The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols.
tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.
In this research, titanium dioxide nanoparticles (TiO2 NPs) were prepared through the sol-gel process at an acidic medium (pH3).TiO2 nanoparticles were prepared from titanium trichloride (TiCl3) as a precursor with Ammonium hydroxide (NH4OH) with 1:3 ratio at 50 °C. The resulting gel was dried at 70 °C to obtain the Nanocrystalline powder. The powder from the drying process was treated thermally at temperatures 500 °C and 700 °C. The crystalline structure, surface morphology, and particle size were studied by using X-ray diffraction (XRD), Atomic Force Microscopy (AFM), and Scanning Electron Microscope (SEM). The results showed (anatase) phase of titanium dioxide with the average grain size
... Show Moreاندماجات الأعمال من المظاهر الطبيعية في غالبية دول العالم، ورغم المنافع الكثيرة لاندماجات الأعمال إلا أن المخاطر التي تنتج منها أدت إلى تعقد الإجراءات القانونية لتنفيذها بشكل كبير، كما تعد المعالجة المحاسبية للاندماج من القضايا المعقدة جداً وتثير جدلاً واسعاً في الفكر المحاسبي لا سيما في ظل وجود مدخلين يؤثران في متضمنات المعالجة المحاسبية للاندماج أولهما المدخل القانوني الذي يقسم الاندماج إلى ثلاثة أشك
... Show MoreThis paper develops a nonlinear transient three-dimensional heat transfer finite element model and a rate independent three-dimensional deformation model, developed for the CO2 laser welding simulations in Al-6061-T6 alloy. Simulations are performed using an indirect coupled thermal-structural method for the process of welding. Temperature-dependent thermal properties of Al-6061-T6, effect of latent heat of fusion, and the convective and radiative boundary conditions are included in the model. The heat input to the model is assumed to be a Gaussian heat source. The finite element code ANSYS12, along with a few FORTRAN subroutines, are employed to obtain the numerical results. The benefit of the proposed methodology is that it
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
... Show MoreRecent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T
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This study aims to identify the most prominent factors that lead to bullying of students with intellectual disabilities in primary and middle schools from the perspectives of special education teachers. A quantitative descriptive approach was utilized. A questionnaire was used as a tool for data collection. The sample consisted of (72) male and female teachers from the Asir region in the Kingdom of Saudi Arabia. The results revealed the most prominent factors that lead to bullying as follows: factors associated with the school and its policies, factors associated with peers, factors associated with students with intellectual disabilities, and factors associated with general education teachers. The findin
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The current study is concerned over the benefits from our Prophet ' Surah , these benefits are seven which are : the first : ( The losing , disappointment , weakness in the affairs of those disbelievers ,the second : showing the affairs of the believers in respect to integrity , forgiveness and rest, the third : Indicating the big difference between the believers and disbelievers , each team has his own characteristics that being distinguished from the other, I have explained the benefit that the disbelievers are in a difficult
... Show MoreThe most important social and psychological problems that lead to Alzheimer's disease in the elderly (field study of a sample of people living in the city of Baghdad). The research aims to: 1. Identify the most important social, psychological and health problems of elderly people with Alzheimer's disease. 2. The most prominent solutions and treatments for people living with this disease. 3. rehabilitation and provision of social, psychological and medical services for people with Alzheimer's disease. The research stages of Alzheimer's disease and its symptoms and the most important causes of Alzheimer's disease, research has strengthened the theoretical framework. The theoretical study unexplained social pressure generating dealt with Al
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