This study employs a critical discourse analysis approach to investigate the linguistic and discursive mechanisms employed by the prominent Russian online news platform Gazeta.ru in its coverage of social news. Drawing on an interdisciplinary framework integrating critical discourse analysis (CDA), media discourse analysis, and sociolinguistic perspectives, the research examines how language is used to construct and disseminate societal narratives. The analysis focuses on a dataset of Gazeta.ru articles published in March 2024, encompassing topics such as health, travel, and consumer affairs. Through a multi-level analytical approach, the study explores macro-level discursive strategies and microlevel linguistic choices, unveiling the intri

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

study aimed to investigate the effect of fish bone in the of chemistry and self-organized learning for students of the second grade‚ achievement . The study sample consisted of 84 students from the second grade students middel in the of alrasheed boysschool, of the Directorate of Educational Karkh II, in two divisions, Division of (a) an experimental group that studied the strategy fish bone, and the Division (d) a control group which studied the usual way. The results indicated the presence of significant differences in favor of the experimental group that studied using the fish bone in achievement and learning self-organized strategy students

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

    Terrestrial laser scanners (TLSs) are 3D imaging systems that provide the most powerful 3D representation and practical solutions for various applications. Hence this is due to effective range measurements, 3D point cloud reliability, and rapid acquisition performance. Stonex X300 TOF scanner delivered better certainty in far-range than in close-range measurements due to the high noise level inherent within the data delivered from Time of Flight (TOF) scanning sensors. However, if these errors are manipulated properly using a valid calibration model, more accurate products can be obtained even from very close-range measurements. Therefore, to fill this gap, this research presents a user-oriented target-based calibration routi

أن صفة التغير المتسارع في نمط الحياة ولّد مبدأ اللايقين عند إتخاذ القرارات المالية لأي ظاهرة عموماً أو نشاط إقتصادي على وجه الخصوص. وهذا يتطلب الأستعانة بالأدوات الأحصائية كمنهج علمي يساعد في وصفها وتحليلها كمياً ومن ثم التنبؤ بها مستقبلاً كمحاولة لسبر غور اللايقين الذي يكتنف المستقبل كمجهول يتوجس منه الجميع. وقد أصبح متخذ القرار الأستثماري أو صاحب رأس المال وغيرهما من المضاربين والمتعاملين في الاسواق الما