Food retailing is now on an accelerated path to a success penetration into the digital market by new ways of value creation at all stages consumer decision process. One most important imperatives in this availability quality data feed process transformation. However, are not so obvious if we consider variety products and suppliers grocery market. Within context transformation industry, Midiadia...

Photonic neural networks (PNNs) are promising to replace conventional deep learning hardware due their potentially higher energy efficiency and computational speed. Other than the fast progress on optical linear transformer, nonlinear activators much less mature. Usually, employ mapping from input amplitude output amplitude, which is limited by high threshold loss, or rely additional bias volta...

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy s...

Epilepsy is a serious brain disorder with diverse seizure types and epileptic syndromes. AMPA receptor antagonist 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzoquinoxaline-2,3-dione (NBQX) attenuates spontaneous recurrent seizures in rats. However, the anti-epileptic effect of NBQX in chronic epilepsy model is poorly understood. Perineuronal nets (PNNs), specialized extracellular matrix structures, su...

The purpose of this paper is to develop an intelligent diagnosis system for breast cancer classification. Artificial Neural Networks and Support Vector Machines were being developed to classify the benign and malignant of breast tumor in fine needle aspiration cytology. First the features were extracted from 92 FNAC image. Then these features were presented to several neural network architectur...

Objectives: The purpose of this study is to investigate the alterations of the hypothalamic-pituitary-adrenal axis hormones, especially salivary cortisol and dehydroepiandrosterone (DHEA) in perinatal depression. Methods: 44 patients with depression and 217 normal subjects in perinatal period were included in this study. Edinburgh Postnatal Depression Scale(EPDS) and Beck Depression Inventory I...

Objectives: The purpose of this study is to investigate the alterations of the hypothalamic-pituitary-adrenal axis hormones, especially salivary cortisol and dehydroepiandrosterone (DHEA) in perinatal depression. Methods: 44 patients with depression and 217 normal subjects in perinatal period were included in this study. Edinburgh Postnatal Depression Scale(EPDS) and Beck Depression Inventory I...

Context: Mutation Testing (MT) is an important tool in traditional Software Engineering (SE) white-box testing. It aims to artificially inject faults a system evaluate test suite's capability detect them, assuming that the suite defects finding will then translate real faults. If MT has long been used SE, it only recently started gaining attention of Deep Learning (DL) community, with researche...

Probabilistic Neural Network (PNN) also termed to be a learning machine is preliminarily used with an extension of various image classifications based on Training networks and Testing networks. To efficiently detect Brain Tumor cells, clustering method based on FCM can also be implemented. The Probabilistic Neural Network (PNN) will be employed to classify the various stages of Tumor cut levels...