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Improving the Reliability of Evolutionary Algorithm for Complex Detection in Noisy Protein-Protein Interaction Networks
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Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological process, and cellular component is used to get the functional domain. The reliability of the proposed algorithm is examined against the algorithms proposed in the literature. To this end, a yeast protein-protein interaction dataset is used in the assessment of the final quality of the algorithms. To make fake negative controls of PPIs that are wrongly informed and are linked to the high-throughput interaction data, different noisy PPINs are created. The noisy PPINs are synthesized with a different and increasing percentage of misinformed PPIs. The results confirm the effectiveness of the extended evolutionary algorithm design to utilize the biological knowledge of the gene ontology. Feeding EA design with GO annotation data improves reliability and produces more accurate detection results than the counterpart algorithms.

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Publication Date
Tue Jan 01 2019
Journal Name
Spe Europec Featured At 81st Eage Conference And Exhibition
Development of Artificial Neural Networks and Multiple Regression Analysis for Estimating of Formation Permeability
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Energy Consumption Analyzing in Single hop Transmission and Multi-hop Transmission for using Wireless Sensor Networks
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Wireless sensor networks (WSNs) are emerging in various application like military, area monitoring, health monitoring, industry monitoring and many more. The challenges of the successful WSN application are the energy consumption problem. since the small, portable batteries integrated into the sensor chips cannot be re-charged easily from an economical point of view. This work focusses on prolonging the network lifetime of WSNs by reducing and balancing energy consumption during routing process from hop number point of view. In this paper, performance simulation was done between two types of protocols LEACH that uses single hop path and MODLEACH that uses multi hop path by using Intel Care i3 CPU (2.13GHz) laptop with MATLAB (R2014a). Th

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Use The moment method to Estimate the Reliability Function Of The Data Of Truncated Skew Normal Distribution
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The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,

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Publication Date
Sun Feb 28 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based f

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Publication Date
Tue Jan 10 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Enhancement the Educational Technology by Using 5G Networks
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With the spread of global markets for modern technical education and the diversity of programs for the requirements of the local and global market for information and communication technology, the universities began to race among themselves to earn their academic reputation. In addition, they want to enhance their technological development by developing IMT systems with integrated technology as the security and fastest response with the speed of providing the required service and sure information and linking it The network and using social networking programs with wireless networks which in turn is a driver of the emerging economies of technical education. All of these facilities opened the way to expand the number of students and s

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Publication Date
Sun Dec 01 2024
Journal Name
Anbar Journal Of Agricultural Sciences
IMPROVING THE QUALITY OF POTATO MINI TUBERS BY SUSTAINABLE CULTIVATION
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Publication Date
Sat Dec 01 2018
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
An Energy-Aware and Load-balancing Routing scheme for Wireless Sensor Networks
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<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

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Publication Date
Sun May 02 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The effect of applying lean construction tools to improving the results of the earned value management model: Applied research in Al-Rasheed General Company for Construction Contracting
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Contracting companies play a prominent role today in economic activity, due to their contribution to the implementation of major construction projects which together constitute the infrastructure of society. Most construction projects also suffer from exceeding the time and cost specified and planned for the completion of the project, and this comes for several reasons, including the work environment, country conditions, The method of managing project costs and the techniques used in its implementation Accordingly, the concepts of lean construction came, which help in addressing the causes of waste, both in time and cost, in addition to the fact that project management needs techniques that are useful in controlling the control and manag

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