HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

          General propositions have dealt with various indicators and features that frame and describe basic architectural concepts, and from those concepts, the concept of identity will be presented here, which represents the nerve of intellectual vision of the state of architecture development, transformation and change. Due to its deep intellectual basis, it was necessary to study multiple features, especially the achievement feature that was considered a major stage describing the nature of change and shift related to the achievement of concept and its role in the development of the architectural field .              &nb

In this study, the feasibility of Forward–Reverse osmosis processes was investigated for treating the oily wastewater. The first stage was applied forward osmosis process to recover pure water from oily wastewater. Sodium chloride (NaCl) and magnesium chloride (MgCl2) salts were used as draw solutions and the membrane that was used in forward osmosis (FO) process was cellulose triacetate (CTA) membrane. The operating parameters studied were: draw solution concentrations (0.25 – 0.75 M), oil concentration in feed solution (FS) (100-1000 ppm), the temperature of FS and draw solution (DS) (30 - 45 °C), pH of FS (4-10) and the flow rate of both DS and FS (20 - 60 l/h). It was found that the water flux and oil concentration in FS increas

The GPS navigation measurements become more widely used in many civilian and scientific application. All GPS navigation data holds many errors, the main error sources arise from the geodetic Datum variation when user apply the GPS measurements with the map. Geodetic datums define the size and shape of the earth and the origin and orientation of the coordinate systems used to map the earth surface. In this paper, the Datum transformation was evaluated in two mathematical methods to overcome the errors due to the difference between the WGS-84 and our country Datum Clarck-1880. The results was evaluated and investigated using Carmin GPS device for GCPs comparison, topographic map for Hilla city, mid Iraq 1:100000 scale, and two georefrencing

The rotation effect upon Morse potential had been studied and the values of the effective potential in potential curves had been calculated for electronic states (X2?+g , B ?u ) K2 molecule. The calculation had been computed for rotational quantum number (J = 5). Also, drawing potential curves for these systems had been done using Herzberg and Gaydon equations. It was found that the values of the dissociation energy which resulting from using Herzberg equation greater than that of Gaydon equation. Besides, it was found that the rotation effect for (X and B) electronic states in Morse potential is very small and in this case may negligible.

 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

    Feature selection represents one of the critical processes in machine learning (ML). The fundamental aim of the problem of feature selection is to maintain performance accuracy while reducing the dimension of feature selection. Different approaches were created for classifying the datasets. In a range of optimization problems, swarming techniques produced better outcomes. At the same time, hybrid algorithms have gotten a lot of attention recently when it comes to solving optimization problems. As a result, this study provides a thorough assessment of the literature on feature selection problems using hybrid swarm algorithms that have been developed over time (2018-2021). Lastly, when compared with current feature selection procedu

E-mail is an efficient and reliable data exchange service. Spams are undesired e-mail messages which are randomly sent in bulk usually for commercial aims. Obfuscated image spamming is one of the new tricks to bypass text-based and Optical Character Recognition (OCR)-based spam filters. Image spam detection based on image visual features has the advantage of efficiency in terms of reducing the computational cost and improving the performance. In this paper, an image spam detection schema is presented. Suitable image processing techniques were used to capture the image features that can differentiate spam images from non-spam ones. Weighted k-nearest neighbor, which is a simple, yet powerful, machine learning algorithm, was used as a clas