With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

in this paper we adopted ways for detecting edges locally classical prewitt operators and modification it are adopted to perform the edge detection and comparing then with sobel opreators the study shows that using a prewitt opreators

Conservative pipes conveying fluid such as pinned-pinned (p-p), clamped–pinned (c-p) pipes and clamped-clamped (c-c) lose their stability by buckling at certain critical fluid velocities. In order to experimentally evaluate these velocities, high flow-rate pumps that demand complicated fluid circuits must be used.

     This paper studies a new experimental approach based on estimating the critical velocities from the measurement of several fundamental natural frequencies .In this approach low flow-rate pumps and simple fluid circuit can be used.

Experiments were carried out on two pipe models at three different boundary conditions. The results showed that the present approach is more accurate for est

            In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample

Massive multiple-input multiple-output (massive-MIMO) is a promising technology for next generation wireless communications systems due to its capability to increase the data rate and meet the enormous ongoing data traffic explosion. However, in non-reciprocal channels, such as those encountered in frequency division duplex (FDD) systems, channel state information (CSI) estimation using downlink (DL) training sequence is to date very challenging issue, especially when the channel exhibits a shorter coherence time. In particular, the availability of sufficiently accurate CSI at the base transceiver station (BTS) allows an efficient precoding design in the DL transmission to be achieved, and thus, reliable communication systems can be obtaine

The combination of carbon nanotubes (CNT) and conducting polymers offers an attractive route for the production of novel compounds that can be used in a variety of applications such as sensors, actuators, and molecular scale electronic devices. In this work, functionalized multiwall carbon nanotubes (f-MWCNTs) were added in different load ratios (3 wt%, 5 wt% and 10 wt%) to thiophen (PTh) polymer to procedure PTh/CNTs nanocomposite and deposited on porous silicon substrate by electropolarization. Photoconductive detectors were fabricated using PTh/f-MWCNTs matrix to work in the near region and middle IR regions. These detectors were illuminated by semiconductor laser diode wavelength of 808(nm) and Nd-YAG laser of wavelength 1064 (n

Free-electron lasers (FELs) are disruptive light sources that offer ultrashort pulses, wide spectral tunability, and superior coherence, making them promising candidates for next-generation photonic technologies. However, conventional FEL facilities are large-scale and complex, limiting their integration into communication systems. This study investigates the potential of compact FELs as scalable and versatile light sources for beyond-6G and quantum communication infrastructures. A theoretical framework was established to model resonance conditions, gain dynamics, coherence properties, pulse-duration-limited bit rates, and signal-to-noise ratio (SNR). These models were implemented in MATLAB simulations using parameters representativ