Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two types of neural networks are used to classify the extracted objects. Tests have been performed on a sequence of frames, and the simulation results by MATLAB showed that the RBF neural network gave a better performance compared with the MLP neural network where the RBF model gave a mean squared error (MSE) equals to 2.36811e-18 against MSE equals to 2.6937e-11 achieved by the MLP model. The more important thing observed is that the RBF approach required less time to classify the detected object as human compared to the MLP, where the RBF took approximately 86.2% lesser time to give the decision.
Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.
This study focuses on the relationship of the smart contracts and legal application in the field of civil and commercial contracts. The study aimed to anticipate the possibility of issuing a new law in the future, Nowadays, smart contracts t is a legal challenge that cannot be ignored, Despite the UAE legislator’s interest in artificial intelligence technologies and studying them from the legislative aspect, especially in the field of self-driving cars and the use of robots, and looking forward to a global leadership in the field of Block chain, it is still early to talk about bringing the Block chain to the ground of legislative reality in light of the challenges and risks arising from many challenges that We discussed them in this co
... Show MoreIn this paper, a new modification was proposed to enhance the security level in the Blowfish algorithm by increasing the difficulty of cracking the original message which will lead to be safe against unauthorized attack. This algorithm is a symmetric variable-length key, 64-bit block cipher and it is implemented using gray scale images of different sizes. Instead of using a single key in cipher operation, another key (KEY2) of one byte length was used in the proposed algorithm which has taken place in the Feistel function in the first round both in encryption and decryption processes. In addition, the proposed modified Blowfish algorithm uses five Sboxes instead of four; the additional key (KEY2) is selected randomly from additional Sbox
... Show MoreCurrently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload.
Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and def
... Show MoreArtemisia is a perennial wild shrub with large branches and compound leaves. Artemisia contains about 400 types, and its medical importance is due to the presence of many active substances and compounds such as volatile oils, alkaloids and flavonoids, glycosides, saponins, tannins, and coumarins. This study was designed to study the effect of the aqueous extract of the fruit of the Artemisia plant on the organs of the body, as well as to know its ability to activate the hepatic enzyme alanine transaminase (ALT/GPT). The fruit of this shrub was extracted using the measurement technique gas chromatography-mass spectrometry (GC/MASS) and organic solvent hexane and ethyl acetate in one to one ratio. It contained 21 compounds, a high percentage
... Show MoreAbstract: Two different shapes of offset optical fiber was studied based on coreless fiber for refractive index (RI)/concentration (con.) measurement, and compare them. These shapes are U and S-shapes, both shapes structures were formed by one segment of coreless fiber (CF) was joined between two single mode (SMF) lead in /lead out with the same displacement (12.268µm) at both sides, the results shows the high sensitive was achieved in a novel S-shape equal 98.768nm/RIU, to our knowledge, no one has ever mentioned or experienced it, it’s the best shape rather than the U-shape which equal 85.628nm/RIU. In this research, it was proved that the offset form has a significant effect on the sensitivity of the sensor. Addi
... Show MoreThe purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift
... Show MoreThe corona virus epidemic outbreak has urged an extreme worldwide effort for re‐purposing obtainable approved medications for its treatment. In this review, we're focusing on the chemicals properties andpharmacologicaleffectiveness of medicationsofsmallmolecule that are presently being evaluated in clinical trials for the management of corona virus (COVID‐19). The current review sheds light on a number of drugs that have been diagnosed to treat COVID‐19 and their biological effects.
The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the