On solving discrete optimization problems with one random element under general regret functions

In this paper we consider the class of stochastic discrete optimization problems in which the feasibility of a solution does not depend on the particular values the random elements in the problem take. Given a regret function, we introduce the concept of the risk associated with a solution, and define an optimal solution as one having the least possible risk. We show that for discrete optimization problems with one random element and with min-sum objective functions a least risk solution for the stochastic problem can be obtained by solving a non-stochastic counterpart where the latter is constructed by replacing the random element of the former with a suitable parameter. We show that the above surrogate is the mean if the stochastic problem has only one symmetrically distributed random element. We obtain bounds for this parameter for certain classes of asymmetric distributions and study the limiting behavior of this parameter in details under two asymptotic frameworks. \u

On solving discrete optimization problems with multiple random elements under general regret functions

In this paper we attempt to find least risk solutions for stochastic discrete optimization problems (SDOP) with multiple random elements, where the feasibility of a solution does not depend on the particular values the random elements in the problem take. While the optimal solution, for a linear regret function, can be obtained by solving an auxiliary (non-stochastic) discrete optimization problem (DOP), the situation is complex under general regret. We characterize a finite number of solutions which will include the optimal solution. We establish through various examples that the results from Ghosh, Mandal and Das (2005) can be extended only partially for SDOPs with additional characteristics. We present a result where in selected cases, a complex SDOP may be decomposed into simpler ones facilitating the job of finding an optimal solution to the complex problem. We also propose numerical local search algorithms for obtaining an optimal solution. \u

Location change in marginal distributions of linear functions of random vectors

AbstractSuppose X and Y are n × 1 random vectors such that l′X + f(l) and l′Y have the same marginal distribution for all n × 1 real vectors l and some real valued function f(l), and the existence of expectations of X and Y is not necessary. Under these conditions it is proven that there exists a vector M such that f(l) = l′M and X + M and Y have the same joint distribution. This result is extended to Banach-space valued random vectors

Indexing human development in India : Indicators, scaling and composition

The paper analyses methodological issues concerning selection of indicators, making them scale-free and construction of composite indices within the framework of measuring human development. It reviews the existing literature in the area and highlights the key areas of concern from the viewpoint of methodology of aggregation. It discusses the implications of the assumptions underlying different techniques, currently being used in India, in the context of an empirical exercise of constructing an index of human development at state level. It examines the advantages and disadvantages of these techniques and proposes improvements therein for bringing them closer to empirical reality and thereby increasing their acceptability among the planners and policy-makers. The study suggests that exercises at determining the levels of human development at the state or district level by official agencies like the Planning Commission, concerned ministries or an international agency must enjoy large acceptability so that these can be used in policy-making. Agreements must be obtained in terms of choice of indicators, scaling, methodology of composition, etc. Establishing certain degree of uniformity in methodology through deliberations in a committee at the highest level (as was done in case of measuring poverty) will accord credence to the results and help clear the uncertainty and inconclusiveness that characterise the current debate.Human DevelopmentHuman Development Index

Mass breeding of silver carp in a cement cistern with crude H.C.G.

The paper presents a resume on experiments carried on mass breeding of the silver carp Hypophthalmichthys molitrix in a cement cistern through administration of crude human chorionic gonadotropin. The experiments proves that human chorionic gonadotropin (H.C.G.) can be used for mass breeding of the fish in simple enclosures, with facilities of some input and output of water and a dose of 5 mg/kg and 18 mg/kg of body weight, for males and females respectively are required for the purpose. Observations were made by using pituitary glands in similar way. For successful breeding of about 80 kg female together, the expenditure towards cost of pituitary gland and H.C.G. are respectively 275 and 117 Rs

Early and better maturity in carp brood stock with control of environment and feeding

Available of carp breeders in their prim state of maturity is a major constraint in hypophysation. Experiments conducted in a fish farm at Naihati, West Bengal, for two consecutive years, 1983-84 and 1984-85, clearly prove that by manipulation of environmental parameters such as metabolites, dissolved oxygen, running water conditions, as also of stock densities and quality and quantity of feed. Catla catla, Hypophythalmichthys molitrix, Labeo rohita, Cirrhina mrigala and Ctenopharyngodon idella can be made to attain better maturity and spawning stage much earlier than normal i.e. even in summer months and the entire stock spawned during the period from March to September. Percentage of successful breeding, quantities of eggs released and fertilised in relation to the body weight of all the species, were also found to be more in comparison to the brood stock raised through the conventional methods

A 60nm CMOS, 3rd and 5th Order Low Pass Filter with Higher Cut-off Frequency

The design of CMOS based low pass filter for analog-to-digital, digital-to-analog and audio applications is described in this paper. Active load resistor and floating inductor is used for the implementation of low pass filter. CMOS technology has become dominant over bipolar technology for analog circuits design in mixed signal system. The differential floating active inductor is designed with CMOS and current sources. The floating inductor may be electronically tuned by varying external bias voltage as well as current. The simulations are obtained by using 65nm CMOS technology on Tanner EDA tool 13.0. The filters are synthesized from 3rd and 5th order low-pass LC prototype and designed using ladder structure. Keywords: Complementary Metal Oxide Semiconductor (CMOS), low pass filter (LPF), active resistor, Power delay product (PDP)

A Fuzzy-based approach to Enhance Cyber Defence Security for Next-generation IoT

In the modern era, the Cognitive Internet of Things (CIoT) in conjunction with IoT evolves which provides the intelligence power of sensing and computation for next-generation IoT (Nx-IoT) networks. The data scientists have discovered a large amount of techniques for knowledge discovery from processed data in CIoT. This task is accomplished successfully and data proceeds for further processing. The major cause for the failure of IoT devices is due to the attacks, in which Web spam is more prominent. There seems a requirement of a technique which can detect the Web spam before it enters into a device. Motivated from these issues, in this article, a cognitive spammer framework (CSF) for Web spam detection is proposed. CSF detects the Web spam by fuzzy rule-based classifiers along with machine learning classifiers. Each classifier produces the quality score of the webpage. These quality scores are then ensembled to generate a single score, which predicts the spamicity of the webpage. For ensembling, the fuzzy voting approach is used in CSF. The experiments were performed using a standard data set WEBSPAM-UK 2007 with respect to accuracy and overhead generated. From the results obtained, it has been demonstrated that CSF improves the accuracy by 97.3%, which is comparatively high in comparison to the other existing approaches in the literature

Modeling and optimal control of dengue disease with screening and information

This study presents a mathematical model for dengue transmission which quantifies two very important aspects: one, the impact of information-based behavioural response, and the other, the segregation of infected human population into two subclasses, ‘detected’ and ‘undetected’. For the proposed model, the sensitivity analysis is conducted to identify the key model parameters which not only influence the basic reproduction number, but also regulate the transmission of dengue. Further, in order to find the optimal pathways for suitable control interventions that reduce the dengue prevalence and economic burden, an optimal control problem is proposed by considering information-induced behavioural change, quarantine, screening, use of repulsive measures and culling of mosquitoes as control interventions. A weighted sum of various costs incurred in applied controls and the cost due to dengue disease (productivity loss) is incorporated in the proposed cost functional. The analysis of control system using Pontryagin’s maximum principle leads the existence of the optimal control profiles. Further, an exhaustive comparative study for seven different control strategies is conducted numerically. Our findings emphasize that every individual control strategy has their own impact on reducing the cumulative count of infection as well as cost. The combined impact of all control interventions is highly effective and economically viable in controlling the prevalence of dengue. We also investigated the effect of the basic reproduction number on the designed control strategies and observed that the comprehensive use of controls keeps a strong tab on the infective even if the severity of epidemic is high

The Costs of Ecosystem Adaptation: Methodology and Estimates for Indian Forests

34 p.This paper presents a detailed methodology for estimating the cost of adaptation to climate change impacts on ecosystems. Up to date estimates are built-up following national investments in measures such as protected areas, with inaccurate estimates of the adaptation level needed. Here we propose a new methodology which identifies vulnerable areas due to climate impacts and the specific adaptation options feasible for these regions. An illustration of the methodology for shifts in forest ecosystems in India is presented. Advantages and future requirements for this methodology are finally discussed