In this research a recent developed practical modeling technique is applied for the glucose regulation system identification. By using this technique a set of mathematical models is obtained instead of single one to compensate for the loss of information caused by the optimization technique in curve fitting algorithms, the diversity of members inside the single set is interpreted in term of restricted range of its parameters, also a diagnosis criteria is developed for detecting any disorder in the glucose regulation system by investigating the influence of variation of the parameters on the response of the system, this technique is applied in this research practically for 20 cases with association of National Center for Diabetes / Al Mustanseryia University.
Abstract
For sparse system identification,recent suggested algorithms are
-norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreHM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
Hydroponics is the cultivation of plants by utilizing water without using soil which emphasizes the fulfillment of the nutritional needs of plants. This research has introduced smart hydroponic system that enables regular monitoring of every aspect to maintain the pH values, water, temperature, and soil. Nevertheless, there is a lack of knowledge that can systematically represent the current research. The proposed study suggests a systematic literature review of smart hydroponics system to overcome this limitation. This systematic literature review will assist practitioners draw on existing literature and propose new solutions based on available knowledge in the smart hydroponic system. The outcomes of this paper can assist future r
... Show MoreThe problem of the study was to identify the possibility of benefiting from the application of the target cost system as a modern cost system to activate the environmental cost management instead of the traditional systems used in the company due to the great transformations witnessed by the business environment in all fields, which have resulted in the search for modern systems to provide more accurate and more appropriate information to reduce Costs, because accurate information makes the company have a complete vision to achieve the company’s goals. To solve this problem, the research was based on the following hypothesis (that the role of the target cost system leads to the activation of environmental cost management). Target c
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