Changes and progresses in information technologies have played an important role the development of intelligent vehicle systems recent years. Driver fatigue is factor accidents. For this reason, traffic accidents involving driver carelessness been followed by researchers. In article, a Multi-tasking Convulational Neural Network (ConNN*) model proposed to detect drowsiness/fatigue. Eye mouth characteristics are utilized for driver's behavior model. these used monitor fatigue. With Multi-task...

This paper presents dynamic neural-network-based model-predictive control (MPC) structure for a baker's yeast drying process. Mathematical model consists of two partial nonlinear differential equations that are obtained from heat and mass balances inside dried granules. The curves granule-based were used as training data neural network (NN) models. target is to predict the moisture content product activity, which very important parameters in process, different horizon values. Genetic-based...

Among the causes of traffic accidents driver drowsiness comes at one first places. According to literature some work has been done in fatigue detection. This paper proposes a Real Time Driver Fatigue Detection Based on Support Vector Machine (SVM) Algorithm. detection mainly focuses drivers' face expressions and behaviors. OpenCV Dlib libraries were utilized detect faces. The proposed system five stages: PERCLOS, count yawn, internal zone mouth opening, eye blinking head extract attributes...

Today, Human face detection algorithms, digital video processing, detection, computer vision etc. are used in many applications. There different applications for and methods studies. It has gained importance to know which method will be used. This study aims detect the number of faces an image figure status fullness medium by using a mobile device. Haar Cascade Classifiers take instant images The analyzed people's detected. Study shows that system works successfully.

Digital multimedia security has taken a very important position with the developing technology. Detecting forgeries in audio signals is one of most challenging application field forensics. In this study, Mel Frequency and Delta based methods are proposed to detect copypaste forgery signals. Firstly, study YAAPT method was used as pitch tracking algorithm voiced/unvoiced segments from Kepstrum Coefficients (MFCC) Delta-Mel (Delta-MFCC) were extract features signal seperated into segments. By...

Fuzzy logic systems have been recognized as a robust and attractive alternative to some classical control methods. The application of fuzzy (FL) technology dynamic system has constrained by the nondynamic nature popular FL architectures. Many difficulties include large rule bases (i.e., curse dimensionality), long training times, etc. These problems can be overcome with network (DFN), unconstrained connectivity processing units called "feurons". In this study, DFN an optimal trajectory...

Abstract One of the most pressing challenges in audio forgery detection—a major topic signal analysis and digital forensics research—is detecting copy-move data. Because data are used numerous sectors, including security, but increasingly tampered with manipulated, studies dedicated to verifying voice have intensified recent years. In our study, 2189 fake files were produced from recordings on TIMIT corpus, for a total 4378 files. After preprocessed detect silent unsilent regions signals,...

Abstract A distributed parameter model was developed to predict the drying behaviour of granular baker's yeast by setting up material and heat balances at particle level. Temperature moisture gradients were calculated for cylindrical spherical granules. The performance with two granule sizes compared experimental measurements. initially used non‐shrinking granules but later modified take shrinkage into account. reduction in size during course estimated good correspondence measurements...

Nowadays, biometric data is the most common used in field of security. Audio signals are one these data. Voice have frequently cases such as identification, banking systems, and forensic solution. The aim this study to determine gender voice signals. In study, many different methods were Firstly, Mel Frequency kepstrum coefficients extract feature from audio signal. Subsequently, attributes classified with support vector machines, k-nearest neighborhood method artificial neural networks. At...

The fruit classification process is commercially important. Fruit production at harvest time quite high. Classification of fruits according to their types and characteristics usually done by hand eye. This method can cause huge losses in terms time, cost labor. In the proposed study, recognition carried out using image processing methods. Convolutional Neural Networks (ConNN) <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> deep learning...