Terminological Importation for Adapting Reusable Knowledge Representation Components in the KSM Environment

This paper describes the adaptation approach of reusable knowledge representation components used in the KSM environment for the formulation and operationalisation of structured knowledge models. Reusable knowledge representation components in KSM are called primitives of representation. A primitive of representation provides: (1) a knowledge representation formalism (2) a set of tasks that use this knowledge together with several problem-solving methods to carry out these tasks (3) a knowledge acquisition module that provides different services to acquire and validate this knowledge (4) an abstract terminology about the linguistic categories included in the representation language associated to the primitive. Primitives of representation usually are domain independent. A primitive of representation can be adapted to support knowledge in a given domain by importing concepts from this domain. The paper describes how this activity can be carried out by mean of a terminological importation. Informally, a terminological importation partially populates an abstract terminology with concepts taken from a given domain. The information provided by the importation can be used by the acquisition and validation facilities to constraint the classes of knowledge that can be described using the representation formalism according to the domain knowledge. KSM provides the LINK-S language to specify terminological importation from a domain terminology to an abstract one. These terminologies are described in KSM by mean of the CONCEL language. Terminological importation is used to adapt reusable primitives of representation in order to increase the usability degree of such components in these domains. In addition, two primitives of representation can share a common vocabulary by importing common domain CONCEL terminologies (conceptual vocabularies). It is a necessary condition to make possible the interoperability between different, heterogeneous knowledge representation components in the framework of complex knowledge - based architectures.

Application of knowledge engineering acquisition techniques to requirements capture: a case study

In this paper we want to point out, by means of a case study, the importance of incorporating some knowledge engineering techniques to the processes of software engineering. Precisely, we are referring to the knowledge eduction techniques. We know the difficulty of requirements acquisition and its importance to minimise the risks of a software project, both in the development phase and in the maintenance phase. To capture the functional requirements use cases are generally used. However, as we will show in this paper, this technique is insufficient when the problem domain knowledge is only in the "experts? mind". In this situation, the combination of the use case with eduction techniques, in every development phase, will let us to discover the correct requirements.

KEMNAD:a knowledge engineering methodology for negotiating agent development

Automated negotiation is widely applied in various domains. However, the development of such systems is a complex knowledge and software engineering task. So, a methodology there will be helpful. Unfortunately, none of existing methodologies can offer sufficient, detailed support for such system development. To remove this limitation, this paper develops a new methodology made up of: (1) a generic framework (architectural pattern) for the main task, and (2) a library of modular and reusable design pattern (templates) of subtasks. Thus, it is much easier to build a negotiating agent by assembling these standardised components rather than reinventing the wheel each time. Moreover, since these patterns are identified from a wide variety of existing negotiating agents (especially high impact ones), they can also improve the quality of the final systems developed. In addition, our methodology reveals what types of domain knowledge need to be input into the negotiating agents. This in turn provides a basis for developing techniques to acquire the domain knowledge from human users. This is important because negotiation agents act faithfully on the behalf of their human users and thus the relevant domain knowledge must be acquired from the human users. Finally, our methodology is validated with one high impact system.

Upgradable Tree Levels Editor of Metaontologies, Ontologies and Knowledge for a Chemistry

* This paper has supported by Far Eastern Branch of the Russian Academy of Sciences, the project 06-III-A-01-005 and Russian Fund of Fundamental Investigation, the project 06-07-89071-a

Insect peptides with improved protease-resistance protect mice against bacterial infection

At a time of the emergence of drug-resistant bacterial strains, the development of antimicrobial compounds with novel mechanisms of action is of considerable interest. Perhaps the most promising among these is a family of antibacterial peptides originally isolated from insects. These were shown to act in a stereospecific manner on an as-yet unidentified target bacterial protein. One of these peptides, drosocin, is inactive in vivo due to the rapid decomposition in mammalian sera. However, another family member, pyrrhocoricin, is significantly more stable, has increased in vitro efficacy against Gram-negative bacterial strains, and if administered alone, as we show here, is devoid of in vitro or in vivo toxicity. At low doses, pyrrhocoricin protected mice against Escherichia call infection, but at a higher dose augmented the infection of compromised animals. Analogs of pyrrhocoricin were, therefore, synthesized to further improve protease resistance and reduce toxicity. A linear derivative containing unnatural amino acids at both termini showed high potency and lack of toxicity in vivo and an expanded cyclic analog displayed broad activity spectrum in vitro. The bioactive conformation of native pyrrhocoricin was determined by nuclear magnetic resonance spectroscopy, and similar to drosocin, reverse turns were identified as pharmacologically important elements at the termini, bridged by an extended peptide domain. Knowledge of the primary and secondary structural requirements for in vivo activity of these peptides allows the design of novel antibacterial drug leads.

Enterprise reference lexicon building from business models

Nowadays, a significant increase on the demand for interoperable systems for exchanging data in business collaborative environments has been noticed. Consequently, cooperation agreements between each of the involved enterprises have been brought to light. However, due to the fact that even in a same community or domain, there is a big variety of knowledge representation not semantically coincident, which embodies the existence of interoperability problems in the enterprises information systems that need to be addressed. Moreover, in relation to this, most organizations face other problems about their information systems, as: 1) domain knowledge not being easily accessible by all the stakeholders (even intra-enterprise); 2) domain knowledge not being represented in a standard format; 3) and even if it is available in a standard format, it is not supported by semantic annotations or described using a common and understandable lexicon. This dissertation proposes an approach for the establishment of an enterprise reference lexicon from business models. It addresses the automation in the information models mapping for the reference lexicon construction. It aggregates a formal and conceptual representation of the business domain, with a clear definition of the used lexicon to facilitate an overall understanding by all the involved stakeholders, including non-IT personnel.

User-centric product derivation in software product lines

Software Product Line (SPL) engineering aims at achieving efficient development of software products in a specific domain. New products are obtained via a process which entails creating a new configuration specifying the desired product’s features. This configuration must necessarily conform to a variability model, that describes the scope of the SPL, or else it is not viable. To ensure this, configuration tools are used that do not allow invalid configurations to be expressed. A different concern, however, is making sure that a product addresses the stakeholders’ needs as best as possible. The stakeholders may not be experts on the domain, so they may have unrealistic expectations. Also, the scope of the SPL is determined not only by the domain but also by limitations of the development platforms. It is therefore possible that the desired set of features goes beyond what is possible to currently create with the SPL. This means that configuration tools should provide support not only for creating valid products, but also for improving satisfaction of user concerns. We address this goal by providing a user-centric configuration process that offers suggestions during the configuration process, based on the use of soft constraints, and identifying and explaining potential conflicts that may arise. Suggestions help mitigating stakeholder uncertainty and poor domain knowledge, by helping them address well known and desirable domain-related concerns. On the other hand, automated conflict identification and explanation helps the stakeholders to understand the trade-offs required for realizing their vision, allowing informed resolution of conflicts. Additionally, we propose a prototype-based approach to configuration, that addresses the order-dependency issues by allowing the complete (or partial) specification of the features in a single step. A subsequent resolution process will then identify possible repairs, or trade-offs, that may be required for viabilization.

eVOC: a controlled vocabulary for unifying gene expression data.

Expression data contribute significantly to the biological value of the sequenced human genome, providing extensive information about gene structure and the pattern of gene expression. ESTs, together with SAGE libraries and microarray experiment information, provide a broad and rich view of the transcriptome. However, it is difficult to perform large-scale expression mining of the data generated by these diverse experimental approaches. Not only is the data stored in disparate locations, but there is frequent ambiguity in the meaning of terms used to describe the source of the material used in the experiment. Untangling semantic differences between the data provided by different resources is therefore largely reliant on the domain knowledge of a human expert. We present here eVOC, a system which associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. We have curated and annotated 7016 cDNA libraries represented in dbEST, as well as 104 SAGE libraries,with expression information,and provide this as an integrated, public resource that allows the linking of transcripts and libraries with expression terms. Both the vocabularies and the vocabulary-annotated libraries can be retrieved from http://www.sanbi.ac.za/evoc/. Several groups are involved in developing this resource with the aim of unifying transcript expression information.

Kuvausmenetelmänvalinta ja käyttöönotto ohjelmistotuoteorganisaatiossa

Useiden pitkän kehityskaaren ohjelmistojen ylläpitäminen ja kehittäminen on vaikeaa, sillä niiden dokumentaatio on vajaata tai vanhentunutta. Tässä diplomityössä etsitään ratkaisua tällaisen ohjelmiston ja sen taustalla olevan järjestelmän kuvaukseen. Tavoitteina on tukea nykyisen ohjelmiston ylläpitoa ja uuden työvoiman perehdyttämistä. Tavoitteena on myös pohjustaa uuden korvaavan ohjelmiston suunnittelua kuvaamalla nykyiseen järjestelmään sitoutunutta sovellusalueosaamista. Työssä kehitetään kuvausmenetelmä järjestelmän kuvaamiseen hierarkkisesti laitteistotason yleiskuvauksesta ohjelmiston luokkarakenteeseen sekä toiminnallisuuteen asti. Laite- ja luokkarakennekuvaukset ovat rakenteellisia kuvauksia, joiden tehtävänä on selittää järjestelmän ja sen osien kokoonpano. Toiminnallisuudesta kertovat kuvaukset on toteutettu käyttötapauskuvauksina. Työssä keskityttiin erityisesti kohdejärjestelmän keskeisen ohjelmiston ja tietokannan kuvaamiseen. Ohjelmistosta valittiin tärkeimmät ja eniten sovellusalueen tietotaitoa sisältävät osat, joista työssä luotiin esimerkkikuvaukset. Kuvauksia on kehitettyä menetelmää hyödyntäen helppo laajentaa tarpeiden mukaan paitsi ohjelmiston muihin osiin, myös laitteiston ja järjestelmän kuvaamiseen kokonaisuudessaan syvemmin.

Tietämyksen välittäminen ohjelmistotestausorganisaatioissa

Ohjelmistotestaus on suuri ja kasvava kustannuserä ohjelmistotuotannossa. Kirjallisuudessa mainittu ohjelmistotestauksen kustannusten osuus on noin 50% ohjelmistokehityshankkeiden budjetista. Tutkimusprojektin tarkoituksena on selvittää, kuinka ohjelmistotestauksen kustannusten kasvu saataisiin pysähtymään tai laskemaan laatua menettämättä. Tässä työssä keskitytään laadullisen analyysin kautta selvittämään ja ymmärtämään tietämyksen välittämistä ohjelmistotestausorganisaatiossa. Tutkimusmateriaali on kerätty haastattelemalla26 organisaatioyksikön edustajia. Näiden organisaatioyksiköiden joukosta on edelleen valittu viisi organisaatioyksikköä lähempään tarkasteluun. Työssä havaittiin muun muassa, että tuotesuuntautuneessa ohjelmistokehityksessä tietämystä on vaivattomampi kodifioida. Esimerkiksi testitapausten määrittäminen ennakkoon on tällöin helpompaa. Kodifiointi mahdollistaa myös testauksen laajamittaisen ulkoistamisen, sillä kodifioitua tietämystä on helpompi välittää. Räätälöityjen järjestelmien testaamisessa tarvittava tietämys vaikuttaa olevan suurelta osin hiljaista, esimerkiksi sovellusalueosaaminen painottuu enemmän.

Improving globally distributed software development and support processes - A workflow view

We propose a new approach and related indicators for globally distributed software support and development based on a 3-year process improvement project in a globally distributed engineering company. The company develops, delivers and supports a complex software system with tailored hardware components and unique end-customer installations. By applying the domain knowledge from operations management on lead time reduction and its multiple benefits to process performance, the workflows of globally distributed software development and multitier support processes were measured and monitored throughout the company. The results show that the global end-to-end process visibility and centrally managed reporting at all levels of the organization catalyzed a change process toward significantly better performance. Due to the new performance indicators based on lead times and their variation with fixed control procedures, the case company was able to report faster bug-fixing cycle times, improved response times and generally better customer satisfaction in its global operations. In all, lead times to implement new features and to respond to customer issues and requests were reduced by 50%.

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

Thinking Outside the Box: Enhancing Science Teaching by Combining (Instead of Contrasting) Laboratory and Simulation Activities

The focus of the present work was on 10- to 12-year-old elementary school students’ conceptual learning outcomes in science in two specific inquiry-learning environments, laboratory and simulation. The main aim was to examine if it would be more beneficial to combine than contrast simulation and laboratory activities in science teaching. It was argued that the status quo where laboratories and simulations are seen as alternative or competing methods in science teaching is hardly an optimal solution to promote students’ learning and understanding in various science domains. It was hypothesized that it would make more sense and be more productive to combine laboratories and simulations. Several explanations and examples were provided to back up the hypothesis. In order to test whether learning with the combination of laboratory and simulation activities can result in better conceptual understanding in science than learning with laboratory or simulation activities alone, two experiments were conducted in the domain of electricity. In these experiments students constructed and studied electrical circuits in three different learning environments: laboratory (real circuits), simulation (virtual circuits), and simulation-laboratory combination (real and virtual circuits were used simultaneously). In order to measure and compare how these environments affected students’ conceptual understanding of circuits, a subject knowledge assessment questionnaire was administered before and after the experimentation. The results of the experiments were presented in four empirical studies. Three of the studies focused on learning outcomes between the conditions and one on learning processes. Study I analyzed learning outcomes from experiment I. The aim of the study was to investigate if it would be more beneficial to combine simulation and laboratory activities than to use them separately in teaching the concepts of simple electricity. Matched-trios were created based on the pre-test results of 66 elementary school students and divided randomly into a laboratory (real circuits), simulation (virtual circuits) and simulation-laboratory combination (real and virtual circuits simultaneously) conditions. In each condition students had 90 minutes to construct and study various circuits. The results showed that studying electrical circuits in the simulation–laboratory combination environment improved students’ conceptual understanding more than studying circuits in simulation and laboratory environments alone. Although there were no statistical differences between simulation and laboratory environments, the learning effect was more pronounced in the simulation condition where the students made clear progress during the intervention, whereas in the laboratory condition students’ conceptual understanding remained at an elementary level after the intervention. Study II analyzed learning outcomes from experiment II. The aim of the study was to investigate if and how learning outcomes in simulation and simulation-laboratory combination environments are mediated by implicit (only procedural guidance) and explicit (more structure and guidance for the discovery process) instruction in the context of simple DC circuits. Matched-quartets were created based on the pre-test results of 50 elementary school students and divided randomly into a simulation implicit (SI), simulation explicit (SE), combination implicit (CI) and combination explicit (CE) conditions. The results showed that when the students were working with the simulation alone, they were able to gain significantly greater amount of subject knowledge when they received metacognitive support (explicit instruction; SE) for the discovery process than when they received only procedural guidance (implicit instruction: SI). However, this additional scaffolding was not enough to reach the level of the students in the combination environment (CI and CE). A surprising finding in Study II was that instructional support had a different effect in the combination environment than in the simulation environment. In the combination environment explicit instruction (CE) did not seem to elicit much additional gain for students’ understanding of electric circuits compared to implicit instruction (CI). Instead, explicit instruction slowed down the inquiry process substantially in the combination environment. Study III analyzed from video data learning processes of those 50 students that participated in experiment II (cf. Study II above). The focus was on three specific learning processes: cognitive conflicts, self-explanations, and analogical encodings. The aim of the study was to find out possible explanations for the success of the combination condition in Experiments I and II. The video data provided clear evidence about the benefits of studying with the real and virtual circuits simultaneously (the combination conditions). Mostly the representations complemented each other, that is, one representation helped students to interpret and understand the outcomes they received from the other representation. However, there were also instances in which analogical encoding took place, that is, situations in which the slightly discrepant results between the representations ‘forced’ students to focus on those features that could be generalised across the two representations. No statistical differences were found in the amount of experienced cognitive conflicts and self-explanations between simulation and combination conditions, though in self-explanations there was a nascent trend in favour of the combination. There was also a clear tendency suggesting that explicit guidance increased the amount of self-explanations. Overall, the amount of cognitive conflicts and self-explanations was very low. The aim of the Study IV was twofold: the main aim was to provide an aggregated overview of the learning outcomes of experiments I and II; the secondary aim was to explore the relationship between the learning environments and students’ prior domain knowledge (low and high) in the experiments. Aggregated results of experiments I & II showed that on average, 91% of the students in the combination environment scored above the average of the laboratory environment, and 76% of them scored also above the average of the simulation environment. Seventy percent of the students in the simulation environment scored above the average of the laboratory environment. The results further showed that overall students seemed to benefit from combining simulations and laboratories regardless of their level of prior knowledge, that is, students with either low or high prior knowledge who studied circuits in the combination environment outperformed their counterparts who studied in the laboratory or simulation environment alone. The effect seemed to be slightly bigger among the students with low prior knowledge. However, more detailed inspection of the results showed that there were considerable differences between the experiments regarding how students with low and high prior knowledge benefitted from the combination: in Experiment I, especially students with low prior knowledge benefitted from the combination as compared to those students that used only the simulation, whereas in Experiment II, only students with high prior knowledge seemed to benefit from the combination relative to the simulation group. Regarding the differences between simulation and laboratory groups, the benefits of using a simulation seemed to be slightly higher among students with high prior knowledge. The results of the four empirical studies support the hypothesis concerning the benefits of using simulation along with laboratory activities to promote students’ conceptual understanding of electricity. It can be concluded that when teaching students about electricity, the students can gain better understanding when they have an opportunity to use the simulation and the real circuits in parallel than if they have only the real circuits or only a computer simulation available, even when the use of the simulation is supported with the explicit instruction. The outcomes of the empirical studies can be considered as the first unambiguous evidence on the (additional) benefits of combining laboratory and simulation activities in science education as compared to learning with laboratories and simulations alone.

DAI-DEPUR: an integrated and distributed architecture for wastewater treatment plants supervision

The activated sludge process - the main biological technology usually applied to wastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take the necessary actions to restore the system’s performance. These decisions are often based both on physical, chemical, microbiological principles (suitable to be modelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AI architecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

Management of industrial wastewater discharges in river basins through agents'argumentation

La gestió de l'aigua residual és una tasca complexa. Hi ha moltes substàncies contaminants conegudes però encara moltes per conèixer, i el seu efecte individual o col·lgectiu és difícil de predir. La identificació i avaluació dels impactes ambientals resultants de la interacció entre els sistemes naturals i socials és un assumpte multicriteri. Els gestors ambientals necessiten eines de suport pels seus diagnòstics per tal de solucionar problemes ambientals. Les contribucions d'aquest treball de recerca són dobles: primer, proposar l'ús d'un enfoc basat en la modelització amb agents per tal de conceptualitzar i integrar tots els elements que estan directament o indirectament involucrats en la gestió de l'aigua residual. Segon, proposar un marc basat en l'argumentació amb l'objectiu de permetre als agents raonar efectivament. La tesi conté alguns exemples reals per tal de mostrar com un marc basat amb agents que argumenten pot suportar diferents interessos i diferents perspectives. Conseqüentment, pot ajudar a construir un diàleg més informat i efectiu i per tant descriure millor les interaccions entre els agents. En aquest document es descriu primer el context estudiat, escalant el problema global de la gestió de la conca fluvial a la gestiódel sistema urbà d'aigües residuals, concretament l'escenari dels abocaments industrials. A continuació, s'analitza el sistema mitjançant la descripció d'agents que interaccionen. Finalment, es descriuen alguns prototips capaços de raonar i deliberar, basats en la lògica no monòtona i en un llenguatge declaratiu (answer set programming). És important remarcar que aquesta tesi enllaça dues disciplines: l'enginyeria ambiental (concretament l'àrea de la gestió de les aigües residuals) i les ciències de la computació (concretament l'àrea de la intel·ligència artificial), contribuint així a la multidisciplinarietat requerida per fer front al problema estudiat. L'enginyeria ambiental ens proporciona el coneixement del domini mentre que les ciències de la computació ens permeten estructurar i especificar aquest coneixement.