IRRIGATE: A dynamic integrated model combining a knowledge-based model and mechanistic biophysical models for border irrigation management

Water management practices in southern France (the Crau plain) need to be modified in order to ensure greater water use efficiency and less environmental damage while maintaining hay production levels. Farmers, water managers and policy makers have expressed the need for new methods to deal with these issues. We developed the biodecisional model IRRIGATE to test new irrigation schedules, new designs for water channels or fields and new distribution planning for a given water resource. IRRIGATE simulates the operation of a hay cropping system irrigated by flood irrigation and includes three main features: (i) border irrigation with various durations of irrigation events and various spatial orders of water distribution, (ii) species-rich grasslands highly sensitive to water deficit, (iii) interactions between irrigation and mowing. It is based on existing knowledge, adapted models and new modules based on experiments and survey data. It includes a rule-based model on the farm scale, simulating dynamically both irrigation and mowing management, and two biophysical models. The two biophysical models are a dynamic crop model on the field scale simulating plant and soil behaviour in relation to water supply, and a flood irrigation model on the border scale simulating an irrigation event according to plant and hydraulic parameters. Model outputs allow environmental (water supply, drainage), social (labour) and agronomic (yields, water productivity and irrigation efficiency) analyses of the performance of the cropping system. IRRIGATE was developed using firstly a conceptual framework describing the system modelled as three sub-systems (biophysical, technical, and decision) interacting within the farm. Then a component-based spatially explicit modelling based on the identification of the interactions between modules, the identification of temporal and spatial scales of modules and the re-use of previous models was used to develop the numerical model. An example of the use of the biodecisional model is presented showing the effects on a real farm of a severe water shortage in 2006.     

Searching for simplified farmers' crop choice models for integrated watershed management in Thailand: A data mining approach

This study used the C4.5 data mining algorithm to model farmers' crop choice in two watersheds in Thailand. Previous attempts in the Integrated Water Resource Assessment and Management Project to model farmers' crop choice produced large sets of decision rules. In order to produce simplified models of farmers' crop choice, data mining operations were applied for each soil series in the study areas. The resulting decision trees were much smaller in size. Land type, water availability, tenure, capital, labor availability as well as non-farm and livestock income were found to be important considerations in farmers' decision models. Profitability was also found important although it was represented in approximate ranges. Unlike the general wisdom on farmers' crop choice, these decision trees came with threshold values and sequential order of the important variables. The decision trees were validated using the remaining unused set of data, and their accuracy in predicting farmers' decisions was around 84%. Because of their simple structure, the decision trees produced in this study could be useful to analysts of water resource management as they can be integrated with biophysical models for sustainable watershed management.     

A novel approach for generic home emergency management and remote monitoring

This paper presents a novel home emergency management system (HEMS) for managing home emergency situations. The proposed solution is a generic and based on normalized technologies. First, we have identified a set of requirements that a robust HEMS should satisfy (interoperability, security, mobility, etc). Then, we have opted for an extended finite‐state machine to detect and manage emergency situations. We also adopted WebRTC to enable communication in an interoperable manner. For securing our HEMS, we have used HTTPS, password, contextual role–based access control, and we have finally installed all the public servers into a protected area. The result obtained from the test‐bed demonstrates that the proposed HEMS fills all the listed requirements. Furthermore, it gives very interesting results in terms of round‐trip delay time and scalability.     

An integrated,generic approach to pattern mining: data mining template library

Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs. However, no practical framework for integrating the FPM tasks has been attempted. In this paper, we describe the design and implementation of the Data Mining Template Library (DMTL) for FPM. DMTL utilizes a generic data mining approach, where all aspects of mining are controlled via a set of properties. It uses a novel pattern property hierarchy to define and mine different pattern types. This property hierarchy can be thought of as a systematic characterization of the pattern space, i.e., a meta-pattern specification that allows the analyst to specify new pattern types, by extending this hierarchy. Furthermore, in DMTL all aspects of mining are controlled by a set of different mining properties. For example, the kind of mining approach to use, the kind of data types and formats to mine over, the kind of back-end storage manager to use, are all specified as a list of properties. This provides tremendous flexibility to customize the toolkit for various applications. Flexibility of the toolkit is exemplified by the ease with which support for a new pattern can be added. Experiments on synthetic and public dataset are conducted to demonstrate the scalability provided by the persistent back-end in the library. DMTL been publicly released as open-source software (), and has been downloaded by numerous researchers from all over the world.     

Design of decision model for sensitive crop irrigation system

Agriculture Industry is highly dependent on environmental and weather conditions. Many times, crops are spoiled because of sudden changes in weather. Therefore, we need a decision model to take care the water requirement of sensitive crops of agriculture industry. The proposed work presents a novel and proficient hybrid model for sensitive crop irrigation system (SCIS). For implementation of the model, brassica crop is taken. The duration and amount of water to be supplied is based upon the weather prediction and soil condition information. The decision model is developed using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) for brassica crops. In this model, if the input data values are available in range, then ANFIS model would be preferred and if the data sets are available for training, testing and validation then ANN model would be the best choice. The soil moisture, soil status in terms of temperature and leaf wetness are the input and flow control of sprinklers is the out for SCIS. The predicted outputs are analysed to assert the suitability of the proposed approach in the brassica crops. The proposed SCIS achieved an accuracy of 91% and 99% for ANFIS and ANN models respectively.     

A holistic and principled approach for the empty-answer problem

We propose a principled optimization-based interactive query relaxation framework for queries that return no answers. Given an initial query that returns an empty-answer set, our framework dynamically computes and suggests alternative queries with fewer conditions than those the user has initially requested, in order to help the user arrive at a query with a non-empty-answer, or at a query for which no matter how many additional conditions are ignored, the answer will still be empty. Our proposed approach for suggesting query relaxations is driven by a novel probabilistic framework based on optimizing a wide variety of application-dependent objective functions. We describe optimal and approximate solutions of different optimization problems using the framework. Moreover, we discuss two important extensions to the base framework: the specification of a minimum size on the number of results returned by a relaxed query and the possibility of proposing multiple conditions at the same time. We analyze the proposed solutions, experimentally verify their efficiency and effectiveness, and illustrate their advantages over the existing approaches.     

SPASS: a generic process-oriented crop model with versatile windows interfaces

Crop simulation models are now widely used in agronomy. A highly modular structure has been developed for crop growth simulation models based on the essential processes that are common to various plant species. This generic process-oriented modular structure was implemented in the SPASS (Soil-Plant-Atmosphere System Simulation) model using Microsoft Visual C/C++ under Windows. SPASS is composed of six parts: (i) data management, (ii) memory allocation/initialization, (iii) Modules for crop, soil and microclimate processes, (iv) model configuration and simulation, (v) graphic/table display and (vi) model knowledge integration. The model can be easily configured using the Windows interface by choosing various combinations of process modules developed based on different model approaches. Up to 30 graphic and 5 table MDI (Multiple Document Interface) child windows can be opened during or after the simulation run. Each child window can be resized freely on the screen for the convenience of data analysis. The model theory can be easily viewed using the online theory book. The SPASS model structure facilitates comparison of different model approaches, transfer of improvements between models, development of multi-crop models and modification of process modules for new applications.     

An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands

The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of the crop modeling system DSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model (WaSSI). GriDSSAT and WaSSI are coupled through the USDA NASS CropScape data to provide crop acreages in each watershed. The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model responds to the weather and includes all other anthropogenic competing uses of water. Examples of the system include an analysis of the hydrologic impact of future expansion of irrigation and the real-time impact of short-term drought.     

Supply chain design: A holistic approach

Local considerations are one of the major pitfalls in designing, operating and managing systems. As such are the “Supply Chain design decisions”, hence we have tried to incorporate systems thinking approach, and in particular the “Theory of Constraints”, into the problem of “Locating a new Distribution Center” among a producer and a set of existing retailers. While customers face known random demand, we look for the least cost location candidate in a plane with direct shipping. Usefulness of an equity function to balance the inventory levels at retail shops is also discussed. The model is finally reduced to a single nonlinear objective and for a hypothetical numerical example it is solved by Particle Swarm Optimization method.     

A holistic approach to collaborative ontology development based on change management

This paper describes our methodological and technological approach for collaborative ontology development in inter-organizational settings. It is based on the formalization of the collaborative ontology development process by means of an explicit editorial workflow, which coordinates proposals for changes among ontology editors in a flexible manner. This approach is supported by new models, methods and strategies for ontology change management in distributed environments: we propose a new form of ontology change representation, organized in layers so as to provide as much independence as possible from the underlying ontology languages, together with methods and strategies for their manipulation, version management, capture, storage and maintenance, some of which are based on existing proposals in the state of the art. Moreover, we propose a set of change propagation strategies that allow keeping distributed copies of the same ontology synchronized. Finally, we illustrate and evaluate our approach with a test case in the fishery domain from the United Nations Food and Agriculture Organisation (FAO). The preliminary results obtained from our evaluation suggest positive indication on the practical value and usability of the work here presented.     

An integrated fuzzy-GA approach for buffer management

This paper deals with a novel buffer management scheme based on evolutionary computing for shared-memory asynchronous transfer mode (ATM) switches. The philosophy behind it is adaptation of the threshold for each logical output queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology, based on genetic algorithms (GAs), which allows the fuzzy system parameters to be derived for each switch size, offering a high degree of scalability to the fuzzy control system. Its performance is comparable to that of the push-out (PO) mechanism, which can be considered ideal from a performance viewpoint, and at any rate much better than that of threshold schemes based on conventional logic. In addition, the fuzzy threshold (FT) scheme is simple and cost-effective when implemented using VLSI technology.     

A new generic approach to model reduction for complex physiologically based drug models

This paper explores the identification problem when dealing with physiological models relating to anaesthetic drugs such as fentanyl. The Mapleson model for drug concentration, which will be the focus of this study, is described by algebraic equations, which are derived from the laws of physics and chemistry, and there are some limitations in its system's analysis, i.e. in the study of its relevant dynamics, and its exploitation from a control design viewpoint. Hence, we propose to represent this model via dynamic differential equations with a reduced number of variables using MATLAB–SIMULINK. Using Mapleson's approach for modelling, the input–output data for each organ can be obtained under a particular drug regimen which in turn can be used to obtain a continuous time-transfer function fit for each of these organs.     

A generic model for building design

The design of building structures has benefited considerably through computer automation, but further developments in this field are still required. This paper presenis a generic approach to computer automation of the detailed design of building structures. Because of its high level of abstraction, the resulting model is applicable to a wide range of structure types. Other advantages include the use of a consistent data model for software design and implementation, abstract data types for the representation of engineering data, the ability to represent heuristic knowledge, and the ability to evaluate design results in an intelligent manner.     

A generic model for software architectures

In other industries, the idea of build corporate culture by establishing a common level of “best practice” is widely known and used. The architecture concept directly supports this goal for our industry and can help us improve problem areas dominated by organizational and social issues, such as health care organizations, educational systems, and so on. Our proposed reference model for architecture specification and development is organized around a set of aspects that structure concepts and rules; these, in turn, specify a conceptual architecture. We have added principles and guidelines to the concepts and rules to give a more complete picture of the architecture and to provide a place to store and communicate successfully applied design patterns and other knowledge related to the architecture. Adding architectural elements is a step toward a more constructive type of architecture representation. Our current research is focused on further refining these concepts and developing a formal specification of the architecture reference model. We are continuing to test our ideas in case studies, such as applying our model to the OSCA architecture and the application machine concept. We are also developing a prototype architecture editor, and we are testing different tools to learn more about integrating them into a real infrastructure and to learn what typical services an infrastructure must provide     

Decomposing Petri nets for process mining: A generic approach

The practical relevance of process mining is increasing as more and more event data become available. Process mining techniques aim to discover, monitor and improve real processes by extracting knowledge from event logs. The two most prominent process mining tasks are: (i) process discovery: learning a process model from example behavior recorded in an event log, and (ii) conformance checking: diagnosing and quantifying discrepancies between observed behavior and modeled behavior. The increasing volume of event data provides both opportunities and challenges for process mining. Existing process mining techniques have problems dealing with large event logs referring to many different activities. Therefore, we propose a generic approach to decompose process mining problems. The decomposition approach is generic and can be combined with different existing process discovery and conformance checking techniques. It is possible to split computationally challenging process mining problems into many smaller problems that can be analyzed easily and whose results can be combined into solutions for the original problems.     

Scenario animation for visual behavior models: A generic approach

Visualizing and simulating formal models in a flexible way becomes increasingly important for the design of complex systems. With GenGED, a tool is available which automatically generates a visual environment to process (create, edit, check, simulate) visual models over a specified visual language. Both the specification of the language and the model manipulation are based on graph grammars. In this paper, we present the means to transform visual models into application oriented views, called scenario views. We show how a model is consistently transferred to a scenario views and animated there. The extension of GenGED concerning scenario animation is discussed.     

Shape mining: A holistic data mining approach for engineering design

Although the integration of engineering data within the framework of product data management systems has been successful in the recent years, the holistic analysis (from a systems engineering perspective) of multi-disciplinary data or data based on different representations and tools is still not realized in practice. At the same time, the application of advanced data mining techniques to complete designs is very promising and bears a high potential for synergy between different teams in the development process. In this paper, we propose shape mining as a framework to combine and analyze data from engineering design across different tools and disciplines. In the first part of the paper, we introduce unstructured surface meshes as meta-design representations that enable us to apply sensitivity analysis, design concept retrieval and learning as well as methods for interaction analysis to heterogeneous engineering design data. We propose a new measure of relevance to evaluate the utility of a design concept. In the second part of the paper, we apply the formal methods to passenger car design. We combine data from different representations, design tools and methods for a holistic analysis of the resulting shapes. We visualize sensitivities and sensitive cluster centers (after feature reduction) on the car shape. Furthermore, we are able to identify conceptual design rules using tree induction and to create interaction graphs that illustrate the interrelation between spatially decoupled surface areas. Shape data mining in this paper is studied for a multi-criteria aerodynamic problem, i.e. drag force and rear lift, however, the extension to quality criteria from different disciplines is straightforward as long as the meta-design representation is still applicable.     

A generic architecture for VPN configuration management

This paper describes the specification of a management architecture allowing virtual private network (VPN) customers to dynamically modify the configuration of their VPN. The specification has been structured according to the ODP viewpoints. A special emphasis has been laid on how changes in the logical VPN configuration affect or are reflected in the underlying physical networks. As a result, an informational and a computational VPN configuration management architecture have been developed illustrating how processing and data can be distributed between the different layers and domains composing the architecture.     

Supporting synchronous collaborative learning: A generic, multi-dimensional model

Future CSCL technologies are described by the community as flexible, tailorable, negotiable, and appropriate for various collaborative settings, conditions and contexts. This paper describes the key design issues of a generic synchronous collaborative learning environment, called Omega+. In this approach, model-based genericity is applied to the four dimensions of collaborative learning: the situation, the interaction, the process, and the way of monitoring individual and group performance. These four aspects are explicitly specified in a set of models that serve as parameters for the generic environment. This opens the possibility of combining many structuring/scaffolding techniques that have been proposed in isolation in the CSCL literature. The paper also emphasizes the specificities and difficulties of evaluating a comprehensive generic support approach. Experimental evaluations conducted by system designers generally isolate the effects of a particular design feature on learning. This kind of evaluation can hardly demonstrate the usefulness of a generic model at the global level and the feasibility of system customization by non-specialist teachers. To address these difficulties, Omega+ is integrated into a larger collaborative web platform dedicated to CSCL practice, evaluation (by collecting anonymized logs), and dissemination (by supporting the technical and pedagogical development of teachers).