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Groundwater Potentials Estimation of a Basement Terrain Using Pumping Test Data for Parts of Sanga Local Government Area, Kaduna State, Northwestern Nigeria

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Open Journal of Modern Hydrology 2016年第4期6卷 222-229页

作者： Hamidu Hassan sidi muhammad waru Garga Ali Bukar Kana muhammad Abdullahi Department of Geology Usmanu Danfodiyo University Sokoto Nigeria Department of Geology University of Maiduguri Maiduguri Nigeria Department of Civil and Water Resources Engineering University of Maiduguri Maiduguri Nigeria Department of Geology Ahmadu Bello University Samaru Zaria Nigeria

Aquifers derived from the crystalline basement rocks for parts of Sanga Local Government area of Kaduna State, Nigeria consist of clay, silt, sand, gravel and laterite materials which may be in various proportions. Using Cooper-Jacobs non-equilibrium graphical method, the hydraulic properties were estimated from pumping test data of 18 boreholes. Conductivity varies from 1.02 × 10﹣2 m/s to 4.07 × 10﹣2 m/s and transmissivity varies from 1.14 × 10﹣1 m2/s to 4.40 × 10﹣1 m2/s. The values of specific capacity range between 1.03 × 10﹣1 m2/s/m and 9.00 × 10﹣2 m2/s/m, and these values indicate that the aquifers in the area have low to moderate ground water potentials. The low yield range of between 0.45 l/s and 1.00 l/s recorded in the area shows the heterogeneous and anisotropy nature of the basement aquifer system in terms of groundwater discharge. On the average, the boreholes assessed have potentials to sustain local to regional supply provided the best drilling method and materials are used and well completion properly done.

关键词： Pumping Test Heterogeneous Anisotropy Conductivity Discharge Sanga

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Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval

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Computers, Materials & Continua 2022年第1期70卷 963-979页

作者： Awais Mahmood muhammad Imran Aun Irtaza Qammar Abbas Habib Dhahri Esam Mohammed Asem Othman Arif Jamal Malik Aaqif Afzaal Abbasi College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(Islamabad Campus) 44000Pakistan University of Engineering and Technology Taxila Pakistan International Islamic University Islamabad44000Pakistan Faculty of Sciences and Technology University of KairouanSidi Bouzid4352Tunisia Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan

Searching images fromthe large image databases is one of the potential research areas of multimedia *** most challenging task for nay CBIR system is to capture the high level semantic of *** researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback(RF).However existing RF based approaches needs a number of iteration to fulfill user’s *** paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the *** previous research work it is reported that SVM based RF approach generating better results for ***,this paper focused on SVM based RF *** enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)before applying SVM on user *** main objective of using thesemeta-heuristic was to increase the positive image sample size from *** steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO,finally SVM is applied using the positive sample generated through *** proposed technique is named as Particle Swarm Optimization Genetic Algorithm-Support Vector Machine Relevance Feedback(PSO-G A-SVMRF).Precisions,recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 *** experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches.

关键词： Feature selection image retrieval particle swarm optimization

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