Intelligent system for time series classification using support vector machines applied to supply-chain

To be able of anticipate demand is a key factor for commercial success in the supply-chain sector. The benefits can be grouped around two main concepts: firstly the optimization of operations through the development of optimal strategies for procurement and secondly the stock reduction that reduces storage costs, handling, etc. There is currently a variety of methods for making predictions, these methods vary from pure statistical methods such as exponential smoothing Holt-Winters or ARIMA models, to those based on artificial intelligence techniques like neural networks or fuzzy systems. However, despite being able to build accurate models, in managing the supply chain based on forecasts there is a problem known as “Forrester effect” irrespective of the model chosen. To monitor the impact of this effect, given the volume of information handled in large corporations, is a very expensive task (often manual) for such corporations because it requires investigating issues such as the adequacy of the model, allocation of known models to the sales time series, discovery of new patterns of behavior, etc. This article proposes an intelligent system based on support vector machines to solve problems concerning the allocation and discovery of new models. With this focus in mind, the system objective is to build groups of time series that share the same forecasting model. For the identification of new models, the system will assign “virtual models” for those groups that do not have a predefined pattern. Using the proposed method, it has been possible to group a sample of more than 14,000 time series (real data taken from a store) in around 70 categories, of which only 12 of them already grouped over 98% of the total.     

Cell formation in group technology using constraint programming and Boolean satisfiability

Cell formation consists in organizing a plant as a set of cells, each of them containing machines that process similar types or families of parts. The idea is to minimize the part flow among cells in order to reduce costs and increase productivity. The literature presents different approaches devoted to solve this problem, which are mainly based on mathematical programming and on evolutionary computing. Mathematical programming can guarantee a global optimal solution, however at a higher computational cost than an evolutionary algorithm, which can assure a good enough optimum in a fixed amount of time. In this paper, we model and solve this problem by using state-of-the-art constraint programming (CP) techniques and Boolean satisfiability (SAT) technology. We present different experimental results that demonstrate the efficiency of the proposed optimization models. Indeed, CP and SAT implementations are able to reach the global optima in all tested instances and in competitive runtime.     

Atomic broadcast in asynchronous crash-recovery distributed systems and its use in quorum-based replication

Atomic broadcast is a fundamental problem of distributed systems: It states that messages must be delivered in the same order to their destination processes. This paper describes a solution to this problem in asynchronous distributed systems in which processes can crash and recover. A consensus-based solution to atomic broadcast problem has been designed by Chandra and Toueg for asynchronous distributed systems where crashed processes do not recover. We extend this approach: it transforms any consensus protocol suited to the crash-recovery model into an atomic broadcast protocol suited to the same model. We show that atomic broadcast can be implemented requiring few additional log operations in excess of those required by the consensus. The paper also discusses how additional log operations can improve the protocol in terms of faster recovery and better throughput. To illustrate the use of the protocol, the paper also describes a solution to the replica management problem in asynchronous distributed systems in which processes can crash and recover. The proposed technique makes a bridge between established results on weighted voting and recent results on the consensus problem.     

Retailers' tagging practices: a potential liability?

This study investigates the coverage of federally mandated information on over‐the‐counter (OTC) drug labels by electronic article surveillance (EAS) tags applied to the exterior of cartons. Using adult‐strength analgesics containing acetaminophen as a case study, researchers investigated the issue in Houston, Texas (24 stores) and Lansing, Michigan (33 stores). The information obscured by EAS tags was identified and classified for a total of 849 packages using a standardized data collection instrument. The results indicated that 293 packages examined, or 34.5%, had information mandated by the US Food and Drug Administration (US FDA) fully or partially obscured by the EAS tags. Retailers and manufacturers should be aware of such practices to reduce potential liability. Recommendations for improving EAS tag usage on OTC products are presented. Copyright © 2004 John Wiley & Sons, Ltd.     

Propane heat pump with low refrigerant charge: design and laboratory tests

Independently of the choice of refrigerant, environmental and or safety issues can be minimised by reducing the amount of refrigerant charge per heat pump or refrigeration system. In the investigation reported here, a laboratory test rig was built, simulating a water-to-water heat pump with a heating capacity of 5 kW. The system was designed to minimize the charge of refrigerant mainly by use of mini-channel aluminium heat exchangers. It was shown that the system could be run with 200 g of propane at typical Swedish operating conditions without reduction of the COP compared to a traditional design. Additional charge reduction is possible by selecting proper compressor lubrication oils or by using a compressor with less lubrication oil.     

The ontological screening of contemporary life: a phenomenological analysis of screens

In this paper, we attempt to show how phenomenology, in a traditional methodological form, can provide an interesting and novel basis for thinking about screens in a world where screens now pervade a great many aspects of human experience. In our analysis, we aim to give a phenomenological account of screen(ing), that is, of its fundamental and foundational meaning. In doing the phenomenological analysis, we ground our argument on the ontology of Heidegger's Being and Time. In doing this, we claim that the screen will only show itself, as that which it is, as a screen in-the-world, where screens already are or have their being ‘as screens’ for this and that purpose, activity or work. We claim, and aim to show, that our analysis provides many insights about the meaning of screens that would be difficult to gain through any other method of investigation. We also argue and show that, although our method is not empirical, its results have important implications for the empirical world.     

DESIGN OF REDUCED‐ORDER FUNCTIONAL OBSERVERS FOR LINEAR SYSTEMS WITH UNKNOWN INPUTS

This brief paper presents new conditions for the existence and design of reduced‐order linear functional state observers for linear systems with unknown inputs. Systematic procedures for the synthesis of reduced‐order functional observers are given. Numerical examples are given to illustrate the attractiveness and simplicity of the new design procedures.     

Nano-scale Au supported on Fe3O4: characterization and application in the catalytic treatment of 2,4-dichlorophenol

Catalytic hydrodechlorination (HDC) is an effective means of detoxifying chlorinated waste. Gold nanoparticles supported on Fe(3)O(4) have been tested in the gas phase (1 atm, 423 K) HDC of 2,4-dichlorophenol. Two 1% w/w supported gold catalysts have been prepared by: (i) stepwise deposition of Au on α-Fe(2)O(3) with subsequent temperature-programmed reduction at 673 K (Au/Fe(3)O(4)-step); (ii) direct deposition of Au on Fe(3)O(4) (Au/Fe(3)O(4)-dir). TEM analysis has established the presence of Au at the nano-scale with a greater mean diameter (7.6 nm) on Au/Fe(3)O(4)-dir relative to Au/Fe(3)O(4)-step (4.5 nm). We account for this difference in terms of stronger (electrostatic) precursor/support interactions in the latter that can be associated with the lower pH point of zero charge (with respect to the final deposition pH) for Fe(2)O(3). Both catalysts promoted the preferential removal of the ortho-Cl substituent in 2,4-dichlorophenol, generating 4-chlorophenol and phenol as products of partial and total HDC, respectively, where Au/Fe(3)O(4)-step delivered a two-fold higher rate (2 × 10(-4) mol(Cl) h(-1) m(Au)(-2)) when compared with Au/Fe(3)O(4)-dir. This unprecedented selectivity response is attributed to activation of the ortho-C-Cl bond via interaction with electron-deficient Au nanoparticles. The results demonstrate the feasibility of a controlled recovery/recycling of chlorophenol waste using nano-structured Au catalysts.