The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This work proposes an ANN based method for fetal heart rate monitoring. Various measurements are taken and given as input to the ANN based classifier to detect fetal health such as ‘Normal’, ‘Suspect’ and ‘Pathologic’. All the design and simulation works are carried out with MATLAB software. ANN based classifier is trained with data from various recordings of cardiotocography. After the network is...
Security of today communication networks depends also on effective hash function. A cryptographic hash function is used to realize a transformation of input to a fixed-size value. This value is called the hash value. One way hash function could be generated also by an artificial neural network (ANN). Theoretical analysis of the possibility of using artificial neural network and chaotic maps for hashing...
Effective generation of hash function is very important for an achievement of a security of today networks. A cryptographic hash function is a transformation that takes an input and returns a fixed-size value, which is called the hash value. A recurrent neural network, as a possible approach, could be used for the hash function generation. The performance of the recurrent neural network (RNN) was...
This paper presents a series of experiments on the classification of emergency phone conversation records using artificial neural networks (ANNs). Input data which were processed by ANNs were the features of callers and events taken from emergency phone calls. The authors analyzed four variants of classification: the groups of callers which have specified features, the groups of events which have...
This paper is using artificial neural network (ANN) to predict oxygen content in the water for the fish farm, so that decrease times of starts of oxygen suppliers. In Southern Taiwan, aquaculture is one of major economic industries. Especially, the important issue is how to effectively monitor the oxygen content in the water, so that the fish will not die and start the oxygen suppliers for the minimum...
Epileptic seizure source identification involves neurologists combing through a substantial amount of data manually, which sometimes takes weeks per patient. This paper presents a methodology for minimizing the amount of data a neurologist has to analyze to identify the seizure focus. The method keeps the neurologist as the final decision maker and aids in the decision making process. It has to be...
In this paper, an approach for increasing the sustainability of inverter-based memristive neuromorphic circuits in the presence of process variation is presented. The approach works based on extracting the impact of process variations on the neurons characteristics during the test phase through a proposed algorithm. In this method, first, some combinations of inputs and weights (based on the neuromorphic...
This paper introduces to diagnosis of Dyslexia using computing system, considered people difficulties in reading, spelling, writing and speaking. Consequently, a computational analysis classifier will be achieved using dyslexia metrics techniques. Accordingly, Gibson test of brain skills will be used with effect of working memory, auditing (hearing and speech) and visual memory and cognition, visual...
With the integration of EVs into the power grid, smart metering using machine-to-machine (M2M) communication is likely to play an important role in real-time energy management and control. Smart devices embedded with advanced metering infrastructure (AMI) can forecast the energy demand as well as perform energy pricing in real time. In this paper, an artificial neural network (ANN) based intelligent...
Effective generation of hash function is very important for an achievement of a security of today networks. A cryptographic hash function is a transformation that takes an input and returns a fixed-size value, which is called the hash value. An artificial neural network (ANN), as a possible approach, could be used for the hash function generation. The performance of the ANN was validated by software...
Biometrics play a crucial role in establishing an individuals identity. A signature is one of the most widely recognized way to authorize transactions and authenticate the human identity as compared to other electronic identification methods such as fingerprint and retina scans. Due to a huge demand for authentication, fast algorithms need to be assimilated for signature recognition and verification...
This paper presents a relaying algorithm based on Artificial Neural Network (ANN) technique for the protection of transmission line. A feed forward ANN with six inputs and eleven outputs has been developed for the detection and classification of faults. Data was generated by simulating a 400 kV, 50Hz, 100 km transmission line in PSCAD/EMTDC at a sampling frequency of 2 kHz. Three ANN configurations...
This paper presents the results of a study developing artificial neural network system (ANN) for classification of Alzheimer's disease (AD) and healthy patients. The classification is done using biomarkers, from cerebrospinal fluid: albumin ratio (CSF/Serum and/or Plasma), Aβ40 (CSF), Aβ42 (CSF), tau-total (CSF) and tau-phospho (CSF). Neural network input parameters are datasets from Alzbiomarkers...
Electrocardiogram (ECG) is used as one of the important diagnostic tool for the detection of the health of a heart. Growing number of heart patients has necessitated development of automatic detection techniques for detecting various abnormalities or arrhythmias of the heart to reduce pressure on physicians and share their load. The present work will help in developing a computer based system that...
In this work realization of automatic scientific articles classification according to Universal Decimal Classifier is presented. Efficiency of neural networks technologies application for current task is researched, and optimal neural network structure and parameters are offered.
The main objective of this research work is to develop an expert system for the diagnosis and detection of Hepatitis and liver disorders based on various Artificial Neural Networks models. In this research work Artificial Neural Networks models like Back Propagation Algorithm, Probabilistic Neural Networks, Competitive learning Networks, Learning vector quantization and Elman Networks have been used...
In this paper various types of classifiers for quantitatively identify teletraffic service devices are proposed. The classification method “K — Nearest Neighbors With Defined Cityblock Metric Distance At Three Nearest Neighbors” is selected. A classifier structure is synthesized based on Adaptive Neuro-Fuzzy Interface Systems (ANFIS) in hybrid learning algorithm and Gaussian type membership function...
Adaptive test of integrated circuits (IC) promises to increase the quality and yield of products with reduced manufacturing test cost compared to traditional static test flows. Two mostly widely used techniques are Statistical Process Control (SPC) and Part Average Testing (PAT), whose capabilities to capture complex correlation between test measurements and the underlying IC's physical and electrical...
Identifying and treating the tumor at its early stages has become one of the major challenges faced in the area of breast imaging field since the number of women diagnosed with breast cancer has gradually increase over the years. Breast thermography has distinguished itself as a promising adjunctive imaging modality to the current breast imaging standard for early detection of breast cancer. It provides...
There is growing interest in unmanned aerial vehicles (UAVs) such as quadrotors over the past several years. Cooperation among multiple quadrotors is one of the areas of focus. This paper proposes a neural network form of control for a cooperative task done by four quadrotors and will be tested through simulations. The task at hand is a ball and plate balancing problem during flight of multiple quadrotors...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.