实现短流程钢铁企业最佳业绩中人的因素

德国巴登钢铁公司（BSW）炼钢厂有2座80t电炉，2座钢包炉和2台5流连铸机，由于BSW的生产和管理人员具有高的素质，精心保养设备，保持高生产率，从而降低生产成本。去年BSW炼钢厂生产140多万t质量合格钢坯。全员劳动生产率超过2000t钢／人·年。     

State-of-the-art of long-term preservation in product lifecycle management

Providing access to digital information for the indefinite future is the intention of long-term digital preservation systems. One application domain that certainly needs to implement such long-term digital preservation processes is the design and engineering industry. In this industry, products are designed, manufactured, and operated with the help of sophisticated software tools provided by product lifecycle management (PLM) systems. During all PLM phases, including geographically distributed cross-domain and cross-company collaboration, a huge amount of heterogeneous digital product data and metadata is created. Legal and economic requirements demand that this product data has to be archived and preserved for a long-time period. Unfortunately, the software that is able to interpret the data will become obsolete earlier than the data since the software and hardware lifecycle is relatively short-lived compared to a product lifecycle. Companies in the engineering industry begin to realize that their data is in danger of becoming unusable while the products are in operation for several decades. To address this issue, different academic and industrial initiatives have been initiated that try to solve this problem. This article provides an overview of these projects including their motivations, identified problems, and proposed solutions. The studied projects are also verified against a classification of important aspects regarding scope and functionality of digital preservation in the engineering industry. Finally, future research topics are identified.     

A Framework for Interactive t-SNE Clustering

In this paper, we describe our progress in creating the framework for an interactive application that allows humans to actively participate in a t-SNE clustering process. t-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction technique that maps high dimensional data sets to lower dimensions that can then be visualized for human interpretation. By prompting users to monitor outlying points during the t-SNE clustering process, we hypothesize that users may be able to make clustering faster and more accurate than purely algorithmic methods. Further research would test these hypotheses directly. We would also attempt to decrease the lag time between the various components of our application and develop an intuitive approach for humans to aid in clustering unlabeled data. Research into human assisted clustering can combine the strengths of both humans and computer programs to improve the results of data analysis.     

In-line holographic electron microscopy in the presence of external magnetic fields

It is now a well-known fact that the phase of electron waves is altered by external magnetic fields via the Aharonov-Bohm effect. This implies that any electron interference effects will be to some degree affected by the presence of such fields. In this study we examine the distortion effects of external (constant and variable) magnetic fields on electron interference and holography. For digital holography, the reconstruction of the object is done via numerical calculations and this leaves the door open for correcting phase distortions in the hologram reconstruction. We design and quantitatively assess such correction schemes, which decidedly depend on our knowledge of the magnetic field values in the holographic recording process. For constant fields of known value we are able to correct for magnetic distortions to a great extent. We find that variable fields are more destructive to the holographic process than constant fields. We define two criteria, related respectively to global and local contrast of the hologram to establish the maximum allowed external field which does not significantly hinder the accuracy of in-line holographic microscopy with electrons.     

On the complexity of deciding avoidability of sets of partial words

Blanchet-Sadri et al. have shown that Avoidability, or the problem of deciding the avoidability of a finite set of partial words over an alphabet of size k≥2, is NP-hard [F. Blanchet-Sadri, R. Jungers, J. Palumbo, Testing avoidability on sets of partial words is hard, Theoret. Comput. Sci. 410 (2009) 968-972]. Building on their work, we analyze in this paper the complexity of natural variations on the problem. While some of them are NP-hard, others are shown to be efficiently decidable. Using some combinatorial properties of de Bruijn graphs, we establish a correspondence between lengths of cycles in such graphs and periods of avoiding words, resulting in a tight bound for periods of avoiding words. We also prove that Avoidability can be solved in polynomial space, and reduces in polynomial time to the problem of deciding the avoidability of a finite set of partial words of equal length over the binary alphabet. We give a polynomial bound on the period of an infinite avoiding word, in the case of sets of full words, in terms of two parameters: the length and the number of words in the set. We give a polynomial space algorithm to decide if a finite set of partial words is avoided by a non-ultimately periodic infinite word. The same algorithm also decides if the number of words of length n avoiding a given finite set of partial words grows polynomially or exponentially with n.     

Steward: Scaling Byzantine Fault-Tolerant Replication to Wide Area Networks

This paper presents the first hierarchical Byzantine fault-tolerant replication architecture suitable to systems that span multiple wide-area sites. The architecture confines the effects of any malicious replica to its local site, reduces message complexity of wide-area communication, and allows read-only queries to be performed locally within a site for the price of additional standard hardware. We present proofs that our algorithm provides safety and liveness properties. A prototype implementation is evaluated over several network topologies and is compared with a flat Byzantine fault-tolerant approach. The experimental results show considerable improvement over flat Byzantine replication algorithms, bringing the performance of Byzantine replication closer to existing benign fault-tolerant replication techniques over wide area networks.     

From I-Awareness to We-Awareness in CSCW

Awareness is one of the central concepts in Computer Supported Cooperative Work, though it has often been used in several different senses. Recently, researchers have begun to provide a clearer conceptualization of awareness that provides concrete guidance for the structuring of empirical studies of awareness and the development of tools to support awareness. Such conceptions, however, do not take into account newer understandings of shared intentionality among cooperating actors that recently have been defined by philosophers and empirically investigated by psychologists and psycho-linguists. These newer conceptions highlight the common ground and socially recursive inference that underwrites cooperative behavior. And it is this inference that is often seamlessly carried out in collocated work, so easy to take for granted and hence overlook, that will require computer support if such work is to be partially automated or carried out at a distance. Ignoring the inferences required in achieving common ground may thus focus a researcher or designer on surface forms of “heeding” that miss the underlying processes of intention shared in and through activity that are critical for cooperation to succeed. Shared intentionality thus provides a basis for reconceptualizing awareness in CSCW research, building on and augmenting existing notions. In this paper, we provide a philosophically grounded conception of awareness based on shared intentionality, demonstrate how it accounts for behavior in an empirical study of two individuals in collocated, tightly-coupled work, and provide implications of this conception for the design of computational systems to support tightly-coupled collaborative work.