Search results for: spatial error models

Authors: Yueying Chen

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A city can be developed through memory, and memory is one of the most important elements for urban contexts. Collective memory is a collection of personal memories that can be preserved with objects, places, and events of heritage, expressing culture through spatial changes. These preserved forms can evoke a sense of community and certain emotions. Collective memory in cities reflects urban spatial alterations and historical developments. It can be preserved and reflected by revitalisation projects. A major current focus in collective memory research is how to identify and preserve memory in an intangible way. The influential elements within the preservation of collective memory mainly include institutions and objects. However, current research lacks the assessment of the collective memory after alterations of urban heritage. The assessment of urban heritage lacks visualization and qualitative methods. The emergence of the application of space syntax can fill in this gap. Hengshan Mansions was a new project in 2015. The original residential area has been replaced with a comprehensive commercial area integrating boutique shopping, upscale restaurants, and creative offices. Hengshan Mansions is located in the largest historic area in Shanghai, and its development is the epitome of the traditional culture in Shanghai. Its alteration is the newest project in this area and presents the new concept of revitalisation of urban heritage. For its physical parts, modern vitality is created, and historical information is preserved at the same time. However, most of the local people are moved away, and its functions are altered a lot. The preservation of its collective memory needs to discuss furtherly. Thus, the article builds a framework to assess the collective memory of urban heritage, including spatial configuration, spatial interaction, and cultural cognition. Then, it selects Hengshan Mansions in Shanghai as a case to analyse the assessed framework. Space syntax can be applied to visualize the assessment. Based on the analysis, the article will explore the influential reasons for the collective memory after alterations and proposes relevant advice for the preservation of the collective memory of urban heritage.

Keywords: collective memory, alternation of urban heritage, space syntax, Hengshan Mansions

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Authors: Amiya Kumar Pati, Spandan Sahu, Kishanjit Kumar Khatua

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River is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. A river flow consisting of small and shallow channels sometimes divide and recombine numerous times because of the slow water flow or the built up sediments. The pattern formed during this process resembles the strands of a braid. Braided streams form where the sediment load is so heavy that some of the sediments are deposited as shifting islands. Braided rivers often exist near the mountainous regions and typically carry coarse-grained and heterogeneous sediments down a fairly steep gradient. In this paper, the apparent shear stress formulae were suitably modified, and the Energy Concept Method (ECM) was applied for the prediction of discharges at the junction of a two-flow braided compound channel. The Energy Concept Method has not been applied for estimating the discharges in the braided channels. The energy loss in the channels is analyzed based on mechanical analysis. The cross-section of channel is divided into two sub-areas, namely the main-channel below the bank-full level and region above the bank-full level for estimating the total discharge. The experimental data are compared with a wide range of theoretical data available in the published literature to verify this model. The accuracy of this approach is also compared with Divided Channel Method (DCM). From error analysis of this method, it is observed that the relative error is less for the data-sets having smooth floodplains when compared to rough floodplains. Comparisons with other models indicate that the present method has reasonable accuracy for engineering purposes.

Keywords: critical flow, energy concept, open channel flow, sediment, two-flow braided compound channel

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Authors: Devon Brown, Liu Chunmei

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This paper will present an analysis as part of the researchers dissertation topic focusing on the intersection of affective and analytical directed acyclic graphs (DAGs) in the context of Decision Support Systems (DSS). The researcher’s work involves analyzing decision theory models like Affective and Bayesian Decision theory models and how they could be implemented under an Affective Computing Framework using Information Fusion and Human-Centered Design. Additionally, the researcher is beginning research on an Affective-Analytic Decision Framework (AADF) model for their dissertation research and are looking to merge logic and analytic models with empathetic insights into affective DAGs. Data-collection efforts begin Fall 2024 and in preparation for the efforts this paper looks to analyze previous research in this area and introduce the AADF framework and propose conceptual models for consideration. For this paper, the research emphasis is placed on analyzing Bayesian networks and Markov models which offer probabilistic techniques during uncertainty in decision-making. Ideally, including affect into analytic models will ensure algorithms can increase user trust with algorithms by including emotional states and the user’s experience with the goal of developing emotionally intelligent A.I. systems that can start to navigate the complex fabric of human emotion during decision-making.

Keywords: decision support systems, explainable AI, HCAI techniques, affective-analytical decision framework

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Authors: Chevonne Reynolds, Robert J. Fletcher, Jr, Celine M. Carneiro, Nicole Jennings, Alison Ke, Michael C. LaScaleia, Mbhekeni B. Lukhele, Mnqobi L. Mamba, Muzi D. Sibiya, James D. Austin, Cebisile N. Magagula, Themba’alilahlwa Mahlaba, Ara Monadjem, Samantha M. Wisely, Robert A. McCleery

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A key challenge for the developing world is reconciling biodiversity conservation with the growing demand for food. In these regions, agriculture is typically interspersed among other land-uses creating heterogeneous landscapes. A primary hypothesis for promoting biodiversity in agricultural landscapes is the habitat heterogeneity hypothesis. While there is evidence that landscape heterogeneity positively influences biodiversity, the application of this hypothesis is hindered by a need to determine which components of landscape heterogeneity drive these effects and at what spatial scale(s). Additionally, whether diverse taxonomic groups are similarly affected is central for determining the applicability of this hypothesis as a general conservation strategy in agricultural mosaics. Two major components of landscape heterogeneity are compositional and configurational heterogeneity. Disentangling the roles of each component is important for biodiversity conservation because each represents different mechanisms underpinning variation in biodiversity. We identified a priori independent gradients of compositional and configurational landscape heterogeneity within an extensive agricultural mosaic in north-eastern Swaziland. We then tested how bird, dung beetle, ant and meso-carnivore diversity responded to compositional and configurational heterogeneity across six different spatial scales. To determine if a general trend could be observed across multiple taxa, we also tested which component and spatial scale was most influential across all taxonomic groups combined, Compositional, not configurational, heterogeneity explained diversity in each taxonomic group, with the exception of meso-carnivores. Bird and ant diversity was positively correlated with compositional heterogeneity at fine spatial scales < 1000 m, whilst dung beetle diversity was negatively correlated to compositional heterogeneity at broader spatial scales > 1500 m. Importantly, because of these contrasting effects across taxa, there was no effect of either component of heterogeneity on the combined taxonomic diversity at any spatial scale. The contrasting responses across taxonomic groups exemplify the difficulty in implementing effective conservation strategies that meet the requirements of diverse taxa. To promote diverse communities across a range of taxa, conservation strategies must be multi-scaled and may involve different strategies at varying scales to offset the contrasting influences of compositional heterogeneity. A diversity of strategies are likely key to conserving biodiversity in agricultural mosaics, and we have demonstrated that a landscape management strategy that only manages for heterogeneity at one particular scale will likely fall short of management objectives.

Keywords: agriculture, biodiversity, composition, configuration, heterogeneity

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Authors: Sinem Tas

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This research paper attempts to study the perspective of personal experience in relation to spatial dynamics and artistic outcomes within the realm of cultural identity. This article serves as a partial analysis within a broader PhD investigation that focuses on the cultural dynamics and political structures behind cultural identity through an autoethnography of narrative while presenting its correlation with artistic creation in the context of space and people. Focusing on the artistic/creative practice project AUTRUI, the primary goal is to analyse and understand the influence of personal experiences and culturally constructed identity as an artist in resulting in the compositional modality of the last image considering self-reflective experience. Referencing the works of Joyce Davidson and Christine Milligan - the scholars who emphasise the importance of emotion and spatial experience in geographical studies contribute to this work as they highlight the significance of emotion across various spatial scales in their work Embodying Emotion Sensing Space: Introducing Emotional Geographies (2004). Their perspective suggests that understanding emotions within different spatial contexts is crucial for comprehending human experiences and interactions with space. Incorporating the insights of scholars like Yi-Fu Tuan, particularly his seminal work Space and Place: The Perspective of Experience (1979), is important for creating an in-depth frame of geographical experience. Tuan's humanistic perspective on space and place provides a valuable theoretical framework for understanding the interplay between personal experiences and spatial contexts. A substantial contextualisation of the geopolitics of Turkey - the implications for national identity and cohesion - will be addressed by drawing an outline of the political and geographical frame as a methodological strategy to understand the dynamics behind this research. Besides the bibliographical reading, the methods used to study this relation are participatory observation, memory work along with memoir analysis, personal interviews, and discussion of photographs and news. The utilisation of the self as data requires the analysis of the written sources with personal engagement. By delving into written sources such as written communications or diaries as well as memoirs, the research gains a firsthand perspective, enriching the analytical depth of the study. Furthermore, the examination of photography and news articles serves as a valuable means of contextualising experiences from a journalist's background within specific geographical settings. The inclusion of interviews with close family members access provides firsthand perspectives and intimate insights rooted in shared experiences within similar geographical contexts, offering complementary insights and diversified viewpoints, enhancing the comprehensiveness of the investigation.

Keywords: art, autoethnography, place and space, Turkey

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Authors: Thomas E. Portegys

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An animal behavior problem is presented in the form of a nest-building task that involves two cooperating virtual birds, a male and female. The female builds a nest into which she lays an egg. The male's job is to forage in a forest for food for both himself and the female. In addition, the male must fetch stones from a nearby desert for the female to use as nesting material. The task is completed when the nest is built, and an egg is laid in it. A goal-seeking neural network and a recurrent neural network were trained and tested with little success. The goal-seeking network was then enhanced with “place cells”, allowing the birds to spatially navigate the world, building the nest while keeping themselves fed. Place cells are neurons in the hippocampus that map space.

Keywords: artificial animal intelligence, artificial life, goal-seeking neural network, nest-building, place cells, spatial navigation

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Authors: Jessemyn Modiini, Timothy Lynar, Elena Sitnikova

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We present a novel enhanced compartmental model for malware spread analysis in cyber security. This paper applies cyber security data features to epidemiological compartmental models to model the infectious potential of malware. Compartmental models are most efficient for calculating the infectious potential of a disease. In this paper, we discuss and profile epidemiologically relevant data features from a Domain Name System (DNS) dataset. We then apply these features to epidemiological compartmental models to network traffic features. This paper demonstrates how epidemiological principles can be applied to the novel analysis of key cybersecurity behaviours and trends and provides insight into threat modelling above that of kill-chain analysis. In applying deterministic compartmental models to a cyber security use case, the authors analyse the deficiencies and provide an enhanced stochastic model for cyber epidemiology. This enhanced compartmental model (SUEICRN model) is contrasted with the traditional SEIR model to demonstrate its efficacy.

Keywords: cybersecurity, epidemiology, cyber epidemiology, malware

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Kittipob Kondee, Chutima Prommak

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In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

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Authors: Brahim Ferdi, Samira Dib

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The unified power quality conditioner (UPQC), a combination of shunt and series active power filter, is one of the best solutions towards the mitigation of voltage and current harmonics problems in distribution power system. PI controller is very common in the control of UPQC. However, one disadvantage of this conventional controller is the difficulty in tuning its gains (Kp and Ki). To overcome this problem, an adaptive fuzzy logic PI controller is proposed. The controller is composed of fuzzy controller and PI controller. According to the error and error rate of the control system and fuzzy control rules, the fuzzy controller can online adjust the two gains of the PI controller to get better performance of UPQC. Simulations using MATLAB/SIMULINK are carried out to verify the performance of the proposed controller. The results show that the proposed controller has fast dynamic response and high accuracy of tracking the current and voltage references.

Keywords: adaptive fuzzy PI controller, current harmonics, PI controller, voltage harmonics, UPQC

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Authors: Naveed Mazhar

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Our cities are known to have significant modifying effects on the local climate. The nature of the modifications depends on a range of physical variables, usually assessed at a wide range of spatial scales. Physical spatial dimensions, such as measured parameters of microclimates and their significant influence on human sensations, are known to have far-reaching effects on human thermal comfort and by corollary a force that influences human perception. Less scholarship has thrown light on the subjective dimension and insufficiently demonstrates a relational approach between human behavior and how it is affected by the phenomenon of urban microclimates. Other than identifying gaps in the most recent scholarship and providing future research opportunities, the scope of this study will help improve urban design guidelines and raise framework standards of socially responsive urban design. This study will help equip future professionals to ameliorate the effects of urban microclimates on participant’s perceptions enabling more frequent usage of the outdoor urban spaces. However, it is informed that the physical parameters of an outdoor open space determine psychological human adaptations and is a measure of the degree to which people are willing to adapt to their surroundings. A large amount of research is available related to urban microclimates. However, very few studies are focused on the elucidation of the critical factors influencing human perceptions of the microclimates in urban spatial configurations. Based on the most recent scholarship, this study has evaluated the role urban microclimatic conditions have in the formation of human perceptions and, by extension, behavioral patterns formulating in outdoor open spaces. Furthermore, this study also defines, in the backdrop of the current scholarly literature, the socio-spatial interdependence of behavioral patterns with relationship to the built urban fabric and its resultant correlation with human perception. A comprehensive review and analysis of the recent research conducted within the scope of the study will help frame gaps, issues, current research methods and future research opportunities.

Keywords: urban design, urban microcliamate, human perception, human behavioral patterns

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Authors: Makram Ben Jeddou

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The ABC classification is widely used by managers for inventory control. The classical ABC classification is based on the Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to take into account other important criteria. From these models, we will consider the ZF model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score based on a normalized average between a good and a bad optimized index can affect the ABC items classification. We will then focus on the weights assigned to each index and propose a classification compromise.

Keywords: ABC classification, multi criteria inventory classification models, ZF-model

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Subham Kharel, Sudha Ravindranath, A. Vidya, B. Chandrasekaran, K. Ganesha Raj, T. Shesadri

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Digitization of urban features is a tedious and time-consuming process when done manually. In addition to this problem, Indian cities have complex habitat patterns and convoluted clustering patterns, which make it even more difficult to map features. This paper makes an attempt to classify urban objects in the satellite image using object-oriented classification techniques in which various classes such as vegetation, water bodies, buildings, and shadows adjacent to the buildings were mapped semi-automatically. Building layer obtained as a result of object-oriented classification along with already available building layers was used. The main focus, however, lay in the extraction of high-rise buildings using spatial technology, digital image processing, and modeling, which would otherwise be a very difficult task to carry out manually. Results indicated a considerable rise in the total number of buildings in the city. High-rise buildings were successfully mapped using satellite imagery, spatial technology along with logical reasoning and mathematical considerations. The results clearly depict the ability of Remote Sensing and GIS to solve complex problems in urban scenarios like studying urban sprawl and identification of more complex features in an urban area like high-rise buildings and multi-dwelling units. Object-Oriented Technique has been proven to be effective and has yielded an overall efficiency of 80 percent in the classification of high-rise buildings.

Keywords: object oriented classification, shadow extraction, high-rise buildings, satellite imagery, spatial technology

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Authors: Akbar

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Pros and cons of the capital punishment in Indonesia have been out of the date. The discourse of capital punishment has no relevance to the theory of punishment and theories of cultural relativism. In fact, the provisions of exceptions to the right to life by administering the death penalty against the perpetrators of serious crimes in Indonesia is a narrow perspective that does not pay attention to the development of the punishment of the crime. This thing is aggravated by an error to understand the natural right and legal right where the prohibition of those rights is result from a failure to distinguish the characteristic of the rights and to remember the raison d’être of law. To parse the irrational above, this paper will try to analyze normatively the error referring to the complementary theory between the sources of international law and the sources of municipal law of Indonesia. Both sources of the law above should be understood in the mutually reinforcing relationship enforceability because of false perceptions against those will create the disintegration between international law and municipal law of Indonesia. This disintegration is explicit not only contrary to the integrative theory of international law but also integrative theory of municipal law of Indonesia.

Keywords: capital punishment, municipal law, right to life, international law, the raison d’être of law, complementary theory, integrative theory

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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The modeling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high-resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve denser and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high-resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D models, environment, matching, pleiades

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Authors: Naji Ali Albakay, Abdulrahman Alothaim, Isa Barshushi

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The most common quadrature amplitude modulator (QAM) applies two Mach-Zehnder Modulators (MZM) and one phase shifter to generate high order modulation format. The bias of MZM changes over time due to temperature, vibration, and aging factors. The change in the biasing causes distortion to the generated QAM signal which leads to deterioration of bit error rate (BER) performance. Therefore, it is critical to be able to lock MZM’s Q point to the required operating point for good performance. We propose a technique for automatic bias control (ABC) of QAM transmitter using BER measurements and gradient descent optimization algorithm. The proposed technique is attractive because it uses the pertinent metric, BER, which compensates for bias drifting independently from other system variations such as laser source output power. The proposed scheme performance and its operating principles are simulated using OptiSystem simulation software for 4-QAM and 16-QAM transmitters.

Keywords: automatic bias control, optical fiber communication, optical modulation, optical devices

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Authors: Amulya P. Rao, Prathima S., Sreedevi N.

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Speech sound disorders (SSD) encompass the major concern in younger population of India with highest prevalence rate among the speech disorders. Children with SSD if not identified and rehabilitated at the earliest, are at risk for academic difficulties. This necessitates early identification using screening tools assessing the frequently misarticulated speech sounds. The literature on frequently misarticulated speech sounds is ample in English and other western languages targeting individuals with various communication disorders. Articulation is language specific, and there are limited studies reporting the same in Kannada, a Dravidian Language. Hence, the present study aimed to identify the frequently misarticulated consonants in Kannada and also to examine the error type. A retrospective, descriptive study was carried out using secondary data analysis of 41 participants (34-phonetic type and 7-phonemic type) with SSD in the age range 3-to 12-years. All the consonants of Kannada were analyzed by considering three words for each speech sound from the Kannada Diagnostic Photo Articulation test (KDPAT). Picture naming task was carried out, and responses were audio recorded. The recorded data were transcribed using IPA 2018 broad transcription. A criterion of 2/3 or 3/3 error productions was set to consider the speech sound to be an error. Number of error productions was calculated for each consonant in each participant. Then, the percentage of participants meeting the criteria were documented for each consonant to identify the frequently misarticulated speech sound. Overall results indicated that velar /k/ (48.78%) and /g/ (43.90%) were frequently misarticulated followed by voiced retroflex /ɖ/ (36.58%) and trill /r/ (36.58%). The lateral retroflex /ɭ/ was misarticulated by 31.70% of the children with SSD. Dentals (/t/, /n/), bilabials (/p/, /b/, /m/) and labiodental /v/ were produced correctly by all the participants. The highly misarticulated velars /k/ and /g/ were frequently substituted by dentals /t/ and /d/ respectively or omitted. Participants with SSD-phonemic type had multiple substitutions for one speech sound whereas, SSD-phonetic type had consistent single sound substitutions. Intra- and inter-judge reliability for 10% of the data using Cronbach’s Alpha revealed good reliability (0.8 ≤ α < 0.9). Analyzing a larger sample by replicating such studies will validate the present study results.

Keywords: consonant, frequently misarticulated, Kannada, SSD

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Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: T. Nishimura, K. Doi, H. Fujimoto, T. Wada

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We conducted perception experiments on tactile symbols to elucidate the impact of the size of these letters on the level of perceptibility. This study was based on the accessible design perspective and aimed at expanding the availability of tactile symbols for the visually impaired who are unable to read Braille characters. In particular, this study targeted people with acquired visual impairments as users of the tactile symbols. The subjects (young and elderly individuals) in this study had normal vision. They were asked to participate in the experiments to identify tactile symbols while unable to see their hand during the experiments. This study investigated the relation between the size and perceptibility of tactile symbols based on an examination using test pieces of these letters in different sizes. The results revealed that the error rates for both young and elderly subjects converged to almost 0% when 12 mm size tactile symbols were used. The findings also showed that the error rate was low and subjects could identify the symbols in 5 s when 16 mm size tactile symbols were introduced.

Keywords: accessible design, tactile sense, tactile symbols, bioinformatic

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Authors: Gonzalo García-Reyes

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Conformastat spherically symmetric exact solutions of Einstein's field equations representing matter distributions made of fluid both perfect and anisotropic from given solutions of Poisson's equation of Newtonian gravity are investigated. The approach is used in the construction of new relativistic models of thick spherical shells and three-component models of galaxies (bulge, disk, and dark matter halo), writing, in this case, the metric in cylindrical coordinates. In addition, the circular motion of test particles (rotation curves) along geodesics on the equatorial plane of matter configurations and the stability of the orbits against radial perturbations are studied. The models constructed satisfy all the energy conditions.

Keywords: general relativity, exact solutions, spherical symmetry, galaxy, kinematics and dynamics, dark matter

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Authors: Subhan Ahmad, Pradeep Bhargava, Ajay Chourasia

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Shear failure in reinforced concrete beams without shear reinforcement leads to loss of property and life since a very little or no warning occurs before failure as in case of flexural failure. Shear strength of reinforced concrete beams decreases as its depth increases. This phenomenon is generally called as the size effect. In this paper, a comparative analysis is performed to estimate the performance of shear strength models in capturing the size effect of reinforced concrete beams made with conventional concrete, self-compacting concrete, and recycled aggregate concrete. Four shear strength models that account for the size effect in shear are selected from the literature and applied on the datasets of slender reinforced concrete beams. Beams prepared with conventional concrete, self-compacting concrete, and recycled aggregate concrete are considered for the analysis. Results showed that all the four models captured the size effect in shear effectively and produced conservative estimates of the shear strength for beams made with normal strength conventional concrete. These models yielded unconservative estimates for high strength conventional concrete beams with larger effective depths ( > 450 mm). Model of Bazant and Kim (1984) captured the size effect precisely and produced conservative estimates of shear strength of self-compacting concrete beams at all the effective depths. Also, shear strength models considered in this study produced unconservative estimates of shear strength for recycled aggregate concrete beams at all effective depths.

Keywords: reinforced concrete beams; shear strength; prediction models; size effect

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Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Hendri Purwadi, Christine McCloud

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Triage is a complex decision-making process that aims to categorize a victim’s level of acuity and the need for medical assistance. Two common triage systems have been widely used in Mass Casualty Incidents (MCIs) and disaster situation are START (Simple triage algorithm and rapid treatment) and SALT (sort, asses, lifesaving, intervention, and treatment/transport). There is currently controversy regarding the effectiveness of SALT over START triage system. This systematic review aims to investigate and compare the effectiveness between SALT and START triage system in disaster and MCIs setting. Literatures were searched via systematic search strategy from 2009 until 2019 in PubMed, Cochrane Library, CINAHL, Scopus, Science direct, Medlib, ProQuest. This review included simulated-based and medical record -based studies investigating the accuracy and applicability of SALT and START triage systems of adult and children population during MCIs and disaster. All type of studies were included. Joana Briggs institute critical appraisal tools were used to assess the quality of reviewed studies. As a result, 1450 articles identified in the search, 10 articles were included. Four themes were identified by review, they were accuracy, under-triage, over-triage and time to triage per individual victim. The START triage system has a wide range and inconsistent level of accuracy compared to SALT triage system (44% to 94. 2% of START compared to 70% to 83% of SALT). The under-triage error of START triage system ranged from 2.73% to 20%, slightly lower than SALT triage system (7.6 to 23.3%). The over-triage error of START triage system was slightly greater than SALT triage system (START ranged from 2% to 53% compared to 2% to 22% of SALT). The time for applying START triage system was faster than SALT triage system (START was 70-72.18 seconds compared to 78 second of SALT). Consequently; The START triage system has lower level of under-triage error and faster than SALT triage system in classifying victims of MCIs and disaster whereas SALT triage system is known slightly more accurate and lower level of over-triage. However, the magnitude of these differences is relatively small, and therefore the effect on the patient outcomes is not significance. Hence, regardless of the triage error, either START or SALT triage system is equally effective to triage victims of disaster and MCIs.

Keywords: disaster, effectiveness, mass casualty incidents, START triage system, SALT triage system

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Authors: C. Bateira, J. Fernandes, A. Costa

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The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.

Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards

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Authors: S. Cencek, A. Markun

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Noise assessment methods are regularly used in scope of Environmental Impact Assessments for planned projects to assess (predict) the expected noise emissions of these projects. Different noise assessment methods could be used. In recent years, we had an opportunity to collaborate in some noise assessment procedures where noise assessments of different laboratories have been performed simultaneously. We identified some significant differences in noise assessment results between laboratories in Slovenia. We estimate that despite good input Georeferenced Data to set up acoustic model exists in Slovenia; there is no clear consensus on methods for predictive noise methods for planned projects. We analyzed input data, methods and results of predictive noise methods for two planned industrial projects, both were done independently by two laboratories. We also analyzed the data, methods and results of two interlaboratory collaborative noise models for two existing noise sources (railway and motorway). In cases of predictive noise modelling, the validations of acoustic models were performed by noise measurements of surrounding existing noise sources, but in varying durations. The acoustic characteristics of existing buildings were also not described identically. The planned noise sources were described and digitized differently. Differences in noise assessment results between different laboratories have ranged up to 10 dBA, which considerably exceeds the acceptable uncertainty ranged between 3 to 6 dBA. Contrary to predictive noise modelling, in cases of collaborative noise modelling for two existing noise sources the possibility to perform the validation noise measurements of existing noise sources greatly increased the comparability of noise modelling results. In both cases of collaborative noise modelling for existing motorway and railway, the modelling results of different laboratories were comparable. Differences in noise modeling results between different laboratories were below 5 dBA, which was acceptable uncertainty set up by interlaboratory noise modelling organizer. The lessons learned from the study were: 1) Predictive noise calculation using formulae from International standard SIST ISO 9613-2: 1997 is not an appropriate method to predict noise emissions of planned projects since due to complexity of procedure they are not used strictly, 2) The noise measurements are important tools to minimize noise assessment errors of planned projects and should be in cases of predictive noise modelling performed at least for validation of acoustic model, 3) National guidelines should be made on the appropriate data, methods, noise source digitalization, validation of acoustic model etc. in order to unify the predictive noise models and their results in scope of Environmental Impact Assessments for planned projects.

Keywords: environmental noise assessment, predictive noise modelling, spatial planning, noise measurements, national guidelines

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: Cassandra Hansen, Paul Doherty, Chris Ferner, German Whitley, Holly Torpey

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Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing.

Keywords: storytelling, wildfire progression maps, volunteered geographic information, spatial and temporal

Procedia PDF Downloads 170