AIMC Topic: Computer Simulation

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Design and Analysis of a Novel Integral Recurrent Neural Network for Solving Time-Varying Sylvester Equation.

IEEE transactions on cybernetics
To solve a general time-varying Sylvester equation, a novel integral recurrent neural network (IRNN) is designed and analyzed. This kind of recurrent neural networks is based on an error-integral design equation and does not need training in advance....

The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning.

Sensors (Basel, Switzerland)
Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones' steering capacity and cognitive gap relate...

Nonfragile H State Estimation for Recurrent Neural Networks With Time-Varying Delays: On Proportional-Integral Observer Design.

IEEE transactions on neural networks and learning systems
In this article, a novel proportional-integral observer (PIO) design approach is proposed for the nonfragile H state estimation problem for a class of discrete-time recurrent neural networks with time-varying delays. The developed PIO is equipped wit...

Can machine learning improve randomized clinical trial analysis?

Seizure
PURPOSE: Recently a realistic simulator of patient seizure diaries was developed that can reproduce effects seen in randomized clinical trials (RCTs). RCTs suffer from high costs and statistical inefficiencies. Using realistic simulation and machine ...

Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients.

CPT: pharmacometrics & systems pharmacology
Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is l...

Co-AMPpred for in silico-aided predictions of antimicrobial peptides by integrating composition-based features.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides (AMPs) are oligopeptides that act as crucial components of innate immunity, naturally occur in all multicellular organisms, and are involved in the first line of defense function. Recent studies showed that AMPs per...

Mathematical and computational modeling for the determination of optical parameters of breast cancer cell.

Electromagnetic biology and medicine
This study enumerates the quantitative measurement of optical parameters used in several diagnostic procedures for malignant tissue. Optical diagnosis is proposed due to its non-invasive and non-destructive nature. This paper recapitulates Fresnel eq...

In silico saturation mutagenesis of cancer genes.

Nature
Despite the existence of good catalogues of cancer genes, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes acros...

Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets.

International journal of molecular sciences
Drug-induced liver toxicity is one of the significant safety challenges for the patient's health and the pharmaceutical industry. It causes termination of drug candidates in clinical trials and also the retractions of approved drugs from the market. ...

Bone collision detection method for robot assisted fracture reduction based on force curve slope.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. Most of the existing robot assisted fracture reduction systems don't have the function of bone collis...