Results 21 to 30 of about 3,901 (232)

LSTM-ARIMA AS A HYBRID APPROACH IN ALGORITHMIC INVESTMENT STRATEGIES

Working Papers
This study focuses on building an algorithmic investment strategy employing a hybrid approach that combines LSTM and ARIMA models referred to as LSTM-ARIMA. This unique algorithm uses LSTM to produce final predictions but boost results of this RNN by adding the residuals obtained from ARIMA predictions among other inputs. The algorithm is tested across
Kamil Kashif, Robert Ślepaczuk
openaire   +2 more sources

Overview of molecular signatures of senescence and associated resources: pros and cons

FEBS Open Bio, EarlyView.
Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas, Sylvia Vagena, Pavlos Pantelis, Giorgos Theocharous, Russel Petty, Konstantinos Evangelou, Vassilis G. Gorgoulis   +6 more
wiley   +1 more source

Governing AI Decision‐Making: Balancing Innovation and Accountability

Politics and Governance
This article explores the growing use of algorithmic models to make or inform decisions within the public sector. Amidst a climate of accelerating investment, expanding system applicability, and rapid technical progress, it concentrates on how key ...
David Mark, John Morison
doaj   +1 more source

Grid Trading System Robot (GTSbot): A Novel Mathematical Algorithm for Trading FX Market

Applied Sciences, 2019
Grid algorithmic trading has become quite popular among traders because it shows several advantages with respect to similar approaches. Basically, a grid trading strategy is a method that seeks to make profit on the market movements of the underlying ...
Francesco Rundo, Francesca Trenta, Agatino Luigi di Stallo, Sebastiano Battiato   +3 more
doaj   +1 more source

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

FEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability

Advanced Engineering Materials, EarlyView.
This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner, Geo Jacob, Florian Raddatz, Gerko Wende   +3 more
wiley   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Joint Control of Radiated and Surface Waves via Space‐Time Coding Metasurfaces

Advanced Functional Materials, EarlyView.
A unified space‐time coding metasurface platform enables simultaneous control of radiated and surface‐confined waves across multiple harmonics. Demonstrated functionalities include multi‐frequency beam shaping; surface‐wave excitation, and hybrid multiplexing.
Zihao Dai, Yi Ning Zheng, Lei Zhang, Xiao Qing Chen, Giuseppe Castaldi, Tie Jun Cui, Vincenzo Galdi   +6 more
wiley   +1 more source

Optimal Markowitz portfolio using returns forecasted with time series and machine learning models

Journal of Big Data
We aim to answer whether using forecasted stock returns based on machine learning and time series models in a mean-variance portfolio framework yields better results than relying on historical returns.
Damian Ślusarczyk, Robert Ślepaczuk
doaj   +1 more source

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source