In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Speech recognition is a very important field that can be used in many applications such as controlling to protect area, banking, transaction over telephone network database access service, voice email, investigations, House controlling and management ... etc. Speech recognition systems can be used in two modes: to identify a particular person or to verify a person’s claimed identity. The family speaker recognition is a modern field in the speaker recognition. Many family speakers have similarity in the characteristics and hard to identify between them. Today, the scope of speech recognition is limited to speech collected from cooperative users in real world office environments and without adverse microphone or channel impairments.

Recently there has been an urgent need to identify the ages from their personal pictures and to be used in the field of security of personal and biometric, interaction between human and computer, security of information, law enforcement. However, in spite of advances in age estimation, it stills a difficult problem. This is because the face old age process is determined not only by radical factors, e.g. genetic factors, but also by external factors, e.g. lifestyle, expression, and environment. This paper utilized machine learning technique to intelligent age estimation from facial images using support vector machine (SVM) on FG_NET dataset. The proposed work consists of three phases: the first phase is image preprocessing include four st

High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

     The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca

    Terrestrial laser scanners (TLSs) are 3D imaging systems that provide the most powerful 3D representation and practical solutions for various applications. Hence this is due to effective range measurements, 3D point cloud reliability, and rapid acquisition performance. Stonex X300 TOF scanner delivered better certainty in far-range than in close-range measurements due to the high noise level inherent within the data delivered from Time of Flight (TOF) scanning sensors. However, if these errors are manipulated properly using a valid calibration model, more accurate products can be obtained even from very close-range measurements. Therefore, to fill this gap, this research presents a user-oriented target-based calibration routine to

Addition of bioactive materials such as Titanium oxide (TiO₂), and incorporation of bio inert ceramic such as alumina (Al₂O₃), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO₂/Al₂O₃/PEEK biocomposites with different

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

Efficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include