A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

A swarm intelligence method for feature tracking in AMV derivation

Feature tracking is a key step in the derivation of Atmospheric Motion Vectors (AMV). Most operational derivation processes use some template matching technique, such as Euclidean distance or cross-correlation, for the tracking step. As this step is very expensive computationally, often shortrange forecasts generated by Numerical Weather Prediction (NWP) systems are used to reduce the search area. Alternatives, such as optical flow methods, have been explored, with the aim of improving the number and quality of the vectors generated and the computational efficiency of the process. This paper will present the research carried out to apply Stochastic Diffusion Search, a generic search technique in the Swarm Intelligence family, to feature tracking in the context of AMV derivation. The method will be described, and we will present initial results, with Euclidean distance as reference.

Historical and current machine intelligence

In this article, we provide an initial insight into the study of MI and what it means for a machine to be intelligent. We discuss how MI has progressed to date and consider future scenarios in a realistic and logical way as much as possible. To do this, we unravel one of the major stumbling blocks to the study of MI, which is the field that has become widely known as "artificial intelligence"

From the buzzing in Turing’s head to machine intelligence contests

This paper presents an analysis of three major contests for machine intelligence. We conclude that a new era for Turing’s test requires a fillip in the guise of a committed sponsor, not unlike DARPA, funders of the successful 2007 Urban Challenge.

A specific group of genes respond to cold dehydration stress in cut Alstroemeria flowers whereas ambient dehydration stress accelerates developmental senescence expression patterns

Petal development and senescence entails a normally irreversible process. It starts with petal expansion and pigment production, and ends with nutrient remobilization and ultimately cell death. In many species this is accompanied by petal abscission. Post-harvest stress is an important factor in limiting petal longevity in cut flowers and accelerates some of the processes of senescence such as petal wilting and abscission. However, some of the effects of moderate stress in young flowers are reversible with appropriate treatments. Transcriptomic studies have shown that distinct gene sets are expressed during petal development and senescence. Despite this, the overlap in gene expression between developmental and stress-induced senescence in petals has not been fully investigated in any species. Here a custom-made cDNA microarray from Alstroemeria petals was used to investigate the overlap in gene expression between developmental changes (bud to first sign of senescence) and typical post-harvest stress treatments. Young flowers were stressed by cold or ambient temperatures without water followed by a recovery and rehydration period. Stressed flowers were still at the bud stage after stress treatments. Microarray analysis showed that ambient dehydration stress accelerates many of the changes in gene expression patterns that would normally occur during developmental senescence. However, a higher proportion of gene expression changes in response to cold stress were specific to this stimulus and not senescence related. The expression of 21 transcription factors was characterized, showing that overlapping sets of regulatory genes are activated during developmental senescence and by different stresses.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

Oxygen isotope composition of bivalve seasonal growth increments and ambient water in the rivers Rhine and Meuse

The application of oxygen isotope ratios ({delta}18O) from freshwater bivalves as a proxy for river discharge conditions in the Rhine and Meuse rivers is investigated. We compared a dataset of water temperature and water {delta}18O values with a selection of recent shell {delta}18O records for two species of the genus Unio in order to establish: (1) whether differences between the rivers in water {delta}18O values, reflecting river discharge conditions, are recorded in unionid shells; and (2) to what extent ecological parameters influence the accuracy of bivalve shell {delta}18O values as proxies of seasonal, water oxygen isotope conditions in these rivers. The results show that shells from the two rivers differ significantly in {delta}18O values, reflecting different source waters for these two rivers. The seasonal shell {delta}18O records show truncated sinusoidal patterns with narrow peaks and wide troughs, caused by temperature fractionation and winter growth cessation. Interannual growth rate reconstructions show an ontogenetic growth rate decrease. Growth lines in the shell often, but not always, coincide with winter growth cessations in the {delta}18O record, suggesting that growth cessations in the shell {delta}18O records are a better age estimator than counting internal growth lines. Seasonal predicted and measured {delta}18O values correspond well, supporting the hypothesis that these unionids precipitate their shells in oxygen isotopic equilibrium. This means that (sub-) fossil unionids can be used to reconstruct spring-summer river discharge conditions, such as Meuse low-discharge events caused by droughts and Rhine meltwater-influx events caused by melting of snow in the Alps.