Search results for: temporal dominance of sensations
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1359

Search results for: temporal dominance of sensations

669 Towards an Adversary-Aware ML-Based Detector of Spam on Twitter Hashtags

Authors: Niddal Imam, Vassilios G. Vassilakis

Abstract:

After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

Procedia PDF Downloads 62
668 Understanding English Language in Career Development of Academics in Non-English Speaking HEIs: A Systematic Literature Review

Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

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The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

Procedia PDF Downloads 137
667 Development and Experimental Validation of Coupled Flow-Aerosol Microphysics Model for Hot Wire Generator

Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

Abstract:

We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

Procedia PDF Downloads 134
666 Assessment of Polycyclic Aromatic Hydrocarbons (PAHs) Pollution Effects on Blood Metabolic Factors of Periophthalmus waltoni from Northern Coast of the Persian Gulf

Authors: Majid Afkhami, Maryam Ehsanpour

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The present study provides information about the nature of adverse effects on fish and the ecological impact that polycyclic aromatic hydrocarbons (PAHs) pollutant are having in the northern coast of Hormuz Strait. The glucose and cholesterol levels were higher in fish from the St3 than in Walton's mudskipper from other stations however St3 samples had lowest total proteins levels. There was a significant positive correlation between glucose and cholesterol with PAHs concentrations in sediment and tissue samples (P<0.05). However, total proteins had adverse significant correlation with PAHs concentrations (P>0.05). The adverse correlation was seen between length and body weight of fish samples with PAHs concentrations. According to the results of this study, the monitoring of contaminants bioaccumulation in the northern part of Hormuz Strait is necessary, because this will give an indication of the temporal and spatial extent of the process, as well as an assessment of the potential impact on aquatic organisms health.

Keywords: PAHs, blood metabolic factors, Periophthalmus waltoni, Hormuz Strait

Procedia PDF Downloads 320
665 Geovisualization of Human Mobility Patterns in Los Angeles Using Twitter Data

Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 106
664 Anaerobic Digestion Batch Study of Taxonomic Variations in Microbial Communities during Adaptation of Consortium to Different Lignocellulosic Substrates Using Targeted Sequencing

Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

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663 Land Cover Classification Using Sentinel-2 Image Data and Random Forest Algorithm

Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

Abstract:

The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

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662 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

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Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 224
661 Agrarian Transitions and Rural Social Relations in Jharkhand, India

Authors: Avinash

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Rural Jharkhand has attracted lesser attention in the field of agrarian studies in India, despite more than eighty percent of its rural population being directly dependent on agriculture as their primary source of livelihood. The limited studies on agrarian issues in Jharkhand have focused predominantly on the subsistence nature of agriculture and low crop productivity. There has also not been much research on agrarian social relations between ‘tribe’ and ‘non-tribe’ communities in the region. This paper is an attempt to understand changing agrarian social relations between tribal and non-tribal communities relating them to different kinds of agrarian transitions taking place in two districts of Jharkhand - Palamu and Khunti. In the Palamu region, agrarian relations are dominated by the presence and significant population size of Hindu high caste land owners, whereas in the Khunti region, agrarian relations are characterized by the population size and dominance of tribes and lower caste land owner cum cultivators. The agrarian relations between ‘upper castes’ and ‘tribes’ in these regions are primarily related to agricultural daily wage labour. However, the agrarian social relations between Dalits and tribal people take the form of ‘communal system of labour exchange’ and ‘household-based labour’. In addition, the ethnographic study of the region depicts steady agrarian transitions (especially shift from indigenous to ‘High Yielding Variety’ (HYV) paddy seeds and growing vegetable cultivation) where ‘Non-Governmental Organizations’ (NGOs) and agricultural input manufacturers and suppliers are playing a critical role in agrarian transitions as intermediaries. While agricultural productivity still remains low, both the regions are witnessing slow but gradual agrarian transitions. Rural-urban linkages in the form of seasonal labour migration are creating capital and technical inflows that are transforming agricultural activities. This study describes and interprets the above changes through the lens of ‘regional rurality’.

Keywords: agrarian transitions, rural Jharkhand, regional rurality, tribe and non-tribe

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660 The Neurofunctional Dissociation between Animal and Tool Concepts: A Network-Based Model

Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from McRae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-worls, resilience to damage

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659 A Small-Scale Study of Fire Whirls and Investigation of the Effects of Near-Ground Height on the Behavior of Fire Whirls

Authors: M. Arabghahestani, A. Darwish Ahmad, N. K. Akafuah

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In this work, small-scale experiments of fire whirl were conducted to study the spinning fire phenomenon and to gain comprehensive understandings of fire tornadoes and the factors that affect their behavior. High speed imaging was used to track the flames at both temporal and spatial scales. This allowed us to better understand the role of the near-ground height in creating a boundary layer flow profile that, in turn contributes to formation of vortices around the fire, and consequent fire whirls. Based on the results obtained from these observations, we were able to spot the differences in the fuel burning rate of the fire itself as a function of a newly defined specific non-dimensional near-ground height. Based on our observations, there is a cutoff non-dimensional height, beyond which a normal fire can be turned into a fire whirl. Additionally, the results showed that the fire burning rate decreases by moving the fire to a height higher than the ground level. These effects were justified by the interactions between vortices formed by, the back pressure and the boundary layer velocity profile, and the vortices generated by the fire itself.

Keywords: boundary layer profile, fire whirls, near-ground height, vortex interactions

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658 From Data Processing to Experimental Design and Back Again: A Parameter Identification Problem Based on FRAP Images

Authors: Stepan Papacek, Jiri Jablonsky, Radek Kana, Ctirad Matonoha, Stefan Kindermann

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FRAP (Fluorescence Recovery After Photobleaching) is a widely used measurement technique to determine the mobility of fluorescent molecules within living cells. While the experimental setup and protocol for FRAP experiments are usually fixed, data processing part is still under development. In this paper, we formulate and solve the problem of data selection which enhances the processing of FRAP images. We introduce the concept of the irrelevant data set, i.e., the data which are almost not reducing the confidence interval of the estimated parameters and thus could be neglected. Based on sensitivity analysis, we both solve the problem of the optimal data space selection and we find specific conditions for optimizing an important experimental design factor, e.g., the radius of bleach spot. Finally, a theorem announcing less precision of the integrated data approach compared to the full data case is proven; i.e., we claim that the data set represented by the FRAP recovery curve lead to a larger confidence interval compared to the spatio-temporal (full) data.

Keywords: FRAP, inverse problem, parameter identification, sensitivity analysis, optimal experimental design

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657 Evaluation of Environmental Impact Assessment of Dam Using GIS/Remote Sensing-Review

Authors: Ntungamili Kenosi, Moatlhodi W. Letshwenyo

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Negative environmental impacts due to construction of large projects such as dams have become an important aspect of land degradation. This paper will review the previous literature on the previous researches or study in the same area of study in the other parts of the world. After dam has been constructed, the actual environmental impacts are investigated and compared to the predicted results of the carried out Environmental Impact Assessment. GIS and Remote Sensing, play an important role in generating automated spatial data sets and in establishing spatial relationships. Results from other sources shows that the normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining. This is mainly due to the expansion of agricultural land and escalating human made structures in the area. Urgent environmental conservation is necessary when adjoining projects site. Less study on the evaluation of EIA on dam has been conducted in Botswana hence there is a need for the same study to be conducted and then it will be easy to be compared to other studies around the world.

Keywords: Botswana, dam, environmental impact assessment, GIS, normalized vegetation index (NDVI), remote sensing

Procedia PDF Downloads 396
656 Development of Pre-Mitigation Measures and Its Impact on Life-Cycle Cost of Facilities: Indian Scenario

Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

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655 I Don’t Know How I Got Here and I Don’t Know How to Get out of It: Understanding Male Pre-service Early Child Education Teachers’ Construction of Professional Identity

Authors: Sabika Khalid, Endale Fantahun Tadesse

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Unlike other professional sectors, a great deal of studies has addressed the overwhelming gender disparity phenomena in the early childhood education (ECE) workforce, which is acknowledged for the dominance of women over men teachers. The irony of ECE being a gendered working environment is not only observed in societies that are ruled by gender roles but also in Western countries that claim to margin the gender gap in several professions. The participation of male teachers in ECE across most countries ranged from 1% to 3% of the total preschool or kindergarten teachers. When it comes to a dynamic Chinese society tempered with a deep-rooted tradition and cultural ideology, the ECE has no less place for males, and males have a low place for ECE. According to the Ministry of Education of China (2020), there are over 5 million kindergarten teachers and staff members, while only 2.3% are accounted for male teachers. The traditional gender-based discourse asserts that giving care and guidance for young children related to nurturing ‘mothering’ labels the profession in ECE as women’s work derived from originated from their ‘naturality.’ Although a large volume of evidence sheds light on the cause for low male teachers, the perception of parents, female teachers working with male teachers, and the experience of male teachers working in ECE, less is known and understood before being a teacher. Hence, this study argues that the promotion of the involvement of male teachers in light of their masculinity identity asset in the children's learning environment is comprehended to understand the construction of male student teachers' (preservice) professional identity during early childhood teacher training that allows obtaining substantial evidence that provides a feasible and robust implication in the preparation of competent and professional male preschool teachers that understand, cherish, and bring harmony in Chinese ECE through professionalism socialization with the stakeholders. This study intended to reveal male ECE preservice teachers’ knowledge of their professional identity, i.e., how they perceive themselves as a teacher and what factors agents these perceptions towards their professional identity.

Keywords: male teachers, Early Childhood Education (ECE), self-identity, perception of stakeholders

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654 A Survey of Recognizing of Daily Living Activities in Multi-User Smart Home Environments

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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653 Cultural Adaptation of Foreign Students in Vienna, A Sociolinguistic Case Study of Iranian Students in Vienna

Authors: Roshanak Nouralian

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The primary focus of my Ph.D. dissertation revolves around the interconnection between language and culture, as well as the crucial role that language plays in facilitating communication and fostering integration within the host society for immigrants. This research specifically focuses on Iranian students studying at various universities in Vienna. Throughout this study, I have attempted to examine and analyze their challenges in various life situations in Austria. The broad dimensions of the research question led the research process to apply a constructivist grounded theory strategy. I have also used critical discourse analysis that is in line with constructivist GT's point of view to look closely at the borders, contradictions, and inequalities that came up in the participants' real-life experiences. Data from individual interviews and group discussions have expanded the research trajectory beyond disciplinary boundaries toward a transdisciplinary approach. The research findings indicate how the language policy of the host society leads to the establishment of power relationships and the arousal of a sense of cultural dominance among the research participants. This study investigates the problems experienced by participants in their daily interactions within the host society. Additionally, the results illustrate the development of a dependency relationship between participants and their host society despite linguistic policies that cause a sense of cultural hegemony. Conversely, the obtained data allowed me to examine the participants' language ideologies. The findings of this study show that social linguistics has the potential to go beyond the boundaries of its field. This is possible by using a variety of research strategies and analyzing people's real-life experiences to find out how language affects different parts of their daily lives. Therefore, in this conference, discussing the logic of employing a constructivist GT strategy along with critical discourse analysis (CDA) in this research, I intend to discuss the achieved results.

Keywords: cultural adapttaion, language policy, language ideology, cultural hegemony, transdisciplinary research, constructivist grounded theory, critical discourse analysis

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652 Critical Evaluation of Groundwater Monitoring Networks for Machine Learning Applications

Authors: Pedro Martinez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Esperanza Montero, Miguel Martín-Loeches

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Groundwater monitoring networks are critical in evaluating the vulnerability of groundwater resources to depletion and contamination, both in space and time. Groundwater monitoring networks typically grow over decades, often in organic fashion, with relatively little overall planning. The groundwater monitoring networks in the Madrid area, Spain, were reviewed for the purpose of identifying gaps and opportunities for improvement. Spatial analysis reveals the presence of various monitoring networks belonging to different institutions, with several hundred observation wells in an area of approximately 4000 km2. This represents several thousand individual data entries, some going back to the early 1970s. Major issues included overlap between the networks, unknown screen depth/vertical distribution for many observation boreholes, uneven time series, uneven monitored species, and potentially suboptimal locations. Results also reveal there is sufficient information to carry out a spatial and temporal analysis of groundwater vulnerability based on machine learning applications. These can contribute to improve the overall planning of monitoring networks’ expansion into the future.

Keywords: groundwater monitoring, observation networks, machine learning, madrid

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651 Association of Work Pattern with the Well-Being and Happiness: Evidence from Married Women Working in Delhi, India

Authors: Kanchan Negi

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Background: Modern work culture has driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and well-being (including happiness) in a sample of working women. Method: Primary data of 360 currently married women working in the education, health, banking and IT sector in Delhi, India, were analysed. Logistic regression was used to estimate physical and psychological well-being and happiness across work characteristics. Results: Relative to 35–40 hours/week, working longer related to poor well-being (ß=0.75, 95% CI 0.12 to 1.39). Compared with not working weekends, working most or all weekends is related to poor physical (ß=0.34, 95% CI 0.08 to 0.61) and psychological well-being (ß=0.50, 95% CI 0.20 to 0.79). Rigid work patterns (ß=0.17, 95% CI −0.09 to 0.42) are also related to poor well-being. Conclusion: Decreased well-being and unhappiness are significantly linked to strenuous and rigid work patterns, suggesting that modern work culture may contribute to poor well-being. Flexible timings, compensatory holidays, work-from-home, and daycare facilities for young ones must be welcomed by companies to ease the dual burden of homemakers and career makers.

Keywords: happiness, well-being, work pattern, working women

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650 Enhancing Scalability in Ethereum Network Analysis: Methods and Techniques

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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649 Sustainable Design of Coastal Bridge Networks in the Presence of Multiple Flood and Earthquake Risks

Authors: Riyadh Alsultani, Ali Majdi

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It is necessary to develop a design methodology that includes the possibility of seismic events occurring in a region, the vulnerability of the civil hydraulic structure, and the effects of the occurrence hazard on society, environment, and economy in order to evaluate the flood and earthquake risks of coastal bridge networks. This paper presents a design approach for the assessment of the risk and sustainability of coastal bridge networks under time-variant flood-earthquake conditions. The social, environmental, and economic indicators of the network are used to measure its sustainability. These consist of anticipated loss, downtime, energy waste, and carbon dioxide emissions. The design process takes into account the possibility of happening in a set of flood and earthquake scenarios that represent the local seismic activity. Based on the performance of each bridge as determined by fragility assessments, network linkages are measured. The network's connections and bridges' damage statuses after an earthquake scenario determine the network's sustainability and danger. The sustainability measures' temporal volatility and the danger of structural degradation are both highlighted. The method is shown using a transportation network in Baghdad, Iraq.

Keywords: sustainability, Coastal bridge networks, flood-earthquake risk, structural design

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648 The Applicability of Western Environmental Criminology Theories to the Arabic Context

Authors: Nawaf Alotaibi, Andy Evans, Alison Heppenstall, Nick Malleson

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Throughout the last two decades, motor vehicle theft (MVT) has accounted for the largest proportion of property crime incidents in Saudi Arabia (SA). However, to date, few studies have investigated SA’s MVT problem. Those that have are primarily focused on the characteristics of car thieves, and most have overlooked any spatial-temporal distribution of MVT incidents and the characteristics of victims. This paper represents the first step in understanding this problem by reviewing the existing MVT studies contextualised within the theoretical frameworks developed in environmental criminology theories – originating in the West – and exploring to what extent they are relevant to the SA context. To achieve this, the paper has identified a range of key features in SA that are different from typical Western contexts, that could limit the appropriateness and capability of applying existing environmental criminology theories. Furthermore, despite these Western studies reviewed so far having introduced a number of explanatory variables for MVT rates, a range of significant elements are apparently absent in the current literature and this requires further analysis. For example, almost no attempts have been made to quantify the associations between the locations of vehicle theft, recovery of stolen vehicles, joyriding and traffic volume.

Keywords: environmental criminology theories, motor vehicle theft, Saudi Arabia, spatial analysis

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647 Decoding the Construction of Identity and Struggle for Self-Assertion in Toni Morrison and Selected Indian Authors

Authors: Madhuri Goswami

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The matrix of power establishes the hegemonic dominance and supremacy of one group through exercising repression and relegation upon the other. However, the injustice done to any race, ethnicity, or caste has instigated the protest and resistance through various modes -social campaigns, political movements, literary expression and so on. Consequently, the search for identity, the means of claiming it and strive for recognition have evolved as the persistent phenomena all through the world. In the discourse of protest and minority literature, these two discourses -African American and Indian Dalit- surprisingly, share wrath and anger, hope and aspiration, and quest for identity and struggle for self-assertion. African American and Indian Dalit are two geographically and culturally apart communities that stand together on a single platform. This paper has sought to comprehend the form and investigate the formation of identity in general and in the literary work of Toni Morrison and Indian Dalit writing, particular, i.e., Black identity and Dalit identity. The study has speculated two types of identity, namely, individual or self and social or collective identity in the literary province of these marginalized literature. Morrison’s work outsources that self-identity is not merely a reflection of an inner essence; it is constructed through social circumstances and relations. Likewise, Dalit writings too have a fair record of discovery of self-hood and formation of identity, which connects to the realization of self-assertion and worthiness of their culture among Dalit writers. Bama, Pawar, Limbale, Pawde, and Kamble investigate their true self concealed amid societal alienation. The study has found that the struggle for recognition is, in fact, the striving to become the definer, instead of just being defined; and, this striving eventually, leads to the introspection among them. To conclude, Morrison as well as Indian marginalized authors, despite being set quite distant, communicate the relation between individual and community in the context of self-consciousness, self-identification and (self) introspection. This research opens a scope for further research to find out similar phenomena and trace an analogy in other world literatures.

Keywords: identity, introspection, self-access, struggle for recognition

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646 Macroinvertebrate Variation of Endorheic Depression Wetlands within North West and Mpumalanga Provinces, South Africa

Authors: Lee-Ann Foster, Wynand Malherbe, Martin Ferriera, Johan Van Vuren

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Aquatic macroinvertebrates are rarely used in wetland assessments due to their variability. However, in terms of biodiversity, these invertebrates form an important component of wetlands. The objective of this study was to compare the spatial and temporal variation of macroinvertebrate assemblages within endorheic depressions in Mpumalanga and North West Provinces of South Africa. Sampling was conducted over a period of two seasons during 2012 and 2013 at all sampling points to account for a wet and dry season. The identification of macroinvertebrate community samples resulted in 24 taxa for both provinces. Results showed similarities in the structure of communities in perennial endorheic depressions in both provinces with the exception of one or two species. Macroinvertebrates sampled in Mpumalanga depressions (locally called pans) were similar to those reported in previous studies completed in the area and most of the macroinvertebrates sampled in Mpumalanga and the North West are known to be commonly found in temporary habitats. The knowledge acquired can now be utilised to enhance the available literature on these systems. Long-term studies have to be implemented to better understand the ecological functioning of the pans in the North West Province.

Keywords: aquatic, macroinvertebrate assemblages, pans, spatial variation

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645 Flood Monitoring Using Active Microwave Remote Sensed Synthetic Aperture Radar Data

Authors: Bikramjit Goswami, Manoranjan Kalita

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Active microwave remote sensing is useful in remote sensing applications in cloud-covered regions in the world. Because of high spatial resolution, the spatial variations of land cover can be monitored in greater detail using synthetic aperture radar (SAR). Inundation is studied using the SAR images obtained from Sentinel-1A in both VH and VV polarizations in the present experimental study. The temporal variation of the SAR scattering coefficient values for the area gives a good indication of flood and its boundary. The study area is the district of Morigaon in the state of Assam in India. The period of flood monitoring study is the monsoon season of the year 2017, during which high flood occurred in the state of Assam. The variation of microwave scattering value shows a distinctive indication of flood from the non-flooded period. Frequent monitoring of flood in a large area (10 km x 10 km) using passive microwave sensing and pin-pointing the actual flooded portions (5 m x 5 m) within the flooded area using active microwave sensing, can be a highly useful combination, as revealed by the present experimental results.

Keywords: active remote sensing, flood monitoring, microwave remote sensing, synthetic aperture radar

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644 A Methodology for Optimisation of Water Containment Systems

Authors: Amir Hedjripour

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The required dewatering configuration for a contaminated sediment dam is discussed to meet no-spill criteria for a defined Average Recurrence Interval (ARI). There is an option for the sediment dam to pump the contaminated water to another storage facility before its capacity is exceeded. The system is subjected to a range of storm durations belonging to the design ARI with concurrent dewatering to the other storage facility. The model is set up in 1-minute time intervals and temporal patterns of storm events are used to de-segregate the total storm depth into partial durations. By running the model for selected storm durations, the maximum water volume in the dam is recorded as the critical volume, which indicates the required storage capacity for that storm duration. Runoff from upstream catchment and the direct rainfall over the dam open area are calculated by taking into account the time of concentration for the catchment. Total 99 different storm durations from 5 minutes to 72 hours were modelled together with five dewatering scenarios from 50 l/s to 500 l/s. The optimised dam/pump configuration is selected by plotting critical points for all cases and storage-dewatering envelopes. A simple economic analysis is also presented in the paper using Present-Value (PV) analysis to assist with the financial evaluation of each configuration and selection of the best alternative.

Keywords: contaminated water, optimisation, pump, sediment dam

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643 Neural Networks for Distinguishing the Performance of Two Hip Joint Implants on the Basis of Hip Implant Side and Ground Reaction Force

Authors: L. Parisi

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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: kinemic gait data, neural networks, hip joint implant, hip arthroplasty, rehabilitation engineering

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642 Toward an Understanding of the Neurofunctional Dissociation between Animal and Tool Concepts: A Graph Theoretical Analysis

Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from Mc Rae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-world, resilience to damage

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641 Gender Based Variability Time Series Complexity Analysis

Authors: Ramesh K. Sunkaria, Puneeta Marwaha

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Nonlinear methods of heart rate variability (HRV) analysis are becoming more popular. It has been observed that complexity measures quantify the regularity and uncertainty of cardiovascular RR-interval time series. In the present work, SampEn has been evaluated in healthy Normal Sinus Rhythm (NSR) male and female subjects for different data lengths and tolerance level r. It is demonstrated that SampEn is small for higher values of tolerance r. Also SampEn value of healthy female group is higher than that of healthy male group for short data length and with increase in data length both groups overlap each other and it is difficult to distinguish them. The SampEn gives inaccurate results by assigning higher value to female group, because male subject have more complex HRV pattern than that of female subjects. Therefore, this traditional algorithm exhibits higher complexity for healthy female subjects than for healthy male subjects, which is misleading observation. This may be due to the fact that SampEn do not account for multiple time scales inherent in the physiologic time series and the hidden spatial and temporal fluctuations remains unexplored.

Keywords: heart rate variability, normal sinus rhythm group, RR interval time series, sample entropy

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640 Integration of Artificial Neural Network with Geoinformatics Technology to Predict Land Surface Temperature within Sun City Jodhpur, Rajasthan, India

Authors: Avinash Kumar Ranjan, Akash Anand

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The Land Surface Temperature (LST) is an essential factor accompanying to rise urban heat and climate warming within a city in micro level. It is also playing crucial role in global change study as well as radiation budgets measuring in heat balance studies. The information of LST is very substantial to recognize the urban climatology, ecological changes, anthropological and environmental interactions etc. The Chief motivation of present study focus on time series of ANN model that taken a sequence of LST values of 2000, 2008 and 2016, realize the pattern of variation within the data set and predict the LST values for 2024 and 2032. The novelty of this study centers on evaluation of LST using series of multi-temporal MODIS (MOD 11A2) satellite data by Maximum Value Composite (MVC) techniques. The results derived from this study endorse the proficiency of Geoinformatics Technology with integration of ANN to gain knowledge, understanding and building of precise forecast from the complex physical world database. This study will also focus on influence of Land Use/ Land Cover (LU/LC) variation on Land Surface Temperature.

Keywords: LST, geoinformatics technology, ANN, MODIS satellite imagery, MVC

Procedia PDF Downloads 226