Majlesi Journal of Telecommunication Devices: 29 (1)

Open Access Article

1 - Design and Simulation of a Waveguide Division De-multiplexer (DWDM) for Communication Application
Yadollah Shahamat Mohammad Vahedi

We design and simulate an efficient wavelength division demultiplexer (WDDM) based on photonic crystal without using either specific materials or complexities in the fabrication process. The photonic crystal consists of a square lattice of Chalcogenide glass with embedd More

We design and simulate an efficient wavelength division demultiplexer (WDDM) based on photonic crystal without using either specific materials or complexities in the fabrication process. The photonic crystal consists of a square lattice of Chalcogenide glass with embedded in air in two dimensions. The structure involves three cavities around the boundary of the waveguide with specified distance from each other for wavelength selection. For obtaining resonant frequencies of the cavities, two dimensional Finite-Difference-Time-Domain (FDTD) simulation is used. Through simulations, characteristic resonant wavelengths of the cavities are obtained in terms of the size of the coupling rods and the inner rod of the cavity. To show the design flexibility of the proposed structure, a WDDM is designed to divide a common input containing wavelengths andinto three distinct ports with a high efficiency.. Manuscript profile

Open Access Article

2 - Decimal Convolutional Code and its Decoder for Low-Power applications
Ali Ghasemi khah Yosef Seifi Kavian

P. Elias proposed convolutional coding at 1955. Convolutional encoders have very simple structure but their decoders are very complex and power consumer. Power consumption and error correction of Convolutional Codes, will be enhanced by increase in their constrain lengt More

P. Elias proposed convolutional coding at 1955. Convolutional encoders have very simple structure but their decoders are very complex and power consumer. Power consumption and error correction of Convolutional Codes, will be enhanced by increase in their constrain length, therefore there is always a trade-off between Power consumption and error correction. In Convolutional Codes, the code specifications remain constant in each frame. If the specifications are changed during each frame in a code, a new code with new performance and specifications is created. This paper, aims to evaluate this issue for the first time and compare its performance with Convolutional Codes. This new code is named “Decimal Convolutional”. If in a decimal convolutional code, constrain length is changed during each frame, the generated code will be a convolutional code with “decimal constrain length”. In this paper, a convolutional code with decimal constrain length is introduced, encoder and Viterbi decoder structure is explained for it and its specification is compared with convolutional code. Using this code, an optimized constrain length can be obtained and relative power consumption of decoder can be also reduced. The proposed design blocks are described by VHDL and they are implemented on Xilinx Spartan3, Xc3s400 FPGA chip. Manuscript profile

Open Access Article

3 - Optimization of Human Recognition from the Iris Images using the Haar wavelet
Nahal Avazpour Mehran Emadi

Today, biometric recognition (based on biological signs) is a common and reliable method for recognizing and identity confirmation based on their behavioral and physiological characteristics. Physiological characteristics are consistent with the physical characteristics More

Today, biometric recognition (based on biological signs) is a common and reliable method for recognizing and identity confirmation based on their behavioral and physiological characteristics. Physiological characteristics are consistent with the physical characteristics of individuals such as fingerprints, iris pattern, facial features, and the like. This type of property often does not change without external exertion. Behavioral characteristics such as signature, spoken pattern and iris are also a scale for identification and identity confirmation. In this study, using the wavelet method, the efficiency of human identification was increased by 75%. Manuscript profile

Open Access Article

4 - Introducing a Two-step Strategy based on Deep Learning Enhance the Accuracy of Intrusion Detection Systems in the Network
Ali Bahmani Amirhassan Monajemi

Intrusion Detection System is one of the most important security features of modern computer networks that can detect network penetration through a series of functions. This system is independently used (e.g. Snort) or with various security equipment (such as Antivirus, More

Intrusion Detection System is one of the most important security features of modern computer networks that can detect network penetration through a series of functions. This system is independently used (e.g. Snort) or with various security equipment (such as Antivirus, UTM, etc.) on the network and detects an attack based on two techniques of abnormal detection and signature-based detection. Currently, most of the researches in the field of intrusion detection systems have been done based on abnormal behavior using a variety of methods including statistical techniques, Artificial Intelligence (AI), data mining, and machine learning. In this study, we can achieve an effective accuracy using a candidate class of the KDD dataset and deep learning techniques. Manuscript profile

Open Access Article

5 - Detection Of Brain Tumors From Magnetic Resonance Imaging By Combining Superpixel Methods And Relevance Vector Machines Classification
Ebrahim Akbari Mehran Emadi

The production of additional cells often forms a mass of tissue that is referred to as a tumor. Tumors can disrupt the proper functioning of the brain and even lead to the patients' death. One of the non-invasive diagnostic methods for this disease is Magnetic Resonance More

The production of additional cells often forms a mass of tissue that is referred to as a tumor. Tumors can disrupt the proper functioning of the brain and even lead to the patients' death. One of the non-invasive diagnostic methods for this disease is Magnetic Resonance Imaging (MRI). The development of an automated or semi-automatic diagnostic system is required by the computer in medical treatments. Several algorithms have been used to detect a tumor, each with its own advantages and disadvantages. In the present study, an automatic method has been developed by the combination of new methods in order to find the exact area of the tumor in the MRI image. This algorithm is based on super pixel and RVM classification. The algorithm used in the super pixel method is the SLIC algorithm, which calculates for each super pixel 13 statistical characteristics and severity. Finally, an educational method introduced from the RVM classification algorithm that can detect the tumor portion from non-tumor in each brain MRI image. BRATS2012 dataset and FLAIR weights have been utilized in this study The results are compared with the results of the BRATS2012 data and The overlap coefficients of Dice, BF score, and Jaccard were 0.898, 0.697 and 0.754, respectively. Manuscript profile

Open Access Article

6 - Improving Image Quality Based on Feature Extraction and Gaussian Model
Alireza Alirezaei Shahraki Mehran Emadi

By expanding the use of digital images in various areas of everyday life, such as medicine, identification, satellite imagery, and even personal cameras and machine vision, it is felt more effective in applying quality improvements to the images used. The low-quality im More

By expanding the use of digital images in various areas of everyday life, such as medicine, identification, satellite imagery, and even personal cameras and machine vision, it is felt more effective in applying quality improvements to the images used. The low-quality images in the machine's vision can expose the efficacy of later processing, such as feature extraction, classification, and pattern recognition. In this thesis, a new method for improving the quality of images based on the extraction of Godin’s combined feature and model has been proposed. Based on the fact that each homogeneous region in the image has a Gaussian distribution histogram, this distribution can be divided into smaller histograms. For the histogram division efficacy, the image is transmitted from the RGB space to the HSV space and the histogram division is applied to the severity region, and the histogram is applied to each sub Histogram based on the statistical characteristics, and the image. Improved results are returned to the RGB color space. Several qualitative and quantitative criteria have been used to evaluate the proposed method. Qualitative comparison results show improved image quality compared to histogram equivalence methods and linear contrast traction. Quantitative evaluation criteria, such as entropy and spatial frequency, as well as signal to noise ratio, and peak signal to noise ratio, are generally proposed for superiority of the method. Manuscript profile

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