Search results for: life-long learning for sustainable development
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 23662

Search results for: life-long learning for sustainable development

21442 Development of Scenarios for Sustainable Next Generation Nuclear System

Authors: Muhammad Minhaj Khan, Jaemin Lee, Suhong Lee, Jinyoung Chung, Johoo Whang

Abstract:

The Republic of Korea has been facing strong storage crisis from nuclear waste generation as At Reactor (AR) temporary storage sites are about to reach saturation. Since the country is densely populated with a rate of 491.78 persons per square kilometer, Construction of High-level waste repository will not be a feasible option. In order to tackle the storage waste generation problem which is increasing at a rate of 350 tHM/Yr. and 380 tHM/Yr. in case of 20 PWRs and 4 PHWRs respectively, the study strongly focuses on the advancement of current nuclear power plants to GEN-IV sustainable and ecological nuclear systems by burning TRUs (Pu, MAs). First, Calculations has made to estimate the generation of SNF including Pu and MA from PWR and PHWR NPPS by using the IAEA code Nuclear Fuel Cycle Simulation System (NFCSS) for the period of 2016, 2030 (including the saturation period of each site from 2024~2028), 2089 and 2109 as the number of NPPS will increase due to high import cost of non-nuclear energy sources. 2ndly, in order to produce environmentally sustainable nuclear energy systems, 4 scenarios to burnout the Plutonium and MAs are analyzed with the concentration on burning of MA only, MA and Pu together by utilizing SFR, LFR and KALIMER-600 burner reactor after recycling the spent oxide fuel from PWR through pyro processing technology developed by Korea Atomic Energy Research Institute (KAERI) which shows promising and sustainable future benefits by minimizing the HLW generation with regard to waste amount, decay heat, and activity. Finally, With the concentration on front and back end fuel cycles for open and closed fuel cycles of PWR and Pyro-SFR respectively, an overall assessment has been made which evaluates the quantitative as well as economical combativeness of SFR metallic fuel against PWR once through nuclear fuel cycle.

Keywords: GEN IV nuclear fuel cycle, nuclear waste, waste sustainability, transmutation

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21441 Predicting Radioactive Waste Glass Viscosity, Density and Dissolution with Machine Learning

Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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21440 Integrated Environmental Management System and Environmental Impact Assessment in Evaluation of Environmental Protective Action

Authors: Moustafa Osman

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The paper describes and analyses different good practice examples of protective levels, and initiatives actions (“framework conditions”) and encourages the uptake of environmental management systems (EMSs) to small and medium-sized enterprises (SMEs). Most of industries tend to take EMS as tools leading towards sustainability planning. The application of these tools has numerous environmental obligations that neither suggests decision nor recommends what a company should achieve ultimately. These set up clearly defined criteria to evaluate environmental protective action (EEPA) into sustainability indicators. The physical integration will evaluate how to incorporate traditional knowledge into baseline information, preparing impact prediction, and planning mitigation measures in monitoring conditions. Thereby efforts between the government, industry and community led protective action to concern with present needs for future generations, meeting the goal of sustainable development. The paper discusses how to set out distinct aspects of sustainable indicators and reflects inputs, outputs, and modes of impact on the environment.

Keywords: environmental management, sustainability, indicators, protective action

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21439 Cognitive and Metacognitive Space in the Task Design at Postgraduate Taught Level

Authors: Mei Lin, Lana Yj Liu, Thin Ngoc Pham

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Postgraduate taught (PGT) students’ learning strategies align with what the learning task constitutes and the environment that the task creates. Cognitively, they can discover new perspectives, challenge general assumptions, establish clear connections, and synthesise information. Metacognitively, their engagement is conducive to the development of planning, monitoring, and evaluating strategies. Given that there has been a lack of longitudinal insights into international PGT students’ experiences of the cognitive and metacognitive space created in the tasks, this paper presentation aims to fill the gaps by longitudinally exploring (1) the fundamentals of task designs to create cognitive and metacognitive space and (2) the opportunities and challenges of multicultural group discussions as a pedagogical approach for the implementation of cognitive and metacognitive space in the learning tasks. Data were collected from the two rounds of semi-structured interviews with 11 international PGT students in two programmes at a UK university -at the end of semester one and at the end of semester two. The findings show that the task designs, to create cognitive and metacognitive space, need to include four interconnected factors: clarity, relevance, motivation, and practicality. In addition, international PGT students perceived that they practised and developed their cognitive and metacognitive abilities while getting immersed in multicultural group discussions. The findings, from the learners’ point of view, make some pedagogy-related suggestions to the task designs at the master’s level, particularly how to engage students in learning during their transition into higher education in a different cultural setting.

Keywords: cognitive space, master students, metacognitive space, task design

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21438 The Design of Local Wisdom Learning for Providing Creative Activities for Juveniles with Exhibit Media: Suan-Oui Youth Center

Authors: Jong Boonpracha

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This paper studied the application of the design of local wisdom learning for providing creative activity for juveniles with exhibit media. The Suan-oui Youth Center has the objectives to design and develop exhibit media that encourage participation and learning of youths on local wisdom of Ratanakosin Island. The research was conducted in three stages: 1) to study the principle of local wisdom learning of cultural heritage at Ratanakosin Island 2) to study exhibit media that encouraged participation and creative activities of youth on local wisdom learning, and 3) to design a youth center that provide media exhibition for local wisdom learning. The research revealed the following: 34.6 percent of respondents wanted to apply local living wisdom in their career and for hobby. At least two kinds of exhibit media effectively provided creative activities for youths. A multi-purpose area, for example, with still pictures, visual symbols, and simulations would increase the level of youths’ interaction and participation.

Keywords: exhibit media, local wisdom, youth center, design

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21437 Biomass Carbon Credit Estimation for Sustainable Urban Planning and Micro-climate Assessment

Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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21436 A Pilot Study of Bangkok High School Students’ Satisfaction Towards Online Learning Platform During Covid-19 Pandemic

Authors: Aung Aung Kyi, Khin Khin Aye

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The mode of teaching and learning has been changed dramatically due to the Covid-19 pandemic that made schools close and students may have been away from the campus. However, many schools all over the countries are helping students to facilitate e-learning through online teaching and learning platform. Regarding this, Sarasas bilingual school in Bangkok conducted the high school students’ satisfaction survey since it is important for every school to improve its quality of education that must meet the students' need. For the good of the school's reputation, the purpose of the study is to examine the level of satisfaction that enhances the best services in the future. This study applied random sampling techniques and the data were collected using a self-administered survey. Descriptive analysis and independent sample t-tests were used to measure the importance of satisfaction components. The results showed G-11 (A) students were extremely satisfied with “Accessibility of course resources and materials through online platform” and “Ontime homework submission” while G-11 (B) students were extremely satisfied with “Teacher assisted with guiding my learning activities” and “Course teacher for this online course interacted with me in a timely fashion”. Additionally, they were also satisfied with a clear understanding of the teacher’s introduction during online learning. A significant difference in the satisfaction was observed between G-11 (A) and G-11 (B) students in terms of “A clear understanding on introduction was given by the teacher at the beginning of this online course”(P=0.03), “Teacher assisted with guiding my learning activities” (P=0.003), and “Comfortable surrounding during online learning” (P=0.02). With regard to gender, it has been seen that female high school students were extremely satisfied with the amount of course interaction with their teacher and her guidance with learning activities during online learning. By understanding the survey assessment, schools can improve their quality of education through the best digital educational platform that helps satisfy their students in the future.

Keywords: Bangkok high school students., covid-19 pandemic, online learning platform, satisfaction

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21435 Valorization of Waste and By-products for Protein Extraction and Functional Properties

Authors: Lorena Coelho, David Ramada, Catarina Nobre, Joaquim Gaião, Juliana Duarte

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The development of processes that allows the valorization of waste and by-products generated by industries is crucial to promote symbiotic relationships between different sectors and is mandatory to “close the loop” in the circular economy paradigm. In recent years, by-products and waste from agro-food and forestry sector have attracted attention due to their potential application and technical characteristics. The extraction of bio-based active compounds to be reused is in line with the circular bioeconomy concept trends, combining the use of renewable resources with the process’s circularity, aiming the waste reduction and encouraging reuse and recycling. Among different types of bio-based materials, which are being explored and can be extracted, proteins fractions are becoming an attractive new raw material. Within this context, BioTrace4Leather project, a collaboration between two Technological Centres – CeNTI and CTIC, and a company of Tanning and Finishing of Leather – Curtumes Aveneda, aims to develop innovative and biologically sustainable solutions for leather industry and accomplish the market circularity trends. Specifically, it aims to the valorisation of waste and by-products from the tannery industry through proteins extraction and the development of an innovative and biologically sustainable materials. The achieved results show that keratin, gelatine, and collagen fractions can be successfully extracted from hair and leather bovine waste. These products could be reintegrated into the industrial manufacturing process to attain innovative and functional textile and leather substrates. ACKNOWLEDGEMENT This work has been developed under BioTrace4Leather scope, a project co-funded by Operational Program for Competitiveness and Internationalization (COMPETE) of PORTUGAL2020, through the European Regional Development Fund (ERDF), under grant agreement Nº POCI-01-0247-FEDER-039867.

Keywords: leather by-products, circular economy, sustainability, protein fractions

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21434 The Impact of Artificial Intelligence on Human Rights Priciples and Obligations

Authors: Rady Farag Aziz Ibrahim

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The gap between Islamic terrorism and human rights has become an important issue in the fight against Islamic terrorism worldwide. This situation is repeated because terrorism and human rights are interconnected in such a way that when the former begins, the latter becomes subject to violence. This unknown relationship was recognized in the Vienna Declaration and Program of Action adopted at the International Conference on Human Rights held in Vienna on 25 June 1993, confirming that terrorist acts, in all their forms and manifestations, aim to destroy the rights of individuals. humanity to destroy. Therefore, Islamic terrorism is a violation of basic human rights. For this purpose, the first part of the article will focus on the relationship between terrorism and human rights and the synergy between these two concepts. The second part then explores the emerging concept of cyber threats and how they exist. Additionally, technology analysis will be conducted against threats based on human rights. This will be achieved through analysis of the concept of 'securitization' of human rights and by striking a balance between counter-terrorism measures and the protection of human rights at all costs. This article concludes with recommendations on how to balance terrorism and human rights today.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development

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21433 Assessing Urban Health Disparities in South Asia: A Comparative Study Using the Urban Health Index

Authors: Fiza Azam, Sahar Zia, Fatima Nazir Ali, Aysha Hanif

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Health is a fundamental human right, and a healthy population is essential for the prosperity and sustainable development of any country. This research is aligned with United Nations' Goal 3: Good Health and Well-being. It aims to assess and rank key health indicators across selected South Asian countries. The study focuses on urban areas in these nations, drawing on data from the World Bank’s primary collection of relevant indicators and specific health determinants outlined by the World Health Organization (WHO). These determinants include the physical environment, income and social status, education, social support networks, and personal behavior. To evaluate disparities in urban health across the region, the Urban Health Index (UHI) developed by Georgia State University, USA, is employed, followed by a mapping technique including visualization through a choropleth map to identify the pattern of spatial variations in our key variables, such as socioeconomic indicators across the region. This index serves as a comparative tool to rank health outcomes, where higher UHI values indicate better health conditions. The findings reveal notable disparities across South Asia. Afghanistan, with the lowest UHI score of 0.0423, ranks first, indicating the least favorable urban health conditions. Pakistan follows with a UHI score of 0.1190. Bangladesh and India rank third and fourth with UHI scores of 0.3099 and 0.3250, respectively. The Maldives and Sri Lanka rank fifth and sixth, with UHI scores of 0.3432 and 0.3495. Bhutan is ranked seventh with a score of 0.4750. Nepal, with a UHI score of 0.5012, ranks eighth, indicating the best urban health conditions among the countries studied. The findings of this research are crucial for addressing health disparities, improving living conditions, and enhancing social well-being in the region. These insights can inform policy measures aimed at reducing inequalities and promoting sustainable urban health in South Asia.

Keywords: urban health index, health disparities, sustainable development, South Asia, World Health Organization, United Nations, living conditions, public health

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21432 Sustaining Language Learning: A Case Study of Multilingual Writers' ePortfolios

Authors: Amy Hodges, Deanna Rasmussen, Sherry Ward

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This paper examines the use of ePortfolios in a two-course sequence for ESL (English as a Second Language) students at an international branch campus in Doha, Qatar. ePortfolios support the transfer of language learning, but few have examined the sustainability of that transfer across an ESL program. Drawing upon surveys and interviews with students, we analyze three case studies that complicate previous research on metacognition, language learning, and ePortfolios. Our findings have implications for those involved in ESL programs and assessment of student writing.

Keywords: TESOL, electronic portfolios, assessment, technology

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21431 Nanotechnology Innovations for the Sustainable Buildings of the Future

Authors: Ayşin Sev, Meltem Ezel

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Sustainability, being the urgent issue of our time, is closely related with the innovations in technology. Nanotechnology (NT), although not a new science, can be regarded relatively a new science for buildings with brand new materials and applications. This paper tends to give a research review of current and near future applications of nanotechnology (NT) for achieving high-performance and healthy buildings for a sustainable future. In the introduction, the driving forces for the sustainability of construction industry are explained. Then, the term NT is defined, and significance of innovations in NT for a sustainable construction industry is revealed. After presenting the application areas of NT and nanomaterials for buildings with a number of cases, challenges in the adoption of this technology are put forward, and finally the impacts of nanoparticles and nanomaterials on human health and environment are discussed.

Keywords: nanomaterial, self-healing concrete, self cleaning sensor, nanosensor, steel, wood, aerogel, flexible solar panel

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21430 Unseen Classes: The Paradigm Shift in Machine Learning

Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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21429 Role of Indigenous Women in Securing Sustainable Livelihoods in Western Himalayan Region, India

Authors: Haresh Sharma, Jaimini Luharia

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The ecology in the Western Himalayan region transforms with the change in altitude. This change is observed in terms of topography, species of flora and fauna and the quality of the soil. The current study focuses on women of indigenous communities of Pangi Valley, which is located in the state of Himachal Pradesh, India. The valley is bifurcated into three different areas –Saichu, Hudan Bhatori, and Sural Bhatori valleys. It is one of the most remote, rugged and difficult to access tribal regions of Chamba district. The altitude of the valley ranges from 2,000 m to 6,000 m above sea level. The Pangi valley is inhabited by ‘Pangwals’ and ‘Bhots’ tribes of the Himalayas who speak their local tribal language called’ Pangwali’. The valley is cut-off from the mainland due to heavy snow and lack of proper roads during peak winters. Due to difficult geographical location, the daily lives of the people are constantly challenged, and they are most of the times deprived of benefits targeted through government programs. However, the indigenous communities earn their livelihood through livestock and forest-based produce while some of them migrate to nearby places for better work. The current study involves snowball sampling methodology for data collection along with in-depth interviews of women members of Self-Help Groups and women farmers. The findings reveal that the lives of these indigenous communities largely depend on forest-based products. So, it creates all the more significance of enhancing, maintaining, and consuming natural resources sustainably. Under such circumstances, the women of the community play a significant role of guardians in conservation and protection of the forests. They are the custodians of traditional knowledge of environment conservation practices that have been followed for many years in the region. The present study also sought to establish a relationship between some of the development initiatives undertaken by the women in the valley that stimulate sustainable mountain economy and conservation practices. These initiatives include cultivation of products like hazelnut, ‘Gucchi’ rare quality mushroom, medicinal plants exclusively found in the region, thereby promoting long term sustainable conservation of agro-biodiversity of the Western Himalayan region. The measures taken by the community women are commendable as they ensure access and distribution of natural resources as well as manage them for future generations. Apart from this, the tribal women have actively formed Self-Help Groups promoting financial inclusion through various activities that augment ownership and accountability towards the overall development of the communities. But, the results also suggest that there’s not enough recognition given to women’s role in forests conservation practices due to several local socio-political reasons. There are not enough research studies done on communities of Pangi Valley due to inaccessibility created out of lack of proper roads and other resources. Also, there emerged a need to concretize indigenous and traditional knowledge of conservation practices followed by women in the community.

Keywords: forest conservation, indigenous community women, sustainable livelihoods, sustainable development, poverty alleviation, Western Himalayas

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21428 Geographical Information System and Multi-Criteria Based Approach to Locate Suitable Sites for Industries to Minimize Agriculture Land Use Changes in Bangladesh

Authors: Nazia Muhsin, Tofael Ahamed, Ryozo Noguchi, Tomohiro Takigawa

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One of the most challenging issues to achieve sustainable development on food security is land use changes. The crisis of lands for agricultural production mainly arises from the unplanned transformation of agricultural lands to infrastructure development i.e. urbanization and industrialization. Land use without sustainability assessment could have impact on the food security and environmental protections. Bangladesh, as the densely populated country with limited arable lands is now facing challenges to meet sustainable food security. Agricultural lands are using for economic growth by establishing industries. The industries are spreading from urban areas to the suburban areas and using the agricultural lands. To minimize the agricultural land losses for unplanned industrialization, compact economic zones should be find out in a scientific approach. Therefore, the purpose of the study was to find out suitable sites for industrial growth by land suitability analysis (LSA) by using Geographical Information System (GIS) and multi-criteria analysis (MCA). The goal of the study was to emphases both agricultural lands and industries for sustainable development in land use. The study also attempted to analysis the agricultural land use changes in a suburban area by statistical data of agricultural lands and primary data of the existing industries of the study place. The criteria were selected as proximity to major roads, and proximity to local roads, distant to rivers, waterbodies, settlements, flood-flow zones, agricultural lands for the LSA. The spatial dataset for the criteria were collected from the respective departments of Bangladesh. In addition, the elevation spatial dataset were used from the SRTM (Shuttle Radar Topography Mission) data source. The criteria were further analyzed with factors and constraints in ArcGIS®. Expert’s opinion were applied for weighting the criteria according to the analytical hierarchy process (AHP), a multi-criteria technique. The decision rule was set by using ‘weighted overlay’ tool to aggregate the factors and constraints with the weights of the criteria. The LSA found only 5% of land was most suitable for industrial sites and few compact lands for industrial zones. The developed LSA are expected to help policy makers of land use and urban developers to ensure the sustainability of land uses and agricultural production.

Keywords: AHP (analytical hierarchy process), GIS (geographic information system), LSA (land suitability analysis), MCA (multi-criteria analysis)

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21427 A Computerized Tool for Predicting Future Reading Abilities in Pre-Readers Children

Authors: Stephanie Ducrot, Marie Vernet, Eve Meiss, Yves Chaix

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Learning to read is a key topic of debate today, both in terms of its implications on school failure and illiteracy and regarding what are the best teaching methods to develop. It is estimated today that four to six percent of school-age children suffer from specific developmental disorders that impair learning. The findings from people with dyslexia and typically developing readers suggest that the problems children experience in learning to read are related to the preliteracy skills that they bring with them from kindergarten. Most tools available to professionals are designed for the evaluation of child language problems. In comparison, there are very few tools for assessing the relations between visual skills and the process of learning to read. Recent literature reports that visual-motor skills and visual-spatial attention in preschoolers are important predictors of reading development — the main goal of this study aimed at improving screening for future reading difficulties in preschool children. We used a prospective, longitudinal approach where oculomotor processes (assessed with the DiagLECT test) were measured in pre-readers, and the impact of these skills on future reading development was explored. The dialect test specifically measures the online time taken to name numbers arranged irregularly in horizontal rows (horizontal time, HT), and the time taken to name numbers arranged in vertical columns (vertical time, VT). A total of 131 preschoolers took part in this study. At Time 0 (kindergarten), the mean VT, HT, errors were recorded. One year later, at Time 1, the reading level of the same children was evaluated. Firstly, this study allowed us to provide normative data for a standardized evaluation of the oculomotor skills in 5- and 6-year-old children. The data also revealed that 25% of our sample of preschoolers showed oculomotor impairments (without any clinical complaints). Finally, the results of this study assessed the validity of the DiagLECT test for predicting reading outcomes; the better a child's oculomotor skills are, the better his/her reading abilities will be.

Keywords: vision, attention, oculomotor processes, reading, preschoolers

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21426 Development of an Automatic Computational Machine Learning Pipeline to Process Confocal Fluorescence Images for Virtual Cell Generation

Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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21425 Gaits Stability Analysis for a Pneumatic Quadruped Robot Using Reinforcement Learning

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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21424 Future Education: Changing Paradigms

Authors: Girish Choudhary

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Education is in a state of flux. Not only one need to acquire skills in order to cope with a fast changing global world, an explosive growth in technology, on the other hand is providing a new wave of teaching tools - computer aided video instruction, hypermedia, multimedia, CD-ROMs, Internet connections, and collaborative software environments. The emerging technology incorporates the group qualities of interactive, classroom-based learning while providing individual students the flexibility to participate in an educational programme at their own time and place. The technology facilitating self learning also seems to provide a cost effective solution to the dilemma of delivering education to masses. Online education is a unique learning domain that provides for many to many communications as well. The computer conferencing software defines the boundaries of the virtual classroom. The changing paradigm provides access of instruction to a large proportion of society, promises a qualitative change in the quality of learning and echoes a new way of thinking in educational theory that promotes active learning and open new learning approaches. Putting it to practice is challenging and may fundamentally alter the nature of educational institutions. The subsequent part of paper addresses such questions viz. 'Do we need to radically re-engineer the curriculum and foster an alternate set of skills in students?' in the onward journey.

Keywords: on-line education, self learning, energy and power engineering, future education

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21423 Formation of Science Literations Based on Indigenous Science Mbaru Niang Manggarai

Authors: Yuliana Wahyu, Ambros Leonangung Edu

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The learning praxis that is proposed by 2013 Curriculum (K-13) is no longer school-oriented as a supply-driven, but now a demand-driven provider. This vision is connected with Jokowi-Kalla Nawacita program to create a competitive nation in the global era. Competition is a social fact that must be faced. Therefore the curriculum will design a process to be the innovators and entrepreneurs.To get this goal, K-13 implements the character education. This aims at creating the innovators and entrepreneurs from an early age (primary school). One part of strengthening it is literacy formations (reading, numeracy, science, ICT, finance, and culture). Thus, science literacy is an integral part of character education. The above outputs are only formed through the innovative process through intra-curricular (blended learning), co-curriculer (hands-on learning) and extra-curricular (personalized learning). Unlike the curriculums before that child cram with the theories dominating the intellectual process, new breakthroughs make natural, social, and cultural phenomena as learning sources. For example, Science in primary schoolsplaceBiology as the platform. And Science places natural, social, and cultural phenomena as a learning field so that students can learn, discover, solve concrete problems, and the prospects of development and application in their everyday lives. Science education not only learns about facts collection or natural phenomena but also methods and scientific attitudes. In turn, Science will form the science literacy. Science literacy have critical, creative, logical, and initiative competences in responding to the issues of culture, science and technology. This is linked with science nature which includes hands-on and minds-on. To sustain the effectiveness of science learning, K-13 opens a new way of viewing a contextual learning model in which facts or natural phenomena are drawn closer to the child's learning environment to be studied and analyzed scientifically. Thus, the topic of elementary science discussion is the practical and contextual things that students encounter. This research is about to contextualize Science in primary schools at Manggarai, NTT, by placing local wisdom as a learning source and media to form the science literacy. Explicitly, this study discovers the concept of science and mathematics in Mbaru Niang. Mbaru Niang is a forgotten potentials of the centralistic-theoretical mainstream curriculum so far. In fact, the traditional Manggarai community stores and inherits much of the science-mathematical indigenous sciences. In the traditional house structures are full of science and mathematics knowledge. Every details have style, sound and mathematical symbols. Learning this, students are able to collaborate and synergize the content and learning resources in student learning activities. This is constructivist contextual learning that will be applied in meaningful learning. Meaningful learning allows students to learn by doing. Students then connect topics to the context, and science literacy is constructed from their factual experiences. The research location will be conducted in Manggarai through observation, interview, and literature study.

Keywords: indigenous science, Mbaru Niang, science literacy, science

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21422 Deep Reinforcement Learning with Leonard-Ornstein Processes Based Recommender System

Authors: Khalil Bachiri, Ali Yahyaouy, Nicoleta Rogovschi

Abstract:

Improved user experience is a goal of contemporary recommender systems. Recommender systems are starting to incorporate reinforcement learning since it easily satisfies this goal of increasing a user’s reward every session. In this paper, we examine the most effective Reinforcement Learning agent tactics on the Movielens (1M) dataset, balancing precision and a variety of recommendations. The absence of variability in final predictions makes simplistic techniques, although able to optimize ranking quality criteria, worthless for consumers of the recommendation system. Utilizing the stochasticity of Leonard-Ornstein processes, our suggested strategy encourages the agent to investigate its surroundings. Research demonstrates that raising the NDCG (Discounted Cumulative Gain) and HR (HitRate) criterion without lowering the Ornstein-Uhlenbeck process drift coefficient enhances the diversity of suggestions.

Keywords: recommender systems, reinforcement learning, deep learning, DDPG, Leonard-Ornstein process

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21421 A Digital Environment for Developing Mathematical Abilities in Children with Autism Spectrum Disorder

Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

Abstract:

Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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21420 Implementing Universal Design for Learning in Social Work Education

Authors: Kaycee Bills

Abstract:

Action research is a method of inquiry useful in solving social problems in social work. This study seeks to address a significant problem: higher education’s use of traditional instructional methods in social work education. Ineffective techniques, such as lecturing, fail to account for students’ variable learning needs. In contrast to traditional pedagogy, universal design for learning (UDL) is a robust framework that '[improves] and [optimizes] teaching and learning for all people' (CAST, 2018), including students with disabilities. For this project, the research team interviewed the UDL and Accessibility Specialist at their institution for two reasons: (1) to learn how to implement UDL practices in their classrooms, and in turn, (2) to motivate other faculty members at their institution to consider enacting UDL principles. A thematic analysis of the interview’s transcript reveals themes relevant to practicing UDL. Implications for future practice, as well as the researcher’s reflections on the research process, are shared in the discussion section.

Keywords: disabilities, higher education, inclusive education, universal design for learning

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21419 Architectural Approaches to a Sustainable Community with Floating Housing Units Adapting to Climate Change and Sea Level Rise in Vietnam

Authors: Nguyen Thi Thu Trang

Abstract:

Climate change and sea level rise is one of the greatest challenges facing human beings in the 21st century. Because of sea level rise, several low-lying coastal areas around the globe are at risk of being completely submerged, disappearing under water. Particularly in Viet Nam, the rise in sea level is predicted to result in more frequent and even permanently inundated coastal plains. As a result, land reserving fund of coastal cities is going to be narrowed in near future, while construction ground is becoming increasingly limited due to a rapid growth in population. Faced with this reality, the solutions are being discussed not only in tradition view such as accommodation is raised or moved to higher areas, or “living with the water”, but also forwards to “living on the water”. Therefore, the concept of a sustainable floating community with floating houses based on the precious value of long term historical tradition of water dwellings in Viet Nam would be a sustainable solution for adaptation of climate change and sea level rise in the coastal areas. The sustainable floating community is comprised of sustainability in four components: architecture, environment, socio-economic and living quality. This research paper is focused on sustainability in architectural component of floating community. Through detailed architectural analysis of current floating houses and floating communities in Viet Nam, this research not only accumulates precious values of traditional architecture that need to be preserved and developed in the proposed concept, but also illustrates its weaknesses that need to address for optimal design of the future sustainable floating communities. Based on these studies the research would provide guidelines with appropriate architectural solutions for the concept of sustainable floating community with floating housing units that are adapted to climate change and sea level rise in Viet Nam.

Keywords: guidelines, sustainable floating community, floating houses, Vietnam

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21418 An Innovative Approach to Improve Skills of Students in Qatar University Spending in Virtual Class though LMS

Authors: Mohammad Shahid Jamil

Abstract:

In this study we have investigated students’ learning and satisfaction in one of the course offered in the Foundation Program at Qatar University. We implied innovative teaching methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which can be used to further improve the teaching methodology. To make sure the full use of technology in Foundation Program at Qatar University has started implementing new ways of teaching Math course by using Blackboard as an innovative interactive tool to support standard teaching such as Discussion board, Virtual class, and Study plan in My Math Lab “MML”. In MML Study Plan is designed in such a way that the student can improve their skills wherever they face difficulties with in their Homework, Quiz or Test. Discussion board and Virtual Class are collaborative learning tools encourages students to engage outside of class time. These tools are useful to share students’ knowledge and learning experiences, promote independent and active learning and they helps students to improve their critical thinking skills through the learning process.

Keywords: blackboard, discussion board, critical thinking, active learning, independent learning, problem solving

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21417 The Use of Artificial Intelligence in the Context of a Space Traffic Management System: Legal Aspects

Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

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21416 A Comparative Analysis Approach Based on Fuzzy AHP, TOPSIS and PROMETHEE for the Selection Problem of GSCM Solutions

Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

Procedia PDF Downloads 163
21415 Sustainable Opportunities of Educational Facilities Provided to the Imprisoned Women's Children in Karachi's Central Jail

Authors: Waqar Un Nisa Faizi, Anila Fatima Shakil, Wilayat Bibi, Sajjad Hayat Akhtar

Abstract:

This study will discuss the sustainable opportunities regarding educational facilities provided to the children of imprisoned women in the different jails of Pakistan particularly in Central Jail of Karachi. It will also discuss the importance of educational facilities which are required for the mental and personal growth of the children as education has the capability to enhance the general knowledge and the personality of any individual. Education is extremely important for the children whether they live in a society or in prison, because they are the future of any country. Therefore, the point of discussion in this paper will be the provision of educational facilities and sustainable opportunities regarding these facilities to the children of imprisoned women in Karachi and other countries of the world.

Keywords: imprisoned, educational facilities, criminal activities, positive atmosphere

Procedia PDF Downloads 343
21414 The Roles of Organizational Culture, Participative Leadership, Employee Satisfaction and Work Motivation Towards Organizational Capabilities

Authors: Inezia Aurelia, Soebowo Musa

Abstract:

Many firms still fail to develop organizational agility. There are more than 40% of organizations think that they are low/not agile in facing market change. Organizational culture plays an important role in developing the organizations to be adaptive in order to manage the VUCA effectively. This study examines the relationships of organizational culture towards participative leadership, employee satisfaction, employee work motivation, organizational learning, and absorptive capacity in developing organizational agility in managing the VUCA environment. 263 employees located from international chemical-based company offices across the globe who have worked for more than three years were the respondents in this study. This study showed that organizational clan culture promotes the development of participative leadership, which it has an empowering effect on people in the organization resulting in employee satisfaction. The study also confirms the role of organizational culture in creating organizational behavior within the organization that fosters organizational learning, absorptive capacity, and organizational agility, while the study also found that the relationship between participative leadership and employee work motivation is not significant.

Keywords: absorptive capacity, employee satisfaction, employee work motivation, organizational agility, organizational culture, organizational learning, participative leadership

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21413 Improved Performance in Content-Based Image Retrieval Using Machine Learning Approach

Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

Procedia PDF Downloads 181