Search results for: domain knowledge
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8736

Search results for: domain knowledge

6366 Traditional Wisdom of Indigenous Vernacular Architecture as Tool for Climate Resilience Among PVTG Indigenous Communities in Jharkhand, India

Authors: Ankush, Harshit Sosan Lakra, Rachita Kuthial

Abstract:

Climate change poses significant challenges to vulnerable communities, particularly indigenous populations in ecologically sensitive regions. Jharkhand, located in the heart of India, is home to several indigenous communities, including the Particularly Vulnerable Tribal Groups (PVTGs). The Indigenous architecture of the region functions as a significant reservoir of climate adaptation wisdom. It explores the architectural analysis encompassing the construction materials, construction techniques, design principles, climate responsiveness, cultural relevance, adaptation, integration with the environment and traditional wisdom that has evolved through generations, rooted in cultural and socioeconomic traditions, and has allowed these communities to thrive in a variety of climatic zones, including hot and dry, humid, and hilly terrains to withstand the test of time. Despite their historical resilience to adverse climatic conditions, PVTG tribal communities face new and amplified challenges due to the accelerating pace of climate change. There is a significant research void that exists in assimilating their traditional practices and local wisdom into contemporary climate resilience initiatives. Most of the studies place emphasis on technologically advanced solutions, often ignoring the invaluable Indigenous Local knowledge that can complement and enhance these efforts. This research gap highlights the need to bridge the disconnect between indigenous knowledge and contemporary climate adaptation strategies. The study aims to explore and leverage indigenous knowledge of vernacular architecture as a strategic tool for enhancing climatic resilience among PVTGs of the region. The first objective is to understand the traditional wisdom of vernacular architecture by analyzing and documenting distinct architectural practices and cultural significance of PVTG communities, emphasizing construction techniques, materials and spatial planning. The second objective is to develop culturally sensitive climatic resilience strategies based on findings of vernacular architecture by employing a multidisciplinary research approach that encompasses ethnographic fieldwork climate data assessment considering multiple variables such as temperature variations, precipitation patterns, extreme weather events and climate change reports. This will be a tailor-made solution integrating indigenous knowledge with modern technology and sustainable practices. With the involvement of indigenous communities in the process, the research aims to ensure that the developed strategies are practical, culturally appropriate, and accepted. To foster long-term resilience against the global issue of climate change, we can bridge the gap between present needs and future aspirations with Traditional wisdom, offering sustainable solutions that will empower PVTG communities. Moreover, the study emphasizes the significance of preserving and reviving traditional Architectural wisdom for enhancing climatic resilience. It also highlights the need for cooperative endeavors of communities, stakeholders, policymakers, and researchers to encourage integrating traditional Knowledge into Modern sustainable design methods. Through these efforts, this research will contribute not only to the well-being of PVTG communities but also to the broader global effort to build a more resilient and sustainable future. Also, the Indigenous communities like PVTG in the state of Jharkhand can achieve climatic resilience while respecting and safeguarding the cultural heritage and peculiar characteristics of its native population.

Keywords: vernacular architecture, climate change, resilience, PVTGs, Jharkhand, indigenous people, India

Procedia PDF Downloads 65
6365 Using the Technological, Pedagogical, and Content Knowledge (TPACK) Model to Address College Instructors Weaknesses in Integration of Technology in Their Current Area Curricula

Authors: Junior George Martin

Abstract:

The purpose of this study was to explore college instructors’ integration of technology in their content area curriculum. The instructors indicated that they were in need of additional training to successfully integrate technology in their subject areas. The findings point to the implementation of a proposed the Technological, Pedagogical, and Content Knowledge (TPACK) model professional development workshop to satisfactorily address the weaknesses of the instructors in technology integration. The professional development workshop is proposed as a rational solution to adequately address the instructors’ inability to the successful integration of technology in their subject area in an effort to improve their pedagogy. The intense workshop would last for 5 days and will be designed to provide instructors with training in areas such as a use of technology applications and tools, and using modern methodologies to improve technology integration. Exposing the instructors to the specific areas identified will address the weaknesses they demonstrated during the study. Professional development is deemed the most appropriate intervention based on the opportunities it provides the instructors to access hands-on training to overcome their weaknesses. The purpose of the TPACK professional development workshop will be to improve the competence of the instructors so that they are adequately prepared to integrate technology successfully in their curricula. At the end of the period training, the instructors are expected to adopt strategies that will have a positive impact on the learning experiences of the students.

Keywords: higher education, modern technology tools, professional development, technology integration

Procedia PDF Downloads 300
6364 Exploiting Fast Independent Component Analysis Based Algorithm for Equalization of Impaired Baseband Received Signal

Authors: Muhammad Umair, Syed Qasim Gilani

Abstract:

A technique using Independent Component Analysis (ICA) for blind receiver signal processing is investigated. The problem of the receiver signal processing is viewed as of signal equalization and implementation imperfections compensation. Based on this, a model similar to a general ICA problem is developed for the received signal. Then, the use of ICA technique for blind signal equalization in the time domain is presented. The equalization is regarded as a signal separation problem, since the desired signal is separated from interference terms. This problem is addressed in the paper by over-sampling of the received signal. By using ICA for equalization, besides channel equalization, other transmission imperfections such as Direct current (DC) bias offset, carrier phase and In phase Quadrature phase imbalance will also be corrected. Simulation results for a system using 16-Quadraure Amplitude Modulation(QAM) are presented to show the performance of the proposed scheme.

Keywords: blind equalization, blind signal separation, equalization, independent component analysis, transmission impairments, QAM receiver

Procedia PDF Downloads 203
6363 Fuzzy Optimization Multi-Objective Clustering Ensemble Model for Multi-Source Data Analysis

Authors: C. B. Le, V. N. Pham

Abstract:

In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

Procedia PDF Downloads 169
6362 Effect of Farmers Field School on Vegetables Production in District Peshawar Khyber Pakhtunkhwa-Pakistan

Authors: Muhammad Zafarullah Khan, Sumeera Abbasi

Abstract:

The Farmers Field School (FFS) aims at benefiting poor farmers by improving their knowledge of existing agricultural technologies and integrated crop management to become independent and confident in their decision. The study on effect of farmer’s field school on vegetables production before and after FFS implementation in district Peshawar in four selected villages on each crop in 2011 was conducted from 80 farmers. The results were compared by using paired t-test. It was observed that 80% of the respondents were satisfied with FFS approach as there was a significant increase in vegetable production. The seed rate of tomato and cucumber decreased from 0.185kg/kanal to 0.1 kg/ kanal and 0.120kg/kanal to 0.01kg/kanal while production of tomato and cucumber were increased from 8158.75kgs/kanal to 1030.25kgs/kanal and 3230kgs/kanal to 5340kgs/kanal, respectively after the activities of FFS. FFS brought a positive effect on vegetable production and technology adoption improving their income, skills and knowledge ultimately lead farmers towards empowerment. The input cost including seed, crop management, FYM, and weedicides for tomato were reduced by Rs.28, Rs. 3170 and Rs.658 and cucumber reduced by Rs.35, Rs.570 and Rs.430. Only fertilizers cost was increased by Rs. 2200 in case of tomato and 465 in case of cucumber. FFS facilitator and coordinator should be more skilled and practical oriented to facilitate poor farmers. In light of the above study, more FFS should be planned so that the more farmers should be benefited.

Keywords: effect, farmer field school, vegetables production, integrated crop management

Procedia PDF Downloads 383
6361 Machine Learning-Enabled Classification of Climbing Using Small Data

Authors: Nicholas Milburn, Yu Liang, Dalei Wu

Abstract:

Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

Procedia PDF Downloads 131
6360 Digital Literacy, Assessment and Higher Education

Authors: James Moir

Abstract:

Recent evidence suggests that academic staff face difficulties in applying new technologies as a means of assessing higher order assessment outcomes such as critical thinking, problem solving and creativity. Although higher education institutional mission statements and course unit outlines purport the value of these higher order skills there is still some question about how well academics are equipped to design curricula and, in particular, assessment strategies accordingly. Despite a rhetoric avowing the benefits of these higher order skills, it has been suggested that academics set assessment tasks up in such a way as to inadvertently lead students on the path towards lower order outcomes. This is a controversial claim, and one that this papers seeks to explore and critique in terms of challenging the conceptual basis of assessing higher order skills through new technologies. It is argued that the use of digital media in higher education is leading to a focus on students’ ability to use and manipulate of these products as an index of their flexibility and adaptability to the demands of the knowledge economy. This focus mirrors market flexibility and encourages programmes and courses of study to be rhetorically packaged as such. Curricular content has become a means to procure more or less elaborate aggregates of attributes. Higher education is now charged with producing graduates who are entrepreneurial and creative in order to drive forward economic sustainability. It is argued that critical independent learning can take place through the democratisation afforded by cultural and knowledge digitization and that assessment needs to acknowledge the changing relations between audience and author, expert and amateur, creator and consumer.

Keywords: higher education, curriculum, new technologies, assessment, higher order skills

Procedia PDF Downloads 362
6359 Investigation of Verbal Feedback and Learning Process for Oral Presentation

Authors: Nattawadee Sinpattanawong

Abstract:

Oral presentation has been used mostly in business communication. The business presentation is carrying out through an audio and visual presentation material such as statistical documents, projectors, etc. Common examples of business presentation are intra-organization and sales presentations. The study aims at investigating functions, strategies and contents of assessors’ verbal feedback on presenters’ oral presentations and exploring presenters’ learning process and specific views and expectations concerning assessors’ verbal feedback related to the delivery of the oral presentation. This study is designed as a descriptive qualitative research; four master students and one teacher in English for Business and Industry Presentation Techniques class of public university will be selected. The researcher hopes that any understanding how assessors’ verbal feedback on oral presentations and learning process may illuminate issues for other people. The data from this research may help to expand and facilitate the readers’ understanding of assessors’ verbal feedback on oral presentations and learning process in their own situations. The research instruments include an audio recorder, video recorder and an interview. The students will be interviewing in order to ask for their views and expectations concerning assessors’ verbal feedback related to the delivery of the oral presentation. After finishing data collection, the data will be analyzed and transcribed. The findings of this study are significant because it can provide presenters knowledge to enhance their learning process and provide teachers knowledge about providing verbal feedback on student’s oral presentations on a business context.

Keywords: business context, learning process, oral presentation, verbal feedback

Procedia PDF Downloads 180
6358 Sustainable Management Practices in Facilities Management for Housing Estates: Literature Review - Case of South Africa

Authors: Chidozie Celestine Uzoigwe, Thabelo Ramantswana

Abstract:

Purpose: The purpose of the paper is to review the current state of knowledge in Sustainable Management (SM) practices in Facilities Management (FM) for housing estates with a view to identifying gaps and drawbacks in the existing body of knowledge. Integrating SM practices in housing estates is understood and applied in some developed countries, but little is known about the concept by practitioners in developing nations like South Africa. Indeed, South African housing studies and policy documents emphasize the significance of sustainability practices in housing estates, but regrettably, it still remains in unsustainable housing for decades. Method: This is done through a comprehensive literature review in combination with the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines and the Recursive Content Abstraction (RCA) analytical approach. Finding: Findings revealed there are significant challenges to the integration of SM practices in FM for housing estates in South Africa, such as lack of understanding and expertise by practitioners, absence of support from top-level management, lack of appropriate sustainability management framework as well as people management. The review further suggests the need for an enabler to guide practitioners in integrating the SM concept in housing estates. Originality: Integrating SM principles in facilities management for housing estates are required to eliminate the detrimental impact the built environment exerts on the well-being of individuals and organizations. Thus, the study underlines the need for an enabler that will facilitate practitioners embedding sustainable management measures in the management of housing estates in South Africa.

Keywords: facilities management, housing estates, sustainable facilities management, sustainable management, south africa

Procedia PDF Downloads 73
6357 The Efficacy of Video Education to Improve Treatment or Illness-Related Knowledge in Patients with a Long-Term Physical Health Condition: A Systematic Review

Authors: Megan Glyde, Louise Dye, David Keane, Ed Sutherland

Abstract:

Background: Typically patient education is provided either verbally, in the form of written material, or with a multimedia-based tool such as videos, CD-ROMs, DVDs, or via the internet. By providing patients with effective educational tools, this can help to meet their information needs and subsequently empower these patients and allow them to participate within medical-decision making. Video education may have some distinct advantages compared to other modalities. For instance, whilst eHealth is emerging as a promising modality of patient education, an individual’s ability to access, read, and navigate through websites or online modules varies dramatically in relation to health literacy levels. Literacy levels may also limit patients’ ability to understand written education, whereas video education can be watched passively by patients and does not require high literacy skills. Other benefits of video education include that the same information is provided consistently to each patient, it can be a cost-effective method after the initial cost of producing the video, patients can choose to watch the videos by themselves or in the presence of others, and they can pause and re-watch videos to suit their needs. Health information videos are not only viewed by patients in formal educational sessions, but are increasingly being viewed on websites such as YouTube. Whilst there is a lot of anecdotal and sometimes misleading information on YouTube, videos from government organisations and professional associations contain trustworthy and high-quality information and could enable YouTube to become a powerful information dissemination platform for patients and carers. This systematic review will examine the efficacy of video education to improve treatment or illness-related knowledge in patients with various long-term conditions, in comparison to other modalities of education. Methods: Only studies which match the following criteria will be included: participants will have a long-term physical health condition, video education will aim to improve treatment or illness related knowledge and will be tested in isolation, and the study must be a randomised controlled trial. Knowledge will be the primary outcome measure, with modality preference, anxiety, and behaviour change as secondary measures. The searches have been conducted in the following databases: OVID Medline, OVID PsycInfo, OVID Embase, CENTRAL and ProQuest, and hand searching for relevant published and unpublished studies has also been carried out. Screening and data extraction will be conducted independently by 2 researchers. Included studies will be assessed for their risk of bias in accordance with Cochrane guidelines, and heterogeneity will also be assessed before deciding whether a meta-analysis is appropriate or not. Results and Conclusions: Appropriate synthesis of the studies in relation to each outcome measure will be reported, along with the conclusions and implications.

Keywords: long-term condition, patient education, systematic review, video

Procedia PDF Downloads 102
6356 Identification and Characterization of Novel Genes Involved in Quinone Synthesis in the Odoriferous Defensive Stink Glands of the Red Flour Beetle, Tribolium castaneum

Authors: B. Atika, S. Lehmann, E. Wimmer

Abstract:

The defense strategy is very common in the insect world. Defensive substances play a wide variety of functions for beetles, such as repellents, toxicants, insecticides, and antimicrobics. Beetles react to predators, invaders, and parasitic microbes with the release of toxic and repellent substances. Defensive substances are directed against a large array of potential target organisms or may function for boiling bombardment or as surfactants. Usually, Coleoptera biosynthesize and store their defensive compounds in a complex secretory organ, known as odoriferous defensive stink glands. The red flour beetle, Tribolium castaneum (Coleoptera: Tenebrionidae), uses these glands to produce antimicrobial p-benzoquinones and 1-alkenes. In the past, the morphology of stink gland has been studied in detail in tenebrionid beetles; however, very little is known about the genes that are involved in the production of gland secretion. In this study, we studied a subset of genes that are essential for the benzoquinone production in red flour beetle. In the first phase, we selected 74 potential candidate genes from a genome-wide RNA interference (RNAi) knockdown screen named 'iBeetle.' All these 74 candidate genes were functionally characterized by RNAi-mediated gene knockdown. Therefore, they were selected for a subsequent gas chromatography-mass spectrometry (GC-MS) analysis of secretion volatiles in respective RNAi knockdown glands. 33 of them were observed to alter the phenotype of stink gland. In the GC-MS analysis, 7 candidate genes were noted to display a strongly altered gland, in terms of secretion color and chemical composition, upon knockdown, showing their key role in the biosynthesis of gland secretion. Morphologically altered stink glands were found for odorant receptor and protein kinase superfamily. Subsequent GC-MS analysis of secretion volatiles revealed reduced benzoquinone levels in LIM domain, PDZ domain, PBP/GOBP family knockdowns and a complete lack of benzoquinones in the knockdown of sulfatase-modifying factor enzyme 1, sulfate transporter family. Based on stink gland transcriptome data, we analyzed the function of sulfatase-modifying factor enzyme 1 and sulfate transporter family via RNAi-mediated gene knockdowns, GC-MS, in situ hybridization, and enzymatic activity assays. Morphologically altered stink glands were noted in knockdown of both these genes. Furthermore, GC-MS analysis of secretion volatiles showed a complete lack of benzoquinones in the knockdown of these two genes. In situ hybridization showed that these two genes are expressed around the vesicle of certain subgroup of secretory stink gland cells. Enzymatic activity assays on stink gland tissue showed that these genes are involved in p-benzoquinone biosynthesis. These results suggest that sulfatase-modifying factor enzyme 1 and sulfate transporter family play a role specifically in benzoquinone biosynthesis in red flour beetles.

Keywords: Red Flour Beetle, defensive stink gland, benzoquinones, sulfate transporter, sulfatase-modifying factor enzyme 1

Procedia PDF Downloads 144
6355 Foggy Image Restoration Using Neural Network

Authors: Khader S. Al-Aidmat, Venus W. Samawi

Abstract:

Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

Procedia PDF Downloads 373
6354 Evaluating the Use of Digital Art Tools for Drawing to Enhance Artistic Ability and Improve Digital Skill among Junior School Students

Authors: Aber Salem Aboalgasm, Rupert Ward

Abstract:

This study investigated some results of the use of digital art tools by junior school children in order to discover if these tools could promote artistic ability and creativity. The study considers the ease of use and usefulness of the tools as well as how to assess artwork produced by digital means. As the use of these tools is a relatively new development in Art education, this study may help educators in their choice of which tools to use and when to use them. The study also aims to present a model for the assessment of students’ artistic development and creativity by studying their artistic activity. This model can help in determining differences in students’ creative ability and could be useful both for teachers, as a means of assessing digital artwork, and for students, by providing the motivation to use the tools to their fullest extent. Sixteen students aged nine to ten years old were observed and recorded while they used the digital drawing tools. The study found that, according to the students’ own statements, it was not the ease of use but the successful effects the tools provided which motivated the children to use them.

Keywords: artistic ability, creativity, drawing digital tool, TAM model, psychomotor domain

Procedia PDF Downloads 318
6353 A Corpus-Based Approach to Understanding Market Access in Fisheries and Aquaculture: A Systematic Literature Review

Authors: Cheryl Marie Cordeiro

Abstract:

Although fisheries and aquaculture studies might seem marginal to international business (IB) studies in general, fisheries and aquaculture IB (FAIB) management is currently facing increasing pressure to meet global demand and consumption for fish in the next coming decades. In part address to this challenge, the purpose of this systematic review of literature (SLR) study is to investigate the use of the term ‘market access’ in its context of use in the generic literature and business sector discourse, in comparison to the more specific literature and discourse in fisheries, aquaculture and seafood. This SLR aims to uncover the knowledge/interest gaps between the academic subject discourses and business sector practices. Corpus driven in methodology and using a triangulation method of three different text analysis software including AntConc, VOSviewer and Web of Science (WoS) analytics, the SLR results indicate a gap in conceptual knowledge and business practices in how ‘market access’ is conceived and used in the context of the pharmaceutical healthcare industry and FAIB research and practice. While it is acknowledged that the product orientation of different business sectors might differ, this SLR study works with the assumption that both business sectors are global in orientation. These business sectors are complex in their operations from product to market. This SLR suggests a conceptual model in understanding the challenges, the potential barriers as well as avenues for solutions to developing market access for FAIB.

Keywords: market access, fisheries and aquaculture, international business, systematic literature review

Procedia PDF Downloads 132
6352 Analysis of Q-Learning on Artificial Neural Networks for Robot Control Using Live Video Feed

Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

Abstract:

Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

Procedia PDF Downloads 358
6351 A Parallel Approach for 3D-Variational Data Assimilation on GPUs in Ocean Circulation Models

Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

Abstract:

This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

Procedia PDF Downloads 399
6350 Comparative Analysis of Different Land Use Land Cover (LULC) Maps in WRF Modelling Over Indian Region

Authors: Sen Tanmoy, Jain Sarika, Panda Jagabandhu

Abstract:

The studies regarding the impact of urbanization using the WRF-ARW model rely heavily on the static geographical information selected, including domain configuration and land use land cover (LULC) data. Accurate representation of LULC data provides essential information for understanding urban growth and simulating meteorological parameters such as temperature, precipitation etc. Researchers are using different LULC data as per availability and their requirements. As far as India is concerned, we have very limited resources and data availability. So, it is important to understand how we can optimize our results using limited LULC data. In this review article, we explored how a LULC map is generated from different sources in the Indian context and what its significance is in WRF-ARW modeling to study urbanization/Climate change or any other meteorological parameters. Bibliometric analyses were also performed in this review article based on countries of study and indexed keywords. Finally, some key points are marked out for selecting the most suitable LULC map for any urbanization-related study.

Keywords: LULC, LULC mapping, LANDSAT, WRF-ARW, ISRO, bibliometric Analysis.

Procedia PDF Downloads 13
6349 Proposal Method of Prediction of the Early Stages of Dementia Using IoT and Magnet Sensors

Authors: João Filipe Papel, Tatsuji Munaka

Abstract:

With society's aging and the number of elderly with dementia rising, researchers have been actively studying how to support the elderly in the early stages of dementia with the objective of allowing them to have a better life quality and as much as possible independence. To make this possible, most researchers in this field are using the Internet Of Things to monitor the elderly activities and assist them in performing them. The most common sensor used to monitor the elderly activities is the Camera sensor due to its easy installation and configuration. The other commonly used sensor is the sound sensor. However, we need to consider privacy when using these sensors. This research aims to develop a system capable of predicting the early stages of dementia based on monitoring and controlling the elderly activities of daily living. To make this system possible, some issues need to be addressed. First, the issue related to elderly privacy when trying to detect their Activities of Daily Living. Privacy when performing detection and monitoring Activities of Daily Living it's a serious concern. One of the purposes of this research is to achieve this detection and monitoring without putting the privacy of the elderly at risk. To make this possible, the study focuses on using an approach based on using Magnet Sensors to collect binary data. The second is to use the data collected by monitoring Activities of Daily Living to predict the early stages of Dementia. To make this possible, the research team suggests developing a proprietary ontology combined with both data-driven and knowledge-driven.

Keywords: dementia, activity recognition, magnet sensors, ontology, data driven and knowledge driven, IoT, activities of daily living

Procedia PDF Downloads 83
6348 A Protocol Study of Accessibility: Physician’s Perspective Regarding Disability and Continuum of Care

Authors: Sidra Jawed

Abstract:

The accessibility constructs and the body privilege discourse has been a major problem while dealing with health inequities and inaccessibility. The inherent problem in this arbitrary view of disability is that disability would never be the productive way of living. For past thirty years, disability activists have been working to differentiate ‘impairment’ from ‘disability’ and probing for more understanding of limitation imposed by society, this notion is ultimately known as the Social Model of Disability. The vulnerable population as disability community remains marginalized and seen relentlessly fighting to highlight the importance of social factors. It does not only constitute physical architectural barriers and famous blue symbol of access to the healthcare but also invisible, intangible barriers as attitudes and behaviours. Conventionally the idea of ‘disability’ has been laden with prejudiced perception amalgamating with biased attitude. Equity in contemporary setup necessitates the restructuring of organizational structure. Apparently simple, the complex interplay of disability and contemporary healthcare set up often ends up at negotiating vital components of basic healthcare needs. The role of society is indispensable when it comes to people with disability (PWD), everything from the access to healthcare to timely interventions are strongly related to the set up in place and the attitude of healthcare providers. It is vital to understand the association between assumptions and the quality of healthcare PWD receives in our global healthcare setup. Most of time the crucial physician-patient relationship with PWD is governed by the negative assumptions of the physicians. The multifaceted, troubled patient-physicians’ relationship has been neglected in past. To compound it, insufficient work has been done to explore physicians’ perspective about the disability and access to healthcare PWD have currently. This research project is directed towards physicians’ perspective on the intersection of health and access of healthcare for PWD. The principal aim of the study is to explore the perception of disability in family medicine physicians, highlighting the underpinning of medical perspective in healthcare institution. In the quest of removing barriers, the first step must be to identify the barriers and formulate a plan for future policies, involving all the stakeholders. There would be semi-structured interviews to explore themes as accessibility, medical training, construct of social model and medical model of disability, time limitations, financial constraints. The main research interest is to identify the obstacles to inclusion and marginalization continuing from the basic living necessities to wide health inequity in present society. Physicians point of view is largely missing from the research landscape and the current forum of knowledge with regards to physicians’ standpoint. This research will provide policy makers with a starting point and comprehensive background knowledge that can be a stepping stone for future researches and furthering the knowledge translation process to strengthen healthcare. Additionally, it would facilitate the process of knowledge translation between the much needed medical and disability community.

Keywords: disability, physicians, social model, accessibility

Procedia PDF Downloads 209
6347 Estimating Poverty Levels from Satellite Imagery: A Comparison of Human Readers and an Artificial Intelligence Model

Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

Abstract:

The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

Procedia PDF Downloads 85
6346 Users’ Information Disclosure Determinants in Social Networking Sites: A Systematic Literature Review

Authors: Wajdan Al Malwi, Karen Renaud, Lewis Mackenzie

Abstract:

The privacy paradox describes a phenomenon whereby there is no connection between stated privacy concerns and privacy behaviours. We need to understand the underlying reasons for this paradox if we are to help users to preserve their privacy more effectively. In particular, the Social Networking System (SNS) domain offers a rich area of investigation due to the risks of unwise information disclosure decisions. Our study thus aims to untangle the complicated nature and underlying mechanisms of online privacy-related decisions in SNSs. In this paper, we report on the findings of a Systematic Literature Review (SLR) that revealed a number of factors that are likely to influence online privacy decisions. Our deductive analysis approach was informed by Communicative Privacy Management (CPM) theory. We uncovered a lack of clarity around privacy attitudes and their link to behaviours, which makes it challenging to design privacy-protecting SNS platforms and to craft legislation to ensure that users’ privacy is preserved.

Keywords: privacy paradox, self-disclosure, privacy attitude, privacy behavior, social networking sites

Procedia PDF Downloads 139
6345 Paradigms of Assessment, Valuation and Quantification to Trade Ecosystem Services: A Review Focusing on Mangroves and Wetlands

Authors: Rama Seth, Luise Noring, Pratim Majumdar

Abstract:

Based on an extensive literature review, this paper presents distinct approaches to value, quantify and trade ecosystem services, with particular emphasis on services provided by mangroves and wetlands. Building on diverse monetary and market-based systems for the improved allocation of natural resources, such trading and exchange-based methods can help tackle the degradation of ecosystem services in a more targeted and structured manner than achievable with stand-alone policy and administrative regulations. Using various threads of literature, the paper proposes a platform that serves as the skeletal foundation for developing an efficient global market for ecosystem services trading. The paper bridges a significant research and practice gap by recommending how to establish an equilibrium in the biosphere via trading mechanisms while also discovering other research gaps and future research potential in the domain of ecosystem valuation.

Keywords: environment, economics, mangroves, wetlands, markets, ESG, global capital, climate investments, valuation, ecosystem services

Procedia PDF Downloads 231
6344 The Obstacles of Applying Electronic Administration at the University of Tabuk from Its Academic Leaders' Perspectives

Authors: Saud Eid Alanazi

Abstract:

The study aimed at recognizing the obstacles of applying of Electronic Administration (e-administration), which refers to any of a number of mechanisms which convert what in a traditional office are paper processes into electronic processes, with the goal being to create a paperless office and improve productivity and performance at the University of Tabuk from its Academic Leaders' Perspectives. The sample of the study consisted of (98) members from deans, vice deans and head of departments from different specialization, gender and position. For achieving the aim of the study, a questionnaire was developed including (45) items distributed into three domains (administrative, human and technical obstacles) . By using appropriate statistical methods to analyze the information, the results indicated that the administrative obstacles domain came in the first rank with a high degree, and the human and technical obstacles came at the second rank with a moderate degree. The study also showed that there were no statistically significant differences attributed to the variables of the members (specialization, gender and position).

Keywords: administration, electronic administration, obstacles, technology, universities

Procedia PDF Downloads 370
6343 Review of Theories and Applications of Genetic Programing in Sediment Yield Modeling

Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

Abstract:

Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

Procedia PDF Downloads 431
6342 New Insight into Fluid Mechanics of Lorenz Equations

Authors: Yu-Kai Ting, Jia-Ying Tu, Chung-Chun Hsiao

Abstract:

New physical insights into the nonlinear Lorenz equations related to flow resistance is discussed in this work. The chaotic dynamics related to Lorenz equations has been studied in many papers, which is due to the sensitivity of Lorenz equations to initial conditions and parameter uncertainties. However, the physical implication arising from Lorenz equations about convectional motion attracts little attention in the relevant literature. Therefore, as a first step to understand the related fluid mechanics of convectional motion, this paper derives the Lorenz equations again with different forced conditions in the model. Simulation work of the modified Lorenz equations without the viscosity or buoyancy force is discussed. The time-domain simulation results may imply that the states of the Lorenz equations are related to certain flow speed and flow resistance. The flow speed of the underlying fluid system increases as the flow resistance reduces. This observation would be helpful to analyze the coupling effects of different fluid parameters in a convectional model in future work.

Keywords: Galerkin method, Lorenz equations, Navier-Stokes equations, convectional motion

Procedia PDF Downloads 378
6341 Sexual Diversity Training for Hong Kong Teachers Preliminary Themes Identified from Qualitative Interviews

Authors: Diana K. Kwok

Abstract:

Despite the fact that Hong Kong government aims to develop an inclusive society, sexual minority students continue to encounter sexual prejudice without legal protection. They also have difficulties accessing relevant services from mental health and educational professionals, who do not receive systematic training to work with sexual minority students. Informed by the literature on sexual prejudice, heterosexual hegemony, genderism, as well as code of practice for frontline practitioners, the authors explored self-perceived knowledge of teachers and sexual minorities on sexuality and sexual prejudice, and how they perceive prejudice towards sexual minorities in Chinese cultural context. Semi-structure qualitative interviews were carried out with 31 school personnel informants (school teachers and counseling team members) and 25 sexual minority informants on their understanding of sexuality knowledge, their perception of sexual prejudice within school context in Hong Kong, as well as their suggested themes on teachers training on sexual prejudice reduction. This presentation specifically focuses on transcripts from sexual minority informants. Data analysis was carried out through NVivo, and followed the procedures spelt out in the qualitative research literature. Trustworthiness of the study was addressed through various strategies. Preliminary themes emerged from transcript content analysis: 1) A gap of knowledge between sexual minority informants and teachers; 2) Perception on sexual prejudice within cultural context; 3) Heterosexual hegemony and genderism within school system; 4) Needs for mandatory training: contents and strategies. The sexual minority informants found that teachers they encountered were predominantly adopted concepts of binary sex and dichotomous gender. Informants also indicated that the teachings of Confucianism cultural values, religiosity in Hong Kong might well be important cultural forces contributing to sexual prejudice manifested in school context. Although human rights and social justice concepts were embedded in professional code of practice of teachers and school helping professionals, informants found that teachers they encountered may face a dilemma when supporting sexual minority students navigating heterosexual hegemony and genderism in, as a consequence of their personal, institutional, cultural and religious backgrounds. Acknowledgments: The sexual prejudice project was funded by the Hong Kong Research Grant Council (ECS28401614), 2015 to 2017.

Keywords: sexual prejudice, Chinese teachers, Chinese sexual minorities, teacher training

Procedia PDF Downloads 273
6340 Personalized Social Resource Recommender Systems on Interest-Based Social Networks

Authors: C. L. Huang, J. J. Sia

Abstract:

The interest-based social networks, also known as social bookmark sharing systems, are useful platforms for people to conveniently read and collect internet resources. These platforms also providing function of social networks, and users can share and explore internet resources from the social networks. Providing personalized internet resources to users is an important issue on these platforms. This study uses two types of relationship on the social networks—following and follower and proposes a collaborative recommender system, consisting of two main steps. First, this study calculates the relationship strength between the target user and the target user's followings and followers to find top-N similar neighbors. Second, from the top-N similar neighbors, the articles (internet resources) that may interest the target user are recommended to the target user. In this system, users can efficiently obtain recent, related and diverse internet resources (knowledge) from the interest-based social network. This study collected the experimental dataset from Diigo, which is a famous bookmark sharing system. The experimental results show that the proposed recommendation model is more accurate than two traditional baseline recommendation models but slightly lower than the cosine model in accuracy. However, in the metrics of the diversity and executing time, our proposed model outperforms the cosine model.

Keywords: recommender systems, social networks, tagging, bookmark sharing systems, collaborative recommender systems, knowledge management

Procedia PDF Downloads 156
6339 Exploring Factors That Affect the Utilisation of Antenatal Care Services: Perceptions of Women in Mangwe Rural District, Zimbabwe

Authors: Leoba Nyathi, Augustine K. Tugli, Takalani G. Tshitangano

Abstract:

Use of health care services is an effective way of improving maternal and child health outcomes, especially in the rural areas. The study aimed to find out the perceptions of women on factors that affect the utilisation of antenatal care services (ANC) in Mangwe Rural District, Zimbabwe. The study was conducted in Mabunga village which is situated in Mangwe Rural District, Matabeleland South Province, Zimbabwe. A qualitative approach using explorative and descriptive design was adopted for the study. A sample of ten women were chosen from the target population by means of convenience sampling and data was collected through semi-structured interviews. Interviews and discussions were audio-taped, transcribed and coded into themes and subthemes. The study results showed that access factors, socio-cultural factors, demographic factors, quality of care and knowledge about antenatal care services were the major factors affecting utilisation of ANC services in Mangwe Rural District. It was discovered that the geographical location of the village to the health care centres has a great impact on utilisation of services. All the women did not initiate ANC services as recommended and they also did not adhere to the number of times they were supposed to visit the health care centres. The findings concluded that women have the knowledge about ANC and they all attended at least once during their last pregnancy. However, inconsistencies in attendance were shown due to access, socio-cultural and demographic factors.

Keywords: antenatal care services, women, utilisation, affect, factors, perceptions

Procedia PDF Downloads 360
6338 Towards an Enhanced Compartmental Model for Profiling Malware Dynamics

Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

Abstract:

We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

Procedia PDF Downloads 95
6337 Investigating the Effect of Metaphor Awareness-Raising Approach on the Right-Hemisphere Involvement in Developing Japanese Learners’ Knowledge of Different Degrees of Politeness

Authors: Masahiro Takimoto

Abstract:

The present study explored how the metaphor awareness-raising approach affects the involvement of the right hemisphere in developing EFL learners’ knowledge regarding the different degrees of politeness embedded within different request expressions. The present study was motivated by theoretical considerations regarding the conceptual projection and the metaphorical idea of politeness is distance, as proposed; this study applied these considerations to develop Japanese learners’ knowledge regarding the different politeness degrees and to explore the connection between the metaphorical concept projection and right-hemisphere dominance. Japanese EFL learners do not know certain language strategies (e.g., English requests can be mitigated with biclausal downgraders, including the if-clause with past-tense modal verbs) and have difficulty adjusting the politeness degrees attached to request expressions according to situations. The present study used a pre/post-test design to reaffirm the efficacy of the cognitive technique and its connection to right-hemisphere involvement by mouth asymmetry technique. Mouth asymmetry measurement has been utilized because speech articulation, normally controlled mainly by one side of the brain, causes muscles on the opposite side of the mouth to move more during speech production. The present research did not administer the delayed post-test because it emphasized determining whether metaphor awareness-raising approaches for developing EFL learners’ pragmatic proficiency entailed right-hemisphere activation. Each test contained an acceptability judgment test (AJT) along with a speaking test in the post-test. The study results show that the metaphor awareness-raising group performed significantly better than the control group with regard to acceptability judgment and speaking tests post-test. These data revealed that the metaphor awareness-raising approach could promote L2 learning because it aided input enhancement and concept projection; through these aspects, the participants were able to comprehend an abstract concept: the degree of politeness in terms of the spatial concept of distance. Accordingly, the proximal-distal metaphor enabled the study participants to connect the newly spatio-visualized concept of distance to the different politeness degrees attached to different request expressions; furthermore, they could recall them with the left side of the mouth being wider than the right. This supported certain findings from previous studies that indicated the possible involvement of the brain's right hemisphere in metaphor processing.

Keywords: metaphor awareness-raising, right hemisphere, L2 politeness, mouth asymmetry

Procedia PDF Downloads 137