Photonic crystal fiber interferometers are used in many sensing applications. In this work, an in-reflection photonic crystal fiber (PCF) based on Mach-Zehnder (micro-holes collapsing) (MZ) interferometer, which exhibits high sensitivity to different volatile organic compounds (VOCs), without the needing of any permeable material. The interferometer is robust, compact, and consists of a stub photonic crystal fiber of large-mode area, photonic crystal fiber spliced to standard single mode fiber (SMF) (corning-28), this splicing occurs with optimized splice loss 0.19 dB In the splice regions the voids of the holey fiber are completely collapsed, which allows the excitation and recombination of core and cladding modes. The device reflection

The ceiling of the midbrain has a couple of optic lobes which are prominent and used as an optic center that reflex what it receives from eye retina fibers. The histology of optic tectum has been studied in Iraqi water snake natrix tesselata tesselata . It was found that the number of optic tectum were seven main strata organized from the outside to the inside as follows : the stratum zonula (SZ), the stratum opticum (SO), the stratum fibrosum et griseum superficialis (SFGS), the stratum griseum central (SGC), the stratum album central (SAC), the stratum griseum periventricular (SGP), and the stratum album periventricular (SAP). the three last strata consider deep layers on the optic tectum It was noticed that the thinnest strata was the fi

A study of some mite species of alfalfa. wheat, and barley was conducted in central Iraq.
The mites were extracted using a tullgren funnel method. Twelve species were recorded. 10 of
them belong to suborder Trombidiformes and 2 belong to suborder Sarcoptiforms. Three
mites, Irnpar(pes hystricinus, Scutacarus longitarsus, and Rhizoglyphus echin opus are new
records for Iraqi mite fauna, and 11 are new host records in alfalfa soil.

In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

Abstract

Black paint laser peening (bPLP) technique is currently applied for many engineering materials , especially for aluminum alloys due to high improvement in fatigue life and strength . Constant and variable   bending fatigue tests have been performed at RT and stress ratio R= -1 . The results of the present  work observed that the significance of the surface work hardening which generated high negative residual stresses in bPLP specimens .The fatigue life  improvement factor (FLIF)  for bPLP constant fatigue behavior was from 2.543 to 3.3 compared to untreated  fatigue and the increase in fatigue strength at 10⁷ cycle was 21% . The bPLP cumulative fatigue life behav

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification