Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To address this challenge, This paper proposes the Neural Control Exponential Weight of Priority Based Rate Control (NEWPBRC) algorithm for adjusting the node transmission rate and facilitate the problem of congestion occur in WMSNs. The proposed algorithm combines Neural Network Controller (NC) with the Exponential Weight of Priority Based Rate Control (EWPBRC) algorithms. The NC controller can calculate the appropriate weight parameter λ in the Exponential Weight (EW) algorithm for estimating the output transmission rate of the sink node, and then, on the basis of the priority of each child node, an appropriate transmission rate is assigned. The proposed algorithm can support four different traffic classes namely, Real Time traffic class (RT class); High priority, Non Real-Time traffic class (NRT1 class); Medium priority, Non Real-Time traffic class (NRT2 class); and Low priority,
Diabetic Nephropathy(DN) is a complex disease manifested by persistence microalbuminuria occurring due to the interaction between hemodynamic and metabolic pathway that activates the local renin-angiotensin-aldosterone system resulting in a decline in renal functions.
This study aimed to quantify the associations between serum aldosterone concentration and fetuin- A as a marker of calcification in type 2 diabetic patients with and without microalbuminuria from one side, and study the possible relationship between aldosterone and fetuin-A with glycemic indices, serum electrolyte, renal function and microalbuminuria and body mass index from the other side.
A case-control study involved eighty-six adult subjects
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An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi
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Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
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In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete
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Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.
 
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