Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation

Combinatorial interaction testing is an important software testing technique that has seen lots of recent interest. It can reduce the number of test cases needed by considering interactions between combinations of input parameters. Empirical evidence shows that it effectively detects faults, in particular, for highly configurable software systems. In real-world software testing, the input variables may vary in how strongly they interact, variable strength combinatorial interaction testing (VS-CIT) can exploit this for higher effectiveness. The generation of variable strength test suites is a non-deterministic polynomial-time (NP) hard computational problem \cite{BestounKamalFuzzy2017}. Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. Nevertheless, they require detailed control for the exploitation and exploration trade-off to avoid premature convergence (i.e. being trapped in local optima) as well as to enhance the solution diversity. Here, we present a new variant of PSO based on Mamdani fuzzy inference system \cite{Camastra2015,TSAKIRIDIS2017257,KHOSRAVANIAN2016280}, to permit adaptive selection of its global and local search operations. We detail the design of this combined algorithm and evaluate it through experiments on multiple synthetic and benchmark problems. We conclude that fuzzy adaptive selection of global and local search operations is, at least, feasible as it performs only second-best to a discrete variant of PSO, called DPSO. Concerning obtaining the best mean test suite size, the fuzzy adaptation even outperforms DPSO occasionally. We discuss the reasons behind this performance and outline relevant areas of future work.Comment: 21 page

Association of Oral Contraceptives use with Breast Cancer and Hormone Receptor Status in Iraqi Women

BACKGROUND: Worldwide, there is a significant concern regarding the association of breast cancer risk and oral contraceptives use. Differences in demographical and pathological breast cancer characteristics in Iraqi patients have been reported compared to other western countries; however, studies addressing the risk of breast cancer among oral contraceptive users in Iraq and subsequent correlation with hormonal receptor status are lacking. AIM: The aim of the study was to evaluate association of breast cancer risk and oral contraceptives use in patients visiting tertiary oncology center and to correlate hormone receptor status with history of oral contraception use in breast cancer patients. PATIENTS AND METHODS: Two hundred women with breast cancer were compared regarding patterns of oral contraceptives use with 300 age-matched healthy female controls by personal interview and questionnaire. Patient’s records were reviewed for hormone receptor status. RESULTS: A significantly higher proportion (49%) of women with breast cancer reported a positive history of combined oral contraceptives use as compared with (35.7%) healthy controls. Ever oral contraceptives users had a significantly increased risk of breast cancer (odds ratio [OR] = 1.73; 95%, confidence interval = 1.2–2.5, p = 0.003), with the highest risk was seen in early use before the age of 20 (OR = 6.62, p = 0.02); whereas increased duration of use did not significantly increase the risk of breast cancer. There was no significant association between estrogen and progesterone receptors expression profile in breast cancer patients and combined oral contraceptive use. CONCLUSION: In Iraqi women, the risk of breast cancer increases with oral contraceptives intake particularly when starts early before the age of 20 years. The hormonal receptor status of breast cancer patients is not significantly affected by combined oral contraceptives use

Influence of Sugar Cane Mechanical Harvest on Clear Juice Quality at Elguneid Sugar Factory

This study aimed to investigate the influence of mechanical harvest on juice clarification in Elguneid sugar factory. Elguneid factory was designed to treat a hand cut cane more than a mechanical cut cane. So, the clarification system was tuned to meet this purpose. Color, turbidity, reducing sugar, sugar content, purity, pH, brix, temperature and phosphate content were determined. The results showed: the color has increased from 3910 to 13921 ICUMSA, turbidity from 3242 to 8496 and reducing sugar increased to 0.928%. Sucrose content decreased from 14.39 to 11.69% and purity from 88 to 83%. The results of Pol% and Purity% were taken at the beginning of crushing season, where the mechanical harvest was higher than hand cut. A comparative study between hand cut and mechanical harvest was made at the middle of the crushing season. The optimum brix in the clarifiers matched the turbidity decreased at brix 12%, 13% respectively. Also from the tests carried out it was shown that the flocculant and phosphoric acid, which were used by the factory personnel was lower than the standard values, phosphoric acid was 183ppm and the polymer was 1,6ppm. These low values affected the precipitation process. There is a relationship between the amount of mud and type of harvest. It was noticed that there is a relationship between sugar yield and type of harvest

Analysis of wind driven self-excited induction generator supplying isolated DC loads

AbstractThis paper presents the analysis, modelling and simulation of wind-driven self-excited induction generator (SEIG). The three-phase SEIG is driven by a variable-speed prime mover to represent a wind turbine. Also, the paper investigates the dynamic performance of the SEIG during start-up, increasing or decreasing the load or rotor speed. The value of the excitation capacitance required for the SEIG is calculated to give suitable saturation level to assure self-excitation and to avoid heavy saturation levels. Matching of the maximum power available from the wind turbine is performed through varying the load value. The effect of AC–DC power conversion on the generator is investigated. The system simulation is carried out using MATLAB/SIMULINK toolbox program

An experimental study of hyper-heuristic selection and acceptance mechanism for combinatorial t-way test suite generation

Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t -way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). Although useful, metaheuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. Hyperheuristics provide an alternative methodology to meta-heuristics which permit adaptive selection and/or generation of meta-heuristics automatically during the search process. This paper describes our experience with four hyper-heuristic selection and acceptance mechanisms namely Exponential Monte Carlo with counter (EMCQ), Choice Function (CF), Improvement Selection Rules (ISR), and newly developed Fuzzy Inference Selection (FIS),using the t -way test generation problem as a case study. Based on the experimental results, we offer insights on why each strategy differs in terms of its performance