Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) network with thickness 4μm was made by the vacuum filtration from suspension (FFS) method. The morphology, structure and optical properties of the MWCNTs film were characterized by SEM and UV-Vis. spectra techniques. The SEM images reflected highly ordered network in the form of ropes or bundles with close-packing which looks like spaghetti. The absorbance spectrum revealed that the network has a good absorbance in the UV-Vis. region. The gas sensor system was used to test the MWCNT-OH network to detect NH₃gas at room temperature. The resistance of the sensor was increased when exposed to the NH₃gas. The sensitivities of the network w

Hydrogen sulfide (H₂S) gas sensor based on cobalt–manganese spinel oxide MnCo₂O₄ thin films that were prepared by chemical precipitation and green synthesis methods. Structural, morphological, and compositional characterizations of MnCo₂O₄ thin films were performed using XRD, FE-SEM, EDS, and AFM. It was found through XRD patterns that MnCo₂O₄ was formed in a cubic spinel structure for both methods; however, the chemically precipitated thin films possessed better crystallinity and larger crystallite sizes, whereas the green-synthesized films exhibited slightly lower crystallinities and smaller sizes, as evidenced by the broader peaks observed. In addition, FE-SEM and AFM images revealed that the MnCo₂O₄ films prepared by

This study provides a systematic and bibliometric review of ASTM F75 cobalt–chromium alloys, focusing on microstructure and the shift from conventional to laser-based manufacturing. Using combined analytical methods, it evaluates microstructure, mechanical properties, corrosion behavior, and biocompatibility. Results show that laser-based techniques such as LPBF and DMLS produce finer grain sizes (1–10 µm vs. 50–200 µm), leading to improved hardness (20–40%) and tensile strength (15–30%). Despite challenges like residual stress and process optimization, these methods show strong potential for high-performance and sustainable applications.

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique wh

A new technique for embedding image data into another BMP image data is presented. The image data to be embedded is referred to as signature image, while the image into which the signature image is embedded is referred as host image. The host and the signature images are first partitioned into 8x8 blocks, discrete cosine transformed “DCT”, only significant coefficients are retained, the retained coefficients then inserted in the transformed block in a forward and backward zigzag scan direction. The result then inversely transformed and presented as a BMP image file. The peak signal-to-noise ratio (PSNR) is exploited to evaluate the objective visual quality of the host image compared with the original image.

     Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd  level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet