Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practica

This paper investigated the treatment of textile wastewater polluted with aniline blue (AB) by electrocoagulation process using stainless steel mesh electrodes with a horizontal arrangement. The experimental design involved the application of the response surface methodology (RSM) to find the mathematical model, by adjusting the current density (4-20 mA/cm2), distance between electrodes (0.5-3 cm), salt concentration (50-600 mg/l), initial dye concentration (50-250 mg/l), pH value (2-12 ) and experimental time (5-20 min). The results showed that time is the most important parameter affecting the performance of the electrocoagulation system. Maximum removal efficiency (96 %) was obtained at a current density of 20 mA/cm2, distance be

At present, the ability to promote national economy by adjusting to political, economic, and technological variables is one of the largest challenges faced by organization productivity. This challenge prompts changes in structure and line productivity, given that cash has not been invested. Thus, the management searches for investment opportunities that have achieved the optimum value of the annual increases in total output value of the production line workers in the laboratory. Therefore, the application of dynamic programming model is adopted in this study by addressing the division of investment expenditures to cope with market-dumping policy and to strive non-stop production at work.

Discrete   logarithms  are applied      in many    cryptographic problems  . For instance ,   in public   key .  and for construction of sets with disti nct sums of  k-clcments.  The   purpose o r  this   paper

is  to  modify  the  method ol' informationl1·iding  using        discrete logarithms  , introduce new properties of St - sets ,   uscdthe direct product   of    groups   to construct  cyclic group and finally, present modified   method   for   knapsack &

     Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd  level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet

A new technique for embedding image data into another BMP image data is presented. The image data to be embedded is referred to as signature image, while the image into which the signature image is embedded is referred as host image. The host and the signature images are first partitioned into 8x8 blocks, discrete cosine transformed “DCT”, only significant coefficients are retained, the retained coefficients then inserted in the transformed block in a forward and backward zigzag scan direction. The result then inversely transformed and presented as a BMP image file. The peak signal-to-noise ratio (PSNR) is exploited to evaluate the objective visual quality of the host image compared with the original image.

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

In this research we will present the signature as a key to the biometric authentication technique. I shall use moment invariants as a tool to make a decision about any signature which is belonging to the certain person or not. Eighteen voluntaries give 108 signatures as a sample to test the proposed system, six samples belong to each person were taken. Moment invariants are used to build a feature vector stored in this system. Euclidean distance measure used to compute the distance between the specific signatures of persons saved in this system and with new sample acquired to same persons for making decision about the new signature. Each signature is acquired by scanner in jpg format with 300DPI. Matlab used to implement this system.