Hasil untuk "General Works"

Ali Nasiri Khiavi, Mehdi Vafakhah, Dongkun Kim et al.

ABSTRACT This study develops a comprehensive framework for mapping flood susceptibility and vulnerability in the Cheshmeh‐Kileh forest watershed in northern Iran by integrating remote sensing (RS), local knowledge, and machine learning (ML) algorithms. This was accomplished through the application of various MLs, such as K‐nearest neighbor (KNN), random forest (RF), support vector regression (SVR), and Naive Bayes. In this study, flood susceptibility refers to the physical propensity of an area to experience flooding, influenced by geo‐environmental factors, while flood vulnerability captures the socio‐economic and institutional dimensions that determine a community's ability to cope with and recover from flood events. This research first identified critical geo‐environmental factors influencing flood susceptibility and utilized remote sensing to locate areas prone to runoff generation. Flood risk zoning was then implemented using machine learning techniques in Python. To assess flood vulnerability, data were collected from local residents via questionnaires, focusing on economic, infrastructural‐physical, institutional‐policy, and social‐cultural aspects. The flood vulnerability map was created by integrating these survey results with population density data to identify areas where high social exposure coincides with high physical susceptibility. Findings indicated that the combined remote sensing‐SVR model was the most effective for sensitivity classification, identifying sub‐watersheds 2 and 8 in the Sehezar River (a major basin within the study area) as the areas with the highest and lowest flooding susceptibility, respectively, with sub‐watershed 10 in the Dohezar River (another major basin) being the most vulnerable. The estimated values for Mean Absolute Error (0.041), Mean Square Error (0.042), Root Mean Square Error (0.205), and Area Under the Curve (0.980) demonstrated high model accuracy. The Friedman statistical test showed that the average scores for the different dimensions of vulnerability decreased in the order of: economic (0.48), social‐cultural (0.44), infrastructural‐physical (0.34), and institutional‐policy (0.28). Consequently, the economic dimension was prioritized for its highest score. Flood vulnerability mapping revealed that sub‐watersheds 5, 11, 14, and 15, which had higher population densities, were naturally more vulnerable to floods. This finding reflects a direct relationship between population density and flood vulnerability. Overall, this study underscores the urgent need for effective planning and preventive strategies to mitigate flood risks and enhance resilience in the region.

Kaiyuan Hou, Xiaotian Zhang, Junjie Yang et al.

Given the complexity and dynamic nature of short-term load sequence data, coupled with prevalent errors in traditional forecasting methods, this study introduces a novel approach for short-term load forecasting. The method integrates multi-frequency sequence feature analysis and multi-point correction using the FEDformer model. Initially, variational mode decomposition (VMD) technology decomposes the load sequence into multiple subsequences, each exhibiting distinct frequency characteristics. Subsequently, for each frequency band of the load sequence, the LightGBM algorithm quantifies the correlation between the load and various influencing factors. The filtered features are then input into the FEDformer model, providing preliminary short-term and long-term sequence prediction results. Finally, a point-by-point forecasting method based on a tree model generates multi-point load prediction results by training multiple LightGBM models. Throughout the forecasting process, a weighted threshold α is set, and a hybrid weighting method is utilized to combine the forecast results from different models, culminating in the final short-term load forecast results. Validation of the proposed hybrid model was conducted on an actual dataset from a specific area, The results exhibit higher prediction accuracy, affirming the proposed method as a novel and effective approach for short-term load forecasting.

M. Laine, S. Procacci

Working in an arbitrary gauge, we derive the source term for scalar-induced gravitational waves (SIGW) valid during a general reheating epoch. Specifically, the dominant energy component is allowed to transition smoothly from an inflaton field to a radiation fluid, possibly via a period of matter domination. Gauge invariance is verified up to second order.

Agenor Manoel da Silva Filho

Uma das mais bem sucedidas obras do campo da História das Ciências no Brasil, “A Matemática no Brasil” conquistou quatro edições ao longo de 30 anos. Um clássico que permanece atual graças a nova edição da Editora Blücher. A presente resenha destaca os pontos mais significativos da obra e suas características textuais e materiais, enfatizando a importância de reedições de trabalhos como este para a difusão do campo. 

И. Н. Карцан, С. А. Нуриев

Машинное обучение включает использование алгоритмов и статистических моделей, которые позволяют компьютерам повысить эффективность выполнения задач на основе опыта, накопленного с помощью данных. При интеграции в бизнес-аналитику алгоритмы машинного обучения анализируют обширные массивы данных, чтобы выявить закономерности, корреляции и выводы, которые могут быть упущены из виду традиционными методами. Машинное обучение революционизирует бизнес-аналитику, снабжая организации передовыми инструментами для обработки больших объемов данных, более точных прогнозов и совершенствования процессов принятия решений. Позволяя компьютерам учиться на данных без необходимости эксплицитного программирования, машинное обучение позволяет компаниям выявлять скрытые тенденции, прогнозировать будущие результаты и автоматизировать сложные задачи с большей точностью. Эта технология повышает эффективность работы и дает предприятиям конкурентное преимущество в более глубоком понимании их данных. В этой статье мы рассмотрим роль машинного обучения в бизнес-аналитике, сосредоточив внимание на его практических приложениях, ключевых преимуществах, проблемах и преобразующем влиянии, которое ожидается от него во всех отраслях мира в ближайшие годы. По мере развития технологий, машинное обучение будет играть все более важную роль в формировании будущего бизнеса, предоставляя новые возможности для инноваций, эффективности и роста.

Kristian Stølevik Olsen, Deepak Gupta

Partial resetting, whereby a state variable $x(t)$ is reset at random times to a value $a x (t)$, $0\leq a \leq 1$, generalizes conventional resetting by introducing the resetting strength $a$ as a parameter. Partial resetting generates a broad family of non-equilibrium steady states (NESS) that interpolates between the conventional NESS at strong resetting ($a=0$) and a Gaussian distribution at weak resetting ($a \to 1$). Here, such resetting processes are studied from a thermodynamic perspective, and the mean cost associated with maintaining such NESS are derived. The resetting phase of the dynamics is implemented by a resetting potential $Φ(x)$ that mediates the resets in finite time. By working in an ensemble of trajectories with a fixed number of resets, we study both the steady-state properties of the propagator and its moments. The thermodynamic work needed to sustain the resulting NESS is then investigated. We find that different resetting traps can give rise to rates of work with widely different dependencies on the resetting strength $a$. Surprisingly, in the case of resets mediated by a harmonic trap with otherwise free diffusive motion, the asymptotic rate of work is insensitive to the value of $a$. For general anharmonic traps, the asymptotic rate of work can be either increasing or decreasing as a function of the strength $a$, depending on the degree of anharmonicity. Counter to intuition, the rate of work can therefore in some cases increase as the resetting becomes weaker $(a\to 1)$ although the work vanishes at $a=1$. Work in the presence of a background potential is also considered. Numerical simulations confirm our findings.

Katrina Reynen, Penny Round, Pearl Subban

Gifted young people from disadvantaged backgrounds are often overlooked for gifted programs due to their relatively lower financial, social and cultural capital. One promising area of research is the reflexive analysis of the enablers and barriers for these students once they have successfully progressed to university. This scoping review examines current research into factors that hinder or enable gifted students from disadvantaged backgrounds to develop their latent talent and complete higher education. It drew on four education databases and analysed ten peer reviewed studies at the junction of giftedness; disadvantage; and young adults. The conclusion is that there is little current research on gifted, disadvantaged, young adult learners. This paper offers a new conceptualization of talent development through a lens of poverty.

Oscar López-Aguayo, J. C. López-Domínguez, M. Sabido

In this work we study the effects of the generalized uncertainty principle (GUP) in cosmology. We start with the Friedmann-Robertson-Walker (FRW) model endowed with a scalar field. After introducing the GUP modification to the model, we solve for the quantum and classical cases. Finally we find the GUP modified Friedmann equations.

Minghao Xia, Sijie Gao

Tolman proposed that the proper temper $T$ of a static self-gravitating fluid in thermodynamic equilibrium satisfies the relation $χT=constant$, where $χ$ is the redshift factor of the spacetime. The Tolman law has been proven for radiation in stationary spacetimes and for perfect fluids in stationary, asymototically flat and axisymmetric spacetimes. It is unclear whether the proof can be extended to more general cases. In this paper, we prove that under some reasonable conditions, the Tolman law always holds for a perfect fluid in a stationary spacetime. The key assumption in our proof is that the particle number density $n$ can not be determined by the energy density $ρ$ and pressure $p$ via the equations of state. This is true for many known fluids with the equation of state $p=p(ρ)$. Then, by requiring that the total entropy of the fluid is an extremum for the variation of $n$ with a fixed metric, we prove the Tolman law. In our proof, only the conservations of stress energy and the total particle number are used, and no field equations are involved. Our work suggests that the Tolman law holds for a generic perfect fluid in a stationary spacetime, even beyond general relativity.

Can Ding, Yiyuan Zhou, Guang Pu et al.

To achieve carbon neutrality in electricity, measures such as increasing the share of renewable energy sources such as wind power and achieving more accurate and faster wind power forecasting, and low carbon retrofitting of thermal power units are all important to achieve the goal. Firstly, the GRU prediction algorithm was used to forecast wind power, which performed well in terms of prediction accuracy and model training speed. Then, we continue to fully utilize the source-side low-carbon characteristics by installing flue gas bypass systems and liquid storage in carbon capture plants to form an integrated carbon capture plant operation, thereby reducing carbon emissions and the proportion of abandoned wind. Secondly, a three-stage low carbon economic dispatch model is established to reduce wind abandonment by combining wind power forecasts on different time scales. Finally, a case study was carried out using a modified IEEE-39 node system. The results show that the proposed three-stage integrated dispatching method can make full use of wind energy and achieve the goal of economic dispatching of the power system.

Jyh-An Lee** Rita Matulionyte*

In Thaler v The Comptroller-General of Patents, Designs and Trade Marks (DABUS), Smith J. held that an AI owner can possibly claim patent ownership over an AI-generated invention based on their ownership and control of the AI system. This AI-owner approach reveals a new option to allocate property rights over AI-generated output. While this judgment was primarily about inventorship and ownership of AI-generated invention in patent law, it has important implications for copyright law. After analysing the weaknesses of applying existing judicial approaches to copyright ownership of AI-generated works, this paper examines whether the AI-owner approach is a better option for determining copyright ownership of AI-generated works. The paper argues that while contracts can be used to work around the AI-owner approach in scenarios where users want to commercially exploit the outputs, this approach still provides more certainty and less transaction costs for relevant parties than other approaches proposed so far.

Ning Qi, Lin Cheng, Yuxiang Wan et al.

Current risk assessment ignores the stochastic nature of energy storage availability itself and thus lead to potential risk during operation. This paper proposes the redefinition of generic energy storage (GES) that is allowed to offer probabilistic reserve. A data-driven unified model with exogenous and endogenous uncertainty (EXU & EDU) description is presented for four typical types of GES. Moreover, risk indices are proposed to assess the impact of overlooking (EXU & EDU) of GES. Comparative results between EXU & EDU are illustrated in distribution system with day-ahead chance-constrained optimization (CCO) and more severe risks are observed for the latter, which indicate that system operator (SO) should adopt novel strategies for EDU uncertainty.

Luis Viveros-Almeida, Iván Realpe-Cabrera

El presente trabajo es una investigación de tipo descriptivo-correlacional, con enfoque cuantitativo, que tiene como objetivo determinar si existe relación entre el tipo de cambio y el flujo de personas, vehículos de carga y livianos (Tulcán e Ipiales), durante el periodo de enero-marzo de 2019. Los principales resultados sugieren que existe una relación baja-moderada entre las tasas de cambio y el flujo de personas, vehículos de carga y livianos. La relación más significativa se dio entre el tipo de cambio y la salida de camiones pequeños (0,327).

Rita Marnoto

O presente número de Biblos. Revista da Faculdade de Letras da Universidade de Coimbra, que é o 7.º da 3.ª série, apresenta um conjunto de contributos dedicado ao tema Dissidências. Compreendendo a dissidência um larguíssimo espectro de atitudes, opiniões e comportamentos, vinculado a um desacordo de ordem conceptual, emocional ou de desempenho relativamente a uma norma estabelecida, os confrontos que dela decorrem propulsionam uma dinâmica que é tão instigante, pela acuidade das questões colocadas, como complexa, pela pluralidade dialética dos fatores envolvidos.

Maximilian Diehl, Karinne Ramirez-Amaro

In this paper, we report the results of our latest work on the automated generation of planning operators from human demonstrations, and we present some of our future research ideas. To automatically generate planning operators, our system segments and recognizes different observed actions from human demonstrations. We then proposed an automatic extraction method to detect the relevant preconditions and effects from these demonstrations. Finally, our system generates the associated planning operators and finds a sequence of actions that satisfies a user-defined goal using a symbolic planner. The plan is deployed on a simulated TIAGo robot. Our future research directions include learning from and explaining execution failures and detecting cause-effect relationships between demonstrated hand activities and their consequences on the robot's environment. The former is crucial for trust-based and efficient human-robot collaboration and the latter for learning in realistic and dynamic environments.

Osvaldo L. Santos-Pereira, Everton M. C. Abreu, Marcelo B. Ribeiro

The Alcubierre warp drive metric is a spacetime construction where a massive particle located inside a spacetime distortion, called warp bubble, travels at velocities arbitrarily higher than the velocity of light. This theoretically constructed spacetime geometry is a consequence of general relativity where global superluminal velocities, also known as warp speeds, are possible, whereas local speeds are limited to subluminal ones as required by special relativity. In this work we analyze the solutions of the Einstein equations having charged dust energy-momentum tensor as source for warp velocities. The Einstein equations with the cosmological constant are written and all solutions having energy-momentum tensor components for electromagnetic fields generated by charged dust are presented, as well as the respective energy conditions. The results show an interplay between the energy conditions and the electromagnetic field such that in some cases the former can be satisfied by both positive and negative matter density. In other cases the dominant and null energy conditions are violated. A result connecting the electric energy density with the cosmological constant is also presented, as well as the effects of the electromagnetic field on the bubble dynamics.

Mayank Gokarna, Raju Singh

DevOps is an emerging practice to be followed in Software Development life cycle. The name DevOps indicates that its an integration of Development and Operations team. It is followed to integrate the various stages of the development lifecycle. DevOps is an extended version of the existing Agile method. DevOps aims at Continuous Integration, Continuous Delivery, Continuous Improvement, faster Feedback and Security. This paper reviews the building blocks of DevOps, challenges in adopting DevOps, models to improve DevOps practices and Future works on DevOps.

Hideki Maeda

In all $n(\ge 3)$-dimensional gravitation theories whose Lagrangians are functions of the Riemann tensor and metric, we show that static solutions are absent unless the total energy-momentum tensor for matter fields is of type I in the Hawking-Ellis classification. In other words, there is no hypersurface-orthogonal timelike Killing vector in a spacetime region with an energy-momentum tensor of type II, III, or IV. This asserts that, if back-reaction is taken into account to give a self-consistent solution, ultra-dense regions with a semiclassical type-IV matter field cannot be static even with higher-curvature correction terms. As a consequence, a static Planck-mass relic is possible as a final state of an evaporating black hole only if the semiclassical total energy-momentum tensor is of type I.

M. Rostamian Delavar

Some Hermite-Hadamard's mid-point type inequalities related to Katugampola fractional integrals are obtained where the first derivative of considered mappings is Lipschitzian or convex. Also some mid-point type inequalities are given for Lipschitzian mappings, with the aim of generalizing the results presented in previous works. Finally as an application, some generalized inequalities in connection with special means are provided.

Shelley Miller

I create murals that look like azulejos, depicting caravels and many decorative features seen in traditional azulejos, but my murals are made entirely of sugar. I make the sugar tiles and hand paint them with edible inks. I am interested in the azulejo, specifically with imagery of ships, as a symbol of colonial power and of national pride (the Nation of Portugal), but only for the means to subvert this pride. I developed this work in Brazil, addressing the country’s history of colonization and the slave trade that supported Portugal’s sugar empire. I continue to use the blue tile reference, even outside the context of Brazil, because I want to reference the general construct of colonization and slavery, showing how oppression has found new forms. I install my ephemeral murals on city walls, where they wash away, fade, crumble and decay, animating a more realistic version of history.