Search results for: multimedia learning theory

Authors: Kehinde, Taye Adetutu

Abstract:

The fact that Nigeria as a nation is faced by myriads of problems associated with religious crises and political insecurity is no news, the spoken statement and actions of most political giant were the major cause of this unrest. The 'unlearnt' youth within the regions has encompassed the situation. This scenario is further compounded by multilingual nature of the country as it is estimated that there exists amount 400 indigenous languages in Nigeria. It is an indisputable fact that english language which has assumed the status of an official language in Nigeria, given its status has a language of power and captivity by a few with no privilege to attend school. However, educating people in their indigenous language; crises can be averted through the proper orientation and mass literacy campaign, especially for the timid illiterate one, so as to live in unity, peace, tranquillity, and harmony as indivisible nation. In investigating the problem in this study with an emphasis on three major Nigerian language (Yoruba, Igbo and Hausa), participants observations and survey questionnaire were administered to about one hundred and twenty (120) respondents who were randomly selected throughout the three major ethnic groups in Nigeria. Findings from this study reveals that teaching and learning of cognitive words and information are more effective in ones mother tongue and helps in stimulating new ideas and changes. This paper was able to explore and critically examine the current state of affairs in Nigeria and proffer possible solutions to the prevailing situations by identifying how indigenous languages and linguistics can be used to ameliorate the present political and religious crisis for Nigeria, thus providing a proper recommendation to achieve meaningful stability and coexistence within a nation.

Keywords: multilingualism, political crisis, religious, Nigeria

Procedia PDF Downloads 433

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

Procedia PDF Downloads 473

Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

Abstract:

Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: conditional generative adversarial net, market and credit risk management, neural network, time series

Procedia PDF Downloads 137

Authors: Manavjit Singh Dhindsa, Ursula Das, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

These days, wildland fires, also known as forest fires, are more prevalent than ever. Wildfires have major repercussions that affect ecosystems, communities, and the environment in several ways. Wildfires lead to habitat destruction and biodiversity loss, affecting ecosystems and causing soil erosion. They also contribute to poor air quality by releasing smoke and pollutants that pose health risks, especially for individuals with respiratory conditions. Wildfires can damage infrastructure, disrupt communities, and cause economic losses. The economic impact of firefighting efforts, combined with their direct effects on forestry and agriculture, causes significant financial difficulties for the areas impacted. This research explores different forest fire spread models and presents a comprehensive review of various techniques and methodologies used in the field. A forest fire spread model is a computational or mathematical representation that is used to simulate and predict the behavior of a forest fire. By applying scientific concepts and data from empirical studies, these models attempt to capture the intricate dynamics of how a fire spreads, taking into consideration a variety of factors like weather patterns, topography, fuel types, and environmental conditions. These models assist authorities in understanding and forecasting the potential trajectory and intensity of a wildfire. Emphasizing the need for a comprehensive understanding of wildfire dynamics, this research explores the approaches, assumptions, and findings derived from various models. By using a comparison approach, a critical analysis is provided by identifying patterns, strengths, and weaknesses among these models. The purpose of the survey is to further wildfire research and management techniques. Decision-makers, researchers, and practitioners can benefit from the useful insights that are provided by synthesizing established information. Fire spread models provide insights into potential fire behavior, facilitating authorities to make informed decisions about evacuation activities, allocating resources for fire-fighting efforts, and planning for preventive actions. Wildfire spread models are also useful in post-wildfire mitigation strategies as they help in assessing the fire's severity, determining high-risk regions for post-fire dangers, and forecasting soil erosion trends. The analysis highlights the importance of customized modeling approaches for various circumstances and promotes our understanding of the way forest fires spread. Some of the known models in this field are Rothermel’s wildland fuel model, FARSITE, WRF-SFIRE, FIRETEC, FlamMap, FSPro, cellular automata model, and others. The key characteristics that these models consider include weather (includes factors such as wind speed and direction), topography (includes factors like landscape elevation), and fuel availability (includes factors like types of vegetation) among other factors. The models discussed are physics-based, data-driven, or hybrid models, also utilizing ML techniques like attention-based neural networks to enhance the performance of the model. In order to lessen the destructive effects of forest fires, this initiative aims to promote the development of more precise prediction tools and effective management techniques. The survey expands its scope to address the practical needs of numerous stakeholders. Access to enhanced early warning systems enables decision-makers to take prompt action. Emergency responders benefit from improved resource allocation strategies, strengthening the efficacy of firefighting efforts.

Keywords: artificial intelligence, deep learning, forest fire management, fire risk assessment, fire simulation, machine learning, remote sensing, wildfire modeling

Procedia PDF Downloads 76

Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

Abstract:

Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

Procedia PDF Downloads 43

Authors: T. Northcut, A. Rai, N. Perkins

Abstract:

Background: The COVID-19 pandemic has had a serious impact on academia in general and social work education in particular, changing permanently the way in which we approach educating students. The new reality of the pandemic coupled with the much-needed focus on racism across the country inspired and required educators to get creative with their teaching styles in order to disrupt the power imbalance in the classroom and attend to the multiple layers of needs of diverse students in precarious sociological and economic circumstances. This paper highlights research examining educators with distinctive positionalities and approaches to classroom instruction who use feminist and antiracist pedagogies while adapting to online teaching during the pandemic. Despite being feminist scholars, whose ideologies developed during different waves of feminism, our commitment to having student-led classrooms, liberation, and equity of all, and striving for social change, unified our feminist teaching pedagogies as well as provided interpersonal support. Methodology: Following a narrative qualitative inquiry methodology, the five authors of this paper came together to discuss our pedagogical styles and underlying values using Zoom in a series of six conversations. Narrative inquiry is an appropriate method to use when researchers are bound by common stories or personal experiences. The use of feminist pedagogy in the classroom before and during the pandemic guided the discussions. After six sessions, we reached the point of data saturation. All data from the dialogic process was recorded and transcribed. We used in vivo, narrative, and descriptive coding for the data analytic process. Results: Analysis of the data revealed several themes, which included (1) the influence of our positionalities as an intersection of race, sexual orientation, gender, and years of teaching experience in the classroom, (2) the meaning and variations between different liberatory pedagogical approaches, (3) the tensions between these approaches and institutional policies and practices, (4) the role of self-reflection in everyday teaching, (5) the distinctions between theory and practice and its utility for students, and (6) the challenges of applying a feminist-centered pedagogical approach during the pandemic while utilizing an online platform. As a collective, we discussed several challenges that limited the use of our feminist pedagogical approaches due to instruction through Zoom.

Keywords: feminist, pedagogy, COVID, zoom

Procedia PDF Downloads 40

Authors: Archana Gupta, Rajesh Kumar

Abstract:

The chemistry of chalcones has generated intensive scientific studies throughout the world. Especially, interest has been focused on the synthesis and biodynamic activities of chalcones. The blue light transmittance, excellent crystallizability and the two planar rings connected through a conjugated double bond show that chalcone derivatives are superior nonlinear organic compounds. 3-(2-Chloro-6-fluoro¬phen¬yl)-1-(2-thien¬yl) prop-2-en-1-one, 3-(2, 4- Dichlorophenyl) – 1 - (4-methylphenyl) – prop -2-en-1-one, (2E)-3-[4-(methylsulfanyl) phenyl]-1-(4-nitrophenyl) prop-2-en-1-one are some chalcone derivatives exhibiting non linear optical (NLO) properties. NLO materials have been extensively investigated in recent years as they are the key elements for photonic technologies of optical communication, optical interconnect oscillator, amplifier, frequency converter etc. Due to their high molecular hyperpolarizabilities, organic materials display a number of significant NLO properties. Experimental measurements and theoretical calculations on molecular hyperpolarizability β have become one of the key factors in the design of second order NLO materials. Theoretical determination of hyperpolarizability is quite useful both in understanding the relationship between the molecular structure and NLO properties. It also provides a guideline to experimentalists for the design and synthesis of organic NLO materials. Quantum-chemical calculations have made an important contribution to the understanding of the electronic polarization underlying the molecular NLO processes and the establishment of structure–property relationships. In the present investigation, the detailed vibrational analysis of some chalcone derivatives is taken up to understand the correlation of the charge transfer interaction and the NLO activity of the molecules based on density functional theory calculations. The vibrational modes contributing toward the NLO activity have been identified and analyzed. Rather large hyperpolarizability derived by theoretical calculations suggests the possible future use of these compounds for non-linear optical applications. The study suggests the importance of π - conjugated systems for non-linear optical properties and the possibility of charge transfer interactions. We hope that the results of the present study of chalcone derivatives are of assistance in development of new efficient materials for technological applications.

Keywords: hyperpolarizability, molecular structure, NLO material, quantum chemical calculations

Procedia PDF Downloads 229

Authors: Chen Chuanzhi, Guo Yunyun

Abstract:

The large linear array feeding parabolic cylindrical antenna of the satellite has the ability of large-area line focusing, multi-directional beam clusters simultaneously in a certain azimuth plane and elevation plane, corresponding quickly to different orientations and different directions in a wide frequency range, dual aiming of frequency and direction, and combining space power. Therefore, the large-diameter parabolic cylindrical antenna has become one of the new development directions of spaceborne antennas. Limited by the size of the rocked fairing, the large-diameter spaceborne antenna is required to be small mass and have a deployment function. After being orbited, the antenna can be deployed by expanding and be stabilized. However, few types of structures can be used to construct large cylindrical shell structures in existing structures, which greatly limits the development and application of such antennas. Aiming at high structural efficiency, the geometrical characteristics of parabolic cylinders and mechanism topological mapping law to the expandable truss are studied, and the basic configuration of deployable truss with cylindrical shell is structured. Then a modular truss parabolic cylindrical antenna is designed in this paper. The antenna has the characteristics of stable structure, high precision of reflecting surface formation, controllable motion process, high storage rate, and lightweight, etc. On the basis of the overall configuration comprehensive theory and optimization method, the structural stiffness of the modular truss parabolic cylindrical antenna is improved. And the bearing density and impact resistance of support structure are improved based on the internal tension optimal distribution method of reflector forming. Finally, a truss-type cylindrical deployable support structure with high constriction-deployment ratio, high stiffness, controllable deployment, and low mass is successfully developed, laying the foundation for the application of large-diameter parabolic cylindrical antennas in satellite antennas.

Keywords: linear array feed antenna, truss type, parabolic cylindrical antenna, spaceborne antenna

Procedia PDF Downloads 148

Authors: Emilie Zimet

Abstract:

During networking and NCCD moderation meetings, best practices for identifying students who require Literacy Intervention are often discussed. Once these students are identified, consideration is given to the most effective process for prioritising those who have the greatest need for Literacy Support and the allocation of resources, tracking of intervention effectiveness and communicating with teachers/external providers/parents. Through a workshop, the group will investigate best practices to identify students who require literacy support and strategies to communicate and track their progress. In groups, participants will examine what they do in their settings and then compare with other models, including the researcher’s model, to decide the most effective path to identification and communication. Participants will complete a worksheet at the beginning of the session to deeply consider their current approaches. The participants will be asked to critically analyse their own identification processes for Literacy Intervention, ensuring students are not overlooked if they fall into the borderline category. A cut-off for students to access intervention will be considered so as not to place strain on already stretched resources along with the most effective allocation of resources. Furthermore, communicating learning needs and differentiation strategies to staff is paramount to the success of an intervention, and participants will look at the frequency of communication to share such strategies and updates. At the end of the session, the group will look at creating or evolving models that allow for best practices for the identification and communication of Literacy Interventions. The proposed outcome for this research is to develop a model of identification of students requiring Literacy Intervention that incorporates the allocation of resources and communication to key stakeholders. This will be done by pooling information and discussing a variety of models used in the participant's school settings.

Keywords: identification, student selection, communication, special education, school policy, planning for intervention

Procedia PDF Downloads 45

Authors: Nikolaos Petropoulos, Elena Blokhina, Andrii Sokolov, Andrii Semenov, Panagiotis Giounanlis, Xutong Wu, Dmytro Mishagli, Eugene Koskin, Robert Bogdan Staszewski, Dirk Leipold

Abstract:

We investigate entanglement and quantum information scrambling (QIS) by the example of a many-body Extended and spinless effective Fermi-Hubbard Model (EFHM and e-FHM, respectively) that describes a special type of quantum dot array provided by Equal1 labs silicon-based quantum computer. The concept of QIS is used in the framework of quantum information processing by quantum circuits and quantum channels. In general, QIS is manifest as the de-localization of quantum information over the entire quantum system; more compactly, information about the input cannot be obtained by local measurements of the output of the quantum system. In our work, we will first make an introduction to the concept of quantum information scrambling and its connection with the 4-point out-of-time-order (OTO) correlators. In order to have a quantitative measure of QIS we use the tripartite mutual information, in similar lines to previous works, that measures the mutual information between 4 different spacetime partitions of the system and study the Transverse Field Ising (TFI) model; this is used to quantify the dynamical spreading of quantum entanglement and information in the system. Then, we investigate scrambling in the quantum many-body Extended Hubbard Model with external magnetic field Bz and spin-spin coupling J for both uniform and thermal quantum channel inputs and show that it scrambles for specific external tuning parameters (e.g., tunneling amplitudes, on-site potentials, magnetic field). In addition, we compare different Hilbert space sizes (different number of qubits) and show the qualitative and quantitative differences in quantum scrambling as we increase the number of quantum degrees of freedom in the system. Moreover, we find a "scrambling phase transition" for a threshold temperature in the thermal case, that is, the temperature of the model that the channel starts to scramble quantum information. Finally, we make comparisons to the TFI model and highlight the key physical differences between the two systems and mention some future directions of research.

Keywords: condensed matter physics, quantum computing, quantum information theory, quantum physics

Procedia PDF Downloads 90

Authors: Ebrahim Panah, Muhammad Yasir Babar

Abstract:

Thanks to the development of online technology and social networks, people are able to communicate as well as learn. WhatsApp is a popular social network which is growingly gaining popularity. This app can be used for communication as well as education. It can be used for instructor-learner, learner-learner, and learner-content interactions; however, very little knowledge is available on these potentials of WhatsApp. The current study was undertaken to investigate university students’ perceptions of WhatsApp used as a tool for instructor-learner dialogue, learner-content dialogue, and learner-learner dialogue. The study adopted a survey approach and distributed the questionnaire developed by Google Forms to 54 (11 males and 43 females) university students. The obtained data were analyzed using SPSS version 20. The result of data analysis indicates that students have positive attitudes towards WhatsApp as a tool for Instructor-Learner Dialogue: it easy to reach the lecturer (4.07), the instructor gives me valuable feedback on my assignment (4.02), the instructor is supportive during course discussion and offers continuous support with the class (4.00). Learner-Content Dialogue: WhatsApp allows me to academically engage with lecturers anytime, anywhere (4.00), it helps to send graphics such as pictures or charts directly to the students (3.98), it also provides out of class, extra learning materials and homework (3.96), and Learner-Learner Dialogue: WhatsApp is a good tool for sharing knowledge with others (4.09), WhatsApp allows me to academically engage with peers anytime, anywhere (4.07), and we can interact with others through the use of group discussion (4.02). It was also found that there are significant positive correlations between students’ perceptions of Instructor-Learner Dialogue (ILD), Learner-Content Dialogue (LCD), Learner-Learner Dialogue (LLD) and WhatsApp Application in classroom. The findings of the study have implications for lectures, policy makers and curriculum developers.

Keywords: instructor-learner dialogue, learners-contents dialogue, learner-learner dialogue, whatsapp application

Procedia PDF Downloads 152

Authors: Abdul Rahmat

Abstract:

Community-based education in the economic empowerment of the family is an attempt to accelerate human development index (HDI) Dumbo Kingdom District of Gorontalo economics (purchasing power) program developed in this activity is the manufacture of functional skills shredded fish, fish balls, fish nuggets, chips anchovies, and corn sticks fish. The target audience of this activity is fishing se mothers subdistrict Dumbo Kingdom include Talumolo Village, Village Botu, Kampung Bugis Village, Village North and Sub Leato South Leato that each village is represented by 20 participants so totaling 100 participants. Time activities beginning in October s/d November 2014 held once a week on every Saturday at 9.00 s/d 13:00/14:00. From the results of the learning process of testing the skills of functional skills of making shredded fish, fish balls, fish nuggets, chips anchovies, fish and corn sticks residents have additional knowledge and experience are: 1) Order the concept include: nutrient content, processing food with fish raw materials , variations in taste, packaging, pricing and marketing sales. 2) Products made: in accordance with the wishes of the residents learned that estimated Eligible selling, product packaging logo creation, preparation and realization of the establishment of Business Study Group (KBU) and pioneered the marketing network with restaurant, store / shop staple food vendors that are around CLC.

Keywords: community development, functional skills, gender, HDI

Procedia PDF Downloads 309

Authors: Rohini Hariharan, Yazhini R., Blessy Maria Mathew

Abstract:

The task of detecting email spam is a very important one in the era of digital technology that needs effective ways of curbing unwanted messages. This paper presents an approach aimed at making email spam categorization algorithms transparent, reliable and more trustworthy by incorporating Local Interpretable Model-agnostic Explanations (LIME). Our technique assists in providing interpretable explanations for specific classifications of emails to help users understand the decision-making process by the model. In this study, we developed a complete pipeline that incorporates LIME into the spam classification framework and allows creating simplified, interpretable models tailored to individual emails. LIME identifies influential terms, pointing out key elements that drive classification results, thus reducing opacity inherent in conventional machine learning models. Additionally, we suggest a visualization scheme for displaying keywords that will improve understanding of categorization decisions by users. We test our method on a diverse email dataset and compare its performance with various baseline models, such as Gaussian Naive Bayes, Multinomial Naive Bayes, Bernoulli Naive Bayes, Support Vector Classifier, K-Nearest Neighbors, Decision Tree, and Logistic Regression. Our testing results show that our model surpasses all other models, achieving an accuracy of 96.59% and a precision of 99.12%.

Keywords: text classification, LIME (local interpretable model-agnostic explanations), stemming, tokenization, logistic regression.

Procedia PDF Downloads 40

Authors: Nelson F. F. Ebecken, Gilberto C. Pereira, Lucio P. de Andrade

Abstract:

Bays, estuaries and coastal ecosystems are some of the most used and threatened natural systems globally. Its deterioration is due to intense and increasing human activities. This paper aims to monitor the socio-ecological in Brazil, model and simulate it through a multilayer network representing a DPSIR structure (Drivers, Pressures, States-Impacts-Responses) considering the concept of Management based on Ecosystems to support decision-making under the National/State/Municipal Coastal Management policy. This approach considers several interferences and can represent a significant advance in several scientific aspects. The main objective of this paper is the coupling of three different types of complex networks, the first being an ecological network, the second a social network, and the third a network of economic activities, in order to model the marine ecosystem. Multilayer networks comprise two or more "layers", which may represent different types of interactions, different communities, different points in time, and so on. The dependency between layers results from processes that affect the various layers. For example, the dispersion of individuals between two patches affects the network structure of both samples. A multilayer network consists of (i) a set of physical nodes representing entities (e.g., species, people, companies); (ii) a set of layers, which may include multiple layering aspects (e.g., time dependency and multiple types of relationships); (iii) a set of state nodes, each of which corresponds to the manifestation of a given physical node in a layer-specific; and (iv) a set of edges (weighted or not) to connect the state nodes among themselves. The edge set includes the intralayer edges familiar and interlayer ones, which connect state nodes between layers. The applied methodology in an existent case uses the Flow cytometry process and the modeling of ecological relationships (trophic and non-trophic) following fuzzy theory concepts and graph visualization. The identification of subnetworks in the fuzzy graphs is carried out using a specific computational method. This methodology allows considering the influence of different factors and helps their contributions to the decision-making process.

Keywords: marine ecosystems, complex systems, multilayer network, ecosystems management

Procedia PDF Downloads 104

Authors: Camille Charlebois-Plante, Marie-Ève Bourassa, Gaelle Dumel, Meriem Sabir, Louis De Beaumont

Abstract:

To the extent of our knowledge, there has been little interest in the chronic effects of mild traumatic brain injury (mTBI) on cognition during normal aging. This is rather surprising considering the impacts on daily and social functioning. In addition, sustaining a mTBI during late adulthood may increase the effect of normal biological aging in individuals who consider themselves normal and healthy. The objective of this study was to characterize the persistent neuropsychological repercussions of mTBI sustained during late adulthood, on average 12 months prior to testing. To this end, 35 mTBI patients and 42 controls between the ages of 50 and 69 completed an exhaustive neuropsychological assessment lasting three hours. All mTBI patients were asymptomatic and all participants had a score ≥ 27 at the MoCA. The evaluation consisted of 20 standardized neuropsychological tests measuring memory, attention, executive and language functions, as well as information processing speed. Performance on tests of visual (Brief Visuospatial Memory Test Revised) and verbal memory (Rey Auditory Verbal Learning Test and WMS-IV Logical Memory subtest), lexical access (Boston Naming Test) and response inhibition (Stroop) revealed to be significantly lower in the mTBI group. These findings suggest that a mTBI sustained during late adulthood induces lasting effects on cognitive function. Episodic memory and executive functions seem to be particularly vulnerable to enduring mTBI effects.

Keywords: cognitive function, late adulthood, mild traumatic brain injury, neuropsychology

Procedia PDF Downloads 166

Authors: Lizhi Ma, Dan Liu

Abstract:

Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

Procedia PDF Downloads 0

Authors: Hamza Javar Magnier, Leslie V. Woodcock

Abstract:

We report extensive molecular dynamics (MD) computational investigations into the thermodynamic description of supercritical properties for a model fluid that is the simplest realistic representation of atoms or molecules. The pair potential is a hard-sphere repulsion of diameter σ with a very short attraction of length λσ. When λ = 1.005 the range is so short that the model atoms are referred to as “adhesive spheres”. Molecular dimers, trimers …etc. up to large clusters, or droplets, of many adhesive-sphere atoms are unambiguously defined. This then defines percolation transitions at the molecular level that bound the existence of gas and liquid phases at supercritical temperatures, and which define the existence of a supercritical mesophase. Both liquid and gas phases are seen to terminate at the loci of percolation transitions, and below a second characteristic temperature (Tc2) are separated by the supercritical mesophase. An analysis of the distribution of clusters in gas, meso- and liquid phases confirms the colloidal nature of this mesophase. The general phase behaviour is compared with both experimental properties of the water-steam supercritical region and also with formally exact cluster theory of Mayer and Mayer. Both are found to be consistent with the present findings that in this system the supercritical mesophase narrows in density with increasing T > Tc and terminates at a higher Tc2 at a confluence of the primary percolation loci. The expended plot of the MD data points in the mesophase of 7 critical and supercritical isotherms in highlight this narrowing in density of the linear-slope region of the mesophase as temperature is increased above the critical. This linearity in the mesophase implies the existence of a linear combination rule between gas and liquid which is an extension of the Lever rule in the subcritical region, and can be used to obtain critical parameters without resorting to experimental data in the two-phase region. Using this combination rule, the calculated critical parameters Tc = 0.2007 and Pc = 0.0278 are found be agree with the values found by of Largo and coworkers. The properties of this supercritical mesophase are shown to be consistent with an alternative description of the phenomenon of critical opalescence seen in the supercritical region of both molecular and colloidal-protein supercritical fluids.

Keywords: critical opalescence, supercritical, square-well, percolation transition, critical parameters.

Procedia PDF Downloads 516

Authors: Silvia Miele, Patrice Rusconi, Harriet Tenenbaum

Abstract:

An increasingly multi-ethnic Europe has been pushing citizens’ boundaries on who should be entitled and to what extent to practise their own diversity. Indeed, according to a Standard Eurobarometer survey conducted in 2017, immigration is seen by Europeans as the most serious issue facing the EU, and a third of respondents reported they do not feel comfortable interacting with migrants from outside the EU. Many of these come from Muslim countries, accounting for 4.9% of Europe population in 2016. However, the figure is projected to rise up to 14% by 2050. Additionally, political debates have increasingly focused on Muslim immigrants, who are frequently portrayed as difficult to integrate, while nationalist parties across Europe have fostered the idea of insuperable cultural differences, creating an atmosphere of hostility. Using a 3 X 3 X 2 between-subjects design, it was investigated how people reason about endorsing religious and non-religious rights to minorities. An online survey has been administered to university students of three different countries (Italy, Spain and the UK) via Qualtrics, presenting hypothetical scenarios through a vignette methodology. Each respondent has been randomly allocated to one of the three following conditions: Christian, Muslim or non-religious (vegan) target. Each condition entailed three questions about children self-determination rights to exercise some control over their own lives and 3 questions about children nurturance rights of care and protection. Moreover, participants have been required to further elaborate on their answers via free-text entries and have been asked about their contact and quality of contact with the three targets, and to self-report religious, national and ethnic identification. Answers have been recorded on a Likert scale of 1-5, 1 being "not at all", 5 being "very much". A two-way ANCOVA will be used to analyse answers to closed-ended questions, while free-text answers will be coded and data will be dichotomised based on Social Cognitive Domain Theory for four categories: moral, social conventional and psychological reasons, and analysed via ANCOVAs. This study’s findings aim to contribute to the implementation of educational interventions and speak to the introduction of governmental policies on human rights.

Keywords: children's rights, Europe, migration, minority

Procedia PDF Downloads 126

Authors: Sukjai Charoensuk, Penphan Pitaksongkram, Michael Christopher

Abstract:

Preliminary evidences supported the effectiveness of mindfulness-based interventions in reducing symptoms associated with a variety of medical and psychological conditions. However, the measurements of mindfulness are questionable since they have not been developed based-on Buddhist experiences. The purpose of this qualitative study was to describe meaning and cultivating factors of mindfulness as experienced by Thai females who practice Dhamma. Participants were purposively selected to include 2 groups of Thai females who practice Dhamma. The first group consisted of 6 female Buddhist monks, and the second group consisted of 7 female who practice Dhamma without ordaining. Data were collected using in-depth interview. The instruments used were demographic data questionnaire and guideline for in-depth interview developed by researchers. Content analysis was employed to analyze the data. The results revealed that Thai women who practice Dhamma described their experience in 2 themes, which were meaning and cultivating factors of mindfulness. The meaning composed of 4 categories; 1) Being Present, 2) Self-awareness, 3) Contemplation, and 4) Neutral. The cultivating factors of mindfulness composed of 2 categories; In-personal factors and Ex-personal factors. The In-personal cultivating factors included 4 sub-categories; Faith and Love, the Five Precepts, Sound body, and Practice. The Ex-personal cultivating factors included 2 sub-categories; Serenity, and Learning. These findings increase understanding about meaning of mindfulness and its cultivating factors. These could be used as a guideline to promote mental health and develop nursing interventions using mindfulness based, as well as, develop the instrument for assessing mindfulness in Thai context.

Keywords: cultivating factor, meaning of mindfulness, practice Dhamma, Thai women

Procedia PDF Downloads 347

Authors: Ching-Hsu Huang, Yao-Ling Liu

Abstract:

Over the past several decades there has been considerable research on the topics of entrepreneurship education and nascent entrepreneurial competence. The purpose of this study is to explore the nascent entrepreneurial competence within entrepreneurship education via the use of three studies. It will be a three-phrases longitudinal study and the effective plan will combine the qualitative and quantitative mixed research methodology in order to understand the issues of nascent entrepreneurship and entrepreneurial competence in hospitality industry in Taiwan. In study one, the systematic literature reviews and twelve nascent entrepreneurs who graduated from hospitality management department will be conducted simultaneously to construct the nascent entrepreneurial competence indicators. Nine subjects who are from industry, government, and academia will be the decision makers in terms of forming the systematic nascent entrepreneurial competence indicators. The relative importance of indicators to each decision maker will be synthesized and compared using the Analytic Hierarchy Process method. According to the results of study one, this study will develop the teaching module of nascent hospitality entrepreneurship. It will include the objectives, context, content, audiences, assessment, pedagogy and outcomes. Based on the results of the second study, the quasi-experiment will be conducted in third study to explore the influence of nascent hospitality entrepreneurship teaching module on learners’ learning effectiveness. The nascent hospitality entrepreneurship education program and entrepreneurial competence will be promoted all around the hospitality industry and vocational universities. At the end, the implication for designing the nascent hospitality entrepreneurship teaching module and training programs will be suggested for the nascent entrepreneurship education. All of the proposed hypotheses will be examined and major finding, implication, discussion, and recommendations will be provided for the government and education administration in hospitality field.

Keywords: entrepreneurial competence, hospitality entrepreneurship, nascent entrepreneurial, training in hospitality entrepreneurship

Procedia PDF Downloads 238

Authors: Yarhands Dissou Arthur, Samuel Asiedu Addo, Jonathan Annan

Abstract:

Interest in subject specific is very essential in the quest to ensure effective teaching and learning. In building interest in subject specific areas requires certain factors and strategies well-spelled out.The factors such as the gender of the student, the type of basic school attended, the parent interest as well as the scare of the basic school mathematics teacher is very important to consider. The relational effect and the contribution these above mentioned variables on student have not been fully investigated and this paper address the effect of these factors on the student interest. In the attainment of this goal, the current paper addresses the effect of parent interest, the type of basic school attended, the scare by basic school mathematics teacher and its effect on student’s interest in mathematics. A cross sectional data collected from two hundred and sixty post-secondary school student were analyzed using descriptive and inferential statistical methods by aid of SPSS version 16. The study found that parent interest and value for mathematics significantly influenced students interest and joy in solving mathematical problems. Moreover, we also observed that the fear imposed by basic school mathematics teachers was found to significantly influence students’ interest. The study further found that the type of basic school attended and gender are factors that do not influence students’ interest in mathematics. In addition to concluding that a student’s interest is influenced by both parent interest and the fear of basic school mathematics teacher, the study also showed that the type of basic school attended and gender does not affect the students’ interest in mathematics.

Keywords: gender, mathematics interest, teacher interest, teacher interest, student interest

Procedia PDF Downloads 359

Authors: Augustar Omoze Ehighalua, Itotenaan Henry Ogiri

Abstract:

As a mono-product economy, Nigeria relies largely on oil revenues for its foreign exchange earnings and the exploration activities of firms operating in the Niger Delta region have left in its wake tales of environmental degradation, poverty and misery. This, no doubt, have created corporate social responsibility issues in the region. The focus of this research is the critical evaluation of the ethical response to Corporate Social Responsibility (CSR) practice by firms operating in Nigeria Delta Swamplands. While CSR is becoming more popular in developed society with effective practice guidelines and reporting benchmark, there is a relatively low level of awareness and selective applicability of existing international guidelines to effectively support CSR practice in Nigeria. This study, haven identified the lack of CSR institutional framework attempts to develop an ethically-driven CSR transparency benchmark laced within a regulatory framework based on international best practices. The research adopts a qualitative methodology and makes use of primary data collected through semi-structured interviews conducted across the six core states of the Niger Delta Region. More importantly, the study adopts an inductive, interpretivist philosophical paradigm that reveal deep phenomenological insights into what local communities, civil society and government officials consider as good ethical benchmark for responsible CSR practice by organizations. The institutional theory provides for the main theoretical foundation, complemented by the stakeholder and legitimacy theories. The Nvivo software was used to analyze the data collected. This study shows that ethical responsibility is lacking in CSR practice by firms in the Niger Delta Region of Nigeria. Furthermore, findings of the study indicate key issues of environmental, health and safety, human rights, and labour as fundamental in developing an effective CSR practice guideline for Nigeria. The study has implications for public policy formulation as well as managerial perspective.

Keywords: corporate social responsibility, CSR, ethics, firms, Niger-Delta Swampland, Nigeria

Procedia PDF Downloads 102

Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

Procedia PDF Downloads 82

Authors: Kazushige Wada, Mayuko Ueda

Abstract:

In the present study, we reanalyzed lapse errors in the last phase of a job, by re-counting near lapse errors and increasing the number of participants. We also examined the results of this study from the perspective of prospective memory (PM), which concerns future actions. This study was designed to investigate whether perceiving the importance of PM tasks caused lapse errors in the last phase of a job and to determine if such errors could be explained from the perspective of PM processing. Participants (N = 34) conducted a computerized clicking task, in which they clicked on 10 figures that they had learned in advance in 8 blocks of 10 trials. Participants were requested to click the check box in the start display of a block and to click the checking off box in the finishing display. This task was a PM task. As a measure of PM performance, we counted the number of omission errors caused by forgetting to check off in the finishing display, which was defined as a lapse error. The perceived importance was manipulated by different instructions. Half the participants in the highly important task condition were instructed that checking off was very important, because equipment would be overloaded if it were not done. The other half in the not important task condition was instructed only about the location and procedure for checking off. Furthermore, we controlled workload and the emotion of surprise to confirm the effect of demand capacity and attention. To manipulate emotions during the clicking task, we suddenly presented a photo of a traffic accident and the sound of a skidding car followed by an explosion. Workload was manipulated by requesting participants to press the 0 key in response to a beep. Results indicated too few forgetting induced lapse errors to be analyzed. However, there was a weak main effect of the perceived importance of the check task, in which the mouse moved to the “END” button before moving to the check box in the finishing display. Especially, the highly important task group showed more such near lapse errors, than the not important task group. Neither surprise, nor workload affected the occurrence of near lapse errors. These results imply that high perceived importance of PM tasks impair task performance. On the basis of the multiprocess framework of PM theory, we have suggested that PM task performance in this experiment relied not on monitoring PM tasks, but on spontaneous retrieving.

Keywords: prospective memory, perceived importance, lapse errors, multi process framework of prospective memory.

Procedia PDF Downloads 441

Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

Abstract:

In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

Procedia PDF Downloads 113

Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

Abstract:

Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

Procedia PDF Downloads 548

Authors: Jacques Lamarche, Juhani Dickinson

Abstract:

This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

Procedia PDF Downloads 30

Authors: Eugene Mashapa

Abstract:

The age of information has witnessed countless unprecedented technological developments, which signal the articulation of succinct technological capabilities that can match these cutting-edge technological trends. These changes have impacted patterns in the production, distribution, and consumption of media content, a space that the Film and Publication Board (FPB) is concerned with. Consequently, the FPB is keen to understand the nature and impact of these technological changes on media content regulation. This exploratory study sought to investigate how content regulators in high and middle-income economies have adapted to the changes in this space, seeking insights into innovations, technological and operational, that facilitate continued relevance during this fast-changing environment. The study is aimed at developing recommendations that could assist and inform the organisation in regulating media content as it evolves. Thus, the overall research strategy in this analysis is applied research, and the analytical model adopted is a mixed research design guided by both qualitative and quantitative research instruments. It was revealed in the study that the FPB was significantly impacted by the unprecedented technological advancements in the media regulation space. Additionally, there exists a need for the FPB to understand the current and future penetrations of 4IR technology in the industry and its impact on media governance and policy implementation. This will range from reskilling officials to align with the technological skills to developing technological innovations as well as adopting co-regulatory or self-regulatory arrangements together with content distributors, where more content is distributed in higher volumes and with increased frequency. Importantly, initiating an interactive learning process for both FPB employees and the general public can assist the regulator and improve FPB’s operational efficiency and effectiveness.

Keywords: media, regulation, technology, film and publications board

Procedia PDF Downloads 98

Authors: Laura Mendez

Abstract:

Tribunals for the prosecution of crimes against humanity have been implemented in recent history via international intervention or imposed by one side of the conflict, as in the cases of Rwanda, Iraq, Argentina, and Chile. However, the creation of a criminal tribunal as the result of a peace agreement between formerly warring parties has been unique to the Colombian peace process. As such, the Colombian Jurisdiction for Peace (SJP), or JEP for its Spanish acronym, is viewed as a site of social contestation where actors shape its design and implementation. This study contributes to the literature of transitional justice by analyzing how the framing of the creation of the Colombian tribunal reveals the parties' interests. The analysis frames the interests of the power-brokers, i.e., the government and the Revolutionary Armed Forces of Colombia (FARC), and the victims in light of the tribunal’s functions. The purpose of this analysis is to understand how the interests of the parties are embedded in the designing of the SJP. This paper argues that the creation of the SJP rests on restorative justice, for which the victim, not the perpetrator, is at the center of prosecution. The SJP’s approach to justice moves from prosecution as punishment to prosecution as sanctions. SJP’s alternative sanctions focused on truth, reparation, and restoration are designed to humanize both the victim and the perpetrator in order to achieve reconciliation. The findings also show that requiring the perpetrator to perform labor to repair the victim as an alternative form of sanction aims to foster relations of reintegration and social learning between victims and perpetrators.

Keywords: transitional justice mechanisms, criminal tribunals, Colombia, Colombian Jurisdiction for Peace, JEP

Procedia PDF Downloads 111

Authors: Javed Mallick

Abstract:

In metropolitan areas, rapid changes in land use and land cover (LULC) have ecological and environmental consequences. Saudi Arabia's cities have experienced tremendous urban growth since the 1990s, resulting in urban heat islands, groundwater depletion, air pollution, loss of ecosystem services, and so on. From 1990 to 2020, this study examines the variance and heterogeneity in land surface temperature (LST) caused by LULC changes in Abha-Khamis Mushyet, Saudi Arabia. LULC was mapped using the support vector machine (SVM). The mono-window algorithm was used to calculate the land surface temperature (LST). To identify LST clusters, the local indicator of spatial associations (LISA) model was applied to spatiotemporal LST maps. In addition, the parallel coordinate (PCP) method was used to investigate the relationship between LST clusters and urban biophysical variables as a proxy for LULC. According to LULC maps, urban areas increased by more than 330% between 1990 and 2018. Between 1990 and 2018, built-up areas had an 83.6% transitional probability. Furthermore, between 1990 and 2020, vegetation and agricultural land were converted into built-up areas at a rate of 17.9% and 21.8%, respectively. Uneven LULC changes in built-up areas result in more LST hotspots. LST hotspots were associated with high NDBI but not NDWI or NDVI. This study could assist policymakers in developing mitigation strategies for urban heat islands

Keywords: land use land cover mapping, land surface temperature, support vector machine, LISA model, parallel coordinate plot

Procedia PDF Downloads 70