There have been many negative phenomena in Iraqi society, especially after the political crises over the last years, such as the spread of violence, the deterioration of the economic situation, the spread of unemployment and poverty, and the disintegration of social ties, divorce, and the entry of the scourge of drugs. Among the most dangerous of these emergent phenomena, the phenomenon of suicide among young people of both sex, which has grown and increased in an unprecedented manner, surpassing all known social norms in Iraqi society and the prevailing religious values. Suicide in Iraqi society has transformed from a simple case to a visible presence in all Iraqi provinces. Suicides cases have registered in all cities of Iraq and of bo
... Show Moreتعد المحاسبة بشكل عام علماً لكنها ليست من العلوم الصرفة وإنما من العلوم الإجتماعية مما يتطلب للتعامل مع المواضيع المحاسبية الأخذ بنظر الاعتبار الأشخاص المعنيين بالموضوع سواء كانوا المعدين للمخرجات المحاسبية أي المحاسبين، أو الاطراف ذوي المصالح المعنيين والمستفيدين من هذه المخرجات أي المستخدمين، ويعد المحاسب جزءاً من العملية الاجرائية نفسها وبهذا يكون دوره مزدوجاً يجمع بين كونه القائم بالبحث والقي
... Show MoreThis paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
... Show More'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal
Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p
This research deals with one scene from the movie Romeo and Juliet, which is the balcony scene, due to the importance of this scene in the formation of the construction of the subsequent events of the movie.
The first chapter contained the methodological framework of the research, where the research problem was identified in how Zeffirelli dealt with the balcony scene in the play Romeo and Juliet and enriched it in the cinematic language with a comparison with the original text of the scene. In the balcony scene with comparative parts between the film and the text and the limits of the research that was limited to the film Zeffirelli and the translated text by Munis Taha Hussein.
The second chapter contained the theoretic
... Show MoreBackground: This study aimed to assess the effect of tooth width in malocclusion in relation to normal, crowding, and spacing dentition. Materials and methods: The sample included dental casts of some dental students and orthodontic patients; their age was (18-25) years and having three groups normal, crowding, and spacing dentition groups. The sample was equally divided to three groups normal, crowding, and spacing dentition groups, each group contained 50 maxillary and 50 mandibular casts that were further subdivided by gender; all the stone casts were measured by highly sensitive digital vernier. Results and Conclusions: Non-significant side difference was found in both dental arches in the three studied groups. Males had higher mesiodis
... Show MoreData generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
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