Hasil untuk "Bibliography"

A. Ledeneva

R. Kanwal

B. Simon

A. Gell

Q. Skinner

B. Richardson, P. Baverstock, M. Adams et al.

V. J. Rayward-Smith, F. Höppner, F. Klawonn et al.

H. Srivastava, Junesang Choi

R. Cignoli, I. L. D'Ottaviano, D. Mundici

El-Ghazali Talbi

R. Berns

Defining Color. Describing Color. Measuring Color. Measuring Color Quality. Colorants. Producing Colors. Back to Principles. Appendix. Bibliography. Index.

B. Henrique, Vinicius Amorim Sobreiro, H. Kimura

Abstract The search for models to predict the prices of financial markets is still a highly researched topic, despite major related challenges. The prices of financial assets are non-linear, dynamic, and chaotic; thus, they are financial time series that are difficult to predict. Among the latest techniques, machine learning models are some of the most researched, given their capabilities for recognizing complex patterns in various applications. With the high productivity in the machine learning area applied to the prediction of financial market prices, objective methods are required for a consistent analysis of the most relevant bibliography on the subject. This article proposes the use of bibliographic survey techniques that highlight the most important texts for an area of research. Specifically, these techniques are applied to the literature about machine learning for predicting financial market values, resulting in a bibliographical review of the most important studies about this topic. Fifty-seven texts were reviewed, and a classification was proposed for markets, assets, methods, and variables. Among the main results, of particular note is the greater number of studies that use data from the North American market. The most commonly used models for prediction involve support vector machines (SVMs) and neural networks. It was concluded that the research theme is still relevant and that the use of data from developing markets is a research opportunity.

L. Richards

F. Bouchut

K. Borre, D. Akos, N. Bertelsen et al.

Masoumeh Hasani, Hamid Keshavarz, Amir Reza Asnafi et al.

Purpose: The current study examined the effectiveness of gamified reading of electronic books among adolescents in school libraries.Method: A randomized sample of students aged 11 to 12 years including two control and experimental groups from four schools participated in this study. According to the Mechanics, Dynamics, and Emotions (MDE) framework, six gamification elements were implemented as group challenges. The experiences were then evaluated based on a quasi-experimental design with a post-test via the GAMEX scale.Findings: Multiple independent t-tests using SPSS 26.0 showed that the gamified experience and its relevant subscales including enjoyment, absorption, creative thinking, activation, absence of negative affect, and dominance differed significantly between the two groups. Therefore, the results revealed that implementing gamification in the reading experience within a gamified environment is highly effective and will influence adolescents' interest, motivation and ability to read in library contexts, which can be of interest to experts and policymakers in education and computer science.Conclusion: Various game mechanisms can be integrated into the educational context or platforms like electronic books to make learning interesting and motivating to the students.

Stefan Marian Ludwig

We show two results on higher amalgamation in the theory $\mathrm{ACFA}^{+}$, the model companion of the theory of difference fields with an additive character (added as a continuous logic predicate) on the fixed field in characteristic 0. On one hand, we show that the non-trivial condition for 3-amalgamation established in a preceding paper is not sufficient for 4-amalgamation. On the other hand, we show that when working over substructures whose $\mathcal{L}_σ$-reduct is a model of $\mathrm{ACFA}$, $n$-amalgamation holds for all $n\geq 3$.

Andrea Secchi, Gaia Forghieri, Paolo Bordone et al.

The intense simulation efforts on hole-spin qubits in germanium have so far focused primarily on singly occupied quantum dots. Here, we theoretically investigate three-hole qubits in germanium and demonstrate that their performance can rival that of single-hole qubits in both strained and unstrained systems. In particular, we find that -- in the widely used quasi-circular geometry -- a three-hole qubit encoding can yield enhancements of the Rabi frequencies of up to two orders of magnitude and a large advantage also in terms of quality factors.

Subhankar Bhadra, Marianna Pensky, Srijan Sengupta

Massive network datasets are becoming increasingly common in scientific applications. Existing community detection methods encounter significant computational challenges for such massive networks due to two reasons. First, the full network needs to be stored and analyzed on a single server, leading to high memory costs. Second, existing methods typically use matrix factorization or iterative optimization using the full network, resulting in high runtimes. We propose a strategy called \textit{predictive assignment} to enable computationally efficient community detection while ensuring statistical accuracy. The core idea is to avoid large-scale matrix computations by breaking up the task into a smaller matrix computation plus a large number of vector computations that can be carried out in parallel. Under the proposed method, community detection is carried out on a small subgraph to estimate the relevant model parameters. Next, each remaining node is assigned to a community based on these estimates. We prove that predictive assignment achieves strong consistency under the stochastic blockmodel and its degree-corrected version. We also demonstrate the empirical performance of predictive assignment on simulated networks and two large real-world datasets: DBLP (Digital Bibliography \& Library Project), a computer science bibliographical database, and the Twitch Gamers Social Network.

Barbara M. Pope

Health sciences libraries serving universities and medical facilities have long used technology to provide library services, but COVID-19 presented libraries with unique challenges. Libraries shut their doors and adapted to conducting reference, instruction, and outreach, remotely. For some libraries described in Virtual Services in the Health Sciences Library: a Handbook, those services had been done in the library; for others, the library had considered adding virtual services. For those libraries that have not made the jump, this text presents strategies to which all health sciences libraries would find a useful reference. Given its practical strategies and engaging text, this reviewer finds Virtual Services in the Health Sciences Library: a Handbook to be an inspiring and a highly recommended reference for health sciences libraries.