Automatic acquisition of Named Entities for Rule-Based Machine Translation

This paper proposes to enrich RBMTdictionaries with Named Entities(NEs) automatically acquired fromWikipedia. The method is appliedto the Apertium English-Spanishsystem and its performance comparedto that of Apertium with and withouthandtagged NEs. The system withautomatic NEs outperforms the onewithout NEs, while results vary whencompared to a system with handtaggedNEs (results are comparable forSpanish to English but slightly worstfor English to Spanish). Apart fromthat, adding automatic NEs contributesto decreasing the amount of unknownterms by more than 10%.

Bootstrapping a statistical speech translator from a rule-based one

We describe a series of experiments in which we start with English to French and English to Japanese versions of an Open Source rule-based speech translation system for a medical domain, and bootstrap correspondign statistical systems. Comparative evaluation reveals that the rule-based systems are still significantly better than the statistical ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; also, a hybrid system only marginally improved recall at the cost of a los in precision. The result suggests that rule-based architectures may still be preferable to statistical ones for safety-critical speech translation tasks.

Implementation of an Integrated Activity-Based Costing in a Holistic Database Management System and its Implications for Operations Management

Diplomityössä on tutkittu reaaliaikaisen toimintolaskennan toteuttamista suomalaisen lasersiruja valmistavan PK-yrityksen tietojärjestelmään. Lisäksi on tarkasteltu toimintolaskennan vaikutuksia operatiiviseen toimintaan sekä toimintojen johtamiseen. Työn kirjallisuusosassa on käsitelty kirjallisuuslähteiden perusteella toimintolaskennan teorioita, laskentamenetelmiä sekä teknisessä toteutuksessa käytettyjä teknologioita. Työn toteutusosassa suunniteltiin ja toteutettiin WWW-pohjainen toimintolaskentajärjestelmä case-yrityksen kustannuslaskennan sekä taloushallinnon avuksi. Työkalu integroitiin osaksi yrityksen toiminnanohjaus- sekä valmistuksenohjausjärjestelmää. Perinteisiin toimintolaskentamallien tiedonkeruujärjestelmiin verrattuna case-yrityksessä syötteet toimintolaskentajärjestelmälle tulevat reaaliaikaisesti osana suurempaa tietojärjestelmäintegraatiota.Diplomityö pyrkii luomaan suhteen toimintolaskennan vaatimusten ja tietokantajärjestelmien välille. Toimintolaskentajärjestelmää yritys voi hyödyntää esimerkiksi tuotteiden hinnoittelussa ja kustannuslaskennassa näkemällä tuotteisiin liittyviä kustannuksia eri näkökulmista. Päätelmiä voidaan tehdä tarkkaan kustannusinformaatioon perustuen sekä määrittää järjestelmän tuottaman datan perusteella, onko tietyn projektin, asiakkuuden tai tuotteen kehittäminen taloudellisesti kannattavaa.

Fuzzy expert system in the prediction of neonatal resuscitation

In view of the importance of anticipating the occurrence of critical situations in medicine, we propose the use of a fuzzy expert system to predict the need for advanced neonatal resuscitation efforts in the delivery room. This system relates the maternal medical, obstetric and neonatal characteristics to the clinical conditions of the newborn, providing a risk measurement of need of advanced neonatal resuscitation measures. It is structured as a fuzzy composition developed on the basis of the subjective perception of danger of nine neonatologists facing 61 antenatal and intrapartum clinical situations which provide a degree of association with the risk of occurrence of perinatal asphyxia. The resulting relational matrix describes the association between clinical factors and risk of perinatal asphyxia. Analyzing the inputs of the presence or absence of all 61 clinical factors, the system returns the rate of risk of perinatal asphyxia as output. A prospectively collected series of 304 cases of perinatal care was analyzed to ascertain system performance. The fuzzy expert system presented a sensitivity of 76.5% and specificity of 94.8% in the identification of the need for advanced neonatal resuscitation measures, considering a cut-off value of 5 on a scale ranging from 0 to 10. The area under the receiver operating characteristic curve was 0.93. The identification of risk situations plays an important role in the planning of health care. These preliminary results encourage us to develop further studies and to refine this model, which is intended to implement an auxiliary system able to help health care staff to make decisions in perinatal care.

Involving users in expert system development

The ultimate criterion of success for interactive expert systems is that they will be used, and used to effect, by individuals other than the system developers. A key ingredient of success in most systems is involving users in the specification and development of systems as they are being built. However, until recently, system designers have paid little attention to ascertaining user needs and to developing systems with corresponding functionality and appropriate interfaces to match those requirements. Although the situation is beginning to change, many developers do not know how to go about involving users, or else tackle the problem in an inadequate way. This paper discusses the need for user involvement and considers why many developers are still not involving users in an optimal way. It looks at the different ways in which users can be involved in the development process and describes how to select appropriate techniques and methods for studying users. Finally, it discusses some of the problems inherent in involving users in expert system development, and recommends an approach which incorporates both ethnographic analysis and formal user testing.

Real-time expert system for fault location on high voltage underground distribution cables

To ensure minimum loss of system security and revenue it is essential that faults on underground cable systems be located and repaired rapidly. Currently in the UK, the impulse current method is used to prelocate faults, prior to using acoustic methods to pinpoint the fault location. The impulse current method is heavily dependent on the engineer's knowledge and experience in recognising/interpreting the transient waveforms produced by the fault. The development of a prototype real-time expert system aid for the prelocation of cable faults is described. Results from the prototype demonstrate the feasibility and benefits of the expert system as an aid for the diagnosis and location of faults on underground cable systems.

Power distribution network design aided by an expert system

The next couple of years will see the need for replacement of a large amount of life-expired switchgear on the UK 11 kV distribution system. Latest technology and alternative equipment have made the choice of replacement a complex task. The authors present an expert system as an aid to the decision process for the design of the 11 kV power distribution network.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

Rule-based morphological processing in a second language: a behavioural investigation

According to dual-system accounts of English past-tense processing, regular forms are decomposed into their stem and affix (played=play+ed) based on an implicit linguistic rule, whereas irregular forms (kept) are retrieved directly from the mental lexicon. In second language (L2) processing research, it has been suggested that L2 learners do not have rule-based decomposing abilities, so they process regular past-tense forms similarly to irregular ones (Silva & Clahsen 2008), without applying the morphological rule. The present study investigates morphological processing of regular and irregular verbs in Greek-English L2 learners and native English speakers. In a masked-priming experiment with regular and irregular prime-target verb pairs (playedplay/kept-keep), native speakers showed priming effects for regular pairs, compared to unrelated pairs, indicating decomposition; conversely, L2 learners showed inhibitory effects. At the same time, both groups revealed priming effects for irregular pairs. We discuss these findings in the light of available theories on L2 morphological processing.

Expert system to calculate the cofficient of friction : an approach to enhance traffic safety

Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems