To achieve safe security to transfer data from the sender to receiver, cryptography is one way that is used for such purposes. However, to increase the level of data security, DNA as a new term was introduced to cryptography. The DNA can be easily used to store and transfer the data, and it becomes an effective procedure for such aims and used to implement the computation. A new cryptography system is proposed, consisting of two phases: the encryption phase and the decryption phase. The encryption phase includes six steps, starting by converting plaintext to their equivalent ASCII values and converting them to binary values. After that, the binary values are converted to DNA characters and then converted to their equivalent complementary DNA sequences. These DNA sequences are converted to RNA sequences. Finally, the RNA sequences are converted to the amino acid, where this sequence is considered as ciphertext to be sent to the receiver. The decryption phase also includes six steps, which are the same encryption steps but in reverse order. It starts with converting amino acid to RNA sequences, then converting RNA sequences to DNA sequences and converting them to their equivalent complementary DNA. After that, DNA sequences are converted to binary values and to their equivalent ASCII values. The final step is converting ASCII values to alphabet characters that are considered plaintext. For evaluation purposes, six text files with different sizes have been used as a test material. Performance evaluation is calculated based on encryption time and decryption time. The achieved results are considered as good and fast, where the encryption and decryption times needed for a file with size of 1k are equal to 2.578 ms and 2.625 ms respectively, while the encryption and decryption times for a file with size of 20k are equal to 268.422 ms and 245.469 ms respectively.
An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. The researchers were developing a new mechanism to retrieval systems which is mainly based on two procedures. The first procedure relies on extract the statistical feature of both original, traditional image by using the histogram and statistical characteristics (mean, standard deviation). The second procedure relies on the T-
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In this paper, we implement and examine a Simulink model with electroencephalography (EEG) to control many actuators based on brain waves. This will be in great demand since it will be useful for certain individuals who are unable to access some control units that need direct contact with humans. In the beginning, ten volunteers of a wide range of (20-66) participated in this study, and the statistical measurements were first calculated for all eight channels. Then the number of channels was reduced by half according to the activation of brain regions within the utilized protocol and the processing time also decreased. Consequently, four of the participants (three males and one female) were chosen to examine the Simulink model duri
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Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n
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Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud
... Show MoreKE Sharquie, AA Noaimi, AM Oweid, JSSDDS, 2009 - Cited by 2
To investigate the antiplaque and antigingivitis efficacy in addition to evaluating side effects and subjects’ perceptions of three commercially available mouthwashes.
This study was a double‐blind, parallel, and short‐term trial. A total of 75 dental students with biofilm‐induced gingivitis were included in the final analysis of the current study. Clinical parameters (plaque index and bleeding on probing) and the staining effect were measured at baseline and after 7 days. In addition, a VAS‐based assessment questionnaire was completed by the participants.
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The new tridentate Schiff base ligand (HL)namely 2-{[1-(3-amino-phenyl)-ethylidene]-hydrazono methyl}- phenol containing (N N O)as donors atoms was prepared in two steps:Step (1): By the reaction of 3- aminoacetophenone with hydrazine monohydrate under reflux in methanol and drops of glacial acetic acid gave the intermediate compound 3-(1- hydrazono ethyl)-phenol amine.Step (2): By the reaction of 3-(1-hydrazono ethyl)-phenol amine with salicyaldehyde under reflux in methanol, gave the ligand (HL).The prepared ligand was characterized by I.R, U.V-Vis,1H- 13C NMR spectra and melting point and reacted with some metal ions under reflux in methanol with (1:1) ratio gave complexes of the general formula: [MClL]. Where: M= Mn(II), Fe(II), Co(II),
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