Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

Pattern based fact extraction from Estonian free-texts

Vabatekstide töötlus on üks keerulisemaid probleeme arvutiteaduses. Tekstide täpne analüüs on tihti mitmestimõistetavuse tõttu arvutite jaoks keeruline või võimatu. Sellegipoolest on võimalik teatud fakte eraldada. Käesolevas töös uurime mustripõhiseid meetodeid faktide tuletamiseks eesti keelsetest tekstidest. Rakendame oma metoodikat reaalsetel tekstidel ning analüüsime tulemusi. Kirjeldame lühidalt aktiivõppe metoodikat, mis võimaldab suuri korpuseid kiiremini märgendada. Lisaks oleme implementeerinud prototüüplahenduse korpuste märgendamiseks ning mustripõhise faktituletuse läbiviimiseks.Natural language processing is one of the most difficult problems, since words and language constructions have often ambiguous meaning that cannot be resolved without extensive cultural background. However, some facts are easier to deduce than the others. In this work, we consider unary, binary and ternary relations between the words that can be deduced form a single sentence. The relations represented by sets of patterns are combined with basic machine learning methods, that are used to train and deploy patterns for fact extraction. We also describe the process of active learning, which helps to speed up annotating relations in large corpora. Other contributions include a prototype implementation with plain-text preprocessor, corpus annotator, pattern miner and fact extractor. Additionally, we provide empirical study about the efficiency of the prototype implementation with several relations and corpora

Wavelet and Multiscale Methods

Various scientific models demand finer and finer resolutions of relevant features. Paradoxically, increasing computational power serves to even heighten this demand. Namely, the wealth of available data itself becomes a major obstruction. Extracting essential information from complex structures and developing rigorous models to quantify the quality of information leads to tasks that are not tractable by standard numerical techniques. The last decade has seen the emergence of several new computational methodologies to address this situation. Their common features are the nonlinearity of the solution methods as well as the ability of separating solution characteristics living on different length scales. Perhaps the most prominent examples lie in multigrid methods and adaptive grid solvers for partial differential equations. These have substantially advanced the frontiers of computability for certain problem classes in numerical analysis. Other highly visible examples are: regression techniques in nonparametric statistical estimation, the design of universal estimators in the context of mathematical learning theory and machine learning; the investigation of greedy algorithms in complexity theory, compression techniques and encoding in signal and image processing; the solution of global operator equations through the compression of fully populated matrices arising from boundary integral equations with the aid of multipole expansions and hierarchical matrices; attacking problems in high spatial dimensions by sparse grid or hyperbolic wavelet concepts. This workshop proposed to deepen the understanding of the underlying mathematical concepts that drive this new evolution of computation and to promote the exchange of ideas emerging in various disciplines

Framework for operability assessment of production facilities: an application to a primary unit of a crude oil refinery

This work focuses on the development of a methodology for the optimization, control and operability of both existing and new production facilities through an integrated environment of different technologies like process simulation, optimization and control systems. Such an integrated environment not only creates opportunities for op¬erational decision making but also serves as training tool for the novice engineers. It enables them to apply engineering expertise to solve challenges unique to the process industries in a safe and virtual environment and also assist them to get familiarize with the existing control systems and to understand the fundamentals of the plant operation. The model-based methodology proposed in this work, starts with the implementation of first principle models for the process units on consideration. The process model is the core of the methodology. The state of art simulation technologies have been used to model the plant for both steady state and dynamic state conditions. The models are validated against the plant operating data to evaluate the reliability of the models. Then it is followed by rigorously posing a multi-optimization problem. In addition to the basic economic variables such as raw materials and operating costs, the so-called “triple-bottom-line” variables related with sustainable and environmental costs are incorporated into the objective function. The methodologies of Life Cycle Assessment (LCA) and Environmental Damage Assessment (EDA) are applied within the optimization problem. Subsequently the controllability of the plant for the optimum state of conditions is evaluated using the dynamic state simulations. Advanced supervisory control strategies like the Model Predictive Control (MPC) are also implemented above the basic regulatory control. Finally, the methodology is extended further to develop training simulator by integrating the simulation case study to the existing Distributed Control System (DCS). To demonstrate the effectiveness of the proposed methodology, an industrial case study of the primary unit of the crude oil refinery and a laboratory scale packed distillation unit is thoroughly investigated. The presented methodology is a promising approach for the operability study and optimization of production facilities and can be extended further for an intelligent and fully-supportable decision making

Life cycle sustainability assessment for selecting construction materials in the preliminary design phase of road construction projects

Road construction project activities cause severe harm to the environment as they consume a tremendous volume of materials and release pollutants into the environment. Besides, an increasing number of researchers is participating in work related to sustainability in the construction industry as well as road construction projects. Similar to other life cycles, a strong influence on sustainability is exerted in the early phases of road construction projects, especially in the preliminary design phase. Especially selecting materials is one of the most critical tasks in this phase because it contributes considerably to the achievement of sustainability targets. For enabling a conscious and systematic selection of materials, a significant evaluation of materials with regard to the three dimensions of sustainability is necessary. However, a well-elaborated and mature instrument supporting such an evaluation has not been developed and presented in literature until now. In the contrary, several studies revealed that the material-dependent activities and the life cycle analysis have been neglected so far. Moreover, selecting materials in the preliminary design phase is mainly based on designers’ experience and not on the application of analytic methods. Such selection is highly error-prone. In this thesis, current material selection methods for sustainable development in the preliminary design phase were analyzed. Initially, material selection studies conducted in the early design phase were analyzed to determine the relevant issues. The result emphasized that the integration of sustainability into material selection in the preliminary design phase encountered many obstacles, such as unavailable information and databases. Then, the most important sustainability criteria for selecting road construction materials were identified, covering the economic, environmental, and social dimensions of sustainability. Next, approaches which suggest the application of LCC, LCA, Social LCA, MCDM, and LCSA in road construction material selection are discussed in order to identify their limitations. Accordingly, this thesis developed an instrument based on the LCC, LCA, Social LCA, MCDM methods, and LCSA for assessing the sustainability performance of road construction materials in the preliminary design phase. The instrument is intended to help designers select the most sustainable materials by addressing the issues that emerge in the preliminary design phase. Firstly, a procedure model for evaluating the sustainability performance of road construction materials is suggested. It is based on two existing procedure models. One is a decision theory-based procedure model for sustainability-oriented evaluations. The model is divided into two levels, with the overall sustainability performance evaluation at the first level and the evaluation of the economic, environmental, and social performances at the second level. Although this procedure model demonstrates some benefits and has been utilized in some cases, the four-step LCA procedure, according to ISO 14044, appears to be more prevalent and well-established. Therefore, it is suggested here to integrate both approaches. This procedure model contributes to integrating the LCC, LCA, and Social LCA). Secondly, this instrument for assessing the sustainable performance of materials is further developed based on the step-by-step models of three pillars of sustainability. This allows for employing numerical methods from the LCC, LCA and Social LCA and thereby reducing the mistakes from the experience-based selection of designers. The proposed instrument also addresses the specific challenges of material selection in the preliminary design phase. The LCC could refine all material-dependent costs incurred during the life cycle and evaluate the material alternatives' total cost. Besides, it defines long-term outcomes by dividing the material life cycle into many consecutive phases and applying the time value of money into the calculation. For the LCA, two scenarios are proposed to solve the problems concerning the lack of available information in the preliminary design phase. Besides, the environmental performance of material-dependent activities, such as the usage of equipment and labor, is also considered in the method. The Social LCA is developed based on the Performance Preference Point (PPR) approach and the Subcategory Assessment Method (SAM) to assess the social performance of road construction materials. The method also shows the potential to support the designers in selecting the most social-friendly material by considering the material-dependent activities and stakeholders. The LCC, LCA, and Social LCA analyses integrated into the LCSA to come up with the general perspective of sustainable level. From the perspective of decision-makers, the importance level of sustainability dimensions might be different. The study suggests applying the AHP method and Likert Scale to evaluate the weightings and then integrating them into the LCSA model to assess the general sustainability performance of road construction materials. After that, a ternary diagram can be drawn to provide a comprehensive picture of the road construction material selection in dependence on these weightings. The assessment of two alternatives, “concrete bricks” and “baked bricks”, was conducted as a case study to illustrate and demonstrate the procedure model

Keyword-Based Querying for the Social Semantic Web

Enabling non-experts to publish data on the web is an important achievement of the social web and one of the primary goals of the social semantic web. Making the data easily accessible in turn has received only little attention, which is problematic from the point of view of incentives: users are likely to be less motivated to participate in the creation of content if the use of this content is mostly reserved to experts. Querying in semantic wikis, for example, is typically realized in terms of full text search over the textual content and a web query language such as SPARQL for the annotations. This approach has two shortcomings that limit the extent to which data can be leveraged by users: combined queries over content and annotations are not possible, and users either are restricted to expressing their query intent using simple but vague keyword queries or have to learn a complex web query language. The work presented in this dissertation investigates a more suitable form of querying for semantic wikis that consolidates two seemingly conflicting characteristics of query languages, ease of use and expressiveness. This work was carried out in the context of the semantic wiki KiWi, but the underlying ideas apply more generally to the social semantic and social web. We begin by defining a simple modular conceptual model for the KiWi wiki that enables rich and expressive knowledge representation. A component of this model are structured tags, an annotation formalism that is simple yet flexible and expressive, and aims at bridging the gap between atomic tags and RDF. The viability of the approach is confirmed by a user study, which finds that structured tags are suitable for quickly annotating evolving knowledge and are perceived well by the users. The main contribution of this dissertation is the design and implementation of KWQL, a query language for semantic wikis. KWQL combines keyword search and web querying to enable querying that scales with user experience and information need: basic queries are easy to express; as the search criteria become more complex, more expertise is needed to formulate the corresponding query. A novel aspect of KWQL is that it combines both paradigms in a bottom-up fashion. It treats neither of the two as an extension to the other, but instead integrates both in one framework. The language allows for rich combined queries of full text, metadata, document structure, and informal to formal semantic annotations. KWilt, the KWQL query engine, provides the full expressive power of first-order queries, but at the same time can evaluate basic queries at almost the speed of the underlying search engine. KWQL is accompanied by the visual query language visKWQL, and an editor that displays both the textual and visual form of the current query and reflects changes to either representation in the other. A user study shows that participants quickly learn to construct KWQL and visKWQL queries, even when given only a short introduction. KWQL allows users to sift the wealth of structure and annotations in an information system for relevant data. If relevant data constitutes a substantial fraction of all data, ranking becomes important. To this end, we propose PEST, a novel ranking method that propagates relevance among structurally related or similarly annotated data. Extensive experiments, including a user study on a real life wiki, show that pest improves the quality of the ranking over a range of existing ranking approaches

Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques

Sustainability Assessment at the 21st century

The sustainability of the human society is endangered by the global human-ecological crisis, which consists of many global problems that are closely related to each other. In this phenomenon, the global population explosion has a central role, because more people have a larger ecological footprint, a larger consumption, more intensive pollution, and a larger emission of carbon dioxide through their activities.This book presents the current state of sustainability and intends to provide the reader with a critical perspective of how the 21st century societies must change their development model facing the new challenges (internet of things, industry 4.0, smart cities, circular economy, sustainable agriculture, etc.), in order to achieve a more liveable world