Traditionally, path selection within routing is formulated as a shortest path optimization problem. The objective function for optimization could be any one variety of parameters such as number of hops, delay, cost...etc. The problem of least cost delay constraint routing is studied in this paper since delay constraint is very common requirement of many multimedia applications and cost minimization captures the need to
distribute the network. So an iterative algorithm is proposed in this paper to solve this problem. It is appeared from the results of applying this algorithm that it gave the optimal path (optimal solution) from among multiple feasible paths (feasible solutions).
In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based
... Show MoreThe second leading cause of death and one of the most common causes of disability in the world is stroke. Researchers have found that brain–computer interface (BCI) techniques can result in better stroke patient rehabilitation. This study used the proposed motor imagery (MI) framework to analyze the electroencephalogram (EEG) dataset from eight subjects in order to enhance the MI-based BCI systems for stroke patients. The preprocessing portion of the framework comprises the use of conventional filters and the independent component analysis (ICA) denoising approach. Fractal dimension (FD) and Hurst exponent (Hur) were then calculated as complexity features, and Tsallis entropy (TsEn) and dispersion entropy (DispEn) were assessed as
... Show MorePhenytoin selective electrodes were constructed based on penytoin-phosphotungstate (Ph-PT) complex with different plasticizers; di-butyl phosphate (DBP), tri-butyl phosphate (TBP), di-butyl phthalate (DBPH),and o-nitro phenyl octyl ether (NPOE) phthalate. The electrodes based on DBPH, ONPOE plasticizers gave Narnistain slope which are, 56.4 and 55.3mV/decade with detection limit of 1.9x10-5 M , 1.8x10-5 and concentration range 10-1 to 10-4 M and pH range 3.0 – 8.0. The electrodes based on TBP and DBP showed non-Nernistain slopes, 40.2,40.5 mV/decade for both plasticizers. Interfering of some cations was investigated and shows no interfering with electrodes response. Potentiometric methods were used for measuring phenytion in
... Show MoreAbstract
The research aims to study the problem of high production costs and low quality and the use of total quality management tools to detect problems of the high cost of failure and low quality products, diagnosis, and developing appropriate solutions.
To achieve the goal, we studied the overall quality tools and its relationship with the costs and the possibility of improving quality through the use of these tools.
Was limited to these tools and study the relation to the reduction of costs and improving quality have been studied serially by the possibility of the reduction.
To achieve the goal, the study of the concept of total quality management
Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
... Show MoreThis study examined the correlation between binder-level fatigue properties and mixture-level cracking resistance in asphalt binders modified with five Nanomaterials (NMs): Nano-Silica (NS), Nano-Alumina (NA), and Nano-Titanium dioxide (NT) at 2%, 4%, and 6% as well as Nano-Zinc oxide (NZ) and Carbon Nanotubes (CNTs) at 1%, 2%, and 3%. Modified binders were subjected to Rolling Thin-Film Oven Test (RTFOT) and Pressure Aging Vessel (PAV) aging and tested at 25 °C using the Linear Amplitude Sweep (LAS) test to determine fatigue life (Nf) and the fatigue parameter G*.sin δ. The corresponding asphalt mixtures were evaluated using the IDEAL-CT test. The results indicated strong correlations between binder and mixture performance for
... Show MoreThis study aimed to explore the relationship between cyberbullying and levels of pessimism and optimism among female university students, emphasizing the significance of these variables in students' psychological well-being. The research problem was identified in the increasing rates of cyberbullying among female students and its negative impact on optimism and pessimism, alongside the lack of effective counseling programs addressing this issue. The study sample consisted of 30 third-year students from the College of Physical Education and Sports Sciences for Women during the academic year 2023--2024. The participants were deliberately selected through a lottery method. The researchers employed the descriptive survey method as it suited the
... Show More