Building language resources for a Multi-Engine English-Filipino machine translation system

In this paper, we present the building of various language resources for a multi-engine bi-directional English-Filipino Machine Translation (MT) system. Since linguistics information on Philippine languages are available, but as of yet, the focus has been on theoretical linguistics and little is done on the computational aspects of these languages, attempts are reported here on the manual construction of these language resources such as the grammar, lexicon, morphological information, and the corpora which were literally built from almost non-existent digital forms. Due to the inherent difficulties of manual construction, we also discuss our experiments on various technologies for automatic extraction of these resources to handle the intricacies of the Filipino language, designed with the intention of using them for the MT system. To implement the different MT engines and to ensure the improvement of translation quality, other language tools (such as the morphological analyzer and generator, and the part of speech tagger) were developed.     

Strategies to create platforms for differentiated services from dedicated and opportunistic resources

This paper is proposing a new platform for implementing services in future service oriented architectures. The basic premise of our proposal is that by combining the large volume of uncontracted resources with small clusters of dedicated resources, we can dramatically reduce the amount of dedicated resources while the goodput provided by the overall system remains at a high level. This paper presents particular strategies for implementing this idea for a particular class of applications. We performed very detailed simulations on synthetic and real traces to evaluate the performance of the proposed strategies. Our findings on compute-intensive applications show that preemptive reallocation of resources is necessary for assured services. The proposed preemption-based scheduling heuristic can significantly improve utilization of the dedicated resources by opportunistically offloading the peak loads on uncontracted resources, while keeping the service quality virtually unaffected.     

Automatic induction of bilingual resources from aligned parallel corpora: application to shallow-transfer machine translation

The availability of machine-readable bilingual linguistic resources is crucial not only for rule-based machine translation but also for other applications such as cross-lingual information retrieval. However, the building of such resources (bilingual single-word and multi-word correspondences, translation rules) demands extensive manual work, and, as a consequence, bilingual resources are usually more difficult to find than “shallow” monolingual resources such as morphological dictionaries or part-of-speech taggers, especially when they involve a less-resourced language. This paper describes a methodology to build automatically both bilingual dictionaries and shallow-transfer rules by extracting knowledge from word-aligned parallel corpora processed with shallow monolingual resources (morphological analysers, and part-of-speech taggers). We present experiments for Brazilian Portuguese–Spanish and Brazilian Portuguese–English parallel texts. The results show that the proposed methodology can enable the rapid creation of valuable computational resources (bilingual dictionaries and shallow-transfer rules) for machine translation and other natural language processing tasks).     

Combining a monad and a comonad

We give a systematic treatment of distributivity for a monad and a comonad as arises in giving category theoretic accounts of operational and denotational semantics, and in giving an intensional denotational semantics. We do this axiomatically, in terms of a monad and a comonad in a 2-category, giving accounts of the Eilenberg–Moore and Kleisli constructions. We analyse the eight possible relationships, deducing that two pairs are isomorphic, but that the other pairs are all distinct. We develop those 2-categorical definitions necessary to support this analysis.     

Quasi-interpretations a way to control resources

This paper presents in a reasoned way our works on resource analysis by quasi-interpretations. The controlled resources are typically the runtime, the runspace or the size of a result in a program execution.Quasi-interpretations allow the analysis of system complexity. A quasi-interpretation is a numerical assignment, which provides an upper bound on computed functions and which is compatible with the program operational semantics. The quasi-interpretation method offers several advantages: (i) It provides hints in order to optimize an execution, (ii) it gives resource certificates, and (iii) finding quasi-interpretations is decidable for a broad class which is relevant for feasible computations.By combining the quasi-interpretation method with termination tools (here term orderings), we obtained several characterizations of complexity classes starting from Ptime and Pspace.     

Combining KADS with ZEUS to Develop a Multi-Agent E-Commerce Application

A KADS based requirement analysis for the management of stock trading portfolios is presented. This provides a theoretical foundation for a stock trading system. This system is designed around portfolio management tasks that include eliciting user profiles, collecting information on the user's portfolio position, monitoring the environment on behalf of the user, and making decision suggestions to meet the user's investment goals. The requirement analysis defines a framework for a Multi-Agent System for Stock Trading (MASST). Experiments in task decomposition and agent interaction using a partially implemented system are described.     

Cellular ants: A method to create collision free trajectories for a cooperative robot team

Creating collision-free trajectories for mobile robots, known as the path planning problem, is considered to be one of the basic problems in robotics. In case of multiple robotic systems, the complexity of such systems increases proportionally with the number of robots, due to the fact that all robots must act as one unit to complete one composite task, such as retaining a specific formation. The proposed path planner employs a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every robot of a team while their formation is kept immutable. The method reacts with obstacle distribution changes and therefore can be used in dynamical or unknown environments, without the need of a priori knowledge of the space. The team is divided into subgroups and all the desired pathways are created with the combined use of a CA path planner and an ACO algorithm. In case of lack of pheromones, paths are created using the CA path planner. Compared to other methods, the proposed method can create accurate collision-free paths in real time with low complexity while the implemented system is completely autonomous. A simulation environment was created to test the effectiveness of the applied CA rules and ACO principles. Moreover, the proposed method was implemented in a system using a real world simulation environment, called Webots. The CA and ACO combined algorithm was applied to a team of multiple simulated robots without the interference of a central control. Simulation and experimental results indicate that accurate collision free paths could be created with low complexity, confirming the robustness of the method.     

Towards the development of a framework to create a virtual organisation breeding environment in the mould and die sector

The effective creation of Virtual Enterprises emerges after the development of: (i) a new working culture and (ii) a computer-enabled infrastructure supporting inter-operation of companies. These developments are facilitated if the potential partners belong to a Virtual Organisation Breeding Environment (VBE). This paper describes a framework to create and support the life cycle of Virtual Enterprises operating (relying on a VBE) in the mould and die sector. The proposed framework is called AmbianCE and it is the result of a 5-year research project in the field of Collaborative Network Organisations. The AmbianCE framework has been validated in a Brazilian VBE called Virfebras. A peculiar characteristic of Virfebras is that many of its members are competitors.     

Combining contemporary and traditional project management tools to resolve a project scheduling problem

In this paper we examine a construction project involving the building of large concrete slabs for three buildings in an office park complex. There are finish-to-start (FS) as well as start-to-start (SS) and finish-to-finish (FF) precedence relationships among the project activities. We prepare an initial project schedule using Microsoft Project and manually validate the results using the precedence diagramming method (PDM) procedure. When the client informs us that the schedule must be shortened we find that Microsoft Project does not have the capability for resolving our particular time/cost tradeoff issues. So we revert to the traditional approach for resolving time/cost tradeoffs in projects and develop an original linear programming formulation for the time/cost tradeoff problem when a project is modeled as a precedence diagram. By combining contemporary (Microsoft Project) and traditional (a linear programming time/cost tradeoff model) project management tools we are able to successfully resolve the scheduling issues associated with the slab construction project. Further, we demonstrate the anomalous effects of start-to-start (SS) and finish-to-finish (FF) relationships via our construction project example in which the solution to the time/cost tradeoff problem requires that certain activities be lengthened in order to shorten the project duration.     

Combining Isomap ordination and imaging spectroscopy to map continuous floristic gradients in a heterogeneous landscape

Mapping requires a meaningful generalization of information. For vegetation maps, classification is frequently used to generalize the species composition of (semi-)natural plant assemblages. As an alternative to classification, ordination methods aim to extract major floristic gradients describing the prevailing compositional variation in a floristic data set as metric variables. This ability has been used previously to derive gradient maps of homogeneous landscapes that show plant species composition in continuous fields. In the present study, gradient mapping was used in a more heterogeneous landscape with intricate environmental gradients and higher variation in vegetation physiognomy. Since established ordination methods may have difficulties to cope with the highly variable plant species composition, we tested the novel method Isometric Feature Mapping (Isomap) against conventional methods (Detrended Correspondence Analysis and Nonmetric Multidimensional Scaling). The resulting floristic gradients were related to hyperspectral imagery (HyMap) using partial least squares regression (PLSR) and subsequently mapped. Prediction uncertainties are provided as additional map. Isomap was able to preserve 74% of the original variation inherent to the floristic data set in a three-dimensional solution. This was considerably more than the established techniques achieved. The PLSR models for the floristic gradients extracted with Isomap showed model fits ranging from R² = 0.59 to R² = 0.73 in calibration and from R² = 0.55 to R² = 0.69 in tenfold cross-validation. The resulting gradient map provides detailed information on compositional vegetation patterns.     

Combining a new data classification technique and regression analysis to predict the Cost-To-Serve new customers

Identifying the Cost-To-Serve (CTS) of customers is one of the most challenging problems in Supply Chain Management because of the diversity in their business activities. For the particular case of the industrial gas business, we are interested in predicting the cost to deliver bulk (liquefied) gas to new customers using a multifactor linear regression model. Developing a single model, i.e. analyzing the observations all at once, produces poor prediction results. Therefore prior to the regression analysis, a new supervised learning technique is used to group customers who are similar in some sense. Classes of customers are represented by hyper-boxes and a linear regression model is subsequently built within each class. The combination of data classification and regression is proven to increase the accuracy of the prediction.Two Mixed-Integer-Linear Programming (MILP) models are developed for data classification purposes. Although we are dealing with a supervised learning method, classes are not predefined in our case. Rather, we input a continuous “classification” attribute that is optimally discretized by the MILP’s in order to minimize the number of misclassifications. Therefore our data classification model offers a broader range of applications. A number of illustrative examples are used to prove the effectiveness of the proposed approach.     

Combining interaction and context design to support collaborative argumentation using a tool for synchronous CMC

Abstract Empirical studies and theory suggest that educational dialogue can be used to support learners in the development of reasoning, critical thinking and argumentation. This paper presents an educational design for synchronous online peer discussion that guides student dialogue in ways that lead to improved argumentation and collaborative knowledge development. This design includes a mediating interface – or tool, linked to a broader set of online educational activities – a designed local context, where the latter aims to provide conditions that support argumentation. The approach is based on collaborative working and dialogue game approaches to discussion. Preliminary findings with UK Open University students showed the argumentation process was more coherent, varied, deeper and extended when using our interaction design compared with the use of a simple unstructured interface.     

Banking 2000? Reengineering at the First National Bank of Southern Africa to create a branch of the future

This case study describes how a major bank reorganised, restructured and retrained a branch in order to solve an operational and financial problem. It applied well-trusted information technology in an innovative way to improve client throughput, increase turnover and raise staff productivity. This was undertaken to simultaneously show the way to the rest of the organisation as to how retail banking should be conducted in the 21st century. The branch of the future showed how reengineering could be used to substantially improve a branch's performance while increasing its attractiveness to the bank's clients. This new approach to retail banking is referred to by the authors as Banking 2000? or the branch of the future.     

Suitable properties of ink to create inkjet-printed surface-directed microchannels that utilize the pinning effect of a triple line on a rough surface

If microfluidic devices can be directly produced using printing techniques, the combination of microfluidics and printing techniques for other applications, such as printed electronics, will make all-printed highly-functionalized microfluidic devices possible. Therefore, we have made efforts to develop a technique for producing microfluidic devices using an inkjet printer. The microchannels that could be created using this technique were a kind of surface-directed channels that utilize the pinning effect of a triple line on a rough surface. In this study, we focused on what were the required properties of the printer ink during the wetting and drying processes of the ink. As a result, one of the properties required during the wetting process was that the advancing contact angle of the ink should be smaller than a certain value, which depended on the average volume of the ink drops ejected from the printhead and the number of drops per unit area. The receding contact angle should be smaller than about one third of each advancing angle. In addition, during the drying process, a small amount of surfactant added to the ink played a critical role in order to leave a continuous stain of the ink. As an application of this inkjet-printed channel, we also created a device for mixing aqueous solutions.     

Supporting science learning in linguistically diverse classrooms: Factors related to the use of bilingual content in a computer-based learning environment

Computer-based learning environments (CBLEs) are a promising means to support language minority (LMi) students in acquiring knowledge and skills through the integration of authentic support in their home language. This study aimed to determine the use of scientific bilingual content offered to fourth-grade students (n = 250) in the CBLE E-Validiv and to identify both student and classroom characteristics related to this use. All the content in E-Validiv is accessible in the language of instruction and one of six other languages. For LMi students, the other language is set to their home language. Multilevel hierarchical regression analyses show that especially LMi students who assess themselves as highly proficient in their home language use the content more in the other language than language majority students. However, even LMi students focus mainly on content in the language of instruction, which indicates that they particularly apply their home language to support their learning process in the language of instruction. Additionally, students who perform higher on science subjects access content more in the language of instruction. The presence of linguistic diversity in the classroom and the positive use of linguistic diversity by the teacher do not seem to matter. The theoretical and practical implications are discussed.     

A novel pattern recognition algorithm: Combining ART network with SVM to reconstruct a multi-class classifier

Based on the principle of one-against-one support vector machines (SVMs) multi-class classification algorithm, this paper proposes an extended SVMs method which couples adaptive resonance theory (ART) network to reconstruct a multi-class classifier. Different coupling strategies to reconstruct a multi-class classifier from binary SVM classifiers are compared with application to fault diagnosis of transmission line. Majority voting, a mixture matrix and self-organizing map (SOM) network are compared in reconstructing the global classification decision. In order to evaluate the method’s efficiency, one-against-all, decision directed acyclic graph (DDAG) and decision-tree (DT) algorithm based SVM are compared too. The comparison is done with simulations and the best method is validated with experimental data.     

从本科生视角看“机器人学”课程教学

机器人技术是当前广受关注的智能科学技术之一。以本科生的视角,就机器人学课程的发展现状进行阐述,并从教学方法、师生课堂互动、教材选取和考核方式等方面探讨课程建设与改革问题,进而对双语教学程度、教学网站功能和实践教学等提出改进建议,以期更好更多地培养创新型人才。