Search results for: spatial batch normalization with dropout
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3240

Search results for: spatial batch normalization with dropout

1320 Statistical and Land Planning Study of Tourist Arrivals in Greece during 2005-2016

Authors: Dimitra Alexiou

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During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: tourism, statistical methods, exponential smoothing, land spatial planning, economy

Procedia PDF Downloads 266
1319 Modeling Food Popularity Dependencies Using Social Media Data

Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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1318 Numerical Modeling on the Vehicle Interior Noise Produced by Rain-the-Roof Excitation

Authors: Zilong Peng, Jun Fan

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With the improvement of the living standards, the requirement on the acoustic comfort of the vehicle interior environment is becoming higher. The rain-the-roof producing interior noise is a common phenomenon for the vehicle, which usually discourages the conversation, especially for the heavy rain. This paper presents some numerical results about the rain-the-roof noise. The impact of each water drop is modeled as a short pulse, and the excitation locations on the roof are generated randomly. The vehicle body is simplified to a box closed with some certain-thickness shells. According to the main frequency components of the rain excitation, the analyzing frequency range is divided as low, high and middle frequency domains, which makes the vehicle body are modeled using finite element method (FEM), statistical energy analysis (SEA) and hybrid FE-SEA method, respectively. Furthermore, the effect of spatial distribution density and size of the rain on the sound pressure level are also discussed. These results may provide a guide for designing a more silent vehicle in the special weather.

Keywords: rain-the-roof noise, vehicle, finite element method, statistical energy analysis

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1317 Supercritical Hydrothermal and Subcritical Glycolysis Conversion of Biomass Waste to Produce Biofuel and High-Value Products

Authors: Chiu-Hsuan Lee, Min-Hao Yuan, Kun-Cheng Lin, Qiao-Yin Tsai, Yun-Jie Lu, Yi-Jhen Wang, Hsin-Yi Lin, Chih-Hua Hsu, Jia-Rong Jhou, Si-Ying Li, Yi-Hung Chen, Je-Lueng Shie

Abstract:

Raw food waste has a high-water content. If it is incinerated, it will increase the cost of treatment. Therefore, composting or energy is usually used. There are mature technologies for composting food waste. Odor, wastewater, and other problems are serious, but the output of compost products is limited. And bakelite is mainly used in the manufacturing of integrated circuit boards. It is hard to directly recycle and reuse due to its hard structure and also difficult to incinerate and produce air pollutants due to incomplete incineration. In this study, supercritical hydrothermal and subcritical glycolysis thermal conversion technology is used to convert biomass wastes of bakelite and raw kitchen wastes to carbon materials and biofuels. Batch carbonization tests are performed under high temperature and pressure conditions of solvents and different operating conditions, including wet and dry base mixed biomass. This study can be divided into two parts. In the first part, bakelite waste is performed as dry-based industrial waste. And in the second part, raw kitchen wastes (lemon, banana, watermelon, and pineapple peel) are used as wet-based biomass ones. The parameters include reaction temperature, reaction time, mass-to-solvent ratio, and volume filling rates. The yield, conversion, and recovery rates of products (solid, gas, and liquid) are evaluated and discussed. The results explore the benefits of synergistic effects in thermal glycolysis dehydration and carbonization on the yield and recovery rate of solid products. The purpose is to obtain the optimum operating conditions. This technology is a biomass-negative carbon technology (BNCT); if it is combined with carbon capture and storage (BECCS), it can provide a new direction for 2050 net zero carbon dioxide emissions (NZCDE).

Keywords: biochar, raw food waste, bakelite, supercritical hydrothermal, subcritical glycolysis, biofuels

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1316 Investigation of Maritime Accidents with Exploratory Data Analysis in the Strait of Çanakkale (Dardanelles)

Authors: Gizem Kodak

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The Strait of Çanakkale, together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: maritime accidents, EDA, Strait of Çanakkale, navigational safety

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1315 Indigo Dye Wastewater Treatment by Fenton Oxidation

Authors: Anurak Khrueakham, Tassanee Chanphuthin

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Indigo is a well-known natural blue dye that is used hither to even though synthetic ones are commercially available. The removal of indigo from effluents is difficult due to its resistance towards biodegradation which causes an aquatic environment effect. Fenton process is a reaction between hydrogen peroxide H2O2 and Fe2+ to generate •OH (highly reactive oxidant (E◦= 2.8 V)). Additionally, •OH is non-selective oxidant which is capable of destroying wide range of organic pollutants in water and wastewater. The aims of this research were to investigate the effect of H2O2, Fe2+ and pH on indigo wastewater oxidation by Fenton process. A liter reactor was operated in all experiments. The batch reactor was prepared by filling 1 liter of indigo wastewater. The pH was adjusted to the desired value; then, FeSO4 at predetermined amount was added. Finally, H2O2 was immediately added to start the Fenton’s reaction. The Fenton oxidation of indigo wastewater was operated for 60 minutes. Residual H2O2 was analyzed using titanium oxalate method. The Fe2+ concentration was determined by phenanthroline method. COD was determined using closed-reflux titrimetric method to indicate the removal efficiency. The results showed that at pH 2 increasing the initial ferrous concentration from 0.1 mM to 1 mM enhanced the indigo removal from 36% to 59%. Fenton reaction was rapidly due to the high generation rate of •OH. The degradation of indigo increased with increasing pH up to pH 3. This can be explained that the scavenging effect of the •OH by H+ in the condition of low pH is severe to form an oxonium ion, resulting in decrease the production of •OH and lower the decolorization efficiency of indigo. Increasing the initial H2O2 concentration from 5 mM to 20 mM could enhance the decolorization. The COD removal was increased from 35% to 65% with increasing H2O2 concentration from 5 mM to 20 mM. The generations of •OH were promoted by the increase of initial H2O2 concentration. However, the higher concentration of H2O2 resulted in the reduction of COD removal efficiency. The initial ferrous concentrations were studied in the range of 0.05-15.0 mM. The results found that the COD removals increased with increasing ferrous concentrations. The COD removals were increased from 32% to 65% when increase the ferrous concentration from 0.5 mM to 10.0 mM. However, the COD removal did not significantly change at higher 10.0 mM. This is because •OH yielding was lower level of oxidation, therefore, the COD removals were not improved. According to the studies, the Fenton’s reagents were important factors for COD removal by Fenton process. The optimum condition for COD removal of indigo dye wastewater was 10.0 mM of ferrous, 20 mM of H2O2 and at pH 3.

Keywords: indigo dye, fenton oxidation, wastewater treatment, advanced oxidation processes

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1314 Distribution of Laurencia caspica, Enteromorpha intestinalis and Cladophora glomerata along the Southern Parts of the Caspian Sea and Their Relation with Environmental Factors

Authors: Neda Mehdipour, Mohammad Hasan Gerami, Reza Rahnama, Ali Hamzehpour, Hanieh Nemati

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Laurencia caspica (red macroalgae) Enteromorpha intestinalis and Cladophora glomerata (green macroalgae) are three major macroalgae that grow along the southern coasts of the Caspian Sea. We investigated spatial and temporal variation of these three macroalgal species on hard substrates and their relation with environmental factors in 2014. Sampling was done seasonally from spring to winter 2014 from eight sites. Results indicated that of these three species had heterogeneity distribution along southern parts of the Caspian Sea. In addition, C. glomerata was dominant taxa in all stations and had maximum contribution in dissimilarities between sampling sites. According to BIO-ENV salinity, pH and Silicate were the best subset variables for explaining changes in the abundance over time of the hard-substrates macroalgae fauna under study. However, the position of species in Redundancy Analysis (RDA) plot revealed that L. caspica associated with temperature, E. intestinalis with pH and C. glomerata associated with phosphate and silicate.

Keywords: macroalgae, distribution, environmental factors, Caspian Sea

Procedia PDF Downloads 388
1313 Exploring Pre-Trained Automatic Speech Recognition Model HuBERT for Early Alzheimer’s Disease and Mild Cognitive Impairment Detection in Speech

Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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1312 A Qualitative Investigation into Street Art in an Indonesian City

Authors: Michelle Mansfield

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Introduction: This paper uses the work of Deleuze and Guattari to consider the street art practice of youth in the Indonesian city of Yogyakarta, a hub of arts and culture in Central Java. Around the world young people have taken to city streets to populate the new informal exhibition spaces outside the galleries of official art institutions. However, rarely is the focus outside the urban metropolis of the ‘Global North.' This paper looks at these practices in a ‘Global South’ Asian context. Space and place are concepts central to understanding youth cultural expression as it emerges on the streets. Deleuze and Guattari’s notion of assemblage enriches understanding of this complex spatial and creative relationship. Yogyakarta street art combines global patterns and motifs with local meanings, symbolism, and language to express local youth voices that convey a unique sense of place on the world stage. Street art has developed as a global urban youth art movement and is theorised as a way in which marginalised young people reclaim urban space for themselves. Methodologies: This study utilised a variety of qualitative methodologies to collect and analyse data. This project took a multi-method approach to data collection, incorporating the qualitative social research methods of ethnography, nongkrong (deep hanging out), participatory action research, online research, in-depth interviews and focus group discussions. Both interviews and focus groups employed photo-elicitation methodology to stimulate rich data gathering. To analyse collected data, rhizoanalytic approaches incorporating discourse analysis and visual analysis were utilised. Street art practice is a fluid and shifting phenomenon, adding to the complexity of inquiry sites. A qualitative approach to data collection and analysis was the most appropriate way to map the components of the street art assemblage and to draw out complexities of this youth cultural practice in Yogyakarta. Major Findings: The rhizoanalytic approach devised for this study proved a useful way of examining in the street art assemblage. It illustrated the ways in which the street art assemblage is constructed. Especially the interaction of inspiration, materials, creative techniques, audiences, and spaces operate in the creations of artworks. The study also exposed the generational tensions between the senior arts practitioners, the established art world, and the young artists. Conclusion: In summary, within the spatial processes of the city, street art is inextricably linked with its audience, its striving artistic community and everyday life in the smooth rather than the striated worlds of the state and the official art world. In this way, the anarchic rhizomatic art practice of nomadic urban street crews can be described not only as ‘becoming-artist’ but as constituting ‘nomos’, a way of arranging elements which are not dependent on a structured, hierarchical organisation practice. The site, streets, crews, neighbourhood and the passers by can all be examined with the concept of assemblage. The assemblage effectively brings into focus the complexity, dynamism, and flows of desire that is a feature of street art practice by young people in Yogyakarta.

Keywords: assemblage, Indonesia, street art, youth

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1311 Hydrogeochemical Characteristics of the Different Aquiferous Layers in Oban Basement Complex Area (SE Nigeria)

Authors: Azubuike Ekwere

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The shallow and deep aquiferous horizons of the fractured and weathered crystalline basement Oban Massif of south-eastern Nigeria were studied during the dry and wet seasons. The criteria were ascertaining hydrochemistry relative to seasonal and spatial variations across the study area. Results indicate that concentrations of major cations and anions exhibit the order of abundance; Ca>Na>Mg>K and HCO3>SO4>Cl respectively, with minor variations across sampling seasons. Major elements Ca, Mg, Na and K were higher for the shallow aquifers than the deep aquifers across seasons. The major anions Cl, SO4, HCO3, and NO3 were higher for the deep aquifers compared to the shallow ones. Two water types were identified for both aquifer types: Ca-Mg-HCO3 and Ca-Na-Cl-SO4. Most of the parameters considered were within the international limits for drinking, domestic and irrigation purposes. Assessment by use of sodium absorption ratio (SAR), percent sodium (%Na) and the wilcox diagram reveals that the waters are suitable for irrigation purposes.

Keywords: shallow aquifer, deep aquifer, seasonal variation, hydrochemistry, Oban massif, Nigeria

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1310 Self-Stigmatization of Deaf and Hard-of-Hearing Students

Authors: Nadezhda F. Mikahailova, Margarita E. Fattakhova, Mirgarita A. Mironova, Ekaterina V. Vyacheslavova, Vladimir A. Mikahailov

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Stigma is a significant obstacle to the successful adaptation of deaf students to the conditions of an educational institution, especially for those who study in inclusion. The aim of the study was to identify the spheres of life which are the most significant for developing of the stigma of deaf students; to assess the influence of factors associated with deafness on the degree of their self-stigmatization (time and degree of hearing loss, type of education - inclusion / differentiation) and to find out who is more prone to stigma - which characteristics of personality, identity, mental health and coping are specific for those deaf who demonstrates stigmatizing attitudes. The study involved 154 deaf and hard-of-hearing students (85 male and 69 female) aged from 18 to 45 years - 28 students of the Herzen State Pedagogical University (St. Petersburg), who study in inclusion, 108 students of the National Research Technological University and 18 students of the Aviation Technical College (Kazan) - students in groups with a sign language interpreter. We used the following methods: modified questionnaire 'Self-assessment and coping strategies' (Jambor & Elliot, 2005), Scale of self-esteem (Rosenberg et al, 1995), 'Big-Five' (Costa&McCrae, 1997), TRF (Becker, 1989), WCQ (Lazarus & Folkman, 1988), self-stigma scale (Mikhailov, 2008). The severity of self-stigmatization of deaf and hard of hearing students was determined by the degree of deafness and the time they live with hearing loss, learning conditions, the type of self-identification (acculturation), personality traits, and the specifics of coping behavior. Persons with congenital hearing loss more often noted a benevolent and sympathetic attitude towards them on the part of the hearers and less often, due to deafness, limited themselves to visiting public places than late deaf people, which indicates 'get rid of' the experience of their defect and normalization of the state. Students studying in conditions of inclusion more often noted the dismissive attitude of society towards deaf people. Individuals with mild to moderate hearing loss were more likely to fear marriage and childbearing because of their deafness than students with profound hearing loss. Those who considered themselves disabled (49% of all respondents) were more inclined to cope with seeking social support and less used 'distancing' coping. Those who believed that their quality of life and social opportunities were most influenced by the attitude of society towards the deaf (39%) were distinguished by a less pronounced sense of self-worth, a desire for autonomy, and frequent usage of 'avoidance' coping strategies. 36.4% of the respondents noted that there have been situations in their lives when people learned that they are deaf, began to treat them worse. These respondents had predominantly deaf acculturation, but more often, they used 'bicultural skills,' specific coping for the deaf, and had a lower level of extraversion and emotional stability. 31.2% of the respondents tried to hide from others that they have hearing problems. They considered themselves to be in a culture of hearing, used coping strategies 'bicultural skills,' and had lower levels of extraversion, cooperation, and emotional stability. Acknowledgment: Supported by the RFBR № 19-013-0040

Keywords: acculturation, coping, deafness, stigmatization

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1309 A Proposal to Integrate Spatially Explicit Ecosystem Services with Urban Metabolic Modelling

Authors: Thomas Elliot, Javier Babi Almenar, Benedetto Rugani

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The integration of urban metabolism (UM) with spatially explicit ecosystem service (ES) stocks has the potential to advance sustainable urban development. It will correct the lack of spatially specificity of current urban metabolism models. Furthermore, it will include into UM not only the physical properties of material and energy stocks and flows, but also the implications to the natural capital that provides and maintains human well-being. This paper presents the first stages of a modelling framework by which urban planners can assess spatially the trade-offs of ES flows resulting from urban interventions of different character and scale. This framework allows for a multi-region assessment which takes into account sustainability burdens consequent to an urban planning event occurring elsewhere in the environment. The urban boundary is defined as the Functional Urban Audit (FUA) method to account for trans-administrative ES flows. ES are mapped using CORINE land use within the FUA. These stocks and flows are incorporated into a UM assessment method to demonstrate the transfer and flux of ES arising from different urban planning implementations.

Keywords: ecological economics, ecosystem services, spatial planning, urban metabolism

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1308 Sparsity-Based Unsupervised Unmixing of Hyperspectral Imaging Data Using Basis Pursuit

Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l1-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l1-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets

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1307 R Software for Parameter Estimation of Spatio-Temporal Model

Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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1306 Increasing Student Engagement through Culturally-Responsive Classroom Management

Authors: Catherine P. Bradshaw, Elise T. Pas, Katrina J. Debnam, Jessika H. Bottiani, Michael Rosenberg

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Worldwide, ethnically and culturally diverse students are at increased risk for school failure, discipline problems, and dropout. Despite decades of concern about this issue of disparities in education and other fields (e.g., 'school to prison pipeline'), there has been limited empirical examination of models that can actually reduce these gaps in schools. Moreover, few studies have examined the effectiveness of in-service teacher interventions and supports specifically designed to reduce discipline disparities and improve student engagement. This session provides an overview of the evidence-based Double Check model which serves as a framework for teachers to use culturally-responsive strategies to engage ethnically and culturally diverse students in the classroom and reduce discipline problems. Specifically, Double Check is a school-based prevention program which includes three core components: (a) enhancements to the school-wide Positive Behavioral Interventions and Supports (PBIS) tier-1 level of support; (b) five one-hour professional development training sessions, each of which addresses five domains of cultural competence (i.e., connection to the curriculum, authentic relationships, reflective thinking, effective communication, and sensitivity to students’ culture); and (c) coaching of classroom teachers using an adapted version of the Classroom Check-Up, which intends to increase teachers’ use of effective classroom management and culturally-responsive strategies using research-based motivational interviewing and data-informed problem-solving approaches. This paper presents findings from a randomized controlled trial (RCT) testing the impact of Double Check, on office discipline referrals (disaggregated by race) and independently observed and self-reported culturally-responsive practices and classroom behavior management. The RCT included 12 elementary and middle schools; 159 classroom teachers were randomized either to receive coaching or serve as comparisons. Specifically, multilevel analyses indicated that teacher self-reported culturally responsive behavior management improved over the course of the school year for teachers who received the coaching and professional development. However, the average annual office discipline referrals issued to black students were reduced among teachers who were randomly assigned to receive coaching relative to comparison teachers. Similarly, observations conducted by trained external raters indicated significantly more teacher proactive behavior management and anticipation of student problems, higher student compliance, less student non-compliance, and less socially disruptive behaviors in classrooms led by coached teachers than classrooms led teachers randomly assigned to the non-coached condition. These findings indicated promising effects of the Double Check model on a range of teacher and student outcomes, including disproportionality in office discipline referrals among Black students. These results also suggest that the Double Check model is one of only a few systematic approaches to promoting culturally-responsive behavior management which has been rigorously tested and shown to be associated with improvements in either student or staff outcomes indicated significant reductions in discipline problems and improvements in behavior management. Implications of these findings are considered within the broader context of globalization and demographic shifts, and their impacts on schools. These issues are particularly timely, given growing concerns about immigration policies in the U.S. and abroad.

Keywords: ethnically and culturally diverse students, student engagement, school-based prevention, academic achievement

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1305 Design and Implementation of a Geodatabase and WebGIS

Authors: Sajid Ali, Dietrich Schröder

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The merging of internet and Web has created many disciplines and Web GIS is one these disciplines which is effectively dealing with the geospatial data in a proficient way. Web GIS technologies have provided an easy accessing and sharing of geospatial data over the internet. However, there is a single platform for easy and multiple accesses of the data lacks for the European Caribbean Association (Europaische Karibische Gesselschaft - EKG) to assist their members and other research community. The technique presented in this paper deals with designing of a geodatabase using PostgreSQL/PostGIS as an object oriented relational database management system (ORDBMS) for competent dissemination and management of spatial data and Web GIS by using OpenGeo Suite for the fast sharing and distribution of the data over the internet. The characteristics of the required design for the geodatabase have been studied and a specific methodology is given for the purpose of designing the Web GIS. At the end, validation of this Web based geodatabase has been performed over two Desktop GIS software and a web map application and it is also discussed that the contribution has all the desired modules to expedite further research in the area as per the requirements.

Keywords: desktop GISSoftware, European Caribbean association, geodatabase, OpenGeo suite, postgreSQL/PostGIS, webGIS, web map application

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1304 Regional Hydrological Extremes Frequency Analysis Based on Statistical and Hydrological Models

Authors: Hadush Kidane Meresa

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The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufficient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments.

Keywords: flood , drought, frequency, magnitude, regionalization, stochastic, ungauged, Poland

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1303 A Diurnal Light Based CO₂ Elevation Strategy for Up-Scaling Chlorella sp. Production by Minimizing Oxygen Accumulation

Authors: Venkateswara R. Naira, Debasish Das, Soumen K. Maiti

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Achieving high cell densities of microalgae under obligatory light-limiting and high light conditions of diurnal (low-high-low variations of daylight intensity) sunlight are further limited by CO₂ supply and dissolved oxygen (DO) accumulation in large-scale photobioreactors. High DO levels cause low growth due to photoinhibition and/or photorespiration. Hence, scalable elevated CO₂ levels (% in air) and their effect on DO accumulation in a 10 L cylindrical membrane photobioreactor (a vertical tubular type) are studied in the present study. The CO₂ elevation strategies; biomass-based, pH control based (types II & I) and diurnal light based, were explored to study the growth of Chlorella sp. FC2 IITG under single-sided LED lighting in the laboratory, mimicking diurnal sunlight. All the experiments were conducted in fed-batch mode by maintaining N and P sources at least 50% of initial concentrations of the optimized BG-11 medium. It was observed that biomass-based (2% - 1st day, 2.5% - 2nd day and 3% - thereafter) and well-known pH control based, type-I (5.8 pH throughout) strategies were found lethal for FC2 growth. In both strategies, the highest peak DO accumulation of 150% air saturation was resulted due to high photosynthetic activity caused by higher CO₂ levels. In the pH control based type-I strategy, automatically resulted CO₂ levels for pH control were recorded so high (beyond the inhibition range, 5%). However, pH control based type-II strategy (5.8 – 2 days, 6.3 – 3 days, 6.7 – thereafter) showed final biomass titer up to 4.45 ± 0.05 g L⁻¹ with peak DO of 122% air saturation; high CO₂ levels beyond 5% (in air) were recorded thereafter. Thus, it became sustainable for obtaining high biomass. Finally, a diurnal light based (2% - low light, 2.5 % - medium light and 3% - high light) strategy was applied on the basis of increasing/decreasing photosynthesis due to increase/decrease in diurnal light intensity. It has resulted in maximum final biomass titer of 5.33 ± 0.12 g L⁻¹, with total biomass productivity of 0.59 ± 0.01 g L⁻¹ day⁻¹. The values are remarkably higher than constant 2% CO₂ level (final biomass titer: 4.26 ± 0.09 g L⁻¹; biomass productivity: 0.27 ± 0.005 g L⁻¹ day⁻¹). However, 135% air saturation of peak DO was observed. Thus, the diurnal light based elevation should be further improved by using CO₂ enriched N₂ instead of air. To the best of knowledge, the light-based CO₂ elevation strategy is not reported elsewhere.

Keywords: Chlorella sp., CO₂ elevation strategy, dissolved oxygen accumulation, diurnal light based CO₂ elevation, high cell density, microalgae, scale-up

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1302 Treatment of Municipal Wastewater by Means of Uv-Assisted Irradiation Technologies: Fouling Studies and Optimization of Operational Parameters

Authors: Tooba Aslam, Efthalia Chatzisymeon

Abstract:

UV-assisted irradiation technologies are well-established for water and wastewater treatment. UVC treatments are widely used at large-scale, while UVA irradiation has more often been applied in combination with a catalyst (e.g. TiO₂ or FeSO₄) in smaller-scale systems. A technical issue of these systems is the formation of fouling on the quartz sleeves that houses the lamps. This fouling can prevent complete irradiation, therefore reducing the efficiency of the process. This paper investigates the effects of operational parameters, such as the type of wastewater, irradiation source, H₂O₂ addition, and water pH on fouling formation and, ultimately, the treatment of municipal wastewater. Batch experiments have been performed at lab-scale while monitoring water quality parameters including: COD, TS, TSS, TDS, temperature, pH, hardness, alkalinity, turbidity, TOC, UV transmission, UV₂₅₄ absorbance, and metal concentrations. The residence time of the wastewater in the reactor was 5 days in order to observe any fouling formation on the quartz surface. Over this period, it was observed that chemical oxygen demand (COD) decreased by 30% and 59% during photolysis (Ultraviolet A) and photo-catalysis (UVA/Fe/H₂O₂), respectively. Higher fouling formation was observed with iron-rich and phosphorous-rich wastewater. The highest rate of fouling was developed with phosphorous-rich wastewater, followed by the iron-rich wastewater. Photo-catalysis (UVA/Fe/H₂O₂) had better removal efficiency than photolysis (UVA). This was attributed to the Photo-Fenton reaction, which was initiated under these operational conditions. Scanning electron microscope (SEM) measurements of fouling formed on the quartz sleeves showed that particles vary in size, shape, and structure; some have more distinct structures and are generally larger and have less compact structure than the others. Energy-dispersive X-ray spectroscopy (EDX) results showed that the major metals present in the fouling cake were iron, phosphorous, and calcium. In conclusion, iron-rich wastewaters are more suitable for UV-assisted treatment since fouling formation on quartz sleeves can be minimized by the formation of oxidizing agents during treatment, such as hydroxyl radicals.

Keywords: advanced oxidation processes, photo-fenton treatment, photo-catalysis, wastewater treatment

Procedia PDF Downloads 79
1301 The Use of X-Ray Computed Microtomography in Petroleum Geology: A Case Study of Unconventional Reservoir Rocks in Poland

Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

Abstract:

High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

Procedia PDF Downloads 259
1300 Images Selection and Best Descriptor Combination for Multi-Shot Person Re-Identification

Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

Abstract:

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

Procedia PDF Downloads 281
1299 Integration GIS–SCADA Power Systems to Enclosure Air Dispersion Model

Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

Abstract:

This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

Procedia PDF Downloads 371
1298 Modeling Thermal Changes of Urban Blocks in Relation to the Landscape Structure and Configuration in Guilan Province

Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab

Abstract:

Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.

Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province

Procedia PDF Downloads 79
1297 A Framework for Automated Nuclear Waste Classification

Authors: Seonaid Hume, Gordon Dobie, Graeme West

Abstract:

Detecting and localizing radioactive sources is a necessity for safe and secure decommissioning of nuclear facilities. An important aspect for the management of the sort-and-segregation process is establishing the spatial distributions and quantities of the waste radionuclides, their type, corresponding activity, and ultimately classification for disposal. The data received from surveys directly informs decommissioning plans, on-site incident management strategies, the approach needed for a new cell, as well as protecting the workforce and the public. Manual classification of nuclear waste from a nuclear cell is time-consuming, expensive, and requires significant expertise to make the classification judgment call. Also, in-cell decommissioning is still in its relative infancy, and few techniques are well-developed. As with any repetitive and routine tasks, there is the opportunity to improve the task of classifying nuclear waste using autonomous systems. Hence, this paper proposes a new framework for the automatic classification of nuclear waste. This framework consists of five main stages; 3D spatial mapping and object detection, object classification, radiological mapping, source localisation based on gathered evidence and finally, waste classification. The first stage of the framework, 3D visual mapping, involves object detection from point cloud data. A review of related applications in other industries is provided, and recommendations for approaches for waste classification are made. Object detection focusses initially on cylindrical objects since pipework is significant in nuclear cells and indeed any industrial site. The approach can be extended to other commonly occurring primitives such as spheres and cubes. This is in preparation of stage two, characterizing the point cloud data and estimating the dimensions, material, degradation, and mass of the objects detected in order to feature match them to an inventory of possible items found in that nuclear cell. Many items in nuclear cells are one-offs, have limited or poor drawings available, or have been modified since installation, and have complex interiors, which often and inadvertently pose difficulties when accessing certain zones and identifying waste remotely. Hence, this may require expert input to feature match objects. The third stage, radiological mapping, is similar in order to facilitate the characterization of the nuclear cell in terms of radiation fields, including the type of radiation, activity, and location within the nuclear cell. The fourth stage of the framework takes the visual map for stage 1, the object characterization from stage 2, and radiation map from stage 3 and fuses them together, providing a more detailed scene of the nuclear cell by identifying the location of radioactive materials in three dimensions. The last stage involves combining the evidence from the fused data sets to reveal the classification of the waste in Bq/kg, thus enabling better decision making and monitoring for in-cell decommissioning. The presentation of the framework is supported by representative case study data drawn from an application in decommissioning from a UK nuclear facility. This framework utilises recent advancements of the detection and mapping capabilities of complex radiation fields in three dimensions to make the process of classifying nuclear waste faster, more reliable, cost-effective and safer.

Keywords: nuclear decommissioning, radiation detection, object detection, waste classification

Procedia PDF Downloads 202
1296 Dynamics of a Reaction-Diffusion Problems Modeling Two Predators Competing for a Prey

Authors: Owolabi Kolade Matthew

Abstract:

In this work, we investigate both the analytical and numerical studies of the dynamical model comprising of three species system. We analyze the linear stability of stationary solutions in the one-dimensional multi-system modeling the interactions of two predators and one prey species. The stability analysis has a lot of implications for understanding the various spatiotemporal and chaotic behaviors of the species in the spatial domain. The analysis results presented have established the possibility of the three interacting species to coexist harmoniously, this feat is achieved by combining the local and global analyzes to determine the global dynamics of the system. In the presence of diffusion, a viable exponential time differencing method is applied to multi-species nonlinear time-dependent partial differential equation to address the points and queries that may naturally arise. The scheme is described in detail, and justified by a number of computational experiments.

Keywords: asymptotically stable, coexistence, exponential time differencing method, global and local stability, predator-prey model, nonlinear, reaction-diffusion system

Procedia PDF Downloads 415
1295 Nitrification and Denitrification Kinetic Parameters of a Mature Sanitary Landfill Leachate

Authors: Tânia F. C. V. Silva, Eloísa S. S. Vieira, João Pinto da Costa, Rui A. R. Boaventura, Vitor J. P. Vilar

Abstract:

Sanitary landfill leachates are characterized as a complex mixture of diverse organic and inorganic contaminants, which are usually removed by combining different treatment processes. Due to its simplicity, reliability, high cost-effectiveness and high nitrogen content (mostly under the ammonium form) inherent in this type of effluent, the activated sludge biological process is almost always applied in leachate treatment plants (LTPs). The purpose of this work is to assess the effect of the main nitrification and denitrification variables on the nitrogen's biological removal, from mature leachates. The leachate samples were collected after an aerated lagoon, at a LTP nearby Porto, presenting a high amount of dissolved organic carbon (1.0-1.3 g DOC/L) and ammonium nitrogen (1.1-1.7 g NH4+-N/L). The experiments were carried out in a 1-L lab-scale batch reactor, equipped with a pH, temperature and dissolved oxygen (DO) control system, in order to determine the reaction kinetic constants at unchanging conditions. The nitrification reaction rate was evaluated while varying the (i) operating temperature (15, 20, 25 and 30ºC), (ii) DO concentration interval (0.5-1.0, 1.0-2.0 and 2.0-4.0 mg/L) and (iii) solution pH (not controlled, 7.5-8.5 and 6.5-7.5). At the beginning of most assays, it was verified that the ammonium stripping occurred simultaneously to the nitrification, reaching up to 37% removal of total dissolved nitrogen. The denitrification kinetic constants and the methanol consumptions were calculated for different values of (i) volatile suspended solids (VSS) content (25, 50 and 100 mL of centrifuged sludge in 1 L solution), (ii) pH interval (6.5-7.0, 7.5-8.0 and 8.5-9.0) and (iii) temperature (15, 20, 25 and 30ºC), using effluent previously nitrified. The maximum nitrification rate obtained was 38±2 mg NH4+-N/h/g VSS (25ºC, 0.5-1.0 mg O2/L, pH not controlled), consuming 4.4±0.3 mg CaCO3/mg NH4+-N. The highest denitrification rate achieved was 19±1 mg (NO2--N+NO3--N)/h/g VSS (30ºC, 50 mL of sludge and pH between 7.5 and 8.0), with a C/N consumption ratio of 1.1±0.1 mg CH3OH/mg (NO2--N+NO3--N) and an overall alkalinity production of 3.7±0.3 mg CaCO3/mg (NO2--N+NO3--N). The denitrification process showed to be sensitive to all studied parameters, while the nitrification reaction did not suffered significant change when DO content was changed.

Keywords: mature sanitary landfill leachate, nitrogen removal, nitrification and denitrification parameters, lab-scale activated sludge biological reactor

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1294 Self-Supervised Pretraining on Sequences of Functional Magnetic Resonance Imaging Data for Transfer Learning to Brain Decoding Tasks

Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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1293 Bulk-Density and Lignocellulose Composition: Influence of Changing Lignocellulosic Composition on Bulk-Density during Anaerobic Digestion and Implication of Compacted Lignocellulose Bed on Mass Transfer

Authors: Aastha Paliwal, H. N. Chanakya, S. Dasappa

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Lignocellulose, as an alternate feedstock for biogas production, has been an active area of research. However, lignocellulose poses a lot of operational difficulties- widespread variation in the structural organization of lignocellulosic matrix, amenability to degradation, low bulk density, to name a few. Amongst these, the low bulk density of the lignocellulosic feedstock is crucial to the process operation and optimization. Low bulk densities render the feedstock floating in conventional liquid/wet digesters. Low bulk densities also restrict the maximum achievable organic loading rate in the reactor, decreasing the power density of the reactor. However, during digestion, lignocellulose undergoes very high compaction (up to 26 times feeding density). This first reduces the achievable OLR (because of low feeding density) and compaction during digestion, then renders the reactor space underutilized and also imposes significant mass transfer limitations. The objective of this paper was to understand the effects of compacting lignocellulose on mass transfer and the influence of loss of different components on the bulk density and hence structural integrity of the digesting lignocellulosic feedstock. 10 different lignocellulosic feedstocks (monocots and dicots) were digested anaerobically in a fed-batch, leach bed reactor -solid-state stratified bed reactor (SSBR). Percolation rates of the recycled bio-digester liquid (BDL) were also measured during the reactor run period to understand the implication of compaction on mass transfer. After 95 ds, in a destructive sampling, lignocellulosic feedstocks digested at different SRT were investigated to quantitate the weekly changes in bulk density and lignocellulosic composition. Further, percolation rate data was also compared to bulk density data. Results from the study indicate loss of hemicellulose (r²=0.76), hot water extractives (r²=0.68), and oxalate extractives (r²=0.64) had dominant influence on changing the structural integrity of the studied lignocellulose during anaerobic digestion. Further, feeding bulk density of the lignocellulose can be maintained between 300-400kg/m³ to achieve higher OLR, and bulk density of 440-500kg/m³ incurs significant mass transfer limitation for high compacting beds of dicots.

Keywords: anaerobic digestion, bulk density, feed compaction, lignocellulose, lignocellulosic matrix, cellulose, hemicellulose, lignin, extractives, mass transfer

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1292 Non-Local Simultaneous Sparse Unmixing for Hyperspectral Data

Authors: Fanqiang Kong, Chending Bian

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Sparse unmixing is a promising approach in a semisupervised fashion by assuming that the observed pixels of a hyperspectral image can be expressed in the form of linear combination of only a few pure spectral signatures (end members) in an available spectral library. However, the sparse unmixing problem still remains a great challenge at finding the optimal subset of endmembers for the observed data from a large standard spectral library, without considering the spatial information. Under such circumstances, a sparse unmixing algorithm termed as non-local simultaneous sparse unmixing (NLSSU) is presented. In NLSSU, the non-local simultaneous sparse representation method for endmember selection of sparse unmixing, is used to finding the optimal subset of endmembers for the similar image patch set in the hyperspectral image. And then, the non-local means method, as a regularizer for abundance estimation of sparse unmixing, is used to exploit the abundance image non-local self-similarity. Experimental results on both simulated and real data demonstrate that NLSSU outperforms the other algorithms, with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, simultaneous sparse representation, sparse regression, non-local means

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1291 Simulation of 1D Dielectric Barrier Discharge in Argon Mixtures

Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

Procedia PDF Downloads 164