiming to entertain, educate, and promote culture and tourism. Gamification of the cultural and touristic environment can enhance its experiential, multi-sensory aspects and broaden the perception of the traveler. The latter's involvement in creating and shaping his personal travel narrations and the possibility of sharing it with others can offer him an alternative, more binding way of getting acquainted with a place. In particular, the paper presents the design of an infrastructure: (a) for the development of interactive travel guides for mobile devices, where sites with specific points of interest will be recommended, with which the user can interact in playful ways and then create his personal travel narratives, (b) for the development of innovative games within virtual reality environment, where the interaction will be offered while the user is moving within the virtual environment; and (c) for an online application where the content will be offered through the browser and the modern 3D imaging technologies (WebGL). The technological products that will be developed within the proposed project can strengthen important sectors of economic and social life, such as trade, tourism, exploitation and promotion of the cultural environment, creative industries, etc. The final applications delivered at the end of the project will guarantee an improved level of service for visitors and will be a useful tool for content creators with increased adaptability, expansibility, and applicability in many regions of Greece and abroad. This paper aims to present the research project by referencing the state of the art and the methodological scheme, ending with a brief reflection on the expected outcome in terms of results.

Keywords: gamification, culture, tourism, AR, VR, applications

Procedia PDF Downloads 141

Authors: M. Naderi, N. Iyyer, K. Goel, N. Phan

Abstract:

A micromechanical analysis of the influence of fiber-matrix interface fracture properties on the transverse tensile response of fiber-reinforced composite is investigated. Augmented finite element method (AFEM) is used to provide high-fidelity damage initiation and propagation along the micromechanical analysis. Effects of fiber volume fraction and fiber shapes are also studies in representative volume elements (RVE) to capture the stochastic behavior of the composite under loading. In addition, defects and voids influence on the composite response are investigated in micromechanical analysis. The results reveal that the response of RVE with constant interface properties overestimates the composite transverse strength. It is also seen that the damage initiation and propagation locations are controlled by the distributions of fracture properties, fibers’ shapes, and defects.

Keywords: cohesive model, fracture, computational mechanics, micromechanics

Procedia PDF Downloads 287

Authors: Shuqi Zhang

Abstract:

Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

Procedia PDF Downloads 91

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

Procedia PDF Downloads 109

Authors: Lima Antony

Abstract:

In G. M. Hopkins’s poetics and aesthetics there is scope for a comparative study with Indian discourses on aesthetics, an area not adequately explored so far. This exploration will enrich the field of comparative study of diverse cultural expressions and their areas of similarity. A comparative study of aesthetic and religious experiences in diverse cultures will open up avenues for the discovery of similarities in self-experiences and their transcendence. Such explorations will reveal similar patterns in aesthetic and religious experiences. The present paper intends to prove this in the theories of Hopkins and Indian aesthetics. From the time of the Vedas Indian sages have believed that aesthetic enjoyment could develop into a spiritual realm. From the Natyasastra of Bharata, Indian aesthetics develops and reaches its culmination in later centuries into a consciousness of union with the mystery of the Ultimate Being, especially in Dhvanaāloka of Anandavardhana and Locana of Abhinavagupta. Dhvanyaloka elaborates the original ideas of rasa (mood or flavor) and dhvani (power of suggestion) in Indian literary theory and aesthetics. Hopkins was successful, like the ancient Indian alankarikas, in creating aesthetically superb patterns at various levels of sound and sense for which he coined the term ‘inscape’. So Hopkins’s aesthetic theory becomes suitable for transcultural comparative study with Indian aesthetics especially the dhvani theories of Anandavardhana and Abhinavagupta. Hopkins’s innovative approach to poetics and his selection of themes are quite suitable for analysis in the light of Indian literary theories. Indian philosophy views the ultimate reality called Brahman, as the 'soul,' or inner essence, of all reality. We see in Hopkins also a search for the essence of things and the chiming of their individuality with the Ultimate Being in multidimensional patterns of sound, sense and ecstatic experience. This search culminates in the realization of a synthesis of the individual self with the Ultimate Being. This is achieved through an act of surrender of the individuality of the self before the Supreme Being. Attempts to reconcile the immanent and transcendent aspects of the Ultimate Being can be traced in the Indian as well as Hopkins’s aesthetics which can contribute to greater understanding and harmony between cultures.

Keywords: Dhvani, Indian aesthetics, transcultural studies, Rasa

Procedia PDF Downloads 146

Authors: S. B. Q. Tran

Abstract:

Drop condensation is the phenomenon that the tiny drops form when the oversaturated vapour present in the environment condenses on a substrate and makes the droplet growth. Recently, this subject has received much attention due to its applications in many fields such as thin film growth, heat transfer, recovery of atmospheric water and polymer templating. In literature, many papers investigated theoretically and experimentally in macro droplet growth with the size of millimeter scale of radius. However few papers about nanodroplet condensation are found in the literature especially theoretical work. In order to understand the droplet growth in nanoscale, we perform the numerical simulation work to study nanodroplet growth. We investigate and discuss the role of the droplet shape and monomer diffusion on drop growth and their effect on growth law. The effect of droplet shape is studied by doing parametric studies of contact angle and disjoining pressure magnitude. Besides, the effect of pinning and de-pinning behaviours is also studied. We investigate the axisymmetric homogeneous growth of 10–100 nm single water nanodroplet on a substrate surface. The main mechanism of droplet growth is attributed to the accumulation of laterally diffusing water monomers, formed by the absorption of water vapour in the environment onto the substrate. Under assumptions of quasi-steady thermodynamic equilibrium, the nanodroplet evolves according to the augmented Young–Laplace equation. Using continuum theory, we model the dynamics of nanodroplet growth including the coupled effects of disjoining pressure, contact angle and monomer diffusion with the assumption of constant flux of water monomers at the far field. The simulation result is validated by comparing with the published experimental result. For the case of nanodroplet growth with constant contact angle, our numerical results show that the initial droplet growth is transient by monomer diffusion. When the flux at the far field is small, at the beginning, the droplet grows by the diffusion of initially available water monomers on the substrate and after that by the flux at the far field. In the steady late growth rate of droplet radius and droplet height follow a power law of 1/3, which is unaffected by the substrate disjoining pressure and contact angle. However, it is found that the droplet grows faster in radial direction than high direction when disjoining pressure and contact angle increase. The simulation also shows the information of computational domain effect in the transient growth period. When the computational domain size is larger, the mass coming in the free substrate domain is higher. So the mass coming in the droplet is also higher. The droplet grows and reaches the steady state faster. For the case of pinning and de-pinning droplet growth, the simulation shows that the disjoining pressure does not affect the droplet radius growth law 1/3 in steady state. However the disjoining pressure modifies the growth rate of the droplet height, which then follows a power law of 1/4. We demonstrate how spatial depletion of monomers could lead to a growth arrest of the nanodroplet, as observed experimentally.

Keywords: augmented young-laplace equation, contact angle, disjoining pressure, nanodroplet growth

Procedia PDF Downloads 269

Authors: Eng Rima Al-Awadhi, Abdul Jaleel Tharayil

Abstract:

In a project-centric organization like KOC, managing the knowledge of the project is of critical importance to the success of the project and the organization. However, due to the very nature and complexity involved, each project engagement generates a lot of 'learnings' that need to be factored into while new projects are initiated and thus avoid repeating the same mistake. But, many a time these learnings are localized and remains as ‘tacit knowledge’ leading to scope re-work, schedule overrun, adjustment orders, concession requests and claims. While KOC follows an asset based organization structure, with a multi-cultural and multi-ethnic workforce and larger chunk of the work is carried out through complex, long term project engagement, diffusion of ‘learnings’ across assets while dealing with the natural entropy of the organization is of great significance. Considering the relatively higher number of mega projects, it's important that the issues raised during the project life cycle are centrally harvested, analyzed and the ‘learnings’ from these issues are shared, absorbed and are in-turn utilized to enhance and refine the existing process and practices, leading to improve the project performance. One of the many factors contributing to the successful completion of a project on time is the reduction in the number of variations or concessions triggered during the project life cycle. The project process integrated knowledge sharing framework discusses the knowledge harvesting methodology adopted, the challenges faced, learnings acquired and its impact on project performance. The framework facilitates the proactive identification of issues that may have an impact on the overall quality of the project and improve performance.

Keywords: knowledge harvesting, project integrated knowledge sharing, performance improvement, knowledge management, lessons learn

Procedia PDF Downloads 393

Authors: Liu Lin Xin

Abstract:

With the increasing complexity of systems, log parsing and anomaly detection have become crucial for maintaining system stability. However, traditional methods often struggle with adaptability and accuracy, especially when dealing with rapidly evolving log content and unfamiliar domains. To address these challenges, this paper proposes approach that integrates Retrieval Augmented Generation (RAG) technology with Prompt Engineering for Large Language Models, applied specifically in LogPrompt. This approach enables dynamic log parsing and intelligent anomaly detection by combining real-time information retrieval with prompt optimization. The proposed method significantly enhances the adaptability of log analysis and improves the interpretability of results. Experimental results on several public datasets demonstrate the method's superior performance, particularly in scenarios lacking training data, where it significantly outperforms traditional methods. This paper introduces a novel technical pathway for log parsing and anomaly detection, showcasing the substantial theoretical value and practical potential.

Keywords: log parsing, anomaly detection, RAG, prompt engineering, LLMs

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Authors: Naiara de Almeida Rios

Abstract:

The environmental education, from Tbilisi, is signaled as an important instrument for conservation and environmental management. However, the social, economic, political and environmental aspects of each place require an environmental management that corresponds to the reality to which they are inserted, as well as environmental education practices. The city of Belém, the capital of the State of Pará, is one of the most important cities in the Amazon Region, and its vast water dimension requires that its watersheds take a careful look at their socio-environmental management. The Estrada Nova Hydrographic Basin is considered as one of the most critical river basins in the city due to flooding, lack of basic sanitation and degradation of water bodies. In this context, environmental education is understood as one of the necessary conditions to reduce environmental degradation. Environmental education presents itself as an instrument of social transformation and conservation of natural resources (especially water resources), where thinking about the sustainability of natural resources is moving towards dialogue on the importance of building an environmental awareness. The commitment that environmental education proposes covers all spheres of society, since the main objective of the same is the transformation of thought and attitudes from the understanding of reality. Therefore, to analyze how the government is managing the basin, as well as the environmental education practices developed in it, is fundamental, so that government can be charged with improvements for the population and for the natural environment. Therefore, the objective of this study is to analyze the influence of environmental education actions developed by local public authorities in the management of the Estrada Nova Hydrographic Basin, Belém/PA. For the accomplishment of this study, some methodological procedures will be used, like documentary analysis, bibliographical survey and fieldwork. If the multivariate statistical method is used to analyze the results obtained in the field. Unfortunately, public policies in the area of ​environmental education in Belém are still moving in short steps, since government interests have had very little dialogue with the socio-environmental problems that affect the Estrada Nova Hydrographic Basin. Both formal and informal environmental education has been poorly developed, hampering the continuous process proposed by water resources management.

Keywords: environmental education, environmental management, hydrographic basin, water resources

Procedia PDF Downloads 187

Authors: Ebtesam Dessouki, Yasaman Mousavi

Abstract:

Christopher Nolan’s Dunkirk (2017) is not a conventional war film. He invites the audience to see the war from within, from the characters’ experiences, through suspense and fear, with the help of talented sound designers and musicians such as Hans Zimmer for an extra dimension creating those feelings. This experience of being among the surviving soldiers makes room for an interpretation of this film using the concept of the Self and the Other. The Self is the soldiers and the audience who try to make sense of their reality given limited information about the enemy and their situation, and the Other is the faceless enemy. However, this film can be taken under an even more detailed analysis theorizing that the Other also exists on different occasions in the film. Overall, Nolan leaves a lot of cues for the audience to track the Other and sometimes breaks the rules for the Other.

Keywords: film, Dunkirk, other, self

Procedia PDF Downloads 69

Authors: Zeinab Papi

Abstract:

This study was aimed at analyzing the copyright laws of Iran, Australia, the U.S., and library portals, thereby providing a proposed framework for the copyright of library resources for the NLAI and other Iranian libraries while considering the current situation and the internal Iranian laws. This is an applied study falling in the category of qualitative approach research. Documentary analysis method and comparative method were used to resolve the problem and answer the questions of the research. The two National Library of Australia (NLA) and Library of Congress (LC), together with the NLAI formed the research community. In addition, the Iranian Law for the Protection of Authors, Composers and Artists Rights (1970); the Australian Copyright Act (1968), and the U.S. Copyright Law (1976) were purposefully selected as three main resources among other documents and resources. Findings revealed that the dimensions of fair and non-profit use, duration of copyright, license, and agreement, copyright policy, moral rights, economic rights, and infringement of copyright were the main dimensions that, along with 49 main components, formed the proposed framework for the copyright of information resources for the NLAI and other Iranian libraries. It should be acknowledged that there are some differences in different copyright fields between countries' laws, and each country takes into account its internal conditions to compile and revise the laws. By following the laws of other countries, it is possible to effectively improve and develop copyright laws. The researcher hopes that this research can have its effects in creating awareness and ability among librarians, formulating a copyright policy in Iranian libraries, and helping legislators in revising copyright laws regarding library exceptions and exemptions.

Keywords: copyright, library resources, National Library and Archives of the I.R. of Iran, National Library of Australia, Library of Congress, copyright law

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Authors: Zaidatol Akmaliah Lope Pihi, Suhaida Abd. Kadir, Keetanjaly Arivayagan

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Lately in educational organization, voluminous studies accentuate the momentous of leadership in mobilizing creativity. Creativity skill is seen as one of the important skills required for the 21st century leadership, which is also known as the tool for creative leader’s mind in engaging and stimulating ideas to execute outcomes. Hence, leaders should create an opportunity by involving every employee and stakeholders in schools to contribute their ideas towards developing creative solutions to enhance school productivity. The focal point of this article is to offer a conceptual framework on creative leadership practices among school leaders towards collaborative school culture. Intensive reviews of literature will be used in the fields of creative leadership and school culture with the aim to nurture leaders into better leaders and encourage collaborative school culture. The framework contributes a new shed on the implication of creative leadership practices and collaborative school culture. It also will contribute a new theory development and offered suggestions for follow up research.

Keywords: 21st century leadership, creative leadership, collaborative, school culture

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Authors: Maniam Kaliannan

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Studies on best practice or “bundles” of human resource management aims at providing a ‘universal solution’ to organizations yet critics challenge this view and place importance on the architecture of human resource processes in response to the dynamic needs of organizations. This paper identifies these best practices and explores how the applications of selected human resource management practices to a case study help solved their human resource problems. The case study includes insights on the problems faced; the approach taken to identify its root causes and explores how selected human resource management practices helped managed the overall predicament. The case study results supports the importance of aligning ‘bundles’ of practices with organizational architecture and ensuring that the architecture of human resource practices evolve with the changing needs of organizations. In addition, a framework based on the events of the case study is proposed to systematically manage their human resources

Keywords: bundles, best practices, human resource management, organizational architecture, framework

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Authors: R. R. Govind

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In the digital age, artificial intelligence (AI) is having a significant impact on the rapid changes that cities are experiencing. This study explores the profound impact of AI on urban morphology, especially with regard to promoting friendly design choices. It addresses a significant research gap by examining the real-world effects of integrating AI into urban design and management. The main objective is to outline a framework for integrating AI to transform urban settings. The study employs an urban design framework to effectively navigate complicated urban environments, emphasize the need for urban management, and provide efficient planning and design strategies. Taking Gangtok's informal settlements as a focal point, the study employs AI methodologies such as machine learning, predictive analytics, and generative AI to tackle issues of 'urban informality'. The insights garnered not only offer valuable perspectives but also unveil AI's transformative potential in addressing contemporary urban challenges.

Keywords: urban design, artificial intelligence, urban challenges, machine learning, urban informality

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Authors: Fahad Ahmed Qureshi

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There were abundant renowned financial markets in Pre-Islamic Arabs. Most of those were patterned and settled during pre-particularized sunshine. Those markets were classified either as vernacular markets helping the neighboring clans, or habitual markets that people sojourned to from all articulations of the Arabian Peninsula, such as Okaz near Mecca. Some of those markets had leading significance due to their geographical positions, such as Prime market of Eden, because of their entanglement in international trade i.e. with the markets of Sub-Continent, Abyssinia, Persia and China. Other markets such as Market of Yamamah annex its gist from being situated on the caravan crossroads. Islamic worldview and Islamic epistemology base of Financial Market’s realistic theory, pragmatic model and operative approach is moderately constrained in terms of its growth. The existent situation only parasol the form of accommodative-modification and splendid-methodologies, which due to depleted and decorous endeavor in explaining Islamic financial market theoretically. This is the demand of time that particular studies should be conduct to magnify the devours in developing theoretical framework for Islamic Financial Market.

Keywords: Islam, financial market, history, research, product development

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Authors: Rie Adachi

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In Japan, it is required to improve students’ English communicative proficiency and the Education Ministry will start English education for the third grade and upper from year 2020 on. Considering the problems with the educational system, Content and Language Integrated Learning (CLIL) is more appropriate to be employed in elementary schools rather than just introducing English lessons. Effective CLIL takes place in the 4Cs Framework, and different strategies are used in various activities, such as arts and crafts, bodily expression, singing, playing roles, etc. After a CLIL workshop for local teachers focused on the 4Cs, the writer conducted a survey of the 36 participants using a questionnaire and found that they did not know the word CLIL, but seemed to have an interest after attending the workshop. The writer concluded that researchers and practitioners need to spread awareness of the 4Cs framework, to apply CLIL into Japanese educational context, to provide CLIL teacher training program and so on, in order to practice CLIL in Japanese elementary schools and nurture students with a global mindset.

Keywords: CLIL, 4Cs, homeroom teachers, intercultural understanding

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Authors: Ibrahim M. S. Shnawa, Naeem R. R. Algebory

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The procedure for the assessment of the urinary mucosal cryoglobulin (UMCG) is being reviewed, testified and evaluated. The major features of UMCG are rather similar to that of serum cryoglobulin. Such evident similarities are forming the reality for the existence of the UMCG. There were seven characterizing criteria useable for the identification for UMCG. Upon matching them to the Irish criteria for serum cryoglobulin, some modifications are being proposed to the 16th standards that has been formulated and built as an Irish criterion. The existence of UMCG is being reported for the first time in human chronic infectious bacterial disease.

Keywords: urinary, mucosal, cryoglubulin, standard immunofixation

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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Authors: Hsiu-Hua Cheng, Chi-Wei Chen

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Lurking behaviour is common in information-seeking oriented communities. Transferring users with lurking behaviour to be contributors can assist virtual communities to obtain competitive advantages. Based on the ecological cognition framework, this study proposes a model to examine the antecedents of lurking behaviour in information-seeking oriented virtual communities. This study argues desire for emotional support, desire for information support, desire for performance-approach, desire for performance -avoidance, desire for mastery-approach, desire for mastery-avoidance, desire for ability trust, desire for benevolence trust, and desire for integrity trust effect on lurking behaviour. This study offers an approach to understanding the determinants of lurking behaviour in online contexts.

Keywords: lurking behaviour, the ecological cognition framework, Information-seeking oriented virtual communities, desire

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Authors: Sharifah Sumayyah Engku Alwi, Masrah Azrifah Azmi Murad

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The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking.

Keywords: information behavior, information seeking, online health information, technology acceptance model, the theory of planned behavior, UTAUT

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