Organic potatoes for processing

Drei Feldversuche auf zwei Standorten (DFH: 51°4, 9°4’, BEL: 52°2’, 8°08’) wurden in den Jahren 2002 bis 2004 durchgeführt, um den Einfluss der Vorfrucht, des Vorkeimens, der N- und K-Düngung und der Sorte auf Nährstoffverfügbarkeit, Gesamt- und sortierte Knollenerträge sowie die Qualität von Kartoffeln und deren Eignung für die industrielle Verarbeitung zu Pommes frites und Chips zu untersuchen. Bestimmt wurden die N- und K-Verfügbarkeit im Boden, die N- und K-Aufnahme von Kraut und Knollen, gesamte Frisch- und Trockenmasseerträge, sortierte Frischmasseerträge für die Verarbeitung, sowie die Gehalte der Knollen an Trockensubstanz und reduzierenden Zuckern. In einer sensorischen Prüfung wurden Qualitätsparameter von Pommes frites (Aussehen/Farbe, Textur und Geschmack/Geruch) bewertet, die gewichtet in einen Qualitätsindex eingingen. Die Qualität der Chips wurde maschinell durch den L-Wert (Helligkeit) des Produktes quantifiziert. Der Gehalt des Bodens an mineralisiertem Nitrat-Stickstoff hing von der Vorfrucht und dem Jahr ab. Nach Erbsen wurden zum Auflaufen der Kartoffeln in den Versuchsjahren 2003 und 2004 (187 und 132 kg NO3-N ha-1) die höchsten NO3-N-Werte in 0-60 cm Boden gemessen verglichen mit Kleegras (169 bzw. 108 kg NO3-N ha-1 oder Getreide (112 kg bzw. 97 kg NO3-N ha-1), obgleich die Differenz nicht in allen Fällen signifikant war. Entsprechend wurden nach Erbsen die höchsten Knollen-Frischmasseerträge (414 und 308 dt ha-1) geerntet. Dasselbe galt für die Trockenmasserträge, was belegt, dass der Trockensubstanzgehalt der Knollen bei verbesserter N-Versorgung nicht im selben Maße sinkt, wie der Frischmasseertrag steigt. Das Vorkeimen der Pflanzknollen führte zu einer rascheren phänologischen Entwicklung im Jugendstadium der Pflanze, beschleunigter Trockenmassebildung des Krautes und einer früheren Einlagerung von Assimilaten vom Kraut in die Knollen. Obwohl die positive Wirkung des Vorkeimens auf den Gesamtertrag bis Ende Juli (+ 26 in 2003 bzw. 34 dt ha-1 in 2004) im Jahr ohne Krautfäuleepidemie von den nicht vorgekeimten Varianten bis zur Endernte im September kompensiert wurde, konnte in diesem Jahr durch Vorkeimen dennoch ein erhöhter Ertragsanteil (+ 12%) der besonders nachgefragten Übergrößen (>50 mm für Pommes frites) erzielt werden. Die durchschnittliche Knollenmasse reagierte positiv auf Vorkeimen (+ 5,4 g), Sortenwahl (Sorte Agria) und ein erhöhtes N-Angebot (Leguminosenvorfrucht). Generell wurde deutlich, dass die Knollengesamterträge unter den Bedingungen des Ökologischen Landbaus (geringe bis mittlere Nährstoffversorgung, verkürzte Vegetationsdauer) sehr stark vom Anbaujahr abhängen. Die Ergebnisse belegen jedoch, dass organisch-mineralische N-K-Düngung den sortierten Ertrag an Knollen für die Verarbeitung signifikant erhöht: Höchste Gesamt- und sortierte Knollenfrischmasseerträge wurden nach kombinierter N (Horngrieß) und mineralischer K- (Kaliumsulfat) Gabe erzielt (348 dt ha-1 im Durchschnitt von 2002-2004). Im Gegensatz dazu kann eine Wirkung von Stallmist auf den Ertrag im Jahr der Ausbringung nicht unbedingt erwartet werden. Steigende Erträge nach Stallmistdüngung wurden lediglich in einem von drei Versuchsjahren (+58 dt ha-1) festgestellt und ließen sich eher auf eine K- als eine N-Wirkung zurückführen. Die Ergebnisse belegen, dass die Sortenwahl eine entscheidende Rolle spielt, wenn die Kartoffeln für die industrielle Verarbeitung zu den oben genannten Produkten angebaut werden. Insgesamt kann festgestellt werden, dass Kartoffelknollen aus ökologischen Anbauverfahren ausreichend hohe Trockensubstanzgehalte aufweisen, um für die Verarbeitung zu Pommes frites (>19%) geeignet zu sein und ohne dass dadurch die Konsistenz des Endproduktes gefährdet würde. Der Trockensubstanzgehalt der Referenzsorte für Chips, „Marlen“, unterschritt das in der Literatur geforderte Minimum für Chips von 23% lediglich, wenn die kombinierte Horngrieß-Kaliumsulfatdüngung zur Anwendung kam. Die Trockensubstanzgehalte der Knollen konnten durch Vorkeimen signifikant gesteigert werden und der Effekt war besonders groß (+1.2% absolut) in dem Jahr mit frühem Auftreten der Krautfäule (Phytophthora infestans), d.h. verkürzter Vegetationszeit. Die Knollen-Trockensubstanzgehalte waren in zwei von drei Experimenten nach Lagerung höher (+0.4 und 0.5% absolut) als noch zur Ernte. Sorten der sehr frühen und frühen Reifegruppe wiesen den größten relativen Anstieg der Gehalte an reduzierenden Zuckern (Glukose und Fruktose) während der Lagerung auf. Den mittelfrühen Sorten „Agria“ und „Marena“ hingegen kann aufgrund des von ihnen erreichten höchsten Qualitätsstandards (Pommes frites) zur Ernte eine sehr gute Eignung für die Bedingungen des Ökologischen Landbaus unterstellt werden. Die durchgehend beste Chipseignung wies die mittelfrühe Referenzsorte „Marlen“ auf. Insgesamt konnte nachgewiesen werden, dass durch gezielte Sortenwahl der Trockensubstanzgehalt und die Konzentration reduzierender Zucker, sowie die Qualität der Endprodukte (Pommes frites und Chips) gezielt beeinflusst werden kann. Im Gegensatz dazu haben acker- und pflanzenbauliche Maßnahmen wie Düngung, Wahl der Vorfrucht und Vorkeimen der Pflanzknollen einen eher geringen Einfluss. Dementsprechend sollte der Landwirt versuchen, durch die Wahl der Sorte den hohen Anforderungen der Industrie an die Rohware gerecht zu werden.

On-line analytical processing with conceptual information systems

A conceptual information system consists of a database together with conceptual hierarchies. The management system TOSCANA visualizes arbitrary combinations of conceptual hierarchies by nested line diagrams and allows an on-line interaction with a database to analyze data conceptually. The paper describes the conception of conceptual information systems and discusses the use of their visualization techniques for on-line analytical processing (OLAP).

A Language for Interactive Cooperative Agents

Cooperative behaviour of agents within highly dynamic and nondeterministic domains is an active field of research. In particular establishing highly responsive teamwork, where agents are able to react on dynamic changes in the environment while facing unreliable communication and sensory noise, is an open problem. Moreover, modelling such responsive, cooperative behaviour is difficult. In this work, we specify a novel model for cooperative behaviour geared towards highly dynamic domains. In our approach, agents estimate each other’s decision and correct these estimations once they receive contradictory information. We aim at a comprehensive approach for agent teamwork featuring intuitive modelling capabilities for multi-agent activities, abstractions over activities and agents, and a clear operational semantic for the new model. This work encompasses a complete specification of the new language, ALICA.

Conceptual knowledge processing with formal concept analysis and ontologies

Among many other knowledge representations formalisms, Ontologies and Formal Concept Analysis (FCA) aim at modeling ‘concepts’. We discuss how these two formalisms may complement another from an application point of view. In particular, we will see how FCA can be used to support Ontology Engineering, and how ontologies can be exploited in FCA applications. The interplay of FCA and ontologies is studied along the life cycle of an ontology: (i) FCA can support the building of the ontology as a learning technique. (ii) The established ontology can be analyzed and navigated by using techniques of FCA. (iii) Last but not least, the ontology may be used to improve an FCA application.

A finite state model for on-line analytical processing in triadic contexts

About ten years ago, triadic contexts were presented by Lehmann and Wille as an extension of Formal Concept Analysis. However, they have rarely been used up to now, which may be due to the rather complex structure of the resulting diagrams. In this paper, we go one step back and discuss how traditional line diagrams of standard (dyadic) concept lattices can be used for exploring and navigating triadic data. Our approach is inspired by the slice & dice paradigm of On-Line-Analytical Processing (OLAP). We recall the basic ideas of OLAP, and show how they may be transferred to triadic contexts. For modeling the navigation patterns a user might follow, we use the formalisms of finite state machines. In order to present the benefits of our model, we show how it can be used for navigating the IT Baseline Protection Manual of the German Federal Office for Information Security.

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Optimization of Processing Technology for Commercial Drying of Bananas (Matooke)

Summary - Cooking banana is one of the most important crops in Uganda; it is a staple food and source of household income in rural areas. The most common cooking banana is locally called matooke, a Musa sp triploid acuminate genome group (AAA-EAHB). It is perishable and traded in fresh form leading to very high postharvest losses (22-45%). This is attributed to: non-uniform level of harvest maturity, poor handling, bulk transportation and lack of value addition/processing technologies, which are currently the main challenges for trade and export, and diversified utilization of matooke. Drying is one of the oldest technologies employed in processing of agricultural produce. A lot of research has been carried out on drying of fruits and vegetables, but little information is available on matooke. Drying of matooke and milling it to flour extends its shelf-life is an important means to overcome the above challenges. Raw matooke flour is a generic flour developed to improve shelf stability of the fruit and to find alternative uses. It is rich in starch (80 - 85%db) and subsequently has a high potential as a calorie resource base. It possesses good properties for both food and non-food industrial use. Some effort has been done to commercialize the processing of matooke but there is still limited information on its processing into flour. It was imperative to carry out an in-depth study to bridge the following gaps: lack of accurate information on the maturity window within which matooke for processing into flour can be harvested leading to non-uniform quality of matooke flour; there is no information on moisture sorption isotherm for matooke from which the minimum equilibrium moisture content in relation to temperature and relative humidity is obtainable, below which the dry matooke would be microbiologically shelf-stable; and lack of information on drying behavior of matooke and standardized processing parameters for matooke in relation to physicochemical properties of the flour. The main objective of the study was to establish the optimum harvest maturity window and optimize the processing parameters for obtaining standardized microbiologically shelf-stable matooke flour with good starch quality attributes. This research was designed to: i) establish the optimum maturity harvest window within which matooke can be harvested to produce a consistent quality of matooke flour, ii) establish the sorption isotherms for matooke, iii) establish the effect of process parameters on drying characteristics of matooke, iv) optimize the drying process parameters for matooke, v) validate the models of maturity and optimum process parameters and vi) standardize process parameters for commercial processing of matooke. Samples were obtained from a banana plantation at Presidential Initiative on Banana Industrial Development (PIBID), Technology Business Incubation Center (TBI) at Nyaruzunga – Bushenyi in Western Uganda. A completely randomized design (CRD) was employed in selecting the banana stools from which samples for the experiments were picked. The cultivar Mbwazirume which is soft cooking and commonly grown in Bushenyi was selected for the study. The static gravitation method recommended by COST 90 Project (Wolf et al., 1985), was used for determination of moisture sorption isotherms. A research dryer developed for this research. All experiments were carried out in laboratories at TBI. The physiological maturity of matooke cv. mbwazirume at Bushenyi is 21 weeks. The optimum harvest maturity window for commercial processing of matooke flour (Raw Tooke Flour - RTF) at Bushenyi is between 15-21 weeks. The finger weight model is recommended for farmers to estimate harvest maturity for matooke and the combined model of finger weight and pulp peel ratio is recommended for commercial processors. Matooke isotherms exhibited type II curve behavior which is characteristic of foodstuffs. The GAB model best described all the adsorption and desorption moisture isotherms. For commercial processing of matooke, in order to obtain a microbiologically shelf-stable dry product. It is recommended to dry it to moisture content below or equal to 10% (wb). The hysteresis phenomenon was exhibited by the moisture sorption isotherms for matooke. The isoteric heat of sorption for both adsorptions and desorption isotherms increased with decreased moisture content. The total isosteric heat of sorption for matooke: adsorption isotherm ranged from 4,586 – 2,386 kJ/kg and desorption isotherm from 18,194– 2,391 kJ/kg for equilibrium moisture content from 0.3 – 0.01 (db) respectively. The minimum energy required for drying matooke from 80 – 10% (wb) is 8,124 kJ/kg of water removed. Implying that the minimum energy required for drying of 1 kg of fresh matooke from 80 - 10% (wb) is 5,793 kJ. The drying of matooke takes place in three steps: the warm-up and the two falling rate periods. The drying rate constant for all processing parameters ranged from 5,793 kJ and effective diffusivity ranged from 1.5E-10 - 8.27E-10 m2/s. The activation energy (Ea) for matooke was 16.3kJ/mol (1,605 kJ/kg). Comparing the activation energy (Ea) with the net isosteric heat of sorption for desorption isotherm (qst) (1,297.62) at 0.1 (kg water/kg dry matter), indicated that Ea was higher than qst suggesting that moisture molecules travel in liquid form in matooke slices. The total color difference (ΔE*) between the fresh and dry samples, was lowest for effect of thickness of 7 mm, followed by air velocity of 6 m/s, and then drying air temperature at 70˚C. The drying system controlled by set surface product temperature, reduced the drying time by 50% compared to that of a drying system controlled by set air drying temperature. The processing parameters did not have a significant effect on physicochemical and quality attributes, suggesting that any drying air temperature can be used in the initial stages of drying as long as the product temperature does not exceed gelatinization temperature of matooke (72˚C). The optimum processing parameters for single-layer drying of matooke are: thickness = 3 mm, air temperatures 70˚C, dew point temperature 18˚C and air velocity 6 m/s overflow mode. From practical point of view it is recommended that for commercial processing of matooke, to employ multi-layer drying of loading capacity equal or less than 7 kg/m², thickness 3 mm, air temperatures 70˚C, dew point temperature 18˚C and air velocity 6 m/s overflow mode.

Eine SPARQL-Schnittstelle für OData-Services

Enterprise-Resource-Planning-Systeme (ERP-Systeme) bilden für die meisten mittleren und großen Unternehmen einen essentiellen Bestandteil ihrer IT-Landschaft zur Verwaltung von Geschäftsdaten und Geschäftsprozessen. Geschäftsdaten werden in ERP-Systemen in Form von Geschäftsobjekten abgebildet. Ein Geschäftsobjekt kann mehrere Attribute enthalten und über Assoziationen zu anderen Geschäftsobjekten einen Geschäftsobjektgraphen aufspannen. Existierende Schnittstellen ermöglichen die Abfrage von Geschäftsobjekten, insbesondere mit Hinblick auf deren Attribute. Die Abfrage mit Bezug auf ihre Position innerhalb des Geschäftsobjektgraphen ist jedoch über diese Schnittstellen häufig nur sehr schwierig zu realisieren. Zur Vereinfachung solcher Anfragen können semantische Technologien, wie RDF und die graphbasierte Abfragesprache SPARQL, verwendet werden. SPARQL ermöglicht eine wesentlich kompaktere und intuitivere Formulierung von Anfragen gegen Geschäftsobjektgraphen, als es mittels der existierenden Schnittstellen möglich ist. Die Motivation für diese Arbeit ist die Vereinfachung bestimmter Anfragen gegen das im Rahmen dieser Arbeit betrachtete SAP ERP-System unter Verwendung von SPARQL. Zur Speicherung von Geschäftsobjekten kommen in ERP-Systemen typischerweise relationale Datenbanken zum Einsatz. Die Bereitstellung von SPARQL-Endpunkten auf Basis von relationalen Datenbanken ist ein seit längerem untersuchtes Gebiet. Es existieren verschiedene Ansätze und Tools, welche die Anfrage mittels SPARQL erlauben. Aufgrund der Komplexität, der Größe und der Änderungshäufigkeit des ERP-Datenbankschemas können solche Ansätze, die direkt auf dem Datenbankschema aufsetzen, nicht verwendet werden. Ein praktikablerer Ansatz besteht darin, den SPARQL-Endpunkt auf Basis existierender Schnittstellen zu realisieren. Diese sind weniger komplex als das Datenbankschema, da sie die direkte Abfrage von Geschäftsobjekten ermöglichen. Dadurch wird die Definition des Mappings erheblich vereinfacht. Das ERP-System bietet mehrere Schnittstellen an, die sich hinsichtlich des Aufbaus, der Zielsetzung und der verwendeten Technologie unterscheiden. Unter anderem wird eine auf OData basierende Schnittstelle zur Verfügung gestellt. OData ist ein REST-basiertes Protokoll zur Abfrage und Manipulation von Daten. Von den bereitgestellten Schnittstellen weist das OData-Interface gegenüber den anderen Schnittstellen verschiedene Vorteile bei Realisierung eines SPARQL-Endpunktes auf. Es definiert eine Abfragesprache und einen Link-Adressierungsmechanismus, mit dem die zur Beantwortung einer Anfrage benötigten Service-Aufrufe und die zu übertragende Datenmenge erheblich reduziert werden können. Das Ziel dieser Arbeit besteht in der Entwicklung eines Verfahrens zur Realisierung eines SPARQL-Endpunktes auf Basis von OData-Services. Dazu wird zunächst eine Architektur vorgestellt, die als Grundlage für die Implementierung eines entsprechenden Systems dienen kann. Ausgehend von dieser Architektur, werden die durch den aktuellen Forschungsstand noch nicht abgedeckten Bereiche ermittelt. Nach bestem Wissen ist diese Arbeit die erste, welche die Abfrage von OData-Schnittstellen mittels SPARQL untersucht. Dabei wird als Teil dieser Arbeit ein neuartiges Konzept zur semantischen Beschreibung von OData-Services vorgestellt. Dieses ermöglicht die Definition von Abbildungen der von den Services bereitgestellten Daten auf RDF-Graphen. Aufbauend auf den Konzepten zur semantischen Beschreibung wird eine Evaluierungssemantik erarbeitet, welche die Auflösung von Ausdrücken der SPARQL-Algebra gegen semantisch annotierte OData-Services definiert. Dabei werden die Daten aller OData-Services ermittelt, die zur vollständigen Abarbeitung einer Anfrage benötigt werden. Zur Abfrage der relevanten Daten wurden Konzepte zur Erzeugung der entsprechenden OData-URIs entwickelt. Das vorgestellte Verfahren wurde prototypisch implementiert und anhand zweier Anwendungsfälle für die im betrachteten Szenario maßgeblichen Servicemengen evaluiert. Mit den vorgestellten Konzepten besteht nicht nur die Möglichkeit, einen SPARQL-Endpunkt für ein ERP-System zu realisieren, vielmehr kann jede Datenquelle, die eine OData-Schnittstelle anbietet, mittels SPARQL angefragt werden. Dadurch werden große Datenmengen, die bisher für die Verarbeitung mittels semantischer Technologien nicht zugänglich waren, für die Integration mit dem Semantic Web verfügbar gemacht. Insbesondere können auch Datenquellen, deren Integration miteinander bisher nicht oder nur schwierig möglich war, über Systeme zur föderierten Abfrage miteinander integriert werden.

Simultaneous Drying and Separation of Composite Agricultural Material for Hay Processing

In composite agricultural materials such as grass, tee, medicinal plants; leaves and stems have a different drying time. By this behavior, after leaving the dryer, the stems may have greater moisture content than desired, while the leaves one minor, which can cause either the appearance of fungi or the collapse of the over-dried material. Taking into account that a lot of grass is dehydrated in forced air dryers, especially rotary drum dryers, this research was developed in order to establish conditions enabling to make a separation of the components during the drying process in order to provide a homogeneous product at the end. For this, a rotary dryer consisting of three concentric cylinders and a circular sieve aligned with the more internal cylinder was proposed; so that, once material enters into the dryer in the area of the inner cylinder, stems pass through sieve to the middle and then continue towards the external cylinder, while the leaves continue by the inner cylinder. For this project, a mixture of Ryegrass and White Clover was used. The characteristics of the components of a mixture were: Drying Rate in thin layer and in rotation, Bulk density, Projected Area, Terminal velocity, weight/Area Ratio, Flux through Rotary sieve. Three drying temperatures; 40°C, 60° C and 80° C, and three rotation speeds; 10 rpm, 20 rpm and 40 rpm were evaluated. It was found that the differences in drying time are the less at 80 °C when the dryer rotates at 40 rpm. Above this speed, the material adheres to the walls of the dryer or sieve and does not flow. According to the measurements of terminal velocity of stems and leaves of the components of the mixture, the speed of the air should be less than 1.5 m s-1 in the inner drum for the leaves and less than 4.5 m s-1 in middle and outer drums for stems, in such way that only the rotational movement of the dryer moves the material and achieves a greater residence time. In other hand, the best rotary sieve separation efficiencies were achieved when the material is dry, but the results are good in all the moisture contents. The best rotary speed of sieve is within the critical rotational speed, i.e. 20 rpm. However, the rotational speed of the dryer, including the sieve in line with the inner cylinder should be 10 rpm or less in order to achieve the greatest residence times of the material inside the dryer and the best agitation through the use of lifting flights. With a finite element analysis of a dryer prototype, using an air flow allowing speeds of air already stated, I was found that the best performance occurs when, through a cover, air enters the dryer front of the Middle cylinder and when the inner cylinder is formed in its entirety through a sieve. This way, air flows in almost equal amounts by both the middle and external cylinders, while part of the air in the Middle cylinder passes through the sieve towards the inner cylinder. With this, leaves do not adhere to the sieve and flow along drier, thanks to the rotating movement of the drums and the showering caused by the lifting flights. In these conditions, the differences in drying time are reduced to 60 minutes, but the residence time is higher for the stems than for leaves, therefore the components of the mixture of grass run out of the dryer with the same desired moisture content.