STIGMERGY-BASED SYNCHRONIZATION OF A SEQUENCE OF TASKS IN A NETWORK OF ASYNCHRONOUS NODES

Social insects are able to build complex architectural structures in spite of their limited capabilities and simple behaviors. The coordination of various activities within a colony of such insects is performed stigmergically through indirect communication. This article describes a stigmergy-based technique by which a set of mobile agents trigger the execution of a sequence of tasks at every node in a network, in a near synchronous manner. These agents use a concept of an innate task-specific potential, which guides them to initiate the execution of a task at various asynchronously operating nodes of a network, in a synchronous manner. This innate potential maintained within the agent also assists in self-healing. The technique is oblivious to both the number of agents and nodes in the network and, hence, is scalable. The proposed technique was emulated on various real static and dynamic topologies by varying different parameters. The results obtained validate the efficacy of the concept of potential. An implementation using real robots has also been presented to portray the practical viability of the proposed technique.     

A Unified Approach to Detecting Spatial Outliers

Spatial outliers represent locations which are significantly different from their neighborhoods even though they may not be significantly different from the entire population. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and implicit knowledge, such as local instability. In this paper, we first provide a general definition of S-outliers for spatial outliers. This definition subsumes the traditional definitions of spatial outliers. Second, we characterize the computation structure of spatial outlier detection methods and present scalable algorithms. Third, we provide a cost model of the proposed algorithms. Finally, we experimentally evaluate our algorithms using a Minneapolis-St. Paul (Twin Cities) traffic data set.     

Photopolymerization of Methyl Methacrylate Sensitized by Tris(2,2′-bipyridine)iron(III)

The photopolymerization of methyl methacrylate (MMA) sensitized by tris(2,2′-bipyridine)iron(III ) complex, [Fe(bpy)₃]³⁺, was studied at 35°C in the presence of an electron donor, triethylamine (TEA) with UV radiation of wavelength 254nm. The initial rate of polymerization, R_p, shows a linear dependence on [MMA] with an exponential value of 1·18±0·04. R_p varies linearly with the square root of the photosensitizer concentration up to 2·00×10^-4moll^-1, and above this concentration, R_p decreases with the increase of photosensitizer concentration. The rate of polymerization is not affected by the concentration of the co-initiator, [TEA]. A suitable mechanism for the reaction is proposed to explain the kinetics of the reaction. © 1997 SCI.     

Methods for detection of Clostridium botulinum toxin in foods

Botulism is a deadly disease caused by ingestion of the preformed neurotoxin produced from the anaerobic spore-forming bacteria Clostridium botulinum. Botulinum neurotoxins are the most poisonous toxins known and have been a concern in the food industry for a long time. Therefore, rapid identification of botulinum neurotoxin using molecular and biochemical techniques is an essential component in the establishment of coordinated laboratory response systems and is the focus of current research and development. Because of the extreme toxicity of botulinum neurotoxin, some confirmatory testing with the mouse bioassay is still necessary, but rapid methods capable of screening large numbers of samples are also needed. This review is focused on the development of several detection methods for botulinum neurotoxins in foods.     

TAPER: a two-step approach for all-strong-pairs correlation query in large databases

Given a user-specified minimum correlation threshold /spl theta/ and a market-basket database with N items and T transactions, an all-strong-pairs correlation query finds all item pairs with correlations above the threshold /spl theta/. However, when the number of items and transactions are large, the computation cost of this query can be very high. The goal of this paper is to provide computationally efficient algorithms to answer the all-strong-pairs correlation query. Indeed, we identify an upper bound of Pearson's correlation coefficient for binary variables. This upper bound is not only much cheaper to compute than Pearson's correlation coefficient, but also exhibits special monotone properties which allow pruning of many item pairs even without computing their upper bounds. A two-step all-strong-pairs correlation query (TAPER) algorithm is proposed to exploit these properties in a filter-and-refine manner. Furthermore, we provide an algebraic cost model which shows that the computation savings from pruning is independent of or improves when the number of items is increased in data sets with Zipf-like or linear rank-support distributions. Experimental results from synthetic and real-world data sets exhibit similar trends and show that the TAPER algorithm can be an order of magnitude faster than brute-force alternatives. Finally, we demonstrate that the algorithmic ideas developed in the TAPER algorithm can be extended to efficiently compute negative correlation and uncentered Pearson's correlation coefficient.     

Synthesis of Y-Ba-Cu-O thin films by an electrodeposition technique

Superconducting thin films of Y-Ba-Cu-O have been synthesized on silver coated copper foils. Precursor films of Y-Ba-Cu were deposited potentiostatically, then heat treated in O₂/air. Energy dispersive X-ray analysis and X-ray diffraction were conducted to characterize the thin film deposits. The onset critical temperature of the superconducting films was found to be around 75 to 91 K, depending upon the processing conditions. This paper describes the experimental procedures and results obtained from preliminary experiments.     

A second-order model for catalytic-transfer hydrogenation of edible oils

A second-order kinetic model for hydrogenation of fatty acids in series has been developed and analyzed. The model is applied to the data obtained for sodium formatecatalyzed hydrogenation of soybean, peanut, corn, and olive oils. There is good agreement between the experimental data and predicted values obtained from the model as evidenced by the analysis of r ² and F-test values. The effect of individual fatty acid composition of various edible oils on the rate of hydrogenation has been explained in view of the mathematical model developed. The individual rate constants seem to obey the Arrhenius rate law. The second-order kinetic analysis discussed is found to be suitable for mathematically describing hydrogenation of vegetable oils by hydrogen donors as compared to the traditional first-order kinetic analysis