Bitemporal Support for Business Process Contingency Management

Modern organisations are increasingly moving from traditional monolithic business systems to environments where more and more tasks are outsourced to third party providers. Therefore, processes must operate in an open and dynamic environment in which the management of time plays a crucial role. Handling time, however, remains a challenging issue yet to be fully addressed. Traditional processing systems only consider business events in a single time dimension, but are unable to handle bitemporal events: events in two time dimensions. Recently, backend systems have started to provide increased support for handling bitemporal events, but these enhanced capabilities have not been carried through to business process management systems. In this paper, we consider the possible relationships that exist between bitemporal properties of events and we show how these relationships affect a business process. In addition, we demonstrate how bitemporal events can be handled to prevent certain undesired effects on the business process

Land Use And Land Cover Classification And Change Detection Using Naip Imagery From 2009 To 2014: Table Rock Lake Region, Missouri

Land use and land cover (LULC) of Table Rock Lake (TRL) region has changed over the last half century after the construction of Table Rock Dam in 1959. This study uses one meter spatial resolution imagery to classify and detect the change of LULC of three typical waterside TRL regions. The main objectives are to provide an efficient and reliable classification workflow for regional level NAIP aerial imagery and identify the dynamic patterns for study areas. Seven class types are extracted by optimal classification results from year 2009, 2010, 2012 and 2014 of Table Rock Village, Kimberling City and Indian Point. Pixel-based post-classification comparison generated from-to” confusion matrices showing the detailed change patterns. I conclude that object-based random trees achieve the highest overall accuracy and kappa value, compared with the other six classification approaches, and is efficient to make a LULC classification map. Major change patterns are that vegetation, including trees and grass, increased during the last five years period while residential extension and urbanization process is not obvious to indicate high economic development in the TRL region. By adding auxiliary spatial information and object-based post-classification techniques, an improved classification procedure can be utilized for LULC change detection projects at the region level

24th International Conference on Information Modelling and Knowledge Bases

In the last three decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied. The series of European – Japanese Conference on Information Modelling and Knowledge Bases (EJC) originally started as a co-operation initiative between Japan and Finland in 1982. The practical operations were then organised by professor Ohsuga in Japan and professors Hannu Kangassalo and Hannu Jaakkola in Finland (Nordic countries). Geographical scope has expanded to cover Europe and also other countries. Workshop characteristic - discussion, enough time for presentations and limited number of participants (50) / papers (30) - is typical for the conference. Suggested topics include, but are not limited to: 1. Conceptual modelling: Modelling and specification languages; Domain-specific conceptual modelling; Concepts, concept theories and ontologies; Conceptual modelling of large and heterogeneous systems; Conceptual modelling of spatial, temporal and biological data; Methods for developing, validating and communicating conceptual models. 2. Knowledge and information modelling and discovery: Knowledge discovery, knowledge representation and knowledge management; Advanced data mining and analysis methods; Conceptions of knowledge and information; Modelling information requirements; Intelligent information systems; Information recognition and information modelling. 3. Linguistic modelling: Models of HCI; Information delivery to users; Intelligent informal querying; Linguistic foundation of information and knowledge; Fuzzy linguistic models; Philosophical and linguistic foundations of conceptual models. 4. Cross-cultural communication and social computing: Cross-cultural support systems; Integration, evolution and migration of systems; Collaborative societies; Multicultural web-based software systems; Intercultural collaboration and support systems; Social computing, behavioral modeling and prediction. 5. Environmental modelling and engineering: Environmental information systems (architecture); Spatial, temporal and observational information systems; Large-scale environmental systems; Collaborative knowledge base systems; Agent concepts and conceptualisation; Hazard prediction, prevention and steering systems. 6. Multimedia data modelling and systems: Modelling multimedia information and knowledge; Contentbased multimedia data management; Content-based multimedia retrieval; Privacy and context enhancing technologies; Semantics and pragmatics of multimedia data; Metadata for multimedia information systems. Overall we received 56 submissions. After careful evaluation, 16 papers have been selected as long paper, 17 papers as short papers, 5 papers as position papers, and 3 papers for presentation of perspective challenges. We thank all colleagues for their support of this issue of the EJC conference, especially the program committee, the organising committee, and the programme coordination team. The long and the short papers presented in the conference are revised after the conference and published in the Series of “Frontiers in Artificial Intelligence” by IOS Press (Amsterdam). The books “Information Modelling and Knowledge Bases” are edited by the Editing Committee of the conference. We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases. Bernhard Thalheim Hannu Jaakkola Yasushi Kiyok

Adaptive Time- and Process-Aware Information Systems

For the digitized enterprise the proper handling of the temporal aspects of its business processes is vital. Delivery times, appointments and deadlines must be met, processing times and durations be monitored, and optimization objectives shall be pursued. However, contemporary Process-Aware Information Systems (PAISs)--the go-to solution for the computer-aided support of business processes—still lack a sophisticated support of the time perspective. Hence, there is a high demand for a more profound support of temporal aspects in PAISs. Accordingly, both the specification and the operational support of temporal aspects constitute fundamental challenges for the further development and dissemination of PAISs. The aim of this thesis is to propose a framework for supporting the time perspective of business processes in PAISs. As PAISs enable the design, execution and evolution of business processes, the designated framework must support these three fundamental phases of the process life cycle. The ATAPIS framework proposed by this thesis essentially comprises three major com-ponents. First, a universal and comprehensive set of time patterns is provided. Respective time patterns represent temporal concepts commonly found in business processes and are based on empirical evidence. In particular, they provide a universal and comprehensive set of notions for describing temporal aspects in business processes. Moreover, a precise formal semantics for each of the time patterns is provided based on an in-depth analysis of a large set of real-world use cases. Respective formal semantics enable the proper integration of the time patterns into PAISs. In turn, the latter will allow for the specification of time-aware process schemas. Second, a generic framework for implementing the time patterns based on their formal semantics is developed. The framework and its techniques enable the verification of time-aware process schemas regarding their temporal consistency, i. e., their ability to be successfully executed without violating any of their temporal constraints. Subsequently, the framework is extended to consider advanced aspects like the contingent nature of activity durations and alternative execution paths as well. Moreover, an algorithm as well as techniques for executing and monitoring time-aware process instances in PAISs is provided. Based on the presented concepts, it becomes possible to ensure that a time-aware process instance may be executed without violating any of its temporal constraints. Third, a set of change operations for dynamically modifying time-aware process instances during run time is suggested. Respective change operations ensure that a modified time-aware process instance remains temporally consistent after the respective modification. Moreover, to reduce the complexity involved when applying multiple change operations a sophisticated approximation-based technique is presented. Overall, the developed change operations allow providing the flexibility required by business processes in practice. Altogether, the ATAPIS framework provides fundamental concepts, techniques and algorithms for integrating the time perspective into PAISs. As beauty of this framework the specification, execution and evolution of business processes is supported by an integrated approach

A Principled Framework for Constructing Natural Language Interfaces To Temporal Databases

Most existing natural language interfaces to databases (NLIDBs) were designed to be used with ``snapshot'' database systems, that provide very limited facilities for manipulating time-dependent data. Consequently, most NLIDBs also provide very limited support for the notion of time. The database community is becoming increasingly interested in _temporal_ database systems. These are intended to store and manipulate in a principled manner information not only about the present, but also about the past and future. This thesis develops a principled framework for constructing English NLIDBs for _temporal_ databases (NLITDBs), drawing on research in tense and aspect theories, temporal logics, and temporal databases. I first explore temporal linguistic phenomena that are likely to appear in English questions to NLITDBs. Drawing on existing linguistic theories of time, I formulate an account for a large number of these phenomena that is simple enough to be embodied in practical NLITDBs. Exploiting ideas from temporal logics, I then define a temporal meaning representation language, TOP, and I show how the HPSG grammar theory can be modified to incorporate the tense and aspect account of this thesis, and to map a wide range of English questions involving time to appropriate TOP expressions. Finally, I present and prove the correctness of a method to translate from TOP to TSQL2, TSQL2 being a temporal extension of the SQL-92 database language. This way, I establish a sound route from English questions involving time to a general-purpose temporal database language, that can act as a principled framework for building NLITDBs. To demonstrate that this framework is workable, I employ it to develop a prototype NLITDB, implemented using ALE and Prolog.Comment: PhD thesis; 405 pages; LaTeX2e, uses the packages/macros: amstex, xspace, avm, examples, dvips, varioref, makeidx, epic, eepic, ecltree; postscript figures include

Remote Sensing Techniques for Change Detection Analysis in Arid and Semi-arid areas

Desertification constitutes a natural hazard for human livelihood, wildlife and vegetation worldwide. Arid and semi-arid areas are the most likely to undergo processes of desertification, and it is a concern of the international community to control, monitor and prevent such a phenomenon. As a mainly arid region, the Middle East is particularly vulnerable to climate-induced impacts on water resources, challenged by high growth population rates and a water-stressed situation. Aim of the reasearch is to investigate Remote Sensing (RS) techniques for desertication studies, with a special focus on the Middle East region. RS is an efficient tool for environmental studies on wide areas of the Earth surface, allowing fast and reproducible analysis on regional and continental scales . For this research two RS methods of change detection analysis have been investigated and further implemented: Change Vector Analysis (CVA), applied to the Tasselled Cap Transform (TCT) outputs, and the Maximum Autocorrelation Factor (MAF) transformation of the Multivariate Alteration Detector (MAD) components (MAD/MAF). The research introduces improvements in the use of both techniques adapting them to desertification studies and proposes a new RS methodology, which has been proven effective in detecting the surface change in arid and semi-arid areas. An added value of the research is the availability of the source code, implemented for this study, to other users, through GFOSS software

Method for landslides detection with semi-automatic procedures: The case in the zone center-east of Cauca department, Colombia

Landslides are a common natural hazard that causes human casualties, but also infrastructure damage and land-use degradation. Therefore, a quantitative assessment of their presence is required by means of detecting and recognizing the potentially unstable areas. This research aims to develop a method supported on semiautomatic methods to detect potential mass movements at a regional scale. Five techniques were studied: Morphometry, SAR interferometry (InSAR), Persistent Scatterer InSAR (PS-InSAR), SAR polarimetry (PolSAR) and NDVI composites of Landsat 5, Landsat 7, and Landsat 8. The case study was chosen within the mid-eastern area of the Cauca state, which is characterised by its mountainous terrain and the presence of slope instabilities, officially registered in the CGS-SIMMA landslide inventory. This inventory revealed that the type `slide' occurred with 77.4% from the entire registries, `fall' with 16.5%, followed by `creeps' with 3%, flows with 2.6%, and `lateral spread' with 0.43%. As a result, we obtained the morphometric variables: slope, CONVI, TWI, landform, which were highly associated with landslides. The effect of a DEM in the processing flow of the InSAR method was similar for the InSAR coherence variable using the DEMs ASTER, PALSAR RTC, Topo-map, and SRTM. Then, a multiInSAR analysis gave displacement velocities in the LOS direction between -10 and 10 mm/year. With the dual-PolSAR analysis (Sentinel-1), VH and VV C-band polarised radar energy emitted median values of backscatters, for landslides, about of -14.5 dB for VH polarisation and -8.5 dB for VV polarisation. Also, L-band fully polarimetric NASA-UAVSAR data allowed to nd the mechanism of dispersion of CGS landslide inventory: 39% for surface scattering, 46.4% for volume dispersion, and 14.6% for double-bounce scattering. The optical remote sensing provided NDVI composites derived from Landsat series between 2012 and 2016, showing that NDVI values between 0.40 and 0.70 had a high correlation to landslides. In summary, we found the highest categories related to landslides by Weight of Evidence method (WofE) for each spaceborne technique applied. Finally, these results were merged to generate the landslide detection model by using the supervised machine learning method of Random Forest. By taking training and test samples, the precision of the detection model was of about 70% for the rotational and translational types.Los deslizamientos son una amenaza natural que causa pérdidas humanas, daños a la infraestructura y degradación del suelo. Una evaluación cuantitativa de su presencia se requiere mediante la detección y el reconocimiento de potenciales áreas inestables. Esta investigación tuvo como alcance desarrollar un método soportado en métodos semi-automáticos para detectar potenciales movimientos en masa a escala regional. Cinco técnicas fueron estudiadas: Morfometría, Interferometría radar, Interferometría con Persistent Scatterers, Polarimetría radar y composiciones del NDVI con los satélites Landsat 5, Landsat 7 y Landsat 8. El caso de estudio se seleccionó dentro de la región intermedia al este del departamento del Cauca, la cual se caracteriza por terreno montañoso y la presencia de inestabilidades de la pendiente oficialmente registrados en el servicio SIMMA del Servicio Geológico Colombiano. Este inventario reveló que el tipo de movimiento deslizamiento ocurrió con una frecuencia relativa de 77.4%, caidos con el 16.5% de los casos y reptaciones con 3%, flujos con 2.6% y propagación lateral con 0.43%. Como resultado, se obtuvo las variables morfométricas: pendiente, convergencia, índice topográfico de humedad y forma del terreno altamente asociados con los deslizamientos. El efecto de un DEM en el procesamiento del método InSAR fue similar para la variable coherencia usando los DEMs: ASTER, PAlSAR RTC, Topo-map y SRTM. Un análisis Multi-InSAR estimó velocidades de desplazamiento en dirección de vista del radar entre -10 y 10 mm/año. El análisis de polarimetría dual del Sentinel-1 arrojó valores de retrodispersión promedio de -14.5 dB en la banda VH y -8.5dB en la banda VV. Las cuatro polarimetrías del sensor aéreo UAVSAR permitió caracterizar el mecanismo de dispersión del Inventario de Deslizamiento así: 39% en el mecanismo de superficie, 46.4% en el mecanismo de volumen y 14.6% en el mecanismo de doble rebote. La información generada en el rango óptico permitió obtener composiciones de NDVI derivados de la plataforma Landsat entre los años 2012 y 2016, mostrando que el rango entre 0.4 y 0.7 tuvieron una alta asociación con los deslizamientos. En esta investigación se determinaron las categorías de las variables de Teledetección más altamente relacionadas con los movimientos en masa mediante el método de Pesos de Evidencias (WofE). Finalmente, estos resultados se fusionaron para generar el modelo de detección de deslizamientos usando el método supervisado de aprendizaje de máquina Random Forest. Tomando muestras aleatorias para entrenar y validar el modelo en una proporción 70:30, el modelo de detección, especialmente los movimientos de tipo rotacional y traslacional fueron clasificados con una tasa general de éxito del 70%.Ministerio de CienciasConvocatoria 647 de 2014Research line: Geotechnics and Geoenvironmental HazardDoctorad

Remote Sensing in Mangroves

The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the worl

The Impact of Land-use change on the Livelihoods of Rural Communities: A case-study in Edd Al-Fursan Locality, South Darfur, Sudan

Ziele der Arbeit sind die Bestimmung der dominanten Landnutzungsarten im Untersuchungsgebiet von Edd Al Fursan (Sudan) sowie die Kartierung und Analyse der Veränderungen der Landnutzung im Zeitraum 1972 bis 2008 mit Hilfe von multi-temporalen Satellitenbildern (Landsat MSS, TM und ETM sowie Terra ASTER). Des weiteren erfolgt eine Evaluierung des Einflusses von Veränderungen der Landnutzung auf die Lebensbedingungen der ländlichen Bevölkerung in Hinblick auf die Verfügbarkeit von Ressourcen mit Hilfe von quantitativen Untersuchungsmethoden. Um diese Aussagen treffen zu können, werden drei Methoden der Bestimmung von Veränderungen der Landnutzung angewandt, und zwar Post Classification Comparison (PCC), Change Vector Analysis (CVA) basierend auf Tasseled Cap Transformation (TCT) sowie Iteratively Reweighted Multivariate Alteration Detection (IR-MAD) mittels Maximum Autocorrelation Factor (MAF). Neben den fernerkundlichen Untersuchungen wurde eine sozio-ökonomische Feldstudie durchgeführt, die vorstrukturierte Fragenkataloge, Interviews und Gruppendiskussionen mit Personen in regionalen und lokalen Schlüsselpositionen und mit älteren Menschen durchgeführt. Fünf Klassen der Landnutzung und Landbedeckung ergeben sich aus einer Klassifikation der Satellitenbilder mit der Methode der größten Wahrscheinlichkeit (Maximum Likelihood), explizit die Klassen Grasland, Waldland, Brachland, bebautes und landwirtschaftlich nicht genutztes Land. Die Klassifikation schafft eine genaue Grundlage für die Kartierung, Quantifizierung und Analyse der Änderungen. Die Gesamtgenauigkeit der Flächenermittlung beträgt 83% für die Jahre 1972 und 1984, 85% für 1989, 87% für 1999 und 92% für 2008. Die Untersuchungen zeigen, dass die Post Classification Comparison (PCC) eine vollinhaltlich geeignete und leicht anzuwendende Methode der Flächenanalyse darstellt. Change Vector Analysis (CVA) beruhend auf Tasseled Cap Transformation (TCT) wird ebenfalls für die Kartierung und Bestimmung von Landnutzungsänderungen verwendet. Durch TCT wird der spektrale Bildinhalt in die Komponenten Greeness und Brightness transformiert sowie in dem dadurch neu definierten Koordinatensystem die CVA durchgeführt. Die Ergebnisse in Form von Vektoren der Veränderung mit messbarer Richtung und messbarem Ausmass der Flächendynamik beweisen, dass die Methode für die Kartierung von Vegetationsbedeckung und insbesondere von Entwaldung und Wiederbewaldung geeignet ist. Durch die Anwendung der Multivariate Alteration Detection (MAD) in Kombination mit dem Maximum Autocorrelation Factor (MAF) werden Veränderungen der Landnutzungsklassen während des betrachteten Zeitraumes visualisiert. Die Ergebnisse beweisen, dass die MAD für die Veränderungsanalyse in multi-spektralen Satellitenbildern sehr gut geeignet ist. Darüber hinaus wird nachgewiesen, dass die Kombination mit dem MAF die Ergebnisse der MAD entscheidend verbessern kann, da Rauschen und geringfügige Änderungen unterdrückt und signifikante Änderungen klarer herausgestellt und damit besser interpretierbar werden. Um die Ursachen für die Veränderungen der Landnutzung und den Einfluss dieser Änderungen auf die Lebensbedingungen der ländlichen Bevölkerung im Projektgebiet zu identifizieren, wurde eine Befragung mittels vorstrukturiertem Fragenkatalog, Interviews und Gruppengesprächen mit 100 GesprächspartnerInnen im Alter zwischen 42 und 65 Jahren in vier nach dem Zufallsprinizip ausgewählten Dörfern ausgeführt. Die Auswertung der sozio-ökonomischen Daten erlaubt die Extraktion der Faktoren, die Landnutzung und deren Änderung beeinflussen, und die zu bestimmten Auswirkungen dieser Änderungen auf die Lebensbedingungen in den Dörfern in Hinsicht auf die Verfügbarkeit von Natur-Ressourcen führen. Die Ergebnisse der Forschungsarbeiten zeigen, dass Fernerkundung und sozio-ökonomische Datenanalyse effizient verknüpft werden können, um anthropogene Einflüsse auf Art und Dynamik von Landnutzung sichtbar zu machen. In bezug auf die gegenständliche Zeitreihe wird durch die Untersuchungen bewiesen, dass zunehmende Bevölkerungszahlen im Gebiet von Edd Al-Fursan in direktem Wirkungszusammenhang mit Veränderungen der Landnutzung stehen

Experiencias docentes potenciando los resultados de aprendizaje: 3ra. Jornada de innovación e investigación educativa de Unapec 2016

En la Universidad APEC (UNAPEC) se concibe la tercera jornada de innovación e investigación educativa como un espacio de reflexión pedagógica para el intercambio de saberes, experiencias y prácticas docentes orientadas a la mejora de los resultados de aprendizaje. Para esta ocasión, la misma tiene como objetivo proporcionar el diálogo profesional y el intercambio académico a fin de construir un entendimiento común sobre el proceso de mejora continua de la institución y promover la innovación e investigación como parte de la cultura de calidad, focalizada en el aprendizaje de los estudiantes