A Multi-Objective Decision Making Approach For Mutual Fund Portfolio

Investment decision-making problems are generally multi-objective in nature such as minimization of the risk and maximization of the return.  These problems can be solved efficiently and effectively using multi-objective decision making (MODM) tools such as a lexicographic goal programming (LGP).  This paper applies the LGP model for selecting an optimum mutual fund portfolio for an investor, while taking into account specific parameters including risk, return, expense ratio and others.  Using sensitivity analysis on the weights in a priority structure of the goals identifies all possible solutions in the decision-making process.  The Euclidean distance method is then used, to measure distances of all possible solutions from the identified ideal solution.  The optimum possible solution is determined by the minimum distance between the ideal solution and other possible solutions of the problem.  The associated weights will be the most appropriate weights in a given priority structure.  The effectiveness and applicability of the LGP model is demonstrated via a case example from broad categories of mutual funds

A Multi-Objective Decision-Making Approach For Mutual Fund Portfolio

Investment decision-making problems are generally multi-objective in nature such as minimization of the risk and maximization of the expected return.  These problems can be solved efficiently and effectively using multi-objective decision making (MODM) tools such as a lexicographic goal programming (LGP).  This paper applies the LGP model for selecting an optimum mutual fund portfolio for an investor, while taking into account specific parameters including risk, return, expense ratio and others.  Sensitivity analysis on the assigned weights in a priority structure of the goals identifies all possible solutions for decision-making.  The Euclidean distance method is then used, to measure distances of all possible solutions from the identified ideal solution.  The optimal solution is determined by the minimum distance between the ideal solution and other possible solutions of the problem. The associated weights with the optimal solution will be the most appropriate weights in a given priority structure.  The effectiveness and applicability of the LGP model is demonstrated via a case example from broad categories of mutual funds

Effect of Jitter on the Settling Time of Mesochronous Clock Retiming Circuits

It is well known that timing jitter can degrade the bit error rate (BER) of receivers that recover the clock from input data. However, timing jitter can also result in an indefinite increase in the settling time of clock recovery circuits, particularly in low swing mesochronous systems. Mesochronous clock retiming circuits are required in repeaterless low swing on-chip interconnects. We first discuss how timing jitter can result in a large increase in the settling time of the clock recovery circuit. Next, the circuit is modelled as a Markov chain with absorbing states. The mean time to absorption of the Markov chain, which represents the mean settling time of the circuit, is determined. The model is validated through behavioural simulations of the circuit, the results of which match well with the model predictions. We consider circuits with (i) data dependent jitter, (ii) random jitter, and (iii) combination of both of them. We show that a mismatch between the strengths of up and down corrections of the retiming can reduce the settling time. In particular, a 10% mismatch can reduce the mean settling time by up to 40%. We leverage this fact toward improving the settling time performance, and propose useful techniques based on biased training sequences and mismatched charge pumps. We also present a coarse+fine clock retiming circuit, which can operate in coarse first mode, to reduce the settling time substantially. These fast settling retiming circuits are verified with circuit simulations.Comment: 23 pages, 40 figure

SELECTIVE ESTROGEN RECEPTOR MODULATORS; ROLE OF SIDE CHAIN IN ACTIVITY MODULATION

Selective estrogen receptor modulators (SERMs) are a class of molecules that activate estrogen receptors (ER), impacting differently on differenttissues. Upon binding to ER, the ligand-receptor complex may present various conformations due to the presence of two different kinds of ERs. Fewof these ligands show estrogenic effects, whereas others will inhibit the action of estrogens. Researchers are working in the direction to generatethe SERMs that have a desirable estrogen-like effects on the various sites i.e., bones, improving lipid profile, reduce hot flushes, but do not act likeestrogens in unwanted ways i.e., causing breast cancer, uterine endometrial proliferation. Given the comprehensive nature of this article, it is not ourintention to revisit many of the issues relating to SERMs, which have already been covered in detail. Rather this article focuses on the aspect thatligand-mediated structural perturbations in and around the ligand binding pocket, contributed by the side chain effects lead to receptor antagonism.Adjusting the balance of these effects may provide a novel strategy for designing of improved SERMs. In the light of this, the article will provide anoverview of the SERMs and their structural diversity.Keywords: Ligand and estrogen receptor, Side chain of selective estrogen receptor modulators, Selective estrogen receptor modulators, Mechanismof action

Assessment of Genetic Diversity in Wild Raspberry (Rubus ellipticus Smith) Native to North-Western Himalayan Region

Nature and magnitude of genetic diversity was assessed in 170 wild raspberry genotypes based on eight quantitative characteristics, viz., fruit weight, fruit length, fruit breadth, TSS, acidity, reducing sugars, non-reducing sugars and Vitamin C. A survey was conducted in three north-western Himalayan states of Himachal Pradesh, Jammu&Kashmir and Uttarakhand. The species was found to be distributed between 760 and 1950m AMSL, 30°10'159" to 33°04'693"N and 74°44'076" to 78°25'681"E. The non-hierarchical cluster analysis resulted in 12 clusters of genotypes. The cluster pattern did not exhibit any interrelation between geographical isolation and genetic diversity. Of the 170 genotypes, 31 fell in Cluster XII, 27 in Cluster V, 19 in Cluster I, 17 in Cluster IX, 16 in Cluster VIII, 15 in Cluster XI, 13 in Cluster II, 12 in Cluster VII, 10 in Cluster III, six in Cluster X, three in Cluster VI and one genotype in Cluster IV. Genotypes falling under Clusters III, VI , VI can be used as parents in hybridization programmes for improving important traits like TSS, fruit weight and acidity respectively

Layout design of user interface components with multiple objectives

A multi-goal layout problem may be formulated as a Quadratic Assignment model, considering multiple goals (or factors), both qualitative and quantitative in the objective function. The facilities layout problem, in general, varies from the location and layout of facilities in manufacturing plant to the location and layout of textual and graphical user interface components in the human–computer interface. In this paper, we propose two alternate mathematical approaches to the single-objective layout model. The first one presents a multi-goal user interface component layout problem, considering the distance-weighted sum of congruent objectives of closeness relationships and the interactions. The second one considers the distance-weighted sum of congruent objectives of normalized weighted closeness relationships and normalized weighted interactions. The results of first approach are compared with that of an existing single objective model for example task under consideration. Then, the results of first approach and second approach of the proposed model are compared for the example task under consideration

A Multi-Factor User Interface Components Layout Problem

This paper presents a multi-factor layout model which combines the qualitative and quantitative factors for the facilities layout problem.  The proposed model is applied to the design of the user interface in order to obtain the best layout of the facilities in which the closeness rating scores are evaluated by using the Goals, Operators, Methods, and Selection (GOMS) technique. The results of the proposed model are compared with that of an existing model to obtain the layouts of user interface components. The model developed here has significant relevance for facility layout design in achieving an optimal interface by structuring the layout of a building to enhance and support production. The user interface model provides support for quick response to changes in customer demand and inventory planning particularly in such an area where timely transfer of information is crucial

A Multi-Factor User Interface Components Layout Problem

This paper presents a multi-factor layout model which combines the qualitative and quantitative factors for the facilities layout problem.  The proposed model is applied to the design of the user interface in order to obtain the best layout of the facilities in which the closeness rating scores are evaluated by using the Goals, Operators, Methods, and Selection (GOMS) technique. The results of the proposed model are compared with that of an existing model to obtain the layouts of user interface components. The model developed here has significant relevance for facility layout design in achieving an optimal interface by structuring the layout of a building to enhance and support production. The user interface model provides support for quick response to changes in customer demand and inventory planning particularly in such an area where timely transfer of information is crucial