Aspect-Oriented Software Development (AOSD) is a technology that helps achieving
better Separation of Concern (SOC) by providing mechanisms to identify all relevant points
in a program at which aspectual adaptations need to take place. This paper introduces a
banking application using of AOSD with security concern in information hiding.

The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different sets of features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used as a dataset f

Image Fusion Using A Convolutional Neural Network

In this research, we did this qualitative and quantitative study in order to improve the assay of aspirin colorimetrically using visible spectrophotometer. This method depends on aqueous hydrolysis of aspirin and then treating it with the ferric chloride acidic solution to give violet colored complex with salicylic acid, as a result of aspirin hydrolysis, which has a maximum absorption at 530nm. This procedure was applied to determine the purity of aspirin powder and tablet. The results were approximately comparative so that the linearity was observed in the high value of both correlation coefficient (R= 0.998) and Determination Coefficient or Linearity (R2= 0.996) while the molar absorpitivity was 1.3× 103 mole

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Iraq has a huge network of pipelines, transport crude oil and final hydrocarbon products as well as portable water. These networks are exposed to extensive damage due to the underground corrosion processes unless suitable protection techniques are used. In this paper we collect the information of cathodic protection for pipeline in practical fields (Oil Group in Al Doura), to obtain data base to understand and optimize the design which is made by simulation for the environmental factors and cathodic protection variables also soil resistivity using wenner four terminal methods for survey sites; and soil pH investigations were recorded for these selected fields were within 7-8, and recording the anodes voltage and its related currents for

The proliferation of cellular network enabled users through various positioning tools to track locations, location information is being continuously captured from mobile phones, created a prototype that enables detected location based on using the two invariant models for Global Systems for Mobile (GSM) and Universal Mobile Telecommunications System (UMTS). The smartphone application on an Android platform applies the location sensing run as a background process and the localization method is based on cell phones. The proposed application is associated with remote server and used to track a smartphone without permissions and internet. Mobile stored data location information in the database (SQLite), then transfer it into location AP

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

In this paper we deal with the problem of ciphering and useful from group isomorphism for construct public key cipher system, Where construction 1-EL- Gamal Algorithm. 2- key- exchange Algorithm