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Ranjith, N.
- A Multi Objective Teacher-Learning-Artificial Bee Colony (MOTLABC) Optimization for Software Requirements Selection
Abstract Views :189 |
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Authors
N. Ranjith
1,
A. Marimuthu
2
Affiliations
1 Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Government Arts College, Coimbatore - 641018, Tamil Nadu, IN
1 Karpagam University, Coimbatore - 641021, Tamil Nadu, IN
2 Government Arts College, Coimbatore - 641018, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 34 (2016), Pagination:Abstract
Background/Objectives: To select optimal software requirements by introducing Multi-objective Teacher-Learning- Artificial Bee Colony Optimization. Methods/Statistical Analysis: Teaching learning based optimization for the multi-objective software requirements selection has two objectives of minimized cost and maximum client satisfaction. Similarly the constraints namely interaction constraints and cost threshold constraints are considered. However, the efficiency of the software product development can be improved further when more efficient optimization techniques is used for the selection of software requirements along with consideration of more objectives and more constraints in larger real datasets. Findings: In this article, a hybrid optimization technique named Multi-Objective Teacher-Learning Artificial Bee Colony Optimization (MOTLABC) is proposed with set of multiple objectives and constraints. The objectives are minimum cost, maximum client satisfaction, minimum time consumption and maximum reliability. The constraints such as time threshold constraint, interaction constraints and cost threshold constraints are considered. The hybrid approach of MOTLABC with the above objectives improves the collection of set of needs for the development of the software. The Pareto optimal problem occurs in multi objective optimization solutions is resolved by the use of Pareto tournament function. Improvements/Applications: The experimental consequences prove that they obtained results perform improved than algorithms proposed in the literature.Keywords
Artificial Bee Colony Optimization, Interaction Constraints, Software Requirements Selection, Teaching Learning Based Optimization.- Chondromalacia Patellae:A Review
Abstract Views :209 |
PDF Views:0
Authors
Affiliations
1 School of Pharmaceutical Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Pallavaram, Chennai-117, Tamilnadu, IN
2 Department of Pharmacognosy, School of Pharmaceutical Sciences, Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai, Tamil Nadu, IN
1 School of Pharmaceutical Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Pallavaram, Chennai-117, Tamilnadu, IN
2 Department of Pharmacognosy, School of Pharmaceutical Sciences, Vels Institute of Science, Technology and Advanced Studies, Pallavaram, Chennai, Tamil Nadu, IN
Source
Research Journal of Pharmacy and Technology, Vol 12, No 1 (2019), Pagination: 412-418Abstract
Chondromalacia patella (knee pain) is the softening and breakdown of the tissue (cartilage) on the underside of the kneecap (patella) and is often referred to as chondromalacia of the patella, patellofemoral syndrome, or runner's knee. Pain Results when the knee and the thigh bone (femur) rub together. Abnormal knee cap positioning, tightness or weakness of the muscles associated with the knee, too much activity involving the knee, and flat feet may increase the likelihood of chondromalacia patella. The undersurface of the patella is covered with hyaline cartilage that articulates with the hyaline cartilage covered femoral groove (trochlear groove). Post-traumatic injuries, microtrauma wear and tear, and iatrogenic injections of medication can lead to the development of chondromalacia. Chondromalacia occurs in any joint and is especially common in joints that have had trauma and deformities. Cartilage is the soft tissue padding which is present between all joint and bones and acts like a shock absorber. The cartilage experiences a lot of wear, tear and damage over time. The cartilage is essentially avascular (has no blood or nerve supply) and is therefore quite a difficult area to heal. Long term therapy is essential in ensuring healthy repair so that further complications are not experienced in the future.Keywords
Chondromalacia, Chondromalacia Patella, Knee Pain, Cartilage.References
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- A Hybrid Ensemble Method for Accurate Fuzzy and Support Vector Machine for Gene Expression in Data Mining
Abstract Views :269 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, KSG College of Arts and Science, IN
1 Department of Computer Science, KSG College of Arts and Science, IN
Source
ICTACT Journal on Soft Computing, Vol 11, No 4 (2021), Pagination: 2444-2448Abstract
Malignancy is a bunch of infection which spreads all through the human body. Since it is an exceptionally deceptive illness its determination is of vital importance. Information mining innovation helps in arranging and bunching the malignancy information and this procedure assists with distinguishing potential disease patients by investigating the data alone. In this examination we analyze three information mining calculations, namely PCA, Genetic calculation and Hierarchical Fuzzy C Means (HFCM). The hereditary calculation is done using the Quantum-enhanced Support Vector Machine (QSVM). The outcome demonstrates that the proposed calculation accomplishes a better outcome when contrasted to the other two calculations.Keywords
PCA, Genetic Algorithm, Hierarchical Fuzzy C Mean, QSVMs, Cluster.References
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