In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

     Drought is a complex phenomenon that has severe impacts on the environment. Vegetation and its conditions are very sensitive to drought effects. This study aimed to monitor and assess the drought severity and its relationships to some ecological variables in ten districts of Erbil Governorate (Kurdistan Region), Iraq, throughout 20 years (1998-2017). The results revealed that droughts frequently hit Erbil throughout the study period. The Landsat time-series- based on Vegetation Condition Index (VCI) significantly correlated with precipitation, Digital Elevation Model (DEM), and latitude. Extreme VCI-based drought area percentages were recorded in 1999, 2000, 2008, and 2011 by 43.4%, 67.9%, 43.3%, and 40.0%, respe

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

Data security is a significant requirement in our time. As a result of the rapid development of unsecured computer networks, the personal data should be protected from unauthorized persons and as a result of exposure AES algorithm is subjected to theoretical attacks such as linear attacks, differential attacks, and practical attacks such as brute force attack these types of attacks are mainly directed at the S-BOX and since the S-BOX table in the algorithm is static and no dynamic so this is a major weakness for the S-BOX table, the algorithm should be improved to be impervious to future dialects that attempt to analyse and break the algorithm  in order to remove these weakness points, Will be generated dynamic substitution box (S-B

Offline Arabic handwritten recognition lies in a major field of challenge due to the changing styles of writing from one individual to another. It is difficult to recognize the Arabic handwritten because of the same appearance of the different characters.  In this paper a proposed method for Offline Arabic handwritten recognition. The   proposed method for recognition hand-written Arabic word without segmentation to sub letters based on feature extraction scale invariant feature transform (SIFT) and   support vector machines (SVMs) to enhance the recognition accuracy. The proposed method  experimented using (AHDB) database. The experiment result  show  (99.08) recognition  rate.