An intelligent information infrastructure to support the streamlining of integrated logistics workflow

Abstract: In today's competitive environment, rapid advances in economic globalization and information technology have forced many organizations to anticipate and respond to increasing volatility and competitive pressures. Numerous researches have focused on developing techniques on the analysis, design and management of whole logistics chains in particular in the domain of data mining, data analysis and data classification. While the data mining techniques and computational intelligence techniques are good independently for solving specific tasks, they can be synergized through the formation of an integrated and unified model, which can take advantage of the goods and offset the flaws of the two techniques. In this paper, an intelligent information infrastructure, which is characterized by its ability to encompass a rich collection of knowledge representation formalisms for dealing with a logistics information flow problem, is presented. Such intelligent information infrastructure includes a two‐step strategy that embraces the combination of online analytical processing and neural networks to support knowledge discovery. In addition, extensible markup language is used to support the overall infrastructure, in order to facilitate the seamless data interchange within an enterprise.     

Patterns of growth in verbal abilities among children with autism spectrum disorder.

Verbal skills were assessed at approximately ages 2, 3, 5, and 9 years for 206 children with a clinical diagnosis of autism (n = 98), pervasive developmental disorders-not otherwise specified (PDD-NOS; n = 58), or nonspectrum developmental disabilities (n = 50). Growth curve analyses were used to analyze verbal skills trajectories over time. Nonverbal IQ and joint attention emerged as strong positive predictors of verbal outcome. The gap between the autism and other 2 groups widened with time as the latter improved at a higher rate. However, there was considerable variability within diagnostic groups. Children with autism most at risk for more serious language impairments later in life can be identified with considerable accuracy at a very young age, while improvement can range from minimal to dramatic. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ticket Servers for Network Traffic Prioritization

For broadband packet networks to be widely useful to society, they must dynamically recognize some network flows, like those that deal with disaster response, military operations, or emergencies as having greater importance than others. This paper proposes an architecture of geographically distributed ticket servers that issue importance tickets that indicate the priority that a flow should be given in the current dynamic network context. Any type of user or flow can be given priority, depending on the user needs and the context. User agents contact ticket servers using an agent communication language; then a ticket server intelligent agent determines how valuable of a ticket to issue. Use of ticket servers and agent communication enables quick adaptation to dynamic context changes and provides user feedback so that high priority communication activities can be conducted effectively.     

Glycoproteins present in human follicular fluid that inhibit the zona-binding capacity of spermatozoa

Previous studies have suggested that human follicular fluid contains factors that reduce the zona-binding capacity of spermatozoa. The present study provides further evidence of the existence of such factors. Using the hemizona binding assay (HZA), we have shown that the inhibitory effect of human follicular fluid on the zona-binding capacity of spermatozoa is concentration-dependent, an inhibitory effect being detected when the concentration of human follicular fluid was > or = 10%. A 1% concentration of human follicular fluid did not possess this inhibitory activity. Heating human follicular fluid at 56 degrees C for 30 min did not affect its inhibitory properties; treatment with proteinase-K abolished such inhibition. Human follicular fluid was fractionated sequentially by concanavalin-A affinity chromatography, Mono Q ion-exchange chromatography and Superose-12 gel filtration. The zona binding inhibitory activity resided in the fraction which bound to the lectin and Mono Q column and contained molecules with native molecular weights of 32 and 192 kDa. Sodium dodecyl sulphate-polyacrylamide gel electrophoresis analysis suggested that the 192 kDa glycoprotein was a tetramer, while the 32 kDa glycoprotein remained as a single molecular species under denaturing conditions. We conclude that two glycoproteins were responsible for the zona binding inhibitory activity of human follicular fluid. The physiological role of these factors remains unclear.     

Fast conditioning algorithm for significant zero curvaturedetection

Zero curvature points are commonly used as features in machine vision. Traditional approaches to zero curvature detection rely heavily on discrete curvature estimation done in scale-space, which is costly to compute. The authors report their work on achieving a quick approximation by using conditioning. The algorithm is efficient and the zero curvature points detected are stable across scales. Usually these detected locations of zero curvatures are used for initialising the coarse-to-fine matching process for object recognition. Hence, the tradeoff between their accuracy and runtime efficiency must be balanced     

A Comparative Study of Three Mapping Methodologies

Map building is one of the core competencies of truly autonomous robots. Numerous techniques have been developed to represent the static and dynamic environments as well as the perceptional sensing frameworks so far. In this paper, on the basis of our previous work, we compare various sensor systems in building the static and dynamic environment map with the segment-based map and Fuzzy-Tuned Grid-Based Map (FTGBM) strategies. From the comparative results of experiments, we propose a probably efficient and trade-off framework which balances the accuracy of the map against the overall system cost.     

Signatures of Incoherence in a Quantum Information Processor

Incoherent noise is manifest in measurements of expectation values when the underlying ensemble evolves under a classical distribution of unitary processes. While many incoherent processes appear decoherent, there are important differences. The distribution functions underlying incoherent processes are either static or slowly varying with respect to control operations and so the errors introduced by these distributions are refocusable. The observation and control of incoherence in small Hilbert spaces is well known. Here we explore incoherence during an entangling operation, such as is relevant in quantum information processing. As expected, it is more difficult to separate incoherence and decoherence over such processes. However, by studying the fidelity decay under a cyclic entangling map we are able to identify distinctive experimental signatures of incoherence. This is demonstrated both through numerical simulations and experimentally in a three qubit nuclear magnetic resonance implementation.