Search results for: spatial batch normalization with dropout

Authors: Abebayehu Yohannes, Hsiu-Ling Chen, Chiu-Chen Chang

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Mathematics reading and spatial ability are important learning components in mathematics education. However, many students struggle to understand real-world problems and lack the spatial ability to form internal imagery. To cope with this problem, in this study, an interactive e-book was developed. The result indicated that both groups had a significant increase in the mathematics reading ability test, and a significant difference was observed in the overall mathematics reading score in favor of the experimental group. In addition, the interactive e-book learning mode had significant impacts on students’ spatial ability. It was also found that the richness of content with visual and interactive elements provided in the interactive e-book enhanced students’ satisfaction with the teaching material.

Keywords: interactive e-books, spatial ability, mathematics reading, satisfaction, three view

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Authors: Rubaiyea Uddin, Rebecca Taylor, Emily Levesque

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The hippocampus, located in the limbic system, is most commonly known for its role in memory and spatial navigation (as cited in Brain Reward and Pathways). It maintains an especially important role in specifically episodic and declarative memory. The hippocampus has also recently been linked to dopamine, the reward pathway’s primary neurotransmitter. Since research has found that dopamine also contributes to memory consolidation and hippocampal plasticity, this neurotransmitter is potentially responsible for contributing to the hippocampus’s role in memory formation. In this experiment we tested to see the effect of tactile cues on spatial navigation for eight different mice. We used a radial arm that had one designated “reward” arm containing sucrose. The presence or absence of bedding was our tactile cue. We attempted to see if the memory of that cue would enhance the mice’s memory of having received the reward in that arm. The results from our study showed there was no significant response from the use of tactile cues on spatial navigation on our 129 mice. Tactile cues therefore do not influence spatial navigation.

Keywords: mice, radial arm maze, memory, spatial navigation, tactile cues, hippocampus, reward, sensory skills, Alzheimer's, neuro-degenerative diseases

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Zaqiatul Mardiah, Afdol Tharik Wastono, Abdul Muta'ali

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In general, the Arabic preposition ‘ala encodes the sense of UP-DOWN schema. However, the use of the preposition ‘ala can has many extended schemas that still have relation to its primary sense. In this paper, we show how the framework of cognitive linguistics (CL) based on image schemas can be applied to analyze the spatial semantic of the use of preposition ‘ala in the horizontal and vertical axes. The preposition ‘ala is usually used in the locative sense in which one physical entity is UP-DOWN relation to another physical entity. In spite of that, the cognitive analysis of ‘ala justifies the use of this preposition in many situations to seemingly encode non-up down-related spatial relations, and non-physical relation. This uncovers some of the unsolved issues concerning prepositions in general and the Arabic prepositions in particular the use of ‘ala as a sample. Using the Arabic corpus data, we reveal that in many cases and situations, the use of ‘ala is extended to depict relations other than the ones where the Trajector (TR) is actually in up-down relation to the Landmark (LM). The instances analyzed in this paper show that ‘ala encodes not only the spatial relations in which the TR and the LM are horizontally or vertically related to each other, but also non-spatial relations.

Keywords: image schema, preposition, spatial semantic, up-down relation

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Authors: Mona K. Fehling, Jakob Unger, Dietmar J. Hecker, Bernhard Schick, Joerg Lohscheller

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Voice disorders origin from disturbances of the vibration patterns of the two vocal folds located within the human larynx. Consequently, the visual examination of vocal fold vibrations is an integral part within the clinical diagnostic process. For an objective analysis of the vocal fold vibration patterns, the two-dimensional vocal fold dynamics are captured during sustained phonation using an endoscopic high-speed camera. In this work, we present an approach allowing a fully automatic analysis of the high-speed video data including a computerized classification of healthy and pathological voices. The approach bases on a wavelet-based analysis of so-called phonovibrograms (PVG), which are extracted from the high-speed videos and comprise the entire two-dimensional vibration pattern of each vocal fold individually. Using a principal component analysis (PCA) strategy a low-dimensional feature set is computed from each phonovibrogram. From the PCA-space clinically relevant measures can be derived that quantify objectively vibration abnormalities. In the first part of the work it will be shown that, using a machine learning approach, the derived measures are suitable to distinguish automatically between healthy and pathological voices. Within the approach the formation of the PCA-space and consequently the extracted quantitative measures depend on the clinical data, which were used to compute the principle components. Therefore, in the second part of the work we proposed a strategy to achieve a normalization of the PCA-space by registering the PCA-space to a coordinate system using a set of synthetically generated vibration patterns. The results show that owing to the normalization step potential ambiguousness of the parameter space can be eliminated. The normalization further allows a direct comparison of research results, which bases on PCA-spaces obtained from different clinical subjects.

Keywords: Wavelet-based analysis, Multiscale product, normalization, computer assisted classification, high-speed laryngoscopy, vocal fold analysis, phonovibrogram

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Authors: Sarita Kumari, Ranjit Kumar Upadhyay

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This paper deals with plankton-fish dynamics where the fish population is growing logistically and nonlinearly harvested. The interaction between phytoplankton and zooplankton population is considered to be Crowley-Martin type functional response. It has been assumed that phytoplankton grows logistically and is affected by a space-dependent growth rate. Conditions for the existence of a positive equilibrium point and their stability analysis (both local and global) have been discussed for the non-spatial system. We have discussed maximum sustainable yields as well as optimal harvesting policy for maximizing the economic gain. The stability and existence of Hopf –bifurcation analysis have been discussed for the spatial system. Different conditions for turning pattern formation have been established through diffusion-driven instability analysis. Numerical simulations have been carried out for both non-spatial and spatial models. Phase plane analysis, the largest Lyapunov exponent, and bifurcation theory are used to numerically analyzed the non-spatial system. Our study shows that spatial heterogeneity, the mortality rate of phytoplankton, and constant harvesting of the fish population each play an important role in the dynamical behavior of the marine system.

Keywords: optimal harvesting, pattern formation, spatial heterogeneity, Crowley-Martin functional response

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Authors: Daijun Chen

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Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

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Authors: Lucie Pospíšilová, Robert Osman, Hana Porkertová

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The scholarly literature demonstrates disability and masculinity in conflict with each other. While disability is associated with dependence, weakness, or helplessness, masculinity is associated with independence, strength, and power. Thus, disabled masculinity might be a dilemma experienced on a personal level. The relationship between masculinity and disability is also interesting from a geographical point of view because the conception of space is gendered. In our society, the skills like spatial orientation, working with the maps, and navigation technologies as same as with scale are associated with masculinity. And because these skills are related to the visual imagination, it is the blindness that is associated with the limitation or even the absence of them. Thus, the conflict of masculinity and disability in the spatial experience is very well apparent in the case of visually impaired men. To study this conflict can tell us a lot not only about the experience of visually impaired men but also about the conception of space in geography and in our society. The paper uses Henri Lefebvre's theory of space based on a triad of spatial practice, representations of space, and representational space. It answers the question: How masculinity and disability intersect in the spatial experience of visually impaired men? The data come from research conducted in Brno and Prague (Czechia) in 2020 and 2021 and include 7 interviews and 6 go-alongs with visually impaired men.

Keywords: disability, masculinity, abstract space, spatial experience, visually impaired men

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Authors: Sunarti Sinaga, Hsueh-Jung Lu, Jia-Rong Lin

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Blue mackerel (Scomber australasicus) is a crucial target species for Taiwan coastal fisheries and has maintained its status as the highest-produced species. Timely measurement of spawning status is crucial for determining the correct management strategy for this species. The objective of this study was to determine size at maturity, fecundity, batch fecundity, and spawning frequency on the basis of samples collected from Nan-Fang-Ao fishing port in Yilan during the spawning season from 2017 to 2019. Histological sections indicated that the blue mackerel are multiple spawners. A higher percentage of female fish spawned at the peak of the gonadosomatic index. The 50% sizes at maturity were 32.02, 32.13, and 29.64 cm. Mean total fecundity (batch fecundity) was 165 (103), 229 (96), and 210 (68) oocytes per ovary-free weight (g) for 2017, 2018, and 2019, respectively; fecundity was determined through observation of postovulatory follicles (POFs). The spawning frequencies (spawning fraction) in 2017, 2018, and 2019 were 3–10 days (0.13), 4–14 days (0.08), and 4–12 days (0.08), respectively. The spawning frequencies determined through the 3 estimated methods, namely the sums of (a) hydrated and Day 0 POFs; (b) Day 1+ POFs, and (c) all data combined, were 1 spawning event per 8, 10, and 9 days, respectively. The reproduction of the blue mackerel was greater in 2017 than it was in 2018 or 2019, as indicated by the higher batch fecundity and shorter spawning seasons. Environmental factors should also be considered as a major factor influencing successful reproduction and the spawning season.

Keywords: scomber australasicus, spawning frequency, batch fecundity, fecundity

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Authors: Gilbert Makanda, Roelf Sypkens

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A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: differential equations, knowledge acquisition, least squares nonlinear, dynamical systems

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Authors: Ife O. Bolaji

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Environmental concerns arising from the use of fossil fuels has increased the interest in the development of renewable and sustainable sources of energy. This would minimize the dependence on fossil fuels and serve as future alternatives. Organic wastes contain carbohydrates, proteins and lipids, which can be utilised as carbon sources for the production of bio-based products. Cellulose is the most abundant natural biopolymer, being the main structural component of lignocellulosic materials. The aim of this project is to develop a biological process for the hydrolysis and fermentation of organic wastes into ethanol and organic acids. The hydrolysis and fermentation processes are integrated in a single vessel using undefined mixed culture microorganisms. The anaerobic fermentation of microcrystalline cellulose was investigated in continuous and batch reactors at 25°C with an appropriate growth medium for cellulase formation, hydrolysis, and fermentation. The reactors were inoculated with soil (B1, C1, C3) or sludge from an anaerobic digester (B2, C2) and the breakdown of cellulose was monitored by measuring the production of ethanol, organic acids and the residual cellulose. The batch reactors B1 and B2 showed negligible microbial activity due to inhibition while the continuous reactors, C1, C2 and C3, exhibited little cellulose hydrolysis which was concealed by the cellulose accumulation in the reactor. At the end of the continuous operation, the reactors C1, C2 and C3 were operated under batch conditions. 48%, 34% and 42% cellulose had been fermented by day 88, 55 and 55 respectively of the batch fermentation. Acetic acid, ethanol, propionic acid and butyric acids were the main fermentation products in the reactors. A stable concentration of 0.6 g/l ethanol and 5 g/L acetic acid was maintained in C3 for several weeks due to reduced activity of methanogens caused by the decrease in pH. Thus far, the results have demonstrated that mixed microbial culture is capable of hydrolysing and fermenting cellulose under lenient conditions. The fermentation of cellulose has been found effective in a combination of continuous and batch processes.

Keywords: cellulose, hydrolysis, mixed culture, organic waste

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Authors: Guangtong Xu, Yi He

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Like most historic and cultural cities in China, the historic urban area of Jingmen city is facing a typical spatial problem of fragmentation and fuzzification. This study focuses on exploring a method for evaluating the existing values of historic urban area based on spatial prototype, a concept introduced into urban morphology from 'Archetype' in architectural typology. As the spatial elements and built-up relationship of historic city, spatial prototype has habitual structural characteristics and formal modulus. It is the inherent logic and order rules behind the scattered historic environment, providing a clue to understand the spatial characteristics and a basis for guiding the construction and conservation in historic urban areas. Three criteria, the resolution of historical elements, the completeness of historical structure and the renewal potential of associated land, were selected to construct the integrated assessment system. These three dimensions are linked to the spatial prototype and its constituent elements, as well as the transformation relationship in ancient and present day. The results showed that historic urban areas have changed from a holistic city to different existing types dominated by their historic structure elements. It is necessary to improve the pertinence of planning strategies and develop diversified management measures in the conservation scope of historic urban area. Moreover, a constructive-conservation strategy should be put forward to enhance the integrity of historic urban area based on the trace of spatial prototype and evaluation results.

Keywords: constructive conservation, existing value, historic urban area, spatial prototype

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Authors: Zohra Mekranfar, Ahmed Saidi, Abdellah Mebrek

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This work aims to develop multi-criteria decision making (MCDM) and spatial data warehouse (SDW) methods, which will be integrated into a GIS according to a ‘GIS dominant’ approach. The GIS operating tools will be operational to operate the SDW. The MCDM methods can provide many solutions to a set of problems with various and multiple criteria. When the problem is so complex, integrating spatial dimension, it makes sense to combine the MCDM process with other approaches like data mining, ascending analyses, we present in this paper an experiment showing a geo-decisional methodology of SWD construction, On-line analytical processing (OLAP) technology which combines both basic multidimensional analysis and the concepts of data mining provides powerful tools to highlight inductions and information not obvious by traditional tools. However, these OLAP tools become more complex in the presence of the spatial dimension. The integration of OLAP with a GIS is the future geographic and spatial information solution. GIS offers advanced functions for the acquisition, storage, analysis, and display of geographic information. However, their effectiveness for complex spatial analysis is questionable due to their determinism and their decisional rigor. A prerequisite for the implementation of any analysis or exploration of spatial data requires the construction and structuring of a spatial data warehouse (SDW). This SDW must be easily usable by the GIS and by the tools offered by an OLAP system.

Keywords: data warehouse, GIS, MCDM, SOLAP

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Authors: Balachandra Kumaraswamy, P. G. Poonacha

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Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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Authors: Caiwei Zhu, Remke Klapwijk

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Spatial thinking, a way of thinking based on the understanding and reasoning of spatial concepts and representations, is embedded in science, technology, engineering, arts, and mathematics (STEAM) learning. Aside from many studies that successfully used targeted training to improve students’ spatial thinking skills, few have closely examined how spatial thinking can be trained in classroom settings. Design and technology education, which receives increasing attention towards its integration into formal curriculums, inherently encompasses a wide range of spatial activities, such as constructing mental representations of design ideas, mentally transforming objects and materials to form designs, visually communicating design plans through annotated drawings, and creating 2D and 3D design artifacts. Among different design topics, biomimicry offers a unique avenue for students to recognize and analyze the shapes and structures in nature. By mapping the forms of plants and animals onto functions, students gain inspiration to solve human design challenges. This study is one of the first to highlight opportunities for training spatial thinking in a biomimicry design project for primary school students. Embracing methodological principles of educational design-based research, this case study is conducted along with iterations in the design of the intervention and collaboration with teachers. Data are harvested from small groups of 10- to 12-year-olds at an international school in the Netherlands. Classroom videos, semi-structured interviews with students, design drawings and artifacts, formative assessment, and the pre- and post-intervention spatial test triangulate evidence for students' spatial thinking. In addition to contributing to a theory of integrating spatial thinking in the primary curriculum, mechanisms underlying such improvement in spatial thinking are explored and discussed.

Keywords: biomimicry, design and technology education, primary education, spatial thinking

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Authors: César Huiliñir, Danilo Villanueva, Pedro Iván Alvarez, Francisco Cubillos

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Biodrying aims at removing water from biowastes and has been mostly studied for municipal solid wastes (MSW), while few studies have dealt with secondary sludge from the paper and pulp industry. The goal of this study was to investigate the effect of initial moisture content (MC) on the batch biodrying of pulp and paper secondary sludge, using rice husks as bulking agents. Three initial MCs were studied (54, 65, and 74% w.b.) in closed batch laboratory-scale reactors under adiabatic conditions and with a constant air-flow rate (0.65 l min-1 kg-1 wet solid). The initial MC of the mixture of secondary sludge and rice husks showed a significant effect on the biodrying process. Using initial moisture content between 54-65% w.b., the solid moisture content was reduce up to 37 % w.b. in ten days, getting calorific values between 8000-9000 kJ kg-1. It was concluded that a decreasing of initial MC improves the drying rate and decreases the solid volatile consumption, therefore, the optimization of biodrying should consider this parameter.

Keywords: biodrying, secondary sludge, initial moisture content, pulp and paper industry, rice husk

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Authors: Hsin-Yueh Chang, Pin-Chen Liao, Jo-Shu Chang, Chun-Yen Chen

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Biofuel has drawn much attention as a potential substitute to fossil fuels. However, biodiesel from waste oil, oil crops or other oil sources can only satisfy partial existing demands for transportation. Due to the feature of being clean, green and viable for mass production, using microalgae as a feedstock for biodiesel is regarded as a possible solution for a low-carbon and sustainable society. In particular, Thraustochytrium sp. BM2, an indigenous heterotrophic microalga, possesses the potential for metabolizing glycerol to produce lipids. Hence, it is being considered as a promising microalgae-based oil source for biodiesel production and other applications. This study was to optimize the culture pH, scale up, assess the feasibility of producing microalgal lipid from crude glycerol and apply operation strategies following optimal results from shake flask system in a 5L stirred-tank fermenter for further enhancing lipid productivities. Cultivation of Thraustochytrium sp. BM2 without pH control resulted in the highest lipid production of 3944 mg/L and biomass production of 4.85 g/L. Next, when initial glycerol and corn steep liquor (CSL) concentration increased five times (50 g and 62.5 g, respectively), the overall lipid productivity could reach 124 mg/L/h. However, when using crude glycerol as a sole carbon source, direct addition of crude glycerol could inhibit culture growth. Therefore, acid and metal salt pretreatment methods were utilized to purify the crude glycerol. Crude glycerol pretreated with acid and CaCl₂ had the greatest overall lipid productivity 131 mg/L/h when used as a carbon source and proved to be a better substitute for pure glycerol as carbon source in Thraustochytrium sp. BM2 cultivation medium. Engineering operation strategies such as fed-batch and semi-batch operation were applied in the cultivation of Thraustochytrium sp. BM2 for the improvement of lipid production. In cultivation of fed-batch operation strategy, harvested biomass 132.60 g and lipid 69.15 g were obtained. Also, lipid yield 0.20 g/g glycerol was same as in batch cultivation, although with poor overall lipid productivity 107 mg/L/h. In cultivation of semi-batch operation strategy, overall lipid productivity could reach 158 mg/L/h due to the shorter cultivation time. Harvested biomass and lipid achieved 232.62 g and 126.61 g respectively. Lipid yield was improved from 0.20 to 0.24 g/g glycerol. Besides, product costs of three kinds of operation strategies were also calculated. The lowest product cost 12.42 $NTD/g lipid was obtained while employing semi-batch operation strategy and reduced 33% in comparison with batch operation strategy.

Keywords: heterotrophic microalga Thrasutochytrium sp. BM2, microalgal lipid, crude glycerol, fermentation strategy, biodiesel

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Authors: Pierre F. Gerard, Frederic F. Leymarie, William Latham

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Architects have developed a series of objective evaluations, using spatial analysis tools such as Isovist, that show how certain spatial qualities are beneficial to specific human activities hosted in the built environments. In return, they can build more adapted environments by tuning those spatial qualities in their design. In parallel, virtual reality technologies have been developed by engineers with the dream of creating a system that immerses users in a new form of spatial experiences. They already have demonstrated a useful range of benefits not only in simulating critical events to assist people in acquiring new skills, but also to enhance memory retention, to name just a few. This paper investigates the effects of two spatial qualities, openness, and complexity, on cognitive performance within immersive virtual environments. Isovist measure is used to design a series of room settings with different levels of each spatial qualities. In an empirical study, each room was then used by every participant to solve a navigational puzzle game and give a rating of their spatial experience. They were then asked to fill in a questionnaire before solving the visual-spatial memory quiz, which addressed how well they remembered the different rooms. Findings suggest that those spatial qualities have an effect on some of the measures, including navigation performance and memory retention. In particular, there is an order effect for the navigation puzzle game. Participants tended to spend a longer time in the complex room settings. Moreover, there is an interaction effect while with more open settings, participants tended to perform better when in a simple setting; however, with more closed settings, participants tended to perform better in a more complex setting. For the visual-spatial memory quiz, participants performed significantly better within the more open rooms. We believe this is a first step in using virtual environments to enhance participant cognitive performances through better use of specific spatial qualities.

Keywords: architecture, navigation, spatial cognition, virtual reality

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Authors: Htet Khaing Lin

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This study explores the relationship between a diverse set of variables, encompassing both environmental and socio-economic factors, and poverty levels in the Philippines for the years 2012, 2015, and 2018. Employing Ordinary Least Squares (OLS), Spatial Lag Models (SLM), and Spatial Error Models (SEM), this study delves into the dynamics of key indicators, including daytime and nighttime land surface temperature, cropland surface, urban land surface, rainfall, population size, normalized difference water, vegetation, and drought indices. The findings reveal consistent patterns and unexpected correlations, highlighting the need for nuanced policies that address the multifaceted challenges arising from the interplay of environmental and socio-economic factors.

Keywords: poverty analysis, OLS, spatial lag models, spatial error models, Philippines, google earth engine, satellite data, environmental dynamics, socio-economic factors

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Authors: Rahma Fitriani, Zerlita Fahdha Pusdiktasari, Herman Cahyo Diartho

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Spatial panel model is commonly used to specify more complicated behavior of economic agent distributed in space at an individual-spatial unit level. There are several spatial panel models which can be adapted based on certain assumptions. A package called splm in R has several functions, ranging from the estimation procedure, specification tests, and model selection tests. In the absence of prior assumptions, a comprehensive procedure which utilizes the available functions in splm must be formed, which is the objective of this study. In this way, the best specification and model can be fitted based on data. The implementation of the procedure works well. It specifies SARAR-FE as the best model for agricultural productivity growth of the 38 East Java’s Regencies/Municipalities.

Keywords: spatial panel, specification, splm, agricultural productivity growth

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Authors: Ali W. N. Alattabi, Clare B. Harris, Rafid M. Alkhaddar, Montserrat Ortoneda, David A. Phipps, Ali Alzeyadi, Khalid S. Hashim

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This study was performed to optimise the hydraulic retention time (HRT) and study its effects on the sludge characteristics and the effluent quality in an aerobic suspension sequencing batch reactor (ASSBR) treating synthetic wastewater. The results showed that increasing the HRT from 6 h to 12 h significantly improved the COD and Nitrate removal efficiency; it was increased from 78.7% - 75.7% to 94.7% – 97% for COD and Nitrate respectively. However, increasing the HRT from 12 h to 18 h reduced the COD and Nitrate removal efficiency from 94.7% - 97% to 91.1% – 94.4% respectively. Moreover, Increasing the HRT from 18 h to 24 h did not affect the COD and Nitrate removal efficiency. Sludge volume index (SVI) was used to monitor the sludge settling performance. The results showed a direct relationship between the HRT and SVI value. Increasing the HRT from 6 h to 12 h led to decrease the SVI value from 123 ml/g to 82.5 ml/g, and then it remained constant despite of increasing the HRT from 12 h to 18 h and to 24 h. The results obtained from this study showed that the HRT of 12 h was better for COD and Nitrate removal and a good settling performance occurred during that range.

Keywords: COD, hydraulic retention time, nitrate, sequencing batch reactor, sludge characteristics

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Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

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Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

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Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: feature fusion, image retrieval, membership function, normalization

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Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Cormac Reale, Luke J. Prendergast, Kenneth Gavin

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While significant improvements have been made in axial pile design methods over recent years, the influence of soils natural variability has not been adequately accounted for within them. Soil variability is a crucial parameter to consider as it can account for large variations in pile capacity across the same site. This paper seeks to address this knowledge deficit, by demonstrating how soil spatial variability can be accommodated into existing cone penetration test (CPT) based pile design methods, in the form of layered non-homogeneous random fields. These random fields model the scope of a given property’s variance and define how it varies spatially. A Monte Carlo analysis of the pile will be performed taking into account parameter uncertainty and spatial variability, described using the measured scales of fluctuation. The results will be discussed in light of Eurocode 7 and the effect of spatial averaging on design capacities will be analysed.

Keywords: pile axial design, reliability, spatial variability, CPT

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Authors: Elżbieta Antczak

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Cities offer important opportunities for economic development and for expanding access to basic services, including health care and education, for large numbers of people. Moreover, green areas (as an integral part of sustainable urban development) present a major opportunity for improving urban environments, quality of lives and livelihoods. This paper examines, using spatial concentration and spatial taxonomic measures, regional diversification of greenery in the cities of Poland. The analysis includes location quotients, Lorenz curve, Locational Gini Index, and the synthetic index of greenery and spatial statistics tools: (1) To verify the occurrence of strong concentration or dispersion of the phenomenon in time and space depending on the variable category, and, (2) To study if the level of greenery depends on the spatial autocorrelation. The data includes the greatest Polish cities, categories of the urban greenery (parks, lawns, street greenery, and green areas on housing estates, cemeteries, and forests) and the time span 2004-2015. According to the obtained estimations, most of cites in Poland are already taking measures to become greener. However, in the country there are still many barriers to well-balanced urban greenery development (e.g. uncontrolled urban sprawl, poor management as well as lack of spatial urban planning systems).

Keywords: greenery, urban areas, regional spatial diversification and concentration, spatial taxonomic measure

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Authors: Amin Mojiri, Hamidi Abdul Aziz

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Leachate is created while water penetrates through the waste in a landfill, carrying some forms of pollutants. In literature, for treatment of wastewater and leachate, different ways of biological treatment were used. Sequencing batch reactor (SBR) is a kind of biological treatment. This study investigated the co-treatment of landfill leachate and domestic waste water by SBR and powdered activated carbon augmented (PAC) SBR process. The response surface methodology (RSM) and central composite design (CCD) were employed. The independent variables were aeration rate (L/min), contact time (h), and the ratio of leachate to wastewater mixture (%; v/v)). To perform an adequate analysis of the aerobic process, three dependent parameters, i.e. COD, color, and ammonia-nitrogen (NH3-N or NH4-N) were measured as responses. The findings of the study indicated that the PAC-SBR showed a higher performance in elimination of certain pollutants, in comparison with SBR. With the optimal conditions of aeration rate (0.6 L/min), leachate to waste water ratio (20%), and contact time (10.8 h) for the PAC-SBR, the removal efficiencies for color, NH3-N, and COD were 72.8%, 98.5%, and 65.2%, respectively.

Keywords: co-treatment, landfill Leachate, wastewater, sequencing batch reactor, activate carbon

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Authors: Jiawei Li

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How cooperation emerges and persists in a population of selfish agents is a fundamental question in evolutionary game theory. Our research shows that Collective Strategies with Master-Slave Mechanism (CSMSM) defeat Tit-for-Tat and other well-known strategies in spatial iterated prisoner’s dilemma. A CSMSM identifies kin members by means of a handshaking mechanism. If the opponent is identified as non-kin, a CSMSM will always defect. Once two CSMSMs meet, they play master and slave roles. A mater defects and a slave cooperates in order to maximize the master’s payoff. CSMSM outperforms non-collective strategies in spatial IPD even if there is only a small cluster of CSMSMs in the population. The existence and performance of CSMSM in spatial iterated prisoner’s dilemma suggests that cooperation first appears and persists in a group of collective agents.

Keywords: Evolutionary game theory, spatial prisoners dilemma, collective strategy, master-slave mechanism

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Authors: Rania Ajmi, Faiza Allouche Khebour, Aude Nuscia Taibi, Sirine Essasi

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Urban green spaces (UGS) as an important contributor can be a significant part of sustainable development. A spatial method was employed to assess and map the spatial distribution of UGS in five districts in Sousse, Tunisia. Ecological management of UGS is an essential factor for the sustainable development of the city; hence the municipality of Sousse has decided to support the districts according to different green spaces characters. And to implement this policy, (1) a new GIS web application was developed, (2) then the implementation of the various green spaces was carried out, (3) a spatial mapping of UGS using Quantum GIS was realized, and (4) finally a data processing and statistical analysis with RStudio programming language was executed. The intersection of the results of the spatial and statistical analyzes highlighted the presence of an imbalance in terms of the spatial UGS distribution in the study area. The discontinuity between the coast and the city's green spaces was not designed in a spirit of network and connection, hence the lack of a greenway that connects these spaces to the city. Finally, this GIS support will be used to assess and monitor green spaces in the city of Sousse by decision-makers and will contribute to improve the well-being of the local population.

Keywords: distributions, GIS, green space, imbalance, spatial analysis

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

Procedia PDF Downloads 34