Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

Aluminum doped zinc selenide ZnSe/n-Si thin films of (250∓20 nm) thickness with (0.01, 0.02 and 0.03), are depositing on the two type of substrate (glass and n-Si) to manufacture (ZnSe/n-Si) solar cell through using thermal vacuum evaporation procedure. physical and optoelectronic properties were examined for the samples. X-Ray and AFM techniques are using to study the structure properties. The energy band gap of as-deposited ZnSe thin films for changed dopant ratio were ranging from (2.6-2.68 eV). The results of Hall effect show that pure and doping films were (p-type), and the concentration carriers and the carriers mobility increases with increase Al-dopant ratio. The (C-V) have shown that the heterojunction were of abrupt type. In add

: Porous silicon (n-PS) films can be prepared by photoelectochemical etching (PECE) Silicon chips n - types with 15 (mA /cm2), in15 minutes etching time on the fabrication nano-sized pore arrangement. By using X-ray diffraction measurement and atomic power microscopy characteristics (AFM), PS was investigated. It was also evaluated the crystallites size from (XRD) for the PS nanoscale. The atomic force microscopy confirmed the nano-metric size chemical fictionalization through the electrochemical etching that was shown on the PS surface chemical composition. The atomic power microscopy checks showed the roughness of the silicon surface. It is also notified (TiO2) preparation nano-particles that were prepared by pulse laser eradication in e

In this research, porous silicon (PS) prepared by anodization etching on surface of single crystalline p-type Si wafer, then Gold nanoparticle (AuNPs) prepared by pulsed laser ablation in liquid. NPs deposited on PS layer by drop casting. The morphology of PS, AuNPs and AuNPs/PS samples were examined by AFM. The crystallization of this sample was characterized by X-ray diffraction (XRD). The electrical properties and sensitivity to CO2 gas were investigated to Al/AuNPs/PS/c-Si/Al, we found that AuNPs plays crucial role to enhance this properties.

This review article summarizes our research focused on Cu(In, Ga)Se2 (CIGS) nanocrystals, including their synthesis and implementation as the active light absorbing material in photovoltaic devices (PVs). CIGS thin films were prepared by arrested precipitation from molecular precursors consisting of CuCl, InCl3, GaCl3 and Se metal onto Mo/soda-lime glass (SLG) substrates. We have sought to use CIGS nanocrystals synthesized with the desired stoichiometry to deposit PV device layers without high temperature processing. This approach, using spray deposition of the CIGS light absorber layers, without high temperature selenization, has enabled up to 1.5 % power conversion efficiency under AM 1.5 solar illumination. The composition and morphology

In this work, porous silicon gas sensor hs been fabricated on n-type crystalline silicon (c-Si) wafers of (100) orientation denoted by n-PS using electrochemical etching (ECE) process at etching time 10 min and etching current density 40 mA/cm2. Deposition of the catalyst (Cu) is done by immersing porous silicon (PS) layer in solution consists of 3ml from (Cu) chloride with 4ml (HF) and 12ml (ethanol) and 1 ml (H2O2). The structural, morphological and gas sensing behavior of porous silicon has been studied. The formation of nanostructured silicon is confirmed by using X-ray diffraction (XRD) measurement as well as it shows the formation of an oxide silicon layer due to chemical reaction. Atomic force microscope for PS illustrates that the p

Structural, optical, and electrical properties of thin films of CdS : Zn prepared by the solution – growth technique are reported as a function of zinc concentration. CdS are window layers influencing the photovoltaic response of CIS solar cells. The zinc doping concentration was varied from 0.05 to 0.5 wt %, zinc doping apparently increase the band gap and lowers the resistivity. All beneficial optical properties of chemically deposited CdS thin films for application as window material in heterojunction optoelectronic devices are retained. Heat treatment in air at 400 °C for 1h modify crystalline structure, optical, and electrical properties of solution growth deposited CdS : Zn films.

Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the