Abstract: In the current research the absorption and fluorescence spectrum of Coumarin (334) and Rhodamine (590) in ethanol solvent at different concentration (10-3, 10-4, 10-5) M had been studied. The absorption intensity of these dyes increases as the Concentration increase in addition to that the spectrum was shifted towards the longer wavelength (red shift). The energy transfer process has been investigated after achievement this condition. The fluorescence peak intensity of donor molecule was decrease and its bandwidth will increases on the contrary of the acceptor molecule its intensity increase gradually and its bandwidth decreases as the acceptor concentration increase.

In the current research the absorption and fluorescence spectrum
of Coumarin (334) and Rhodamine (590) in ethanol solvent at
different concentration (10-3, 10-4, 10-5) M had been studied. The
absorption intensity of these dyes increases as the Concentration
increase in addition to that the spectrum was shifted towards the
longer wavelength (red shift). The energy transfer process has been
investigated after achievement this condition. The fluorescence peak
intensity of donor molecule was decrease and its bandwidth will
increases on the contrary of the acceptor molecule its intensity
increase gradually and its bandwidth decreases as the acceptor
concentration increase.

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data.

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï