The reduction to pole of the aeromagnetic map of the western desert of Iraq has been used to outline the main basement structural features. Three selected magnetic anomalies are used to determine the depths of their magnetic sources. The estimated depths are obtained by using slope half slope method and have been corrected through the application of a published nomogram. These depths are compared with previous published depth values which provide a new look at the basement of the western desert in addition to the thickness map of the Paleozoic formations. The results shed light on the important of the great depths of the basement structures and in turn the sedimentary cover to be considered for future hydrocarbon exploration

     This research is focused on an interpretive of 2D seismic data to study is reinterpreting seismic data by applying sufficient software (Petrel 2017) of the area between Al-Razzazah Lake and the Euphrates river belonging to Karbala'a and Al-Anbar Governorates, central Iraq. The delineation of the sub-surface structural features and evaluation of the structure of Najmah and Zubair Formations was done. The structure interpretation showed that the studied area was affected by normal fault bearing (NW-SE) direction with a small displacement. In contrast, time and depth maps showed monocline structures (nose structures) located in the western part of the studied area.

  In the last decade, the web has rapidly become an attractive platform, and an indispensable part of our lives. Unfortunately, as our dependency on the web increases so programmers focus more on functionality and appearance than security, has resulted in the interest of attackers in exploiting serious security problems that target web applications and web-based information systems e.g. through an SQL injection attack.     SQL injection in simple terms, is the process of passing SQL code into interactive web applications that employ database services such applications accept user input  such as form  and then include this input in database requests, typically SQL statements in a way that was not intende

In this study, a chaotic method is proposed that generates S-boxes similar to AES S-boxes with the help of a private key belonging to

In this study, dynamic encryption techniques are explored as an image cipher method to generate S-boxes similar to AES S-boxes with the help of a private key belonging to the user and enable images to be encrypted or decrypted using S-boxes. This study consists of two stages: the dynamic generation of the S-box method and the encryption-decryption method. S-boxes should have a non-linear structure, and for this reason, K/DSA (Knutt Durstenfeld Shuffle Algorithm), which is one of the pseudo-random techniques, is used to generate S-boxes dynamically. The biggest advantage of this approach is the produ

Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le

     In this paper, time spent and the repetition of using the Social Network Sites (SNS) in Android applications are investigated. In this approach, we seek to raise the awareness and limit, but not eliminate the repeated uses of SNS, by introducing AndroidTrack. This AndroidTrack is an android application that was designed to monitor and apply valid experimental studies in order to improve the impacts of social media on Iraqi users. Data generated from the app were aggregated and updated periodically at Google Firebase Real-time Database. The statistical factor analysis (FA) was presented as a result of the user’s interactions.

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

The estimation of the regular regression model requires several assumptions to be satisfied such as "linearity". One problem occurs by partitioning the regression curve into two (or more) parts and then joining them by threshold point(s). This situation is regarded as a linearity violation of regression. Therefore, the multiphase regression model is received increasing attention as an alternative approach which describes the changing of the behavior of the phenomenon through threshold point estimation. Maximum likelihood estimator "MLE" has been used in both model and threshold point estimations. However, MLE is not resistant against violations such as outliers' existence or in case of the heavy-tailed error distribution. The main goal of t