Overall performance measurement in a supply chain: towards a supplier-prime manufacturer based model

This study deals with the supply chain (SC) overall performance expression. The developed idea concerns more particularly the performance of the manufactured products. Indeed, two companies or more contribute to the manufacturing of products that are generally assembled by the prime manufacturer company. Moreover, in the industrial practice, performance scorecards are defined with regard to each process; and the overall performance is neither expressed for each company, nor for the whole SC. We propose here to identify the SC overall performance to the combination of the performances of the different involved companies in the SC. Thus, in order to obtain a definition of such performance, we choose to focus first on the performance of the prime manufacturer. In this sense, the approach is based on the SCOR model for the handling of the main processes around the considered product manufacturing. The prime manufacturer performance is then defined as the aggregation of its involved processes?? performances. While the prime manufacturer performance is strongly dependent on the suppliers?? performance, we suggest the integration of the impacting supplier performance into the prime manufacturer scorecards. From an operational point of view, the MACBETH methodology is used to coherently express both processes and overall performances. More precisely, the Choquet aggregation integral operator is applied in order to model mutual interactions between processes. Finally, the expression of a bearing??s manufacturer performance illustrates the proposition.     

Maintaining Views in Object-Relational Databases

View materialization is an important way of improving the performance of query processing. When an update occurs to the source data from which a materialized view is derived, the materialized view has to be updated so that it is consistent with the source data. This update process is called view maintenance. The incremental method of view maintenance, which computes the new view using the old view and the update to the source data, is widely preferred to full view recomputation when the update is small in size. In this paper we investigate how to incrementally maintain views in object-relational (OR) databases. The investigation focuses on maintaining views defined in OR-SQL, a language containing the features of object referencing, inheritance, collection, and aggregate functions including user-defined set aggregate functions. We propose an architecture and algorithms for incremental OR viewmaintenance. We implement all algorithms and analyze the performance of them in comparison with full view recomputation. The analysis shows that the algorithms significantly reduce the cost of updating a vieww hen the size of an update to the source data is relatively small. Received 23 May 2000 / Revised 27 March 2001 / Accepted in revised form 30 April 2001 Correspondence and offprint requests to: Jixue Liu, School of Computer and Information Science, University of South Australia, Mawson Lakes, Adelaide SA5084, Australia. Email: jixue.liu@unisa.edu.auau     

Product family modeling for mass customization

With growing reliance on modeling in product development, it is imperative to describe product families in a cohesive way. In particular, mass customization calls for a close integration of product life cycle from customer recognition to delivery and services. This paper proposes a triple-view scheme for modeling product families. Technical challenges are discussed by comparing product family modeling with modeling single products. Individual modeling formalisms for different views are discussed. An example of product family modeling in power supply design is presented to illustrate the feasibility and potential of the proposed approach.     

Soil Water Content and Dry Density by Time Domain Reflectometry

Soil water content and dry density are two important properties for compaction quality control. This paper presents a new method for determining soil water content and dry density using a single time domain reflectometry test, which is an improvement over that designated by ASTM D6780. This new method is based on simultaneous measurement of apparent dielectric constant and bulk electrical conductivity on the same soil sample. Calibration equations correlate these two parameters with soil gravimetric water content and dry density, which are simultaneously solved after adjusting field-measured conductivity to a standard conductivity. The method compensates for temperature effects. The test process takes about 3 min and all calculations are automated. Testing may be done in situ using a special probe that provides sufficient sampling volume or in a compaction mold adapted to form a probe. Laboratory and field tests results show this one-step method is a fast, accurate, and safe method for construction quality control.     

Asymmetric tensor field visualization for surfaces

Asymmetric tensor field visualization can provide important insight into fluid flows and solid deformations. Existing techniques for asymmetric tensor fields focus on the analysis, and simply use evenly-spaced hyperstreamlines on surfaces following eigenvectors and dual-eigenvectors in the tensor field. In this paper, we describe a hybrid visualization technique in which hyperstreamlines and elliptical glyphs are used in real and complex domains, respectively. This enables a more faithful representation of flow behaviors inside complex domains. In addition, we encode tensor magnitude, an important quantity in tensor field analysis, using the density of hyperstreamlines and sizes of glyphs. This allows colors to be used to encode other important tensor quantities. To facilitate quick visual exploration of the data from different viewpoints and at different resolutions, we employ an efficient image-space approach in which hyperstreamlines and glyphs are generated quickly in the image plane. The combination of these techniques leads to an efficient tensor field visualization system for domain scientists. We demonstrate the effectiveness of our visualization technique through applications to complex simulated engine fluid flow and earthquake deformation data. Feedback from domain expert scientists, who are also co-authors, is provided.     

Unraveling Membrane Perturbations Caused by the Bacterial Riboregulator Hfq

Hfq is a pleiotropic regulator that mediates several aspects of bacterial RNA metabolism. The protein notably regulates translation efficiency and RNA decay in Gram-negative bacteria, usually via its interaction with small regulatory RNAs. Previously, we showed that the Hfq C-terminal region forms an amyloid-like structure and that these fibrils interact with membranes. The immediate consequence of this interaction is a disruption of the membrane, but the effect on Hfq structure was unknown. To investigate details of the mechanism of interaction, the present work uses different in vitro biophysical approaches. We show that the Hfq C-terminal region influences membrane integrity and, conversely, that the membrane specifically affects the amyloid assembly. The reported effect of this bacterial master regulator on membrane integrity is discussed in light of the possible consequence on small regulatory RNA-based regulation.     

Low Bit-Rate Object Coding of Musical Audio Using Bayesian Harmonic Models

This paper deals with the decomposition of music signals into pitched sound objects made of harmonic sinusoidal partials for very low bit-rate coding purposes. After a brief review of existing methods, we recast this problem in the Bayesian framework. We propose a family of probabilistic signal models combining learned object priors and various perceptually motivated distortion measures. We design efficient algorithms to infer object parameters and build a coder based on the interpolation of frequency and amplitude parameters. Listening tests suggest that the loudness-based distortion measure outperforms other distortion measures and that our coder results in a better sound quality than baseline transform and parametric coders at 8 and 2 kbit/s. This work constitutes a new step towards a fully object-based coding system, which would represent audio signals as collections of meaningful note-like sound objects     

An improved approach to find membership functions and multiple minimum supports in fuzzy data mining

Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge. Since items may have their own characteristics, different minimum supports and membership functions may be specified for different items. In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions. In that paper, minimum supports and membership functions of all items are encoded in a chromosome such that it may be not easy to converge. In this paper, an enhanced approach is proposed, which processes the items in a divide-and-conquer strategy. The approach is called divide-and-conquer genetic-fuzzy mining algorithm for items with Multiple Minimum Supports (DGFMMS), and is designed for finding minimum supports, membership functions, and fuzzy association rules. Possible solutions are evaluated by their requirement satisfaction divided by their suitability of derived membership functions. The proposed GA framework maintains multiple populations, each for one item’s minimum support and membership functions. The final best minimum supports and membership functions in all the populations are then gathered together to be used for mining fuzzy association rules. Experimental results also show the effectiveness of the proposed approach.     

Characterization of a Cutibacterium acnes Camp Factor 1-Related Peptide as a New TLR-2 Modulator in In Vitro and Ex Vivo Models of Inflammation

Cutibacterium acnes (C. acnes) has been implicated in inflammatory acne where highly mutated Christie–Atkins–Munch–Petersen factor (CAMP)1 displays strong toll like receptor (TLR)-2 binding activity. Using specific antibodies, we showed that CAMP1 production was independent of C. acnes phylotype and involved in the induction of inflammation. We confirmed that TLR-2 bound both mutated and non-mutated recombinant CAMP1, and peptide array analysis showed that seven peptides (A14, A15, B1, B2, B3, C1 and C3) were involved in TLR-2 binding, located on the same side of the three-dimensional structure of CAMP1. Both mutated and non-mutated recombinant CAMP1 proteins induced the production of C-X-C motif chemokine ligand interleukin (CXCL)8/(IL)-8 in vitro in keratinocytes and that of granulocyte macrophage-colony stimulating factor (GM-CSF), tumor necrosis factor (TNF)-α, IL-1β and IL-10 in ex vivo human skin explants. Only A14, B1 and B2 inhibited the production of CXCL8/IL-8 by keratinocytes and that of (GM-CSF), TNF-α, IL-1β and IL-10 in human skin explants stimulated with rCAMP1 and C. acnes. Following pretreatment with B2, RNA sequencing on skin explants identified the 10 genes displaying the strongest differential expression as IL6, TNF, CXCL1, CXCL2, CXCL3, CXCL8, IL-1β, chemokine ligand (CCL)2, CCL4 and colony stimulating factor (CSF)2. We, thus, identified a new CAMP1-derived peptide as a TLR-2 modulator likely to be a good candidate for clinical evaluation.