Results 121 to 130 of about 155,072 (308)

MODIFIED MAXIMUM AUTO-CORRELATION ESTIMATION FOR CHAOTIC INITIAL CONDITION MODULATION SCHEME

Journal of Engineering and Sustainable Development, 2016
In this paper, an efficient technique for initial condition estimation of chaotic map in binary phase shift keying initial condition modulation (BPSK-ICM) scheme is proposed. This technique is named maximum autocorrelation estimation (MACE).
Hikmat Najem Abdullah, Ibrahim Fahmi Ali   +1 more
doaj  

Foucault–Barker Mask: Nonconventional Schlieren Technique

Optics
We present a theoretical framework for designing optical masks, which are useful for implementing nonconventional Schlieren techniques. We revisit the use of effective transfer functions, which emphasize the role of symmetries in the design of coded ...
Cristina M. Gómez-Sarabia, Jorge Ojeda-Castañeda   +1 more
doaj   +1 more source

An Energy-Balancing Technique using Spatial Autocorrelation for Wireless Sensor Networks [PDF]

, 2016
Hyonam Jeong, Jun Hwang
openalex   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Impact of Biomimetic Pinna Shape Variation on Clutter Echoes: A Machine Learning Approach

Advanced Intelligent Systems, EarlyView.
Bats with dynamic ear structures navigate dense, echo‐rich environments, yet the echoes they receive are highly random. This study shows that machine learning can reliably detect structural signatures in these seemingly chaotic biosonar signals. The results open new directions for biologically inspired sensing, where time‐varying receiver shapes ...
Ibrahim Eshera, Sanmeel Lagad, Rolf Müller   +2 more
wiley   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

Advanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk, Lingyin Meng, Christer Borgfeldt, Jens Eriksson, Donatella Puglisi   +4 more
wiley   +1 more source

Bio‐to‐Robot Transfer of Fish Sensorimotor Dynamics via Interpretable Model

Advanced Intelligent Systems, EarlyView.
This study demonstrates how a biologically interpretable model trained on real‐fish muscle activity can accurately predict the motion of a robotic fish. By linking real‐fish sensorimotor dynamics with robotic fish, the work offers a transparent, data‐efficient framework for transferring biological intelligence to bioinspired robotic systems.
Waqar Hussain Afridi, Ahsan Tanveer, Rahdar Hussain Afridi, Muhammad Hamza, Mingxin Wu, Liang Li, Guangming Xie   +6 more
wiley   +1 more source

Self‐Creation of Accelerated Temporal Mirrors

Advanced Physics Research, EarlyView.
The field of temporal analog effects is rapidly emerging and seen as a driver of a paradigm shift in photonics. It promises striking new phenomena but remains experimentally challenging. This work introduces a mechanism that automatically creates a temporal mirror with simple optical means, unlocking practical access to extreme nonlinear dynamics and ...
Oliver Melchert, Surajit Bose, Uwe Morgner, Ihar Babushkin, Ayhan Demircan   +4 more
wiley   +1 more source