This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

In this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.

In this work, a magnetic switch was prepared using two typesof ferrofluid materials, the pure ferrofluid and ferrofluid doped with copper nanoparticles (10 nm). The critical magnetic field (Hc) and the state of magnetic saturation (Hs) were studied using three types of laser sources. The main parameters of the magnetic switch measured using pure ferrofluid and He-Ne Laser source were Hc(0.5 mv, 0.4 G), Hs (8.5 mv, 3 G). For the ferrofluid doped with copper nanoparticles were Hc (1 mv, 4 G), Hs (15 mv, 9.6 G), Using green semiconductor laser for the Pure ferrofluid were Hc (0.5 mv, 0.3 G) Hs (15 mv, 2.9 G). While the ferrofluid doped with copper nanoparticles were Hc (0.5 mv, 1 G), Hs (12 mv, 2.8 G) and by using the violet semiconductor l

In this research the hard chromium electroplating process, which is one of the common methods of overlay coating was used, by using chromium acid as source of chromium and sulphuric acid as catalyst since the ratio between chromic acid and sulphuric acid is (100 : 1) consequently. Plating process was made by applying current of density (40 Amp / dm²) and the range of solution temperature was (50 – 55^oC) with different time periods (1-5 hr). A  low carbon steel type (Ck₁₅) was used as substrate for hard chromium electroplating. Solid carburization was carried out for hard chromium plating specimen at temperature (925^oC) with time duration (2 hr) to be followed with quenching and tempering

The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO₂ in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO₂ micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO₂ micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO₂ nanoparticle. GIC-contai

Purpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.

Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.

Methodology:

Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).

This study explored the development and qualities of the response of electrochemical properties of enrofloxacin-selective electrodes using precipitation based on producing phosphotungstic, after utilizing a matrix of polyvinyl chloride (PVC) and dibutyl phthalate or dibutyl phosphate as a plasticizer. The resulting membrane sensors were an enrofloxacin-phosphotungstic electrode (sensors 1) and an ENR-DOP-PTA electrode (sensors 2). Linear responses of (ENR-DBPH-PTA) and (ENR-DOP-PTA) within the concentration ranges of 2.1×10^-6-10^-1 and 3.0×10^-6-10^-2 mol. L^-1, respectively, for both sensors were observed. Slopes of 51.61±0.24 and 39.40± 0.16 mV/decade and pH ranges equal to 2.5-8.5