Collaborative Recommender System based on Improved Firefly Algorithm

Sharma, Bharti; Hashmi, Adeel; Gupta, Charu; Jain, Amita

doi:10.13053/cys-26-2-4232

Cited by 5 publications

(2 citation statements)

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“…The most common manifestation is generalized weakness. As such, any other electrolyte aberrations should also be suspected, including hypokalemia and hypomagnesemia 28 . Additionally, the following diagnoses can be considered 28 29 .…”

Section: Differential Diagnosis Of Hypophosphatemiamentioning

confidence: 99%

Hypophosphatemia and Type-2 Diabetes Mellitus: A Review

Karmakar,

Mohiuddin,

Nargish

et al. 2024

Eastern Med. Coll. J.

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Type-2 diabetes is a global public health crisis that threatens the economies of all nations, particularly developing countries. Type-2 diabetes mellitus has been suggested to be the most common endocrine disorder associated with several metabolic disturbances including changes in serum calcium, zinc, magnesium, or phosphate. Moreover, those who have poor glycemic control and longtime diabetes mellitus are more likely to decrease the blood phosphate level. Low serum phosphate level may be associated with morbidity and mortality from cardiovascular disease in these patients. So, the findings of this study may suggest that serum phosphate is an important screening parameter in type-2 diabetic patients especially who have poor glycemic control and longtime diabetes mellitus. Eastern Med Coll J. July 2023; 8 (2): 45-50

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Section: Differential Diagnosis Of Hypophosphatemiamentioning

confidence: 99%

Hypophosphatemia and Type-2 Diabetes Mellitus: A Review

Karmakar,

Mohiuddin,

Nargish

et al. 2024

Eastern Med. Coll. J.

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“…The way nature and its living beings co-exist in harmony is astonishing. The last two decades have witnessed extensive research in the area of developing and applying nature-inspired techniques for solving various combinatorial optimization problems [6]. Nature-inspired techniques such as ACO (Ant Colony Optimization) [7][8][9], GA (Genetic Algorithms), BCO (Bee Colony Optimization) [10,11], PSO (Particle Swarm Optimization) [12], NSGA -II (Nondominated Sorting Genetic Algorithm II) [13], Bat-inspired algorithm [14], flower pollination algorithm [15], cuckoo search algorithm [16,17], Cuscuta search [18], CSA [19], and hybrid approaches [20,21] (combining two or more different approaches) have already been applied to solve the regression test selection and prioritization problem.…”

Section: Related Workmentioning

confidence: 99%

Multi-Objective Fault-Coverage Based Regression Test Selection and Prioritization Using Enhanced ACO_TCSP

Singhal

Jatana²,

Sheoran³

et al. 2023

Mathematics

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Regression testing of the software during its maintenance phase, requires test case prioritization and selection due to the dearth of the allotted time. The resources and the time in this phase are very limited, thus testers tend to use regression testing methods such as test case prioritization and selection. The current study evaluates the effectiveness of testing with two major goals: (1) Least running time and (2) Maximum fault coverage possible. Ant Colony Optimization (ACO) is a well-known soft computing technique that draws its inspiration from nature and has been widely researched, implemented, analyzed, and validated for regression test prioritization and selection. Many versions of ACO approaches have been prolifically applied to find solutions to many non-polynomial time-solvable problems. Hence, an attempt has been made to enhance the performance of the existing ACO_TCSP algorithm without affecting its time complexity. There have been efforts to enhance the exploration space of various paths in each iteration and with elite exploitation, reducing the total number of iterations required to converge to an optimal path. Counterbalancing enhanced exploration with intelligent exploitation implies that the run time is not adversely affected, the same has also been empirically validated. The enhanced algorithm has been compared with the existing ACO algorithm and with the traditional approaches. The approach has also been validated on four benchmark programs to empirically evaluate the proposed Enhanced ACO_TCSP algorithm. The experiment revealed the increased cost-effectiveness and correctness of the algorithm. The same has also been validated using the statistical test (independent t-test). The results obtained by evaluating the proposed approach against other reference techniques using Average Percentage of Faults Detected (APFD) metrics indicate a near-optimal solution. The multiple objectives of the highest fault coverage and least running time were fruitfully attained using the Enhanced ACO_TCSP approach without compromising the complexity of the algorithm.

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The Use of Metaheuristics in the Evolution of Collaborative Filtering Recommender Systems: A Review

Gebreselassie,

Olusanya

2024

Lecture Notes in Computer Science

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Collaborative Recommender System based on Improved Firefly Algorithm

Cited by 5 publications

References 0 publications

Hypophosphatemia and Type-2 Diabetes Mellitus: A Review

Hypophosphatemia and Type-2 Diabetes Mellitus: A Review

Multi-Objective Fault-Coverage Based Regression Test Selection and Prioritization Using Enhanced ACO_TCSP

The Use of Metaheuristics in the Evolution of Collaborative Filtering Recommender Systems: A Review

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