Mehdi Khalili

A robust image watermarking scheme based on discrete wavelet transforms

This paper presents a robust image watermarking method based on discrete wavelet transform. In this method, first, the watermark is coded with chaotic map and then embedded in the middle frequency band of the image to minimize the changes. This process improves the image continuity and robustness against different image processing attacks. Experimental results show that, the proposed method not only achieves the main objectives of watermarking successfully, but also has higher robustness against different attacks compared to the earlier works.

An effective segmentation method for dermoscopy images

In this paper, an improved segmentation method of the pigmented skin lesions have been proposed in which to achieve the high characteristics of segmentation, converting the RGB images to U channel of YUV color space and noise reduction with fourier-domain filtering properties is done in pre-processing step. Also, Otsu thresholding and morphological reconstruction algorithms are used respectively in segmentation and post-processing steps. The experimental results reveal that the proposed scheme not only attains satisfactory sensitivity, but also has a higher accuracy (about 96.13%) and specificity (about 97.74%) compared to the related existing methods.

A Robust Blind Audio Watermarking Scheme Based on DCT-DWT-SVD

In this paper, Watermarking hybrid sound algorithm is presented to protect the copyright of audio files, which, in addition to the clarity and consistency of the audio signal, has increased the strength and strength. To this end, a hybrid algorithm for voice signal cryptography is presented in the three domain parser transforms, discrete cosine transform, and discrete wavelet transforms. So, after discrete cosine transformation (DCT) on the host signal, by selecting the sub-band of low frequency, which contains the highest signal energy, two discrete wavelet transform (DWT) with a random wavelet filter on the low-frequency coefficients of conversion A discrete cosine applies, after selecting the approximation coefficients, the resulting one-dimensional matrix is converted to a two-dimensional matrix, and finally the resulting matrix is applied to a single value decomposition (SVD), which results in the formation of a The diameter matrix is that the watermark bits are embedded in the first layer of the dipole matrix, so that the two bits with value S (1,1), S (2,2) of the matrix The diameter S is chosen, first compares the first and second intersections of the diameter matrix S, which is multiplied by the coefficient θ multiplied by the obtained two bits and is used as a fixed value in the embedding formula and The title of the new watermark is embedded in S (1,1). The results of the implementation show that the proposed algorithm succeeded not only in achieving transparency and resistance to general audio processing attacks, such as Gaussian white noise, quantization rates, decreasing and increasing the rate of sampling, compression and low pass filtering. But has achieved better results than other similar algorithms.

Non Correlation DWT Based Watermarking Behavior in Different Color Spaces

There are two digital watermarking techniques. Digital watermarking techniques based on correlation and digital watermarking techniques that are not based on correlation. In previous work, we proposed a DWT2 based CDMA image watermarking scheme to study the effects of using eight color spaces RGB, YCbCr, JPEG-YCbCr, YIQ, YUV, HSI, HSV and CIELab, on watermarking algorithms based on correlation techniques. This paper proposes a non correlation based image watermarking scheme in wavelet transform domain and tests it in the same color spaces, to develop studying, reach a comprehensive analysis and focus on satisfying the requirements of based non coloration watermarking algorithms. To achieve more security, imperceptibility and robustness of the proposed scheme, first, the binary watermark image encodes by applying ATM, CCM and exclusive OR. Then, the scrambled watermark embeds into intended quantized approximation coefficients of wavelet transform by LSB insertion technique.

A Hybrid Method to Predict Success of Dental Implants

Background/Objectives: The market demand for dental implants is growing at a significant pace. Results obtained from real cases shows that some dental implants do not lead to success. Hence, the main problem is whether machine learning techniques can be successful in prediction of success of dental implants. Methods/Statistical Analysis: This paper presents a combined predictive model to evaluate the success of dental implants. The classifiers used in this model are W-J48, SVM, Neural Network, K-NN and Naive Bayes. All internal parameters of each classifier are optimized. These classifiers are combined in a way that results in the highest possible accuracies. Results: The performance of the proposed method is compared with single classifiers. Results of our study show that the combinative approach can achieve higher performance than the best of the single classifiers. Using the combinative approach improves the sensitivity indicator by up to 13.3%. Conclusion/Application: Since diagnosis of patients whose implant does not lead to success is very important in implant surgery, the presented model can help surgeons to make a more reliable decision on level of success of implant operation prior to surgery.

Comparison of the accuracy of effort estimation methods

The COCOMO Model is one of the best software cost estimation models. This model is a kind of experimental model which has been made up through gathering data on different software projects, and mainly takes cost and schedule of the project under consideration. But hypotheses presented in early phases will be changing during time, and variable estimations might increase or decrease pre-suggested budget of the project. In this paper, COCOMO Model has been studied as a suggested method of cost and effort estimation. At first, different software effort estimation methods are described and finally, according to accomplished evaluations findings, the optimal COCOMO model is presented.

An suggested method to university courses presentation based on cart algorithm to pun universities

In this paper is provided a method to deliver courses by the head of department by algorithm clementine software which called cart. Cart is the classification rules. In this study, was applied cart algorithm on data of Qom Pun University, Dept. Computer and Informatics Engineering with 28018 records. The results show that the algorithm has discovered.

A new method to enhance the efficiency of peer-to-peer vehicular networks

Forecasting the next route of vehicles in Vehicular Ad-hoc Networks (VANET) that are based on routing pattern is useful to estimate the stability time of the route. Also, estimation of the stability time of the route, before changing the route, causes a node to be informed and then compensates the lost connection. In this paper, we establish a sustainable path between the two vehicles and largely reduced the network overhead. So that, first, a clustering structure to dividing the nodes will be used which effects on the efficiency. In the second stage before ending the connection between the two vehicles, the alternative routes were studied and considered to be stable to replace new route. Finally, the results show that the proposed method that uses clustering and considering stability time between two vehicles can reduce the delay of requesting the packet by the desired to an acceptable level. The experimental results show that, the proposed method improves the rate and number of sent packets, time and also the number of dropped packets, compared ASAP protocol.

Increasing energy efficiency through maximizing channel capacity with a minimum power allocation in the Femtocell network

Femtocell networks are a very promising solution for increasing the system capacity via making the transceiver and transmitter close to each other. This makes links with higher qualities. The spectrum dedicated to the femtocell network is mainly from the spectrum licensed given to macrocell. This paper investigates the maximum of the energy efficiency in Downlink connections of the femtocell networks over a fading environment. To increase the energy efficiency in the femtocell network, optimizing capacity and power are studied at the same time. The power allocation limits and channel capacity increase are considered simultaneously. In this article, it is concluded that simultaneous optimization of the channel capacity increase and power allocation limits leads to an energy efficiency increase in these networks.

A joint 3D DWT and SPIHT based algorithm for 3D MRI image compression

In this paper, an effective algorithm is proposed to compress the magnetic resonance imaging (MRI) images. In the proposed scheme, 3D discrete wavelet transform (DWT) and set partitioning in hierarchical trees (SPIHT) coding are jointed to achieve more desired quality reconstruction. To achieve the goal, the lifting based wavelet transformation is employed to apply 3D DWT. Also, in SPIHT coding, finding the largest wavelet coefficient of the decomposed MRI image, transmission of the acceptable coefficients, and refinement processes are employed. The experimental results show that the proposed scheme not only achieves satisfactory MRI image quality reconstruction, but also improves the similar terms in the earlier works.