In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-PCF-SMF). While the effective performance parameters for Multi-Mode Fiber- Photonic Crystal Fiber- Multi-Mode Fiber (MMF-PCF-MMF) such as the sensitivity is approaching 9.5 μm/RIU, SNR is 0.0173, FOM is10.86 and the resolution is 4x〖10〗^(-4) is achieved. The concentrations were calculated practically and theoretically for each of the sensors, and it was found that the practical concentrations that were obtained are close or equal to the concentrations that were theoretically obtained through the dilution law, where the concentrations were obtained 0.096, 0.15, 0.26, 0.38, 0.49 practically and 0.1, 0.2 and 0 3, 0.4 and 0.5 theoretically For SMF-PCF-SMS, concentrations of 0.089, 0.16, 0.23, 0.34, and 0.45 were practically obtained, and 0.1, 0.2, 0.3, 0.4, and 0.5 theoretically for MMF-PCF-MMF. The suggested sensor has a strong mechanical structure, low cost, and easy fabrication, allowing it to provide a greater measurement range and action area to the measured samples without lengthening the sensor.
The research team seeks to study the phenomena of random housing in Iraqi society in general and Baghdad city in particular by standing on the causes behind this phenomena and its relation with security situation in Baghdad. The researchers adopted a theoretical and practical framework. The main objective is to diagnose the risks caused by the escalation of slums in Baghdad city.
The present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation c
... Show MoreDouble hydrothermal method was used to prepare nano gamma alumina using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, CTAB (cetyltrimethylammonium bromide) as surfactant, and variable acids: weak acids like; citric, and acitic acids, and strong acids like; hydrochloric and nitric acids as a bridge between aluminum salts and surfactant. Different crystallization times 12, 24, 48, and 72 hrs were applied. All the batches were prepared at pH equals to 9. XRD diffraction technique was used to investigate the crystalline nano gamma alumina pure from surfactant. N2 adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the average p
... Show MoreIn this study, SnO2 nanoparticles were prepared from cost-low tin chloride (SnCl2.2H2O) and ethanol by adding ammonia solution by the sol-gel method, which is one of the lowest-cost and simplest techniques. The SnO2 nanoparticles were dried in a drying oven at a temperature of 70°C for 7 hours. After that, it burned in an oven at a temperature of 200°C for 24 hours. The structure, material, morphological, and optical properties of the synthesized SnO2 in nanoparticle sizes are studied utilizing X-ray diffraction. The Scherrer expression was used to compute nanoparticle sizes according to X-ray diffraction, and the results needed to be scrutinized more closely. The micro-strain indicates the broadening of diffraction peaks for nano
... Show MoreThe present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation costs
... Show MoreThe aim of this study is to examine the effectiveness of fishbowl strategy as one of the effective learning strategies for intermediate students’ achievement in geography subject. To do this, three classes of second intermediate were chosen from Noor Al-Mustafa School for academic years (2015-2016). (64) Student were selected as a sample that distributed into two equal groups: experimental and control group. The research used the achievement test as an instrument to come up with the finding of the study. The experiment began on Tuesday 13th of October 2015 and ended on Tuesday 5th January 2016. Through this time, the researcher taught them the first and second chapter in geography of Arab homeland using fishbowl s
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
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