9,302 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Spatial adaptive settlement systems in archaeology. Modelling long-term settlement formation from spatial micro interactions
Despite research history spanning more than a century, settlement patterns still hold a promise to contribute to the theories of large-scale processes in human history. Mostly they have been presented as passive imprints of past human activities and spatial interactions they shape have not been studied as the driving force of historical processes. While archaeological knowledge has been used to construct geographical theories of evolution of settlement there still exist gaps in this knowledge. Currently no theoretical framework has been adopted to explore them as spatial systems emerging from micro-choices of small population units.
The goal of this thesis is to propose a conceptual model of adaptive settlement systems based on complex adaptive systems framework. The model frames settlement system formation processes as an adaptive system containing spatial features, information flows, decision making population units (agents) and forming cross scale feedback loops between location choices of individuals and space modified by their aggregated choices. The goal of the model is to find new ways of interpretation of archaeological locational data as well as closer theoretical integration of micro-level choices and meso-level settlement structures.
The thesis is divided into five chapters, the first chapter is dedicated to conceptualisation of the general model based on existing literature and shows that settlement systems are inherently complex adaptive systems and therefore require tools of complexity science for causal explanations. The following chapters explore both empirical and theoretical simulated settlement patterns based dedicated to studying selected information flows and feedbacks in the context of the whole system.
Second and third chapters explore the case study of the Stone Age settlement in Estonia comparing residential location choice principles of different periods. In chapter 2 the relation between environmental conditions and residential choice is explored statistically. The results confirm that the relation is significant but varies between different archaeological phenomena. In the third chapter hunter-fisher-gatherer and early agrarian Corded Ware settlement systems were compared spatially using inductive models. The results indicated a large difference in their perception of landscape regarding suitability for habitation. It led to conclusions that early agrarian land use significantly extended land use potential and provided a competitive spatial benefit. In addition to spatial differences, model performance was compared and the difference was discussed in the context of proposed adaptive settlement system model. Last two chapters present theoretical agent-based simulation experiments intended to study effects discussed in relation to environmental model performance and environmental determinism in general. In the fourth chapter the central place foragingmodel was embedded in the proposed model and resource depletion, as an environmental modification mechanism, was explored. The study excluded the possibility that mobility itself would lead to modelling effects discussed in the previous chapter.
The purpose of the last chapter is the disentanglement of the complex relations between social versus human-environment interactions. The study exposed non-linear spatial effects expected population density can have on the system and the general robustness of environmental inductive models in archaeology to randomness and social effect. The model indicates that social interactions between individuals lead to formation of a group agency which is determined by the environment even if individual cognitions consider the environment insignificant. It also indicates that spatial configuration of the environment has a certain influence towards population clustering therefore providing a potential pathway to population aggregation. Those empirical and theoretical results showed the new insights provided by the complex adaptive systems framework. Some of the results, including the explanation of empirical results, required the conceptual model to provide a framework of interpretation
Improving diagnostic procedures for epilepsy through automated recording and analysis of patients’ history
Transient loss of consciousness (TLOC) is a time-limited state of profound cognitive impairment characterised by amnesia, abnormal motor control, loss of responsiveness, a short duration and complete recovery. Most instances of TLOC are caused by one of three health conditions: epilepsy, functional (dissociative) seizures (FDS), or syncope. There is often a delay before the correct diagnosis is made and 10-20% of individuals initially receive an incorrect diagnosis. Clinical decision tools based on the endorsement of TLOC symptom lists have been limited to distinguishing between two causes of TLOC. The Initial Paroxysmal Event Profile (iPEP) has shown promise but was demonstrated to have greater accuracy in distinguishing between syncope and epilepsy or FDS than between epilepsy and FDS. The objective of this thesis was to investigate whether interactional, linguistic, and communicative differences in how people with epilepsy and people with FDS describe their experiences of TLOC can improve the predictive performance of the iPEP. An online web application was designed that collected information about TLOC symptoms and medical history from patients and witnesses using a binary questionnaire and verbal interaction with a virtual agent. We explored potential methods of automatically detecting these communicative differences, whether the differences were present during an interaction with a VA, to what extent these automatically detectable communicative differences improve the performance of the iPEP, and the acceptability of the application from the perspective of patients and witnesses. The two feature sets that were applied to previous doctor-patient interactions, features designed to measure formulation effort or detect semantic differences between the two groups, were able to predict the diagnosis with an accuracy of 71% and 81%, respectively. Individuals with epilepsy or FDS provided descriptions of TLOC to the VA that were qualitatively like those observed in previous research. Both feature sets were effective predictors of the diagnosis when applied to the web application recordings (85.7% and 85.7%). Overall, the accuracy of machine learning models trained for the threeway classification between epilepsy, FDS, and syncope using the iPEP responses from patients that were collected through the web application was worse than the performance observed in previous research (65.8% vs 78.3%), but the performance was increased by the inclusion of features extracted from the spoken descriptions on TLOC (85.5%). Finally, most participants who provided feedback reported that the online application was acceptable. These findings suggest that it is feasible to differentiate between people with epilepsy and people with FDS using an automated analysis of spoken seizure descriptions. Furthermore, incorporating these features into a clinical decision tool for TLOC can improve the predictive performance by improving the differential diagnosis between these two health conditions. Future research should use the feedback to improve the design of the application and increase perceived acceptability of the approach
DATA AUGMENTATION FOR SYNTHETIC APERTURE RADAR USING ALPHA BLENDING AND DEEP LAYER TRAINING
Human-based object detection in synthetic aperture RADAR (SAR) imagery is complex and technical, laboriously slow but time critical—the perfect application for machine learning (ML). Training an ML network for object detection requires very large image datasets with imbedded objects that are accurately and precisely labeled. Unfortunately, no such SAR datasets exist. Therefore, this paper proposes a method to synthesize wide field of view (FOV) SAR images by combining two existing datasets: SAMPLE, which is composed of both real and synthetic single-object chips, and MSTAR Clutter, which is composed of real wide-FOV SAR images. Synthetic objects are extracted from SAMPLE using threshold-based segmentation before being alpha-blended onto patches from MSTAR Clutter. To validate the novel synthesis method, individual object chips are created and classified using a simple convolutional neural network (CNN); testing is performed against the measured SAMPLE subset. A novel technique is also developed to investigate training activity in deep layers. The proposed data augmentation technique produces a 17% increase in the accuracy of measured SAR image classification. This improvement shows that any residual artifacts from segmentation and blending do not negatively affect ML, which is promising for future use in wide-area SAR synthesis.Outstanding ThesisMajor, United States Air ForceApproved for public release. Distribution is unlimited
The Process of Comparing Images of Emotional Expressions
Introduction. We conducted an experiment in the paradigm of direct comparison of images of strong and weakly expressed emotional expressions with a detailed justification of the assessment made and registration of eye movements.
Methods. Photo images from the VEPEL database (video images of natural transient facial expressions: joy, sadness, fear, surprise, anger, disgust, calm face) were used as stimulus material. The subjects were students of Moscow universities (72 people, of which 10 men, 62 women; age from 18 to 39 years, average age = 22.0, standard deviation = 4.0. Exposure time is unlimited, until the justification is completed. Research objective: image comparison (rank scale of similarity between images from 1 to 9) with registration of eye movements.
Results. Based on individual assessments of similarity between images of emotional expressions, the reconstruction of the two-dimensional space was performed using the multidimensional scaling method. The reconstruction is described by Core Affect model by J. Russell. The presence of individual variability of similarity scores (the tendency to select a certain range of scores) is shown. The following individual indicators were singled out for further search of possible predictors: the average similarity score between images, the standard deviation of the similarity score between images, and the average individual duration of fixations. The presence of variability of estimates for different pairs of compared images is shown. The minimum variability of similarity estimates is achieved for the next pairs: fear–fear weak, joy – joy weak; anger – anger weak; disgust weak – anger; neutral – sadness weak. The maximum variability of similarity estimates is achieved for pairs of joy weak – fear weak; joy – fear weak; sadness – joy weak; joy weak – anger weak; neutral – joy weak. The analysis of the duration of visual fixations during the similarity assessment was carried out. It is shown that different similarity scores correspond to different distribution patterns of fixation durations in the evaluation process.
Discussion. Based on our results, we can conclude that there are several convergent evaluation justification processes based on an initial similarity score between images
Science and Innovations for Food Systems Transformation
This Open Access book compiles the findings of the Scientific Group of the United Nations Food Systems Summit 2021 and its research partners. The Scientific Group was an independent group of 28 food systems scientists from all over the world with a mandate from the Deputy Secretary-General of the United Nations. The chapters provide science- and research-based, state-of-the-art, solution-oriented knowledge and evidence to inform the transformation of contemporary food systems in order to achieve more sustainable, equitable and resilient systems
Recommended from our members
Healthy Diet: A Definition for the United Nations Food Systems Summit 2021
Life Satisfaction and Psychological and Physical Well-Being
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section Health-Related Quality of Life and Well-Being . It showcases a review and empirical studies on life satisfaction and its related aspects. The studies are from several countries on a wide range of samples including university students, faculty, nurses, entrepreneurs, adolescents, national databases, refugees, and community samples
Prof. Dr. V. K. KumarProf. Dr. Jasmin Tahmaseb-McConathaGuest Editorshttps://digitalcommons.wcupa.edu/ctsmfaculty_books/1028/thumbnail.jp
Impacts of Innovation School System in Korea: A Latent Space Item Response Model with Neyman-Scott Point Process
South Korea's educational system has faced criticism for its lack of focus on
critical thinking and creativity, resulting in high levels of stress and
anxiety among students. As part of the government's effort to improve the
educational system, the innovation school system was introduced in 2009, which
aims to develop students' creativity as well as their non-cognitive skills. To
better understand the differences between innovation and regular school systems
in South Korea, we propose a novel method that combines the latent space item
response model (LSIRM) with the Neyman-Scott (NS) point process model. Our
method accounts for the heterogeneity of items and students, captures
relationships between respondents and items, and identifies item and student
clusters that can provide a comprehensive understanding of students'
behaviors/perceptions on non-cognitive outcomes. Our analysis reveals that
students in the innovation school system show a higher sense of citizenship,
while those in the regular school system tend to associate confidence in
appearance with social ability. We compare our model with exploratory item
factor analysis in terms of item clustering and find that our approach provides
a more detailed and automated analysis
- …