Arrested precipitation methode used to synthesize CuInSe2 (CIS) nanocrystals were added to a hot solvent with organic capping ligands to control nanocrystal formation and growth. CIS thin films deposited onto Soda-Lima Glass (SLG) substrate by spray-coat, then selenized in Ar-atmosphere to form CIS thin films. PVs were made with power conversion efficiencies of 0.631% as-deposited and 0.846% after selenization, for Mo coated, under AM 1.5 illuminations. (XRD) and (EDX) it is evident that CIS have chalcopyrite structure as the major phase with a preferred orientation along (112) direction and Cu:In:Se nanocrystals is nearly 1:1:2 atomic ratio.

The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the resear

Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

Micro-perforated panel (MPP) absorber is increasingly gaining popularity as an alternative sound absorber in buildings compared to the well-known synthetic porous materials. A single MPP has a typical feature of a Helmholtz resonator with a high amplitude of absorption but a narrow absorption frequency bandwidth. To improve the bandwidth, a single MPP can be cascaded with another single MPP to form a double-layer MPP. This paper proposes the introduction of inhomogeneous perforation in the double-layer MPP system (DL-iMPP) to enhance the absorption bandwidth of a double-layer MPP. Mathematical models are proposed using the equivalent electrical circuit model and are validated with experiments with good agreement. It is revealed that the DL-

A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It  was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode

Objectives: Successful endodontic treatment outcome requires effective shaping and cleaning of root canals. This study aims to evaluate the smear layer removal after continuous chelation (CC) ) NaOCL\HEDP( and sequential chelation (SC) )NaOCL\EDTA( and their influence on the push-out bond strength (POBS) of Bio-C sealer. Materials and Methods: Palatal roots of the maxillary first molar (n=72) were divided into four groups (n=18) as follows: 3% NaOCL, SC: 3% NaOCL followed by 17% EDTA, CC: 3% NaOCL \9% HEDP and Distilled water. Thirty-two roots (n=8/group) were split longitudinally for smear layer evaluation using SEM. Forty roots were obturated with Guttapercha and Bio-C sealer using a single cone technique. Thre