Academic Articles & Research Papers

A neural-network-based detection of epilepsy

Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...

Neural networks in process fault diagnosis

Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural netw...

Progress in neural networks

Receptive field calculus, Jan J. Koenderink visual reconstruction and data fusion, D. Suter visual perception of translational and rotational motion, Jim-Shih Liaw, Irwin K. King and Michael A. Arbib neural network for recovering observer m...

Slimmable Neural Networks

We present a simple and general method to train a single neural network executable at different widths (number of channels in a layer), permitting instant and adaptive accuracy-efficiency trade-offs at runtime. Instead of training individua...

Artificial Neural Networks for Misuse Detection

Misuse detection is the process of attempting to identify instances of network attacks by comparing current activity against the expected actions of an intruder. Most current approaches to misuse detection involve the use of rule-based expe...

Neural Networks for Chemical Engineers

Part 1 Theoretical issues: an introduction to artificial neural networks, D.T. Pham unsupervised neural learning, E. Oja back-propagation and its variations, D. Tsaptsinos the general approximation problem for feed-forward neural networks, ...

Recurrent Neural Networks

From the Publisher: With applications ranging from motion detection to financial forecasting, recurrent neural networks (RNNs) have emerged as an interesting and important part of neural network research. Recurrent Neural Networks: Design ...

Default Detection Rate-Dependent Software Reliability Model with Imperfect Debugging

From the perspective of FDR (fault detection rate), which is an indispensable component in reliability modeling, this paper proposes two kinds of reliability models under imperfect debugging. This model is a relatively flexible and unified ...

Holistic Parameter Optimization for Software Defect Prediction

A software defect prediction (SDP) model identifies the defect-prone modules. Setting appropriate parameters in an SDP model is critical because it affects the model performance. In a recent study, parameters were automatically explored usi...

Polarized Multiwavelength Emission from Pulsar Wind—Accretion Disk Interaction in a Transitional Millisecond Pulsar

Transitional millisecond pulsars (tMSPs) bridge the evolutionary gap between accreting neutron stars in low-mass X-ray binaries and millisecond radio pulsars. These systems exhibit a unique subluminous X-ray state characterized by the prese...

Sustainable clove-derived nitrogen-doped carbon dots with programmable multimodal fluorescence for metal ion and fluoride sensing

The development of sustainable fluorescent nanomaterials from renewable biomass represents a promising strategy for environmentally benign chemical sensing. In this work, nitrogen-doped carbon dots (N-CDs) were synthesized from clove biomas...

Laser-induced porous graphene electrodes from polyketimine membranes for paracetamol sensing

The development of cost-effective materials for fabricating electrodes is crucial for drug, pharmaceutical and environmental applications. This paper presents the synthesis and characterization of a novel polyketimine (PKI) membrane obtaine...

A bibliometric review of unilateral neglect: Trends, frontiers, and frameworks

BACKGROUND: Owing to the adverse effects of unilateral neglect (UN) on rehabilitation outcomes, fall risk, and activities of daily living, this field has gradually got considerable interest. Notwithstanding, there is presently an absence of...

Sensitivity and Features of Computed Tomography in Diagnosis of COVID-19 Pneumonia: A Meta-analysis

Introduction: Early diagnosis of COVID-19 is important for disease treatment and management. Computed Tomography (CT) is a fast and easy modality for diagnosis and management plan of patients with COVID-19. In the literature, several stu...

Dielectric‐Confinement‐Induced in‐Plane Photoelectric Anisotropy in Isotropic Quasi‐1D γ‐GaS Nanoribbon

ABSTRACT The growing demand for polarized photodetection has driven the need for compact, integrated, and multifunctional device architectures. Although one‐dimensional (1D) materials are of significant interest for their innate polarizatio...

Encapsulating acetylcholinesterase (AChE) into metal-organic frameworks for selective and sensitive colorimetric detection of carbaryl residue in water samples.

Post-quantum cognitive zero trust architecture for healthcare IoT devices.

Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-enabled cyber threats, but introduced heightened cybersecurity risks, particularly from emer...

Bridging Deep Learning and Quantum Computing for EEG-Driven P300 Targeted ASD Response Detection

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose diagnosis relies heavily on subjective behavioral assessments. Electroencephalography (EEG) provides an inexpensive and non-invasive method of objective biomarker detect...

SERS of Bottled Water: Automated PET Nanoplastic Detection and Quantification.

Feasibility of one-stop multi-energy dynamic photon-counting perfusion CT for resectable HCC evaluation: lesion detection and histopathological correlations.