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.
The vortex rate sensor is a fluidic gyroscope with no moving parts and can be used in very difficult
conditions like radiation, high temperature and noise with minimum cost of manufacturing and
maintenance. A vortex rate sensor made of wood has been designed and manufactured to study
theoretically and experimentally its static performance .A rig has been built to carry out the study,
the test carried out with three different air flow rates (100, 150, and 200 l/min).The results show that
the relation between the differential pressure taken from the sensor pickoff points and the angular
velocity of the sensor was linear.The present work involved theoretical and experimental study of
vortex rate sensor static characteri
The vortex rate sensor is a fluidic gyroscope with no moving parts and can be used in very difficult conditions like radiation, high temperature and noise with minimum cost of manufacturing and maintenance. A vortex rate sensor made of wood has been designed and manufactured to study theoretically and experimentally its static performance .A rig has been built to carry out the study,
the test carried out with three different air flow rates (100, 150, and 200 l/min).The results show that the relation between the differential pressure taken from the sensor pickoff points and the angular velocity of the sensor was linear.The present work involved theoretical and experimental study of vortex rate sensor static characteristics .Vortex rat
The present work focuses on the experimental implementation of one of the fiber optical sensors, the optical glass fiber built on surface Plasmon resonance. A type of optical glass fiber was used in this work, single-mode no-core fiber with pre-tapering diameter: (125.1 μm) and (125.3 μm), respectively. The taper method can be tested by measuring the output power of the optical fiber before and after chemical etching to show the difference in cladding diameter due to the effect of hydrofluoric acid with increasing time for the taper process. The optical glass fiber sensor can be fabricated using the taper method to reduce the cladding diameter of the fibers to (83.12 µm, 64.37 µm, and 52.45 µm) for single-mode fibers using Hydrofluoric
... Show MoreIn recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
... Show MoreThe aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).
This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different video
... Show MoreVisual analytics becomes an important approach for discovering patterns in big data. As visualization struggles from high dimensionality of data, issues like concept hierarchy on each dimension add more difficulty and make visualization a prohibitive task. Data cube offers multi-perspective aggregated views of large data sets and has important applications in business and many other areas. It has high dimensionality, concept hierarchy, vast number of cells, and comes with special exploration operations such as roll-up, drill-down, slicing and dicing. All these issues make data cubes very difficult to visually explore. Most existing approaches visualize a data cube in 2D space and require preprocessing steps. In this paper, we propose a visu
... Show MoreThe using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible parametric models and these models were nonparametric, many researchers, are interested in the study of the function of permanence and its estimation methods, one of these non-parametric methods.
For work of purpose statistical inference parameters around the statistical distribution for life times which censored data , on the experimental section of this thesis has been the comparison of non-parametric methods of permanence function, the existence
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