Detection and Filtering of Collaborative Malicious Users in Reputation System using Quality Repository Approach

Online reputation system is gaining popularity as it helps a user to be sure about the quality of a product/service he wants to buy. Nonetheless online reputation system is not immune from attack. Dealing with malicious ratings in reputation systems has been recognized as an important but difficult task. This problem is challenging when the number of true user's ratings is relatively small and unfair ratings plays majority in rated values. In this paper, we have proposed a new method to find malicious users in online reputation systems using Quality Repository Approach (QRA). We mainly concentrated on anomaly detection in both rating values and the malicious users. QRA is very efficient to detect malicious user ratings and aggregate true ratings. The proposed reputation system has been evaluated through simulations and it is concluded that the QRA based system significantly reduces the impact of unfair ratings and improve trust on reputation score with lower false positive as compared to other method used for the purpose.Comment: 14 pages, 5 figures, 5 tables, submitted to ICACCI 2013, Mysore, indi

Understanding hypervolume behavior theoretically for benchmarking in evolutionary multi/many-objective optimization

Hypervolume (HV) is one of the most commonly used metrics for evaluating the Pareto front (PF) approximations generated by multiobjective evolutionary algorithms. Even so, HV is a resultant of a complex interplay between the PF shape, number of objectives, and user-specified reference points which, if not well understood, may lead to misinformed inferences about benchmarking performance. In order to understand this behavior, some previous studies have investigated such interactions empirically. In this letter, a new and unconventional approach is taken for gaining further insights about HV behavior. The key idea is to develop theoretical formulas for certain linear (equilateral simplex) and quadratic (orthant) PFs in two specific orientations: 1) regular and 2) inverted. These PFs represent a large number of problems in the existing DTLZ and WFG suites commonly used for benchmarking. The numerical experiments are presented to demonstrate the utility of the proposed work in benchmarking, and in understanding the contributions of the different regions of the PFs, such as corners, edges, as well explaining the contrast between the HV behaviors for regular versus inverted PFs. This letter provides a foundation and computationally fast means to undertake parametric studies to understand various aspects of HV

Investigating the equivalence between PBI and AASF scalarization for multi-objective optimization

Scalarization refers to a generic class of methods to combine multiple conflicting objectives into one in order to find a Pareto optimal solution to the original problem. Augmented achievement scalarizing function (AASF) is one such method used popularly in the multi-criterion decision-making (MCDM) field. In evolutionary multi-objective optimization (EMO) literature, scalarization methods such as penalty boundary intersection (PBI) are commonly used to compare similar solutions within a population. Both AASF and PBI methods require a reference point and a reference direction for their calculation. In this paper, we aim to analytically derive and understand the commonalities between these two metrics and gain insights into the limitations of their standard parametric forms. We show that it is possible to find an equivalent modified AASF formulation for a given PBI parameter and vice versa for bi-objective problems. Numerical experiments are presented to validate the theory developed. We further discuss the challenges in extending this to higher objectives and show that it is still possible to achieve limited equivalence along symmetric reference vectors. The study connects the two philosophies of solving multi-objective optimization problems, provides a means to gain a deeper understanding of both these measures, and expands their parametric range to provide more flexibility of controlling the search behavior of the EMO algorithms

Identifying Stochastically Non-dominated Solutions Using Evolutionary Computation

We consider the problem of finding a solution robust to disturbances of its decision variables, and explain why this should be framed as problem to identify all stochastically non-dominated solutions. Then we show how this can be formulated as an unconventional multi-objective optimization problem and solved using evolutionary computation. Because evaluating stochastic dominance in a black-box setting is computationally very expensive, we also propose more efficient algorithm variants that utilize surrogate models and re-use historical data. Empirical results on several test problems demonstrate that the algorithm indeed finds the stochastically non-dominated solutions, and that the proposed efficiency enhancements are able to drastically cut the number of required function evaluations while maintaining good solution quality

Investigating Normalization Bounds for Hypervolume-Based Infill Criterion for Expensive Multiobjective Optimization

While solving expensive multi-objective optimization problems, there may be stringent limits on the number of allowed function evaluations. Surrogate models are commonly used for such problems where calls to surrogates are made in lieu of calls to the true objective functions. The surrogates can also be used to identify infill points for evaluation, i.e., solutions that maximize certain performance criteria. One such infill criteria is the maximization of predicted hypervolume, which is the focus of this study. In particular, we are interested in investigating if better estimate of the normalization bounds could help in improving the performance of the surrogate assisted optimization algorithm. Towards this end, we propose a strategy to identify a better ideal point than the one that exists in the current archive. Numerical experiments are conducted on a range of problems to test the efficacy of the proposed method. The approach outperforms conventional forms of normalization in some cases, while providing comparable results for others. We provide critical insights on the search behavior and relate them with the underlying properties of the test problems

Partial Evaluation Strategies for Expensive Evolutionary Constrained Optimization

Constrained optimization problems (COPs) are frequently encountered in real-world design applications. For some COPs, the evaluation of the objective(s) and/or constraint(s) may involve significant computational/temporal/financial cost. Such problems are referred to as expensive COPs (ECOPs). Surrogate modeling has been widely used in conjunction with optimization methods for such problems, wherein the search is partially driven by an approximate function instead of true expensive evaluations. However, for any true evaluation, nearly all existing methods compute all objective and constraint values together as one batch. Such full evaluation approaches may be inefficient for cases where the objective/constraint(s) can be evaluated independently of each other. In this article, we propose and study a constraint handling strategy for ECOPs using partial evaluations. The constraints are evaluated in a sequence determined based on their likelihood of being violated; and the evaluation is aborted if a constraint violation is encountered. Modified ranking strategies are introduced to effectively rank the solutions using the limited information thus obtained, while saving on significant function evaluations. The proposed algorithm is compared with a number of its variants to establish the utility of its key components systematically. Numerical experiments and benchmarking are conducted on a range of mathematical and engineering design problems to demonstrate the efficacy of the approach compared to state-of-The-Art evolutionary optimization approaches

Metabolic effects of Olanzapine versus Iloperidone: A 24 weeks randomized, prospective, interventional study

Atypical antipsychotics have become the mainstay of therapy for psychosis. Though extrapyramidal side effects have been reduced with atypical antipsychotics, yet there are increased concerns over metabolic effects. The present study is aimed to comparatively evaluate the metabolic profile of olanzapine and iloperidone in cases of psychosis. A prospective, randomized, open label, observational study of 6 months duration was conducted in the Department of Pharmacology and Department of Psychiatry, Rohilkhand Medical College and Hospital, Bareilly. A total of 62 patients of both sexes newly diagnosed with psychosis (ICD-10, F20- F29) were included in the study, 31 each in olanzapine and iloperidone groups. Demographic parameters were recorded, following which the patient’s body weight, BMI, fasting blood sugar and lipid profile were estimated at baseline. Follow-up of the patients was done periodically after one month, three months and six months. Olanzapine treated patients showed markedly significant rise in body weight up to 7 kg at the endpoint (p<0.0001) at each follow-up, with a significant increase in BMI. Rise in fasting blood sugar (FBS), total cholesterol (TC), triglycerides (TG) and low-density lipoprotein (LDL) levels werealso statistically significant. At the same time, significant decrease in HDL levels was also observed. Iloperidone treated patients showed statistically significant less rise in body weight (upto 1kg, p<0.05) and BMI. No significant changes in fasting blood sugar, total cholesterol, LDL and HDL levels were noted, while TG levels were significantly reduced. Iloperidone caused numerically less rise in bodyweight and BMI, and fewer metabolic adverse effects as compared to olanzapine, and hence should be preferred.Keywords: Atypical antipsychotics; Weight gain; Blood sugar level; Dyslipidemi

Excess Enthalpies of Mixing of Binary Mixtures of NaCl, KCl, NaBr and KBr in Mixed Ternary Solvent Systems at 298.15 K

Excess enthalpies of mixing for six possible binary combinations of solutions of NaCl, KCl, NaBr and KBr in mixed ternary solvents composed of formamide, 1,4-dioxane and water have been determined using a flow microcalorimeter at constant ionic strengths of 0.500 and 1.000 mol kg–1 at 298.15 K. Unlike the case of water, the data do not supportYoung’s cross square rule. Pitzer’s virial coefficient theory has been utilized to obtain binary and ternary interaction parameters, i.e. θH and ψH. The data were also analysed in terms of the Friedman model and it was found that interactions between solvated ions are dictated not only by coulombic interactions but also by appreciable asymmetric effects.Keywords: Enthalpy of mixing, ternary solvents, Pitzer theory, Friedman model, cross square rule

Utility of adzuki bean [Vigna angularis (Willd.) Ohwi & Ohashi] simple sequence repeat (SSR) markers in genetic analysis of mungbean and related Vigna spp.

In the present study, 78 mapped simple sequence repeat (SSR) markers representing 11 linkage groups of adzuki bean were evaluated for transferability to  mungbean and related Vigna spp. 41 markers amplified characteristic bands in at least one Vigna species. The transferability percentage across the genotypes ranged from 60.97 to 92.6% with 87.8% in Vigna radiata and Vigna mungo, 62.2% in Vigna unguiculata, 91.8% in Vigna umbellata, 78% in Vigna mungo var. sylvestris and 80% in Vigna trilobata, respectively. Five major clusters were observed using unweighted pair group method with an arithmetic mean (UPGMA) with each cluster representing a particular Vigna species. We have successfully utilized adzuki bean SSRs in amplifying microsatellite sequences in Vigna species and inferring phylogenetic relationships by correlating the rate of transfer among them. The polymorphic SSR markers identified in this study would be useful in the analysis of genetic diversity, gene mapping and other aspects of genetic studies in mungbean and related species.Key words: Adzuki bean, simple sequence repeat (SSR), inter-genomic marker transferability, genetic diversity, mungbean, Vigna spp

Randomized, interventional, prospective, comparative study to evaluate the antihypertensive efficacy and tolerability of ramipril versus telmisartan in stage 1 hypertensive patients with diabetes mellitus

Angiotensin converting enzyme inhibitors and angiotensin receptor blockers are keystones for therapy of hypertension in diabetes because they show favourable effects on diabetic nephropathy and cardiovascular disease outcomes. A prospective, randomized, interventional clinical study of one year duration was conducted to comparatively evaluate anti-hypertensive efficacy and tolerability profile of ramipril versus telmisartan in stage 1 hypertensive patients associated with type 2 diabetes mellitus, amongst patients of either sex attending the medicine OPD of Rohilkhand Medical College and Hospital, Bareilly. Clearance from institutional ethical committee and written informed consent of the participants was taken. The enrolled 222 patients were randomized into ramipril and telmisartan groups, of these only 192 patients completed the study. The data obtained were statistically analyzed by paired and unpaired t-test using SPSS software. Prevalence of hypertension in diabetics was more in 41 to 50 years age group, in females (male: female ratio= 0.92:1) and in rural areas (rural: urban ratio= 0.61:1). Baseline BP values were equally matched in both groups. The SBP and DBP were reduced from baseline in all the ten follow-ups and were statistically significant (p <0.0001 for both groups). Regarding adverse effects, both drugs were well tolerated though dry irritating cough and dizziness was more in ramipril group. Both ramipril and telmisartan as monotherapy were equally effective in lowering SBP and DBP on prolonged use in diabetic hypertensives but the incidence of adverse effects was higher with ramipril hence telmisartan be preferred.KEY WORDS: Ramipril; Telmisartan; Systolic; Diastolic blood pressure; Stage 1hypertensive patients; Diabetes mellitu