Synthesis of Azo Coupled Crown Ethers Containing Transition Metal and other Chromophoric Environments and Their Ion Complexation Properties

The crown ethers, 2,3-benzo-1,4,7,10,13-pentaoxa-cyclopentadeca-2-ene and 2,3, ll,12-dibenzo-l,4,7,10,13,16-hexaoxscyclooctadeca-2,11-diene are incorporated into H,N'-ethylenebis(acetylacetoneimino) nickel(II) and copper(II), phenol, and β-naphthol by diazo coupling reactions. The selective nature of the coupling reaction has-been demonstrated by the isolation of both asymmetric mono- and symmetric bis(glyoxalarylcrownhydrazoneimino) metal(II) complexes. An interesting binuclear complex containing two intramolecularly rearranged (glyoxal-hydrazonearylimino) metal(II) groups joined by 18-crown-6 result8 when bis(arenediazonium)-18-crown-6 is coupled with the metal(I1) Schiff bases. The substituted ethers form cationic salts with NaClO4, KCNS, NH4CNS, 14g(CNS)2 and Ca(CNS)2. All the synthesised ethers exhibit ion selectivity sequence as K+ > Na+ and Ca2+ > Mg2+.

Synthesis of Azo Coupled Crown Ethers Containing Transition Metal and other Chromophoric Environments and Their Ion Complexation Properties

The crown ethers, 2,3-benzo-1,4,7,10,13-pentaoxa-cyclopentadeca-2-ene and 2,3, ll,12-dibenzo-l,4,7,10,13,16-hexaoxscyclooctadeca-2,11-diene are incorporated into H,N'-ethylenebis(acetylacetoneimino) nickel(II) and copper(II), phenol, and β-naphthol by diazo coupling reactions. The selective nature of the coupling reaction has-been demonstrated by the isolation of both asymmetric mono- and symmetric bis(glyoxalarylcrownhydrazoneimino) metal(II) complexes. An interesting binuclear complex containing two intramolecularly rearranged (glyoxal-hydrazonearylimino) metal(II) groups joined by 18-crown-6 result8 when bis(arenediazonium)-18-crown-6 is coupled with the metal(I1) Schiff bases. The substituted ethers form cationic salts with NaClO4, KCNS, NH4CNS, 14g(CNS)2 and Ca(CNS)2. All the synthesised ethers exhibit ion selectivity sequence as K+ > Na+ and Ca2+ > Mg2+.

The Consequences of Phenotypic Plasticity in Cyclically Varying Environments: A Genetic Algorithm Study

By “phenotypic plasticity” we refer to the capacity of a genotype to exhibit different phenotypes, whether in the same or in different environments. We have previously demonstrated that phenotypic plasticity can improve the degree of adaptation achieved via natural selection (Behera & Nanjundiah, 1995). That result was obtained from a genetic algorithm model of haploid genotypes (idealized as one-dimensional strings of genes) evolving in a fixed environment. Here, the dynamics of evolution is examined under conditions of a cyclically varying environment. We find that the rate of evolution, as well as the extent of adaptation (as measured by mean population fitness) is lowered because of environmental cycling. The decrease is adaptation caused by a varying environment can, however, be partly or wholly compensated by an increase in the degree of plasticity that a genotype is capable of. Also, the reduction of population fitness caused by a variable environment can be partially offset by decreasing the total number of genetic loci. We conjecture that an increase in genome size may have been among the factors responsible for the evolution of phenotypic plasticity.

Frontier Based Multiple Goal Search in Unknown Environments

We present a frontier based algorithm for searching multiple goals in a fully unknown environment, with only information about the regions where the goals are most likely to be located. Our algorithm chooses an ``active goal'' from the ``active goal list'' generated by running a Traveling Salesman Problem (Tsp) routine with the given centroid locations of the goal regions. We use the concept of ``goal switching'' which helps not only in reaching more number of goals in given time, but also prevents unnecessary search around the goals that are not accessible (surrounded by walls). The simulation study shows that our algorithm outperforms Multi-Heuristic LRTA* (MELRTA*) which is a significant representative of multiple goal search approaches in an unknown environment, especially in environments with wall like obstacles.

Goal Seeking for Robots in Unknown Environments

We consider the problem of goal seeking by robots in unknown environments. We present a frontier based algorithm for finding a route to a goal in a fully unknown environment, where information about the goal region (GR), the region where the goal is most likely to be located, is available. Our algorithm efficiently chooses the best candidate frontier cell, which is on the boundary between explored space and unexplored space, having the maximum ``goal seeking index'', to reach the goal in minimal number of moves. Modification of the algorithm is also proposed to further reduce the number of moves toward the goal. The algorithm has been tested extensively in simulation runs and results demonstrate that the algorithm effectively directs the robot to the goal and completes the search task in minimal number of moves in bounded as well as unbounded environments. The algorithm is shown to perform as well as a state of the art agent centered search algorithm RTAA*, in cluttered environments if exact location of the goal is known at the beginning of the mission and is shown to perform better in uncluttered environments.

Context based service discovery for ubiquitous applications

Service discovery is vital in ubiquitous applications, where a large number of devices and software components collaborate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrounding environment can be used to improve the quality of service matching. To make use of context information in service matching, a service discovery technique needs to address certain challenges. Firstly, it is required that the context information shall have unambiguous representation. Secondly, the devices in the environment shall be able to disseminate high level and low level context information seamlessly in the different networks. And thirdly, dynamic nature of the context information be taken into account. We propose a C-IOB(Context-Information, Observation and Belief) based service discovery model which deals with the above challenges by processing the context information and by formulating the beliefs based on the observations. With these formulated beliefs the required services will be provided to the users. The method has been tested with a typical ubiquitous museum guide application over different cases. The simulation results are time efficient and quite encouraging.

An Effective Seamless Connectivity Scheme for Ubiquitous Applications

The idea of ubiquity and seamless connectivity in networks is gaining more importance in recent times because of the emergence of mobile devices with added capabilities like multiple interfaces and more processing abilities. The success of ubiquitous applications depends on how effectively the user is provided with seamless connectivity. In a ubiquitous application, seamless connectivity encompasses the smooth migration of a user between networks and providing him/her with context based information automatically at all times. In this work, we propose a seamless connectivity scheme in the true sense of ubiquitous networks by providing smooth migration to a user along with providing information based on his/her contexts automatically without re-registration with the foreign network. The scheme uses Ubi-SubSystems(USS) and Soft-Switches(SS) for maintaining the ubiquitous application resources and the users. The scheme has been tested by considering the ubiquitous touring system with several sets of tourist spots and users.

Performance Modeling based on Multidimensional Surface Learning for Performance Predictions of Parallel Applications in Non-Dedicated Environments

Modeling the performance behavior of parallel applications to predict the execution times of the applications for larger problem sizes and number of processors has been an active area of research for several years. The existing curve fitting strategies for performance modeling utilize data from experiments that are conducted under uniform loading conditions. Hence the accuracy of these models degrade when the load conditions on the machines and network change. In this paper, we analyze a curve fitting model that attempts to predict execution times for any load conditions that may exist on the systems during application execution. Based on the experiments conducted with the model for a parallel eigenvalue problem, we propose a multi-dimensional curve-fitting model based on rational polynomials for performance predictions of parallel applications in non-dedicated environments. We used the rational polynomial based model to predict execution times for 2 other parallel applications on systems with large load dynamics. In all the cases, the model gave good predictions of execution times with average percentage prediction errors of less than 20%

Generalization of the collision cone approach for motion safety in 3-D environments

Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies.