Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

Infrared photoconductive detectors working in the far-infrared region and room temperature were fabricated. The detectors were fabricated using three types of carbon nanotubes (CNTs); MWCNTs, COOH-MWCNTs, and short-MWCNTs. The carbon nontubes suspension is deposited by dip coating and drop–casting techniques to prepare thin films of CNTs. These films were deposited on porous silicon (PSi) substrates of n-type Si. The I-V characteristics and the figures of merit of the fabricated detectors were measured at a forward bias voltage of 3 and 5 volts as well as at dark and under illumination by IR radiation from a CO2 laser of 10.6 μm wavelengths and power of 2.2 W. The responsivity and figures of merit of the photoconductive detector

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

One of the critical factors for dental implant success is accurate clinical and radiological assessment. Cone-beam computed tomography systems (CBCT) allow surgeons to determine the quality and quantity before surgery, aiding in treatment planning. This study highlights the importance of such an assessment Materials and Methods A total of 40 patients were referred to CBCT scanning for pre-dental implant assessment in the Oral and Maxillofacial Radiology department at Al-Shaheed Gazi Al Hariri Hospital from 2021 to 2022. The patients were between 18 and 50 years old. All data were analyzed with on-demand 3D software (Kavo OP 3D: Cone Beam 3D imaging Germany). Results: Regarding the ridge shape: In the upper anterior and posterior regions, th

   The inhibitive action of a blend of sodium nitrite/sodium hexametaphosphate (SN+SHMP) on corrosion of carbon steel in simulated cooling water systems (CWS) has been investigated by weight loss and electrochemical polarization technique. The effect of temperature, velocity, and salts concentrations on corrosion of carbon steel were studied in the absence and presence of mixed inhibiting blend. Also the effect of inhibitors blend concentrations (SN+SHMP), temperatures, and rotational velocity, i.e., Reynolds number (Re) on corrosion rate of carbon steel were investigated using Second-order Rotatable Design (Box-Wilson Design) in performing weight loss and corrosion potential approach. Electrochemical polarization measurements

The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and A

The new ligand [N1,N4-bis((1H-benzo[d]Glyoxalin-2-yl)carbamothioyl)Butanedi amide] (NCB) derived from Butanedioyl diisothiocyanate with 2-aminobenz imidazole was used to prepare a chain of new metal complexes of Cr(III), Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Ag(I), Cd(II) by general formula [M(NCB)]Xn ,Where M= Cr(III), n=3, X=Cl; Mn(II), Co(II), Ni(II), Cu(II), Pd(II), Cd(II) ,n=2 , X=Cl; Ag(I), n=1, X=NO3. Characterized compounds on the basis of 1H, 13CNMR (for (NCB), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H, %N and %S, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA),while its corrosion inhibition for mild steel in Ca(OH)2 solution is studied by weight loss. These measureme

For the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a