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The power output of solar energy conversion facilities such as photovoltaic systems is highly dependent and proportional to the amount of solar radiation absorbed on the collecting surface. In order to have an efficient design of these systems, it is essential to perform solar resource assessment on the intended location prior to installation. Advancements in computational intelligence led to applications...
In this work a machine learning approach is proposed for prediction of volatile substance abuse. Machine learning technique used in this work is artificial neural networks (ANN). Two ANN modules are designed, ANN-D to predict whether a person is using VSA or not and ANN-C to predict the time of use. Input features used are age, gender, country, ethnicity, education, neuroticism, openness to experience,...
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...
Roller element bearing fault diagnosis is crucial in industry to maintain that the machine is in good condition so that there is no delay of work due to machine breakdown. This paper discusses the use of Extreme Learning Machine (ELM) algorithm to classify bearing faults. The performance of ELM is compared with Back Propagation (BP) algorithm. It was found that the results show that the ELM has smaller...
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...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
Average flow velocity in a multipath transit time Ultrasonic Meter (USM) is calculated by integrating the mean flow velocities along all of the acoustic paths. Every path has a weight that represents its contribution to the average velocity. In the conventional weighting methods, the flow for the entire USM is assumed to be fully developed and symmetrical, so that each path has a fixed weight of USM's...
In recent years use of image processing techniques for texture analysis of machined surface is gaining importance in the field of manufacturing. This manuscript addresses texture identification methodology using Wavelet transform and artificial intelligence techniques. Captured images of machined surface using Electric discharge machining, milling, sand blasting and shaping is decomposed in to sub...
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...
One of the most challenging tasks for energy domain stakeholders is to have a better preview of the electricity consumption. Having a more trustable expectation of electricity consumption can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study using a Methodology to Obtain Genetic fuzzy rule-based systems Under the iterative...
This paper presents a unique and efficient artificial neural network (ANN) based fault detection, classification and location on part of the Nigerian 132kV transmission line. The objective is to evaluate the performance of ANN based relays connected at both ends of the lines using feed-forward non-linear supervised back propagation algorithm with Levenberg-marguardt network topology. Using the PSCAD/EMTP...
Personality is the defining essence of an individual as it guides the way we think, act and interpret external stimuli. Classification of personality is important as it can serves as a framework in the job assignment task, particularly, in the high risk job including the Police Force. There are many attributes of individual traits but not all of them can be used to indicate individual personality...
A flaw or drift from expected operational performance in one electronic module or component may affect the reliability of the entire upper-level electronic product or system. Therefore, it is important to ensure the required quality of each individual electronic part through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a...
Now a day's recognition of satellite image authenticity has received too much attention due to the invention of various remote sensing image inpainting algorithms. Satellite image forgery can be referred as a technique in which fake satellite image is generated by the creation and alternation of new image contents. This paper proposes an algorithm for the identification of inpainted remote sensing...
Unknown awareness is very important for many applications such as face recognition. In a typical unknown aware classifier, an “unknown” label is assigned to strange test instances. This study proposes an unknown aware classifier known as UAkNN by extending the well-known kNN classifier. In UAkNN, unknown awareness is achieved by exploiting distances between instances of individual classes. These distances...
Concrete can be molded to any shape and size, and once hardened it can withstand tremendous amount of compressive loads. This ability of concrete makes it the most widely used material in construction and thus, a need for identification and prediction of its compressive strength. Nondestructive tests have been solely preferred for this purpose and a drop-impact test machine prototype named; Material...
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...
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