EWR(R)无头轧制和工字轮式卷取机组

在加热炉之后对钢坯进行焊接(EWR（R）)的无头轧制工艺和棒卷生产用的工字轮式卷取机组，能够消除钢坯间隔时间、降低废品率、减少轧机停机时间、消除冷床上的短捧材、减少切头切尾、消耗件的寿命长、易于车间管理和“定制”盘卷质量。工字轮式卷取机组能够以无扭方法将热轧圆钢、方钢和扁钢卷成高度紧凑的／大质量卷材，以及在不进行中间离线操作的情况下，直接提供给下游冷加工生产线。     

MOFBOTS: Metal–Organic‐Framework‐Based Biomedical Microrobots

Motile metal?organic frameworks (MOFs) are potential candidates to serve as small‐scale robotic platforms for applications in environmental remediation, targeted drug delivery, or nanosurgery. Here, magnetic helical microstructures coated with a kind of zinc‐based MOF, zeolitic imidazole framework‐8 (ZIF‐8), with biocompatibility characteristics and pH‐responsive features, are successfully fabricated. Moreover, it is shown that this highly integrated multifunctional device can swim along predesigned tracks under the control of weak rotational magnetic fields. The proposed systems can achieve single‐cell targeting in a cell culture media and a controlled delivery of cargo payloads inside a complex microfluidic channel network. This new approach toward the fabrication of integrated multifunctional systems will open new avenues in soft microrobotics beyond current applications.     

Social Network-Aware Interfaces as Facilitators of Innovation

Achieving continuous innovation in organizations requires a balance between exploiting yet acquired knowledge and exploring new knowledge.In addition to having the adequate resources,change and innovation capabilities require specific management support and organizational structures.Recent research has pointed out the importance of social network structure and of the activity of agents that work across domains or disciplines in the innovation-oriented behaviour of organizations.As a consequence,information systems should ideally be able to support the analysis,development and management of such social structure for the benefit of organizational objectives.Current social network interfaces provide an established mental model to workers that can be hypothesized to be adequate for supporting activities that foster innovative behaviour.That behaviour is facilitated through exposing the activities of other workers across organizational structures.This paper reports on the design of a user interface specifically targeted to manage the social aspects of innovation based on some aspects of Hargadon’s model of innovation and knowledge brokering.The emergent nature of interactions in social network sites is used as the metaphor to foster situated cognition.The interface design assessment is described and some metrics for innovative behaviour that could be derived for such an interface are sketched.     

Chemical changes in nitrogenous compounds during fermentation of sour doughs and bread doughs

Summary The evolution of sour doughs (SD), prepared using a wheat bran extract as the starting material, and their respective bread doughs (BD) has been investigated by determining the chemical changes which take place in 0.85 mol/L NaCl-soluble nitrogen compounds during fermentation. The quantitative changes determined are: total nitrogen content (TN), primary amine nitrogen (AN) and-amine nitrogen of free amino acids (AAN) in the total soluble fraction (SN), protein (PSN) and non-protein (NPSN) subfractions. During fermentation,-amine nitrogen of the free amino acids (AAN_SN) and peptides (AN_NPSN-AAN_SN), increase in SD and decrease in BD. Changes are larger and faster in peptide nitrogen and even larger during the third and fifth steps. The total protein content (TN_PSN) decreases in both SD and BD. Results are discussed in relation to the quality of the bread obtained in each case.

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Chemische Veranderungen der Stickstoffverbindungen aus Sauerteigen und den damit hergestellten Brotteigen

Zusammenfassung Es wird die Entwicklung von Sauerteigen mit Weizenkleiextrakt als Starter und ihren entsprechenden Brotteigen durch Bestimmung der chemischen Veranderungen der in 0,85 mol/L NaCl1 slichen Stickstoffverbindungen wahrend der Gärung untersucht. Die quantitativen Veränderungen des Gesamt-Stickstoffgehalts (TN), des primären Aminostickstoffs (AN) und des -Aminostickstoffs der freien Aminosauren (AAN) in der loslichen Fraktion (SN) und in den Proteinen (PSN) und Nicht-Proteinen (NPNS) der Subfraktionen. Wahrend der Gärung steigt der Anteil des-Aminostickstoffs in den freien Aminosäuren (AAN_SN) und Peptiden (AN_NPSN-AAN_SN) in den Sauerteigen (SD) an und vermindert sich in den Brotteigen (BD). Die Veränderungen sind hoher und schneller beim Peptidstickstoff und größer wahrend der dritten und funften Stufe sowohl beim Sauer- als auch beim Brotteig; in beiden nimmt der Proteingehalt (TN_PSN) ab. Die Ergebnisse werden bezogen auf die Qualität der hergestellten Brote besprochen.

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Paper presented at the 7th World Congress of Food Science and Technology, Singapore (Singapore), 28 September – 2 October 1987     

On the choice of the best imputation methods for missing values considering three groups of classification methods

In real-life data, information is frequently lost in data mining, caused by the presence of missing values in attributes. Several schemes have been studied to overcome the drawbacks produced by missing values in data mining tasks; one of the most well known is based on preprocessing, formerly known as imputation. In this work, we focus on a classification task with twenty-three classification methods and fourteen different imputation approaches to missing values treatment that are presented and analyzed. The analysis involves a group-based approach, in which we distinguish between three different categories of classification methods. Each category behaves differently, and the evidence obtained shows that the use of determined missing values imputation methods could improve the accuracy obtained for these methods. In this study, the convenience of using imputation methods for preprocessing data sets with missing values is stated. The analysis suggests that the use of particular imputation methods conditioned to the groups is required.     

Studying the effectiveness of multi-user immersive environments for collaborative evaluation tasks

Massively Multiuser On-line Learning (MMOL) Platforms, often called “virtual learning worlds”, constitute a still unexplored context for communication-enhanced learning, where synchronous communication skills in an explicit social setting enhance the potential of effective collaboration. In this paper, we report on an experimental study of collaborative evaluation in an MMOL setting with 21 graduate students enrolled in university courses in technology-mediated teaching and learning. This study was carried out using a prototype of a 3D MMOL platform built around an interactive space called “MadriPolis”. This space was used to recreate an adequate scenario for a collaborative experience about Learning Object evaluation using the mainstream Learning Object Review Instrument (LORI), which is based on a Convergent Participation Model (CPM). The same experience was carried out using a conventional LCMS (Learning Content Management System) platform with the aim of contrasting the outcomes and interaction patterns in the two settings. This study makes use of Social Network Analysis (SNA) measures to describe the interactions between tutors and learners. By dwelling on the advantages of immersive environments, SNA indexes revealed that these interactions were rather dense and that student participation was rather broad-based in the case of the MMOL. The results suggest that MMOL platforms could be used in collaborative evaluation tasks as a means to enhance both tutor interaction patterns and the strength of the group's relationship.     

Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification

Nearest neighbor classification is one of the most used and well known methods in data mining. Its simplest version has several drawbacks, such as low efficiency, high storage requirements and sensitivity to noise. Data reduction techniques have been used to alleviate these shortcomings. Among them, prototype selection and generation techniques have been shown to be very effective. Positioning adjustment of prototypes is a successful trend within the prototype generation methodology.Evolutionary algorithms are adaptive methods based on natural evolution that may be used for searching and optimization. Positioning adjustment of prototypes can be viewed as an optimization problem, thus it can be solved using evolutionary algorithms. This paper proposes a differential evolution based approach for optimizing the positioning of prototypes. Specifically, we provide a complete study of the performance of four recent advances in differential evolution. Furthermore, we show the good synergy obtained by the combination of a prototype selection stage with an optimization of the positioning of prototypes previous to nearest neighbor classification. The results are contrasted with non-parametrical statistical tests and show that our proposals outperform previously proposed methods.     

IPTV service based on a content-zapping paradigm

Internet protocol television (IPTV) generically designates a real-time distribution service for multimedia contents over an IP network, such as the Internet. There are many advantages of IPTV deployment over current digital or air broadcast TV signals: integration, the use of the switched internet protocol (IP), the possibility to build home networks that can be used to share multimedia contents over different devices, the easy implementation of video on demand services and the usage of better compression and encryption standards. In order to implement this kind of service, it is extremely useful to have a system that can efficiently classify multimedia contents and users and distribute them in a customized way. This paper proposes a novel IPTV service for the distribution of personalized multimedia contents over IP networks based on the concept of content-zapping, in contrast to traditional channel-zapping: each client system receives a multimedia streaming that is automatically composed by the system based on the user preferences and the user will only interact with the system by requesting a content change or marking a content as favorite. The paper will describe the general functionality of the service and will present the detailed architecture of the IPTV server, the key component of the service infrastructure. The server must maintain a list of media contents residing in other systems and must keep a dynamic classification of the multimedia contents that are stored in its database. This classification is built and gradually refined based on the interactions between clients and multimedia contents. Special attention is given in the paper to the classification model, describing the general ideas that are used to automatically suggest multimedia contents to a specific user (that is characterized by his complete profile). A specific content may be suggested to the user based on the knowledge of the user profile and/or based on specific and dynamic information, such as the user position, the local temperature, date and time. The availability of this information obviously depends on the specific user device that is being used. The proposed system allows any client device to connect, allowing a high level of interoperability. It is also possible to use all the device capabilities and sensors, like Global Positioning System (GPS), accelerometers, light sensors, noise sensors, etc., thus creating a context environment that helps classify each user profile. These context-awareness mechanisms applied to mobile devices with wireless network (802.11b/g/n, WiMAX, GSM, UMTS, etc.) capabilities allow a better user experience and more accurate multimedia suggestions, due to the deep knowledge about the user device, network and environment. The system also allows the users to suggest contents to other users in the same “group of friends”. Several performance tests were already conducted and the results obtained show that the proposed system is very stable and fast, even for high increases on the number of users.     

A memetic algorithm for evolutionary prototype selection: A scaling up approach

Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. Evolutionary algorithms have been used recently for prototype selection showing good results. However, due to the complexity of this problem when the size of the databases increases, the behaviour of evolutionary algorithms could deteriorate considerably because of a lack of convergence. This additional problem is known as the scaling up problem.

Memetic algorithms are approaches for heuristic searches in optimization problems that combine a population-based algorithm with a local search. In this paper, we propose a model of memetic algorithm that incorporates an ad hoc local search specifically designed for optimizing the properties of prototype selection problem with the aim of tackling the scaling up problem. In order to check its performance, we have carried out an empirical study including a comparison between our proposal and previous evolutionary and non-evolutionary approaches studied in the literature.

The results have been contrasted with the use of non-parametric statistical procedures and show that our approach outperforms previously studied methods, especially when the database scales up.