Dwijesh Dutta Majumder

Fuzzy mean-variance-skewness portfolio selection models by interval analysis

In portfolio selection problem, the expected return, risk, liquidity etc. cannot be predicted precisely. The investor generally makes his portfolio decision according to his experience and his economic wisdom. So, deterministic portfolio selection is not a good choice for the investor. In most of the recent works on this problem, fuzzy set theory is widely used to model the problem in uncertain environments. This paper utilizes the concept of interval numbers in fuzzy set theory to extend the classical mean-variance (MV) portfolio selection model into mean-variance-skewness (MVS) model with consideration of transaction cost. In addition, some other criteria like short and long term returns, liquidity, dividends, number of assets in the portfolio and the maximum and minimum allowable capital invested in stocks of any selected company are considered. Three different models have been proposed by defining the future financial market optimistically, pessimistically and in the combined form to model the fuzzy MVS portfolio selection problem. In order to solve the models, fuzzy simulation (FS) and elitist genetic algorithm (EGA) are integrated to produce a more powerful and effective hybrid intelligence algorithm (HIA). Finally, our approaches are tested on a set of stock data from Bombay Stock Exchange (BSE).

On edge and line linking with connectionist models

In this paper two connectionist models for mid-level vision problems, namely, edge and line linking, have been presented. The processing elements (PE) are arranged in the form of two-dimensional lattice in both the models. The models take the strengths and the corresponding directions of the fragmented edges (or lines) as the input. The state of each processing element is updated by the activations received from the neighboring processing elements. In one model, each neuron interacts with its eight neighbors, while in the other model, each neuron interacts over a larger neighborhood. After convergence, the output of the neurons represent the linked edge (or line) segments in the image. The first model directly produces the linked line segments, while the second model produces a diffused edge cover. The linked edge segments are found by finding out the spine of the diffused edge cover. The experimental results and the proof of convergence of the network models have also been provided. >

A connectionist model for category perception: theory and implementation

A connectionist model for learning and recognizing objects (or object classes) is presented. The learning and recognition system uses confidence values for the presence of a feature. The network can recognize multiple objects simultaneously when the corresponding overlapped feature train is presented at the input. An error function is defined, and it is minimized for obtaining the optimal set of object classes. The model is capable of learning each individual object in the supervised mode. The theory of learning is developed based on some probabilistic measures. Experimental results are presented. The model can be applied for the detection of multiple objects occluding each other.

Fuzzy differential inclusions in atmospheric and medical cybernetics

Uncertainty management in dynamical systems is receiving attention in artificial intelligence, particularly in the fields of qualitative and model based reasoning. Fuzzy dynamical systems occupy a very important position in the class of uncertain systems. It is well established that the fuzzy dynamical systems represented by a set of fuzzy differential inclusions (FDI) are very convenient tools for modeling and simulation of various uncertain systems. In this paper, we discuss about the mathematical modeling of two very complex natural phenomena by means of FDIs. One of them belongs to the atmospheric cybernetics (the term has been used in a broad sense) of the genesis of a cyclonic storm (cyclogenesis), and the other belongs to the bio-medical cybernetics of the evolution of tumor in a human body. Since a discussion of the former already appears in a previous paper by the first author, here, we present very briefly a theoretical formalism of cyclone formation. On the other hand, we treat the latter system more elaborately. We solve the FDIs with the help of an algorithm developed in this paper to numerically simulate the mathematical models. From the simulation results thus obtained, we have drawn a number of interesting conclusions, which have been verified, and this vindicates the validity of our models.

Facilitation of functional compartmentalization of bone marrow cells in leukemic mice by biological response modifiers: an immunotherapeutic approach

Biological Response Modifiers (BRMs) including interleukin-2 (IL-2), interferon-gamma (IFN-gamma) and sheep erythrocytes (SRBC) protected N,N-ethylnitrosourea (ENU) induced leukaemic mice. Two cell types from the bone marrow were isolated in density specific gradient representing two distinct compartments, the low density cells being more CD34 positive than the high density group. Investigations with the functional efficacy of such compartments revealed significant improvement of cytotoxic efficacy and phagocytic burst at the high density compartment (HDC) level. The high density compartment was found to be more responsive towards the BRMs compared to the cells of the low density compartment (LDC). It was suggested that use of BRMs in vivo can stimulate a potent functional progenitor compartmentalization in normal as well as leukaemic mice. These observations are expected to help a logistic approach towards combined BRM therapy at the clinical level.

Nano-materials: Science of bottom-up and top-down

Abstract The most frequently used high tech words in the scientific world now are Computer, gene and nanometer. On 29 December 1959, Richard P Feynman [1] gave a talk at the annual meeting of the American Physical society that hasbecome one of the twentieth century’s classic science lectures titled “There is Plenty of Room at the Bottom”. He presented a technological vision of the miniaturization of materials, manipulating and controlling things on asmall scale called “Nanotechnology”. Feynman visualized a technology using a toolbox of nature to build nano-object by atom by atom or molecule by molecule. Taking into account of the future potential of nanoscience, National Science and Technology Council (NSTC) of the White House created the interagency working group on Nanoscience,Engineering and Technology (IWGN) in 1998. A grant of

Nano-fabricated materials in cancer treatment and agri-biotech applications: Buckyballs in quantum holy grails

497 million was granted to National Nanotechnology Institute (NNI) in the year 2001 and made it a top science and technology priority. Scientists are already developing nano-applications that will be bringing revolution in a host of products and services like battery storage capacity, computer chip minimization, drug delivery, facial creams, food processing, agricultural insect control, solar energy management and water purification. The United States have decided to spend US

Feature selection and gene clustering from gene expression data

3.7 billion during 2005–2008 and have spent almost US

Mean-Entropy-Skewness Fuzzy Portfolio Selection by Credibility Theory Approach

3 billion during 2002–2005. The European Union will spend US

Methods of Evaluation and Extraction of Membership Functions--Review with a New Approach

1.7 billion and the figures for other countries are - Japan (US