Search results for: spatial metrics

Authors: Maryam Khalili, Fateme Ghanei

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As one of the most significant phenomena of industrialized societies, tourism plays a key role in encouraging regional developments and enhancing higher standards of living for local communities in particular. Traveling is a formative experience endowed with lessons on various aspects of life. It allows us learning how to enhance the social position as well as the social relationships. However, people forget the need to travel and gain first-hand experiences as they have to cope with the ever-increasing rate of stress created by the disorders and routines of the urban dwelling style. In this paper, various spaces of such experiences were explored through a virtual tour with two underlying aims: 1) encouraging, informing, and educating the community in terms of tourism development, and 2) introducing a temporary release from the routines. This study enjoyed a practical-qualitative research methodology, and the required data were collected through observation and using a multiple-response questionnaire. The participants (19-48 years old) included 41 citizens of both genders (63.4% male and 36.6% female) from two regions in Tehran, selected by cluster-probability sampling. The results led to development of a spatial design for a virtual tour experience in Tehran where different areas are explored to both raise people’s awareness and educate them on their cultural heritage.

Keywords: ecotourism, education, gamification, social interaction, urban design, virtual tour

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Authors: Andrew R. Winters, Gregor J. Gassner

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A high-order numerical magentohydrodynamics (MHD) solver built upon a non-linear entropy stable numerical flux function that supports eight traveling wave solutions will be described. The method is designed to treat the divergence-free constraint on the magnetic field in a similar fashion to a hyperbolic divergence cleaning technique. The solver is especially well-suited for flows involving strong discontinuities due to its strong stability without the need to enforce artificial low density or energy limits. Furthermore, a new formulation of the numerical algorithm to guarantee positivity of the pressure during the simulation is described and presented. By construction, the solver conserves mass, momentum, and energy and is entropy stable. High spatial order is obtained through the use of a third order limiting technique. High temporal order is achieved by utilizing the family of strong stability preserving (SSP) Runge-Kutta methods. Main attributes of the solver are presented as well as details on an implementation of the new solver into the multi-physics, multi-scale simulation code FLASH. The accuracy, robustness, and computational efficiency is demonstrated with a variety of numerical tests. Comparisons are also made between the new solver and existing methods already present in FLASH framework.

Keywords: entropy stability, finite volume scheme, magnetohydrodynamics, pressure positivity

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Authors: Kaushika Vinotheeswaran

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The Greater Toronto Area (GTA), located in Ontario, Canada, is among the fastest-growing metropolitan areas in North America. Rapid urbanization within the GTA has led to increased imperviousness and surface runoff, contributing to wetland loss. Wetland cover and land cover data from the Southern Ontario Land Resource Information System were analyzed to characterize wetland loss to built-up areas and land conversions between 2005 and 2015, evaluating the extent of urbanization-induced wetland loss. Spatial analysis revealed a significant increase in the number of wetlands lost from 2005 to 2011 compared to the period from 2011 to 2015, with these losses attributed to increased urban expansions within the GTA. Non-wetland conversions, such as agricultural and impervious built-up uses to support urban expansions, played a significant role in wetland loss. Current approaches to wetland policy implementation and land-use planning strategies do not effectively identify or mitigate damage to wetlands in advance of development, resulting in significant wetland loss. Therefore, wetland conservation policies must be re-evaluated to address gaps in policy practice and focus on minimizing wetland loss.

Keywords: wetland loss, urbanization, impervious, pervious, wetland conservation

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Authors: Daniel Nieto, Ramiro Couceiro

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Microfluidic chips have demonstrated their significant application potentials in microbiological processing and chemical reactions, with the goal of developing monolithic and compact chip-sized multifunctional systems. Heat generation and thermal control are critical in some of the biochemical processes. The paper presents a laser direct-write technique for rapid prototyping and manufacturing of microheater chips and its applicability for perfusion cell culture outside a cell incubator. The aim of the microheater is to take the role of conventional incubators for cell culture for facilitating microscopic observation or other online monitoring activities during cell culture and provides portability of cell culture operation. Microheaters (5 mm × 5 mm) have been successfully fabricated on soda-lime glass substrates covered with aluminum layer of thickness 120 nm. Experimental results show that the microheaters exhibit good performance in temperature rise and decay characteristics, with localized heating at targeted spatial domains. These microheaters were suitable for a maximum long-term operation temperature of 120ºC and validated for long-time operation at 37ºC. for 24 hours. Results demonstrated that the physiology of the cultured SW480 adenocarcinoma of the colon cell line on the developed microheater chip was consistent with that of an incubator.

Keywords: laser microfabrication, microheater, bioengineering, cell culture

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Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Samar Alkindy

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Purpose: The BIM model has been used to support the planning of different construction projects in the industry by showing the different stages of the construction process. The model has been instrumental in identifying some of the common errors in the construction process through the spatial arrangement. The continuous use of the BIM model in the construction industry has resulted in various radical changes such as virtual prototyping. Construction virtual prototyping is a highly advanced technology that incorporates a BIM model with realistic graphical simulations, and facilitates the simulation of the project before a product is built in the factory. The paper presents virtual prototyping in the construction industry by examining its application, challenges and benefits to a construction project. Methodology approach: A case study was conducted for this study in four major construction projects, which incorporate virtual construction prototyping in several stages of the construction project. Furthermore, there was the administration of interviews with the project manager and engineer and the planning manager. Findings: Data collected from the methodological approach shows a positive response for virtual construction prototyping in construction, especially concerning communication and visualization. Furthermore, the use of virtual prototyping has increased collaboration and efficiency between construction experts handling a project. During the planning stage, virtual prototyping has increased accuracy, reduced planning time, and reduced the amount of rework during the implementation stage. Irrespective of virtual prototyping being a new concept in the construction industry, the findings outline that the approach will benefit the management of construction projects.

Keywords: construction operations, construction planning, process simulation, virtual prototyping

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Authors: Md. Imran H. Khan, T. Farrell, M. A. Karim

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Highly porous and hygroscopic characteristics of pear make it complex to understand the cellular level water distribution. In pear tissue, water is mainly distributed in three different spaces namely, intercellular water, intracellular water, and cell wall water. Understanding of these three types of water in pear tissue is crucial for predicting actual heat and mass transfer during drying. Therefore, the aim of the present study was to investigate the proportion of intercellular water, intracellular water, and cell wall water inside the pear tissue. During this study, Green Anjou Pear was taken for the investigation. The experiment was performed using 1H-NMR- T2 relaxometry. Various types of water component were calculated by using multi-component fits of the T2 relaxation curves. The experimental result showed that in pear tissue 78-82% water exist in intracellular space; 12-16% water in intercellular space and only 2-4% water exist in the cell wall space. The investigated results quantify different types of water in plant-based food tissue. The highest proportion of water exists in intracellular spaces. It was also investigated that the physical properties of pear and the proportion of the different types of water has a strong relationship. Cell wall water depends on the proportion of solid in the sample tissue whereas free water depends on the porosity of the material.

Keywords: intracellular water, intercellular water, cell wall water, physical property, pear

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Authors: Peter Joseph Basil Morris, Chhabi Nigam, S. Ramakrishnan, P. Radhakrishna

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data using the Range Migration Algorithm (RMA) for the spotlight mode of operation. Unlike in polar format algorithm (PFA), space-variant defocusing and geometric distortion effects are mitigated in RMA since it does not assume that the illuminating wave-fronts are planar. This facilitates the use of RMA for imaging scenarios involving severe differential range curvatures enabling the imaging of larger scenes at fine resolution and at shorter ranges with low center frequencies. The RMA algorithm for the spotlight mode of SAR is analyzed in this paper using the airborne data. Pre-processing operations viz: - range de-skew and motion compensation to a line are performed on the raw data before being fed to the RMA component. Various stages of the RMA viz:- 2D Matched Filtering, Along Track Fourier Transform and Slot Interpolation are analyzed to find the performance limits and the dependence of the imaging geometry on the resolution of the final image. The ability of RMA to compensate for severe differential range curvatures in the two-dimensional spatial frequency domain are also illustrated in this paper.

Keywords: range migration algorithm, spotlight SAR, synthetic aperture radar, matched filtering, slot interpolation

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Authors: Moses Abrahamson

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This paper examines Edgar Degas’s The Rehearsal of the Ballet Onstage (1874) through the lens of gaze, spatiality, and women’s labor within the context of 19th-century Parisian modernity. Degas’s depiction of ballet dancers, who were often subject to sexual exploitation by wealthy patrons of the Paris Opera, extends beyond a mere aesthetic rendering of performance. Instead, the painting highlights the Opera’s backstage dynamics, where class and gender intersect through power imbalances. By analyzing the gazes of the Opera’s male patrons and ballet masters, the paper explores the implicit commodification of the dancers, drawing on Mulvey’s theory of the male gaze and its manifestation in the portrayal of working-class women. Degas’s positioning of these figures, coupled with his perspective as both artist and patron, reveals his engagement with the spatial layout of the Opera and the modern social hierarchies it embodies. The painting serves as a microcosm of broader sociocultural transformations, where Degas reflects on the labor of ballet dancers as both private toil and public spectacle, connecting his artistic process to the gendered and classed politics of modern Parisian society.

Keywords: class dynamics, male gaze, spatiality, modernity

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Authors: Jayati Das

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Kolkata, one of the fastest-growing metropolises in India, has been suffering from air pollution for many decades. Mismanagement of government and an increase in automobiles have been fuelling this problem. The study aims to portray the quality of air along with the influence of traffic flow and vehicular growth and the effects on human health. It further shows the correlation between the emission of pollution during weekdays and weekends with the help of a scatter diagram and trend line. An assessment of Kolkata air quality is done where the listed pollutants’ (RPM, SPM, NO2, and SO2) annual average concentrations are classified into four different categories. Our observed association between childhood Acute Respiratory disorder and early life exposure to traffic-related air pollutants is biologically plausible. The period of in utero and the first year of life is critical in the development of the immune and respiratory systems and potentially harmful effects of toxic pollutants during this period might result in the long-lasting impaired capacity to fight infections and increased risk of allergic manifestations. Up-to-date knowledge about the seasonal and spatial variation of asthma and studying the air quality of the area is done through Geographical Information System (GIS). Steps are taken by the government to control air pollution by alternative public transport like the metro and compulsory certification of period-driven vehicles which test for Carbon mono oxide.

Keywords: air pollution, asthma, GIS, hotspots, governance

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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The use of Geographic Information System (GIS) tools in the analysis of traffic crash data can help to identify locations or hotspots with high instances or risk of traffic crashes. The identification of traffic crash hotspots can effectively improve road safety measures. Mapping of road traffic crash hotspots can help the concerned authorities to give priority and take targeted measures and improvements to the road structure at these locations to reduce traffic crashes and fatalities. In Oman, there are countless rural roads that have more risks for traveling vehicles compared to urban roads. The likelihood of traffic crashes as well as fatality rate may increase with the presence of risks that are associated with the rural type of community. In this paper, the traffic crash hotspots on rural roads in Oman are specified using spatial analysis methods in GIS and traffic crash data. These hotspots are ranked based on the frequency of traffic crash occurrence (i.e., number of traffic crashes) and the rate of fatalities. The result of this study presents a map visualization of locations on rural roads with high traffic crashes and high fatalities rates.

Keywords: road safety, rural roads, traffic crash, GIS tools

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Authors: S. Ilakkiya, A. Merline

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A multiple-input multiple-output (MIMO) radar systems use modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets. This paper deals with the design of transmit beamspace matrix and DOA estimation for multiple-input multiple-output (MIMO) radar with collocated antennas.The design of transmit beamspace matrix is based on minimizing the difference between a desired transmit beampattern and the actual one while enforcing the constraint of uniform power distribution across the transmit array elements. Rotational invariance property is established at the transmit array by imposing a specific structure on the beamspace matrix. Semidefinite programming and spatial-division based design (SDD) are also designed separately. In MIMO radar systems, DOA estimation is an essential process to determine the direction of incoming signals and thus to direct the beam of the antenna array towards the estimated direction. This estimation deals with non-adaptive spectral estimation and adaptive spectral estimation techniques. The design of the transmit beamspace matrix and spectral estimation techniques are studied through simulation.

Keywords: adaptive and non-adaptive spectral estimation, direction of arrival estimation, MIMO radar, rotational invariance property, transmit, receive beamforming

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Authors: Panwasn Mahalawalert

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The purposes of this research were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2013 (SWUSAT). SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was analyzed in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of DIF and DTF analysis for all 10 tests in year 2013. Gender was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF is between 6.67% - 60%. There are 5 tests that most of items favors female group and 2 tests that most of items favors male group. There are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small level.

Keywords: aptitude test, differential item functioning, differential test functioning, educational measurement

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Authors: Elizabeta Krstić Vukelja

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Digitization of personal data is a consequence of the development of information and communication technologies that create a new work environment with many advantages and challenges, but also potential threats to privacy and personal data protection. Regulation (EU) 2016/679 of the European Parliament and of the Council is becoming a law and obligation that should address the issues of personal data protection and information security. The existence of the Regulation leads to the conclusion that national legislation in the field of virtual environment, protection of the rights of EU citizens and processing of their personal data is insufficiently effective. In the health system, special emphasis is placed on the processing of special categories of personal data, such as health data. The healthcare industry is recognized as a particularly sensitive area in which a large amount of medical data is processed, the digitization of which enables quick access and quick identification of the health insured. The protection of the individual requires quality IT solutions that guarantee the technical protection of personal categories. However, the real problems are the technical and human nature and the spatial limitations of the application of the Regulation. Some conclusions will be drawn by analyzing the implementation of the basic principles of the Regulation on the example of the Croatian health care system and comparing it with similar activities in other EU member states.

Keywords: regulation, healthcare system, personal dana protection, quality data assurance

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Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao

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In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.

Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution

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Authors: Ruangdech Sirikit

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The purposes of this study were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2011 (SWUSAT 2011) SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was carried out in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of data analysis for all 10 tests in year 2011. Sex was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF was between 10% - 46.67%. There are 4 tests that most of items favors female group. There are 3 tests that most of items favors male group and there are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small DIF effect variance.

Keywords: differential item functioning, differential test functioning, SWUSAT, aptitude test

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Rana Zeina

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Objective: The association between Sensory problems and cognitive abilities has been studied in individuals with Autism Spectrum Disorders (ASDs). In this study, we used a neuropsychological test to evaluate memory and attention in ASDs children with sensory problems compared to the ASDs children without sensory problems. Methods: Four visual memory tests of Cambridge Neuropsychological Test Automated Battery (CANTAB) including Big/Little Circle (BLC), Simple Reaction Time (SRT), Intra/Extra Dimensional Set Shift (IED), Spatial Recognition Memory (SRM), were administered to 14 ASDs children with sensory problems compared to 13 ASDs without sensory problems aged 3 to 12 with IQ of above 70. Results: ASDs Individuals with sensory problems performed worse than the ASDs group without sensory problems on comprehension, learning, reversal and simple reaction time tasks, and no significant difference between the two groups was recorded in terms of the visual memory and visual comprehension tasks. Conclusion: The findings of this study suggest that ASDs children with sensory problems are facing deficits in learning, comprehension, reversal, and speed of response to stimuli.

Keywords: visual memory, attention, autism spectrum disorders, CANTAB eclipse

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Authors: Shaker Alsharif, Xavier Banquy

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Controlled drug delivery technology represents one of the most rapidly advancing areas of science in which chemists and chemical engineers are contributing to human health care. Such delivery systems provide numerous advantages compared to conventional dosage forms including improved efficacy, and improved patient compliance and convenience. Such systems often use synthetic polymers as carriers for the drugs. As a result, treatments that would not otherwise be possible are now in conventional use. The role of bilayered vesicles as efficient carriers for drugs, vaccines, diagnostic agents and other bioactive agents have led to a rapid advancement in the liposomal drug delivery system. Moreover, the site avoidance and site-specific drug targeting therapy could be achieved by formulating a liposomal product, so as to reduce the cytotoxicity of many potent therapeutic agents. Our project focuses on developing and building hydrogel with nanoinclusion of liposomes loaded with active compounds such as proteins and growth factors able to release them in a controlled fashion. In order to achieve that, we synthesize several liposomes of two different phospholipids concentrations encapsulating model drug. Then, formulating hydrogel with specific mechanical properties embedding the liposomes to manage the release of active compound.

Keywords: controlled release, hydrogel, liposomes, active compounds

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Authors: Angga Hidayah Ramadhan, Luciana Andrawina, M. Azani Hasibuan

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Data will be as a core of the decision if it has a good treatment or process, which is process that data into information, and information into knowledge to make a wisdom or decision. Today, many companies have not realize it include XYZ University Admission Directorate as executor of National Admission called Seleksi Masuk Bersama (SMB) that during the time, the workers only uses their feeling to make a decision. Whereas if it done, then that company can analyze the data to make a right decision to get a pin sales from student candidate or registrant that follow SMB as many as possible. Therefore, needs Knowledge Management System (KMS) with Geographic Information System (GIS) use 5C4C that can process that company data becomes more useful and can help make decisions. This information system can process data into information based on the pin sold data with 5C (Contextualized, Categorize, Calculation, Correction, Condensed) and convert information into knowledge with 4C (Comparing, Consequence, Connection, Conversation) that has been several steps until these data can be useful to make easier to take a decision or wisdom, resolve problems, communicate, and quicker to learn to the employees have not experience and also for ease of viewing/visualization based on spatial data that equipped with GIS functionality that can be used to indicate events in each province with indicator that facilitate in this system. The system also have a function to save the tacit on the system then to be proceed into explicit in expert system based on the problems that will be found from the consequences of information. With the system each team can make a decision with same ways, structured, and the important is based on the actual event/data.

Keywords: 5C4C, data, information, knowledge

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Authors: Praveen Priyadarshi

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What is the nature of the 'political subjects' in the new urban spaces of the Indian cities? How do they become a 'public'? The paper explores these questions by studying the National Capital Region's gated communities in India. Even as the 'gated-ness' of these neighborhoods constantly underlines the definitive spatial boundary of the 'public' that it is constituted within the walls of a particular gated community, the making of this 'public' occurs as much in the digital spaces—in the digital space of online messaging apps and platforms—populated by unique digital identities. It is through constant exchanges of the digital identities that the 'public' is created. However, the institutional framework and the formal rules governing the making of the public are still analogue because they presume and privilege traditional modes of participation for people to constitute a 'public'. The institutions are designed as rules and norms governing people's behavior when they participate in traditional, physical mode, whereas rules and norms designed in the algorithms regulate people's social and political behavior in the digital domain. In exploring this disjuncture between the analogue institutions and the digital public, the paper analytically evaluates the nature of everyday politics in gates neighborhoods in India.

Keywords: gated communities, everyday politics, new urban spaces, digital publics

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Authors: Sun Shi, Sun Cheng

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The pedestrian corridor is the most crowded area in the public space. The crowded severity has been focused on the field of evacuation strategies of the entrance in large public spaces. The aim of this paper is to analyze the walking efficiency in different spaces of pedestrian corridor with the variation of spatial parameters. The congestion condition caused by the variation of walking efficiency is modeled as well. This study established the space model of the walking corridor by setting the width, slope, turning form and turning angle of the pedestrian corridor. The pedestrian preference of walking mode varied with the difference of the crowded severity, walking speed, field of vision, sight direction and the expected destination, which is influenced by the characters of physical space form. Swarm software is applied to build Agent model. According to the output of the Agent model, the relationship between the pedestrian corridor width, ground slope, turning forms, turning angle and the walking efficiency, crowded severity is acquired. The results of the simulation can be applied to pedestrian corridor design in order to reduce the crowded severity and the potential safety risks caused by crowded people.

Keywords: crowded severity, multi-agent, pedestrian preference, urban space design

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Authors: J. Jarolímek, P. Urban, P. Pavlínek, D. Dzúrová

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The industry constitutes a dominant economic sector in Czechia. The automotive industry represents the most important industrial sector in terms of gross value added and the number of employees. The objective of this study was to analyse the occurrence of occupational diseases (OD) in the automotive industry in Czechia during the 2001-2014 period. Whereas the occurrence of OD in other sectors has generally been decreasing, it has been increasing in the automotive industry, including growing spatial discrepancies. Data on OD cases were retrieved from the National Registry of Occupational Diseases. Further, we conducted a survey in automotive companies with a focus on occupational health services and positions of the companies in global production networks (GPNs). An analysis of OD distribution in the automotive industry was performed (age, gender, company size and its role in GPNs, regional distribution of studied companies, and regional unemployment rate), and was accompanied by an assessment of the quality and range of occupational health services. The employees older than 40 years had nearly 2.5 times higher probability of OD occurrence compared with employees younger than 40 years (OR 2.41; 95% CI: 2.05-2.85). The OD occurrence probability was 3 times higher for women than for men (OR 3.01; 95 % CI: 2.55-3.55). The OD incidence rate was increasing with the size of the company. An association between the OD incidence and the unemployment rate was not confirmed.

Keywords: occupational diseases, automotive industry, health geography, unemployment

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Authors: Haoyang Liang, Dandong Ge

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With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

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Authors: Fereshteh Pashaei Kamali, Elham Kazemi, Shokooh Neshani Fam

Abstract:

The subject of sustainable development is a reformist revision of modernism and tradition, proposing reconciliatory strategies between these two. Sustainability in architecture cannot only be interpreted as the construction’s physical stability, but also as stability, the preserving of the continuous totality of earth and its energy resources as well, whose available resources and materials should be employed more efficiently. In other words, by referring to the building ecology, emphasizing the combinatory capacity of the building with the environmental factors (existence context), the aim of sustainability is to achieve spatial quality and comfort, as well as proper design in the architectural composition. To achieve these traditional Iranian architecture objectives, it is essential to plan on protecting the environment, maintaining aesthetic measures and responding to the needs of each climatic region. This study was conducted based on the descriptive-analytical method, and aimed to express the design patterns compatible with the climate of the Tabriz residential fabric. The present article attempts to express the techniques and patterns used in traditional Iranian architecture, especially the Tabriz Sharbatoglu houses and Ghadaki houses, which are supposed to be in accordance with modern concepts of sustainable architecture.

Keywords: sustainable architecture, climate, Tabriz, Sharbatoglu house, Ghadaki house

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Authors: N. S. Kubanza, D. Simatele, D. K. Das

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The purpose of this paper is to understand the urban environmental problems in Kinshasa and the consequences of these for the poor. This paper particularly examines the concept of environmental injustice in solid waste management in Kinshasa, the capital of the Democratic Republic of Congo (DRC). The urban low-income communities in Kinshasa face multiple consequences of poor solid waste management associated with unhealthy living conditions. These situations stemmed from overcrowding, poor sanitary, accumulation of solid waste, resulting in the prevalence of water and air borne diseases. Using a mix of reviewed archival records, scholarly literature, a semi-structured interview conducted with the local community members and qualitative surveys among stakeholders; it was found that solid waste management challenge in Kinshasa is not only an environmental and health risk issues, but also, a problem that generates socio-spatial disparities in the distribution of the solid waste burden. It is argued in the paper that the urban poor areas in Kinshasa are often hardest affected by irregularities of waste collection. They lack sanitary storage capacities and have undermined organizational capacity for collective action within solid waste management. In view of these observations, this paper explores mechanisms and stakeholders’ engagement necessary to lessen environmental injustice in solid waste management (SWM) in Kinshasa.

Keywords: environmental justice, solid waste management, urban environmental problems, urban poor

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Alan Luo, Hunter N. B. Moseley

Abstract:

Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from x-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for x-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across x-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.

Keywords: biomacromolecular structure, coenzyme, electron density discrepancy analysis, x-ray crystallography

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