Hasil untuk "Geography. Anthropology. Recreation"

Renfei Kuang, Jinhai Zhao, Tuo Zhang et al.

Offshore wind turbines are prone to structural damage over time due to environmental factors, which increases operational costs and the risk of accidents. Early detection of structural damage through monitoring systems can help reduce maintenance costs. However, under complex external conditions and varying structural parameters, existing methods struggle to accurately and quickly detect damage. Understanding the factors that influence structural health is critical for effective long-term monitoring, as these factors directly affect the accuracy and timeliness of damage identification. This study comprehensively analyzed 5 MW offshore wind turbine measurement data, including constructing a digital twin model, establishing a surrogate model, and performing a sensitivity analysis. For monopile-based turbines, sensors in x and y directions were installed at four heights on the pile foundation and tower. Via Bayesian optimization, the finite element model’s structural parameters were updated to align its modal parameters with sensor data analysis results. The update efficiencies of different objective functions and the impacts of neural network hyperparameters on the surrogate model were examined. The sensitivity of the turbine’s structural parameters to modal parameters was studied. The results showed that the modal flexibility matrix is more effective in iteration. A 128-neuron, double-hidden-layer neural network balanced computational efficiency and accuracy well in the surrogate model for modal analysis. Flange damage and soil degradation near the pile mainly impacted the turbine’s health.

Zachary Sheldon, Peeyush Kumar

This paper explores the intersection of economic anthropology and generative artificial intelligence (GenAI). It examines how large language models (LLMs) can simulate human decision-making and the inductive biases present in AI research. The study introduces two AI models: C.A.L.L.O.N. (Conventionally Average Late Liberal ONtology) and M.A.U.S.S. (More Accurate Understanding of Society and its Symbols). The former is trained on standard data, while the latter is adapted with anthropological knowledge. The research highlights how anthropological training can enhance LLMs' ability to recognize diverse economic systems and concepts. The findings suggest that integrating economic anthropology with AI can provide a more pluralistic understanding of economics and improve the sustainability of non-market economic systems.

Kazuki Sakamoto, Connor T. Jerzak, Adel Daoud

Earth observation (EO) data such as satellite imagery can have far-reaching impacts on our understanding of the geography of poverty, especially when coupled with machine learning (ML) and computer vision. Early research used computer vision to predict living conditions in areas with limited data, but recent studies increasingly focus on causal analysis. Despite this shift, the use of EO-ML methods for causal inference lacks thorough documentation, and best practices are still developing. Through a comprehensive scoping review, we catalog the current literature on EO-ML methods in causal analysis. We synthesize five principal approaches to incorporating EO data in causal workflows: (1) outcome imputation for downstream causal analysis, (2) EO image deconfounding, (3) EO-based treatment effect heterogeneity, (4) EO-based transportability analysis, and (5) image-informed causal discovery. Building on these findings, we provide a detailed protocol guiding researchers in integrating EO data into causal analysis -- covering data requirements, computer vision model selection, and evaluation metrics. While our focus centers on health and living conditions outcomes, our protocol is adaptable to other sustainable development domains utilizing EO data.

Piotr Kuwałek

Voltage fluctuations are one of the most common low-frequency disturbances of power quality. Diagnostics of these disturbances are a complex process because voltage fluctuations affect different loads in different ways. Therefore, there is no measure of power quality that allows for the complementary assessment of severity of this disturbance, allow for the identification of sources of voltage fluctuations, and post-factum investigation of their effects. Among the currently used measures of voltage fluctuations, voltage fluctuation indices have the greatest diagnostic capabilities. Many preliminary studies also show the potential possibility of recreation of voltage fluctuations, including: based on voltage fluctuation indices. This paper presents the results of research on methods of recreation of voltage fluctuations from voltage fluctuation indices. The research carried out included a set of data obtained in a real power grid. Moreover, the impact of the discrimination period on the accuracy of recreation of voltage fluctuations has been assessed. The presented research results show, on the one hand, the usefulness of voltage fluctuation indices in the process of recreation of voltage fluctuations and, on the other hand, further challenges in the recreation of voltage fluctuations.

Kenneth S. Tramm, Jason T. Minter, Catherine A. Seaton

Abstract Risk‐based corrective action (RBCA) programs employ conservative models to develop default values for soil screening, which simplify the risk assessment process. However, for several naturally occurring metals (e.g., arsenic and lead), these published screening values are often unrealistic and well below the documented background levels in soil. This can lead to confusion among the regulated community and inexperienced regulators, as it will inappropriately identify naturally occurring conditions as a release (false positive or Type I error). An effective RBCA program requires the incorporation of defensible background threshold values (BTVs) in the screening process. Recent datasets and BTV development methods are available to enhance existing RBCA programs and reduce the occurrence of Type I errors. This review evaluated the role “background” currently plays in the Texas Risk Reduction Program (TRRP) and offers defensible approaches in minimizing Type I errors estimated by one Texas municipality to directly result in an unnecessary expenditure of over $250,000 annually to address this confusion in the form of additional assessment, remediation, soil management, and even disposal requirements. The same BTV development process demonstrated in this Texas case study can also inform risk assessment efforts in other areas where BTVs can supplement existing RBCA programs.

Song Gao

This paper examines the recent advances and applications of AI in human geography especially the use of machine (deep) learning, including place representation and modeling, spatial analysis and predictive mapping, and urban planning and design. AI technologies have enabled deeper insights into complex human-environment interactions, contributing to more effective scientific exploration, understanding of social dynamics, and spatial decision-making. Furthermore, human geography offers crucial contributions to AI, particularly in context-aware model development, human-centered design, biases and ethical considerations, and data privacy. The synergy beween AI and human geography is essential for addressing global challenges like disaster resilience, poverty, and equitable resource access. This interdisciplinary collaboration between AI and geography will help advance the development of GeoAI and promise a better and sustainable world for all.

Yerko Torres-Nova

Roughly speaking, the problem of geography asks for the existence of varieties of general type after we fix some invariants. In dimension $1$, where we fix the genus, the geography question is trivial, but already in dimension $2$, it becomes a hard problem in general. In higher dimensions, this problem is essentially wide open. In this paper, we focus on geography in dimension $3$. We generalize the techniques which compare the geography of surfaces with the geography of arrangements of curves via asymptotic constructions. In dimension $2$ this involves resolutions of cyclic quotient singularities and a certain asymptotic behavior of the associated Dedekind sums and continued fractions. We discuss the general situation with emphasis on dimension $3$, analyzing the singularities and various resolutions that show up, and proving results about the asymptotic behavior of the invariants we fix.

Yin Ching Lai

Hong Kong' senior geography curriculum has included GIS since the early 2000s. However, GIS in secondary schools does not play a significant role in Hong Kong secondary geography education. Analyzing GIS benefits by literature review, it is believed that GIS should be included in both the senior and junior geography curriculum. Moreover, the literature review indicates that without clear instruction from the Hong Kong Education Bureau (EDB), low preparedness of Hong Kong geography teachers, and unsupportive attitudes from academia and textbook publishers, GIS cannot be implemented in secondary schools of Hong Kong. Therefore, suggestions are made for the EDB, geography teachers, academia and textbook publishers to facilitate GIS involvement in senior and junior geography curriculums. The EDB can develop clear guidelines for teachers, academia and textbook publishers' references, and offer student-centered GIS educational courses for teachers. It is important for teachers to be prepared for advanced GIS technology and to even learn along with students. Academics and textbook publishers can provide free GIS maps targeted at Hong Kong' junior and senior geography curriculums. Although the report provides brief information towards the GIS implementation in Hong Kong geography education, it can inspire new ideas from other scholars to facilitate the usage of GIS in Hong Kong secondary school geography teaching.

Widodo Bayu, Dewi Renanti Medhanita, Indriasari Sofiyanti et al.

As the digital world evolves, safeguarding digital assets becomes crucial for organizations, particularly educational institutions. LSP SV-IPB, as a vocational certification body, manages student data, academic records, and other valuable information. Therefore, it is essential to implement an effective protection strategy. The research aims to develop and implement digital asset protection strategies at the LSP SV-IPB. The protection focuses on data storage management so that passive data is properly stored as the main backup and transactional data runs efficiently. The Synology Network Attached Storage (NAS) was proposed as the development model. NAS has proven efficient in managing data and providing reliable backups. Through NAS, passive data can be properly archived and protected, while transactional data can be accessed and processed at optimal speed. Hence, literature studies, software analysis, and experiments on the network environment were conducted. Model development was conducted using the design and implementation of NAS infrastructure at the LSP SV-IPB. Data collection covered the effective and efficient use of NAS in maintaining data integrity and mitigating the risk of losing important information. The results of this study are expected to contribute to the development of an efficient and reliable digital asset protection strategy within the LSP SV-IPB environment.

Zaika Yulvi, Charisma Nuril, Leta Milleila Nursanti Luh

As a foundation for transportation infrastructure, soft ground has limited bearing capacity and high compression. To prevent embankment failure, lightweight material is suggested. In the construction of road embankments, EPS can be regarded as an environmentally sustainable lightweight fill material. The study's goal is to create a formula for GB (Geo-bead) concrete mixing as a lightweight fill ingredient. Several tests are performed on the material specimens, including bulk density, interface shear strength, unconfined compression, and a SEM of the composite material. The tests were designed to determine the physical and mechanical qualities using GB percentages (20%, 30%, and 40%). Composite material has a lower density than compacted sand. The friction angle falls between the adhesion of GB-GB and GB-cemented sand. A ductile failure pattern develops because the bond between cement paste and GB is less than that between cement sand. The composite material's CBR passed embankment specifications. In the case of an embankment on soft soil, the 2D FEM analysis expressed settlement by compacted sand and lightweight fill material. Lightweight geo bead backfill decreases soft soil settlement, preventing failure.

Evan Cleave, Cailin Wark, Emmanuel Kyeremeh

For cities, immigration is now considered a vital part of local economic and community development. Over the past half-century, many cities have experienced a series challenges caused by the impacts of late-stage demographic transition; the slow bleeding of skilled domestic workers to larger metropolitan areas; and the decline of traditional economic sectors. As a result, there has been a prioritization of attracting and retaining high-skilled and well-educated immigrants by local governments through locally-focused, place-based policies. Within this context, this paper examines the ways that cities in the Province of Ontario, Canada are constructing and implementing immigrant attraction, integration, and retention strategies. To achieve this goal, we identified and examined the local immigration policies of the 52 cities in Ontario, 36 of which have a formal immigration policy document. A comprehensive content analysis was conducted on these available to identify the ways that immigration is conceptualized, and the specific policies and approaches that local governments are implementing. Statistical analysis was used to determine if there was variation in policy across different types of cities. Based on this analysis, local governments are generally developing holistic, place-based policies – however, there is variation in approaches across cities of different sizes and geographies. These place-specific policies draw on local assets and advantages (i.e. existing migrant communities; local amenities and attractions; economic and education opportunities) while also work to enhance enhancing local capacity (i.e. building networks and immigration partnerships; training employers and city workers).

Zurahmah Zainuddin, Agustang Agustang, Ilham Laman

Social studies and social sciences are interconnected. Both are related to basic human needs, then these basic needs can be achieved by basic human activities. Basic human activities include education, production and consumption, organization and government, protection and maintenance, aesthetics and recreation. All of them build social sciences. In the social sciences, it is classified into fields of science which include, among others, history, economics, political science, law, geography, anthropology, and social psychology. And in it there are facts, concepts, generalizations that were developed to build Social Sciences (IPS).

Ujjwal Sen

We find that the set of local quantum operations and classical communication for multiparty quantum states can be considered as analogous to online meetings between members of a population. Moreover, monotonicity properties of quantum and classical correlations of quantum states of shared systems also carry over to relations between members of the population, giving rise to what may be termed as a second law of anthropology.

Jeff Calder, Reed Coil, Annie Melton et al.

Machine learning (ML), being now widely accessible to the research community at large, has fostered a proliferation of new and striking applications of these emergent mathematical techniques across a wide range of disciplines. In this paper, we will focus on a particular case study: the field of paleoanthropology, which seeks to understand the evolution of the human species based on biological and cultural evidence. As we will show, the easy availability of ML algorithms and lack of expertise on their proper use among the anthropological research community has led to foundational misapplications that have appeared throughout the literature. The resulting unreliable results not only undermine efforts to legitimately incorporate ML into anthropological research, but produce potentially faulty understandings about our human evolutionary and behavioral past. The aim of this paper is to provide a brief introduction to some of the ways in which ML has been applied within paleoanthropology; we also include a survey of some basic ML algorithms for those who are not fully conversant with the field, which remains under active development. We discuss a series of missteps, errors, and violations of correct protocols of ML methods that appear disconcertingly often within the accumulating body of anthropological literature. These mistakes include use of outdated algorithms and practices; inappropriate train/test splits, sample composition, and textual explanations; as well as an absence of transparency due to the lack of data/code sharing, and the subsequent limitations imposed on independent replication. We assert that expanding samples, sharing data and code, re-evaluating approaches to peer review, and, most importantly, developing interdisciplinary teams that include experts in ML are all necessary for progress in future research incorporating ML within anthropology.

Wu Jun, Zheng Shiyong, Zheng Shiyong et al.

With the disclosure of ESG, the investment related to ESG disclosure has increased, and the trend of changes in intangible capital has shown an “inverted S-shaped” curve. The research shows that, in the initial stage of investment in ESG construction, new ESG investments increase intangible capital. With the increase in ESG investment and the advancement of time, the positive effect of the increase in ESG scores on intangible capital begins to appear and gradually offsets the cost of ESG investment. However, when the ESG score of a company is raised to a certain level, the marginal effect of continuing to increase ESG investment will reduce the increase in intangible capital.

Mokras-Grabowska Justyna, Mroczek-Żulicka Aleksandra, Olasik Marta

This article is an attempt at investigating new meanings and significance of computer-based entertainment during the COVID-19 pandemic. The authors explore how and to what extent students in Poland have been using electronics for entertainment during the global crisis, what emotions appeared and whether they were able and willing to engage in an auto-reflexive process. The article presents the results of the questionnaire interview designed for the purposes of this particular study. The authors chose to reveal the multi-facetedness of the theme in question, i.e. focus on the possibilities and the future that computer-based etertainment offers, leading to transformations both externally and internally.

Ajda Pretnar Žagar, Tomaž Hočevar, Tomaž Curk

What kind of questions about human mobility can computational analysis help answer? How to translate the findings into anthropology? We analyzed a publicly available data set of road traffic counters in Slovenia to answer these questions. The data reveals interesting information on how a nation drives, how it travels for tourism, which locations it prefers, what it does during the week and the weekend, and how its habits change during the year. We conducted the empirical analysis in two parts. First, we defined interesting traffic spots and designed computational methods to find them in a large data set. As shown in the paper, traffic counters hint at potential causes and effects in driving practices that we can interpret anthropologically. Second, we used clustering to find groups of similar traffic counters as described by their daily profiles. Clustering revealed the main features of road traffic in Slovenia. Using the two quantitative approaches, we outline the general properties of road traffic in the country and identify and explain interesting outliers. We show that quantitative data analysis only partially answers anthropological questions, but it can be a valuable tool for preliminary research. We conclude that open data are a useful component in an anthropological analysis and that quantitative discovery of small local events can help us pinpoint future fieldwork sites.

Nathan Fox, Carson Geissler

Generalized Geography is a combinatorial game played on a directed graph. Players take turns moving a token from vertex to vertex, deleting a vertex after moving the token away from it. A player unable to move loses. It is well known that the computational complexity of determining which player should win from a given position of Generalized Geography is PSPACE-complete. We introduce several rule variants to Generalized Geography, and we explore the computational complexity of determining the winner of positions of many resulting games. Among our results is a proof that determining the winner of a game known in the literature as Undirected Partizan Geography is PSPACE-complete, even when restricted to being played on a bipartite graph.

M. Boerngen

Alexandrine Royer

Over the next few years, society as a whole will need to address what core values it wishes to protect when dealing with technology. Anthropology, a field dedicated to the very notion of what it means to be human, can provide some interesting insights into how to cope and tackle these changes in our Western society and other areas of the world. It can be challenging for social science practitioners to grasp and keep up with the pace of technological innovation, with many being unfamiliar with the jargon of AI. This short guide serves as both an introduction to AI ethics and social science and anthropological perspectives on the development of AI. It intends to provide those unfamiliar with the field with an insight into the societal impact of AI systems and how, in turn, these systems can lead us to rethink how our world operates.