The current research deals with the study of aesthetic relations in the field of interior design and the extent to which its mechanisms achieve sensory stimulation between the internal and external spaces, to generate a continuous visual connection that is an extension of it, achieving in turn sensory stimulation for the users of those spaces. The internal and external spaces meet the desired purpose of feeling pleasure and beauty.” The current research aims to “discover the nature of aesthetic relations between the internal and external spaces and the extent to which mechanisms can achieve sensory stimulation in residential spaces.” The first topic included the concept of aesthetic relations, sensory excitement, and perception at

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

  The current research is interested in the objective study of revitalizing the religious sites and the extent to which they achieve the pragmatic and semantic ends, because they are derived from history and civilization and have a clear impact over the recipient. The research question is (what are the techniques of developing the spaces of the religious shrines in accordance with revitalizing the interior spaces within them?).
The research aims at determining the weak and strong points in the process of revitalizing the interior spaces in the religious shrines.
The theoretical framework consists of two parts: the first addressed the revitalization in the interior design, and the second addressed the religious shrines and th

Type 2 diabetes mellitus (T2DM) is the most frequent endocrinal disease commonly associated with thyroid disorders .The study is conducted at the Specialized Center for Endocrinology and Diabetes in Baghdad ,during December 2014 up to October 2015.This study was done to investigate the prevalence of anti- thyroid peroxidase (Anti-TPO) antibody in patients suffered from type 2 diabetes with thyroid disorders .The study groups included a total number of 80 subjects consisting of 60 type 2 diabetic patients divided into 20 hyperthyroidism subjects (group 1) ,20 hypothyroidism subjects (group 2), 20 euthyroidism subjects (group 3) and 20 healthy controls (group 4) . The fasting blood samples were analyzed for (T3,T4,TSH) by using Vitek Immuno d

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

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s