A distributed LiDAR processing model based on OWS and BPEL

MARVEL is a kernel for software development environments that enacts a processing modeling notation, called the MARVEL Strategy Language (MSL). The software process is defined in MSL as a collection of modular strategies, where different (sets of these) strategies are appropriate for different tool suites, user roles, phases of the lifecycle, management policies, etc. Each strategy specifies a partial object-oriented data model and a partial rule-based process model. The strategies are supplemented by a collection of envelopes, each of which describes how to apply one or more of the external tools used during software development activities; this includes the mapping from the inputs/outputs of these tools and the MARVEL objectbase and the command lines to invoke these tools. Multiple MSL strategies are merged to obtain the full data and process models for enaction by the MARVEL kernel.Each software development activity is described in MSL by a rule specifying the precondition and multiple postconditions of the activity. Both preconditions and postconditions are written in a subset of the first order predicate logic, stylized to incorporate directives for efficient queries and updates. A precondition is a logical statement that must be true before the activity is initiated; a postcondition is a logical statement asserted to be true when the activity completes. Multiple mutually exclusive postconditions reflect the multiple possible results of many activities. An activity is typically a particular combination of software development tool, options specific to that tool, and typed arguments. The notion of activity could be extended to include loading a new set of strategies to take over at this point in the process, to support both nesting of hierarchical activities and successive activity phases.Enaction of an MSL process model is implemented by what we call opportunistic processing, consisting primarily of forward and backward chaining among the rules. When a user initiates an activity, MARVEL applies backward chaining to attempt to satisfy its precondition. If this is not possible, MARVEL could use the rules in the style of an expert system to explain the problem. Once an activity has completed, MARVEL asserts one of its postconditions and uses forward chaining to automatically carry out other activities whose results are presumed to be needed in the near future.We have designed two facilities for controlling this processing, to prevent runaway automation. Hints are additional MSL preconditions that affect automatic but not user-initiated invocation of tools. Implicit queries represent a reflective capacity to keep tabs on estimated costs of automatic behavior and request user confirmation when certain user-selected thresholds are reached.MARVEL version 2.10 was recently completed, an upgrade over the version 2.01 that was demonstrated at the 3rd PSDE conference in November 1988. This latest version of MARVEL adds an X11 windows graphical user interface and new subsystems called Marvelizer and Organ. Marvelizer is a tool for immigrating existing software systems from the Unix file system or (a restricted class of) existing software development environment into a MARVEL objectbase. Organ is a set of commands for reorganizing MARVEL objectbases as the project and/or system structure evolves. Marvelizer has been used to immigrate Marvel itself, including about 35,000 lines of C code, into a C/Marvel objectbase. We would like to use the C/Marvel set of MSL strategies, which support activities using the user's favorite editor, lint, cc, ar, ranlib, less (and soon rcs, dbx and mail), for our own further development of MARVEL. Both MARVEL and C/Marvel were in use during the Spring 1989 semester by students in my E6123y Programming Environments and Software Tools course (admittedly a captive audience).We have discovered several difficulties with the MARVEL paradigm that seem likely to apply at least partially to enaction of other notations for software process modeling. First, constructing and debugging a process model is hard. We have run into many unanticipated interactions among rules, particularly among those defined in different strategies that happen to be loaded into the MARVEL kernel at the same time. We are working on debugging facilities that will uncover all direct and transitive dependencies by constructing a graphical dataflow graph of the currently loaded rules. It is feasible for a user to enable and disable individual rules, both during debugging to see how that affects the dataflow among rules and also during operation because certain behavior is not currently desired. This would be dangerous, however, if done by a naive user: if rules were turned off and on at arbitrary points, it would be possible for MARVEL to get into what is an inconsistent state with respect to the full set of rules in such a way that automatic recovery is impossible.Similar difficulties seem likely to arise for any enactable process modeling paradigm. The following questions need to be answered: How does an implementor go about writing, testing and debugging a process model? For non-trivial processes, the model is likely to be very large and hence should be modularized. What is the appropriate style of interface among process model modules and how is it enforced? Is the process model visible to the users and, if so, how is it presented? If the users can modify the process model during enaction, how does this affect continuing the process? Should (can) consistency be enforced or should (can) inconsistencies be detected and repaired?Second, constructing envelopes is even harder. We currently use the Shell languages (e.g., CShell) as notations for defining envelopes. Writing the Shell scripts requires an intimate knowledge of both the tool and the mapping of the MARVEL objectbase onto the file system. Although there is no way to avoid the former, we hope to minimize the latter by developing a higher level envelope language that understands the MARVEL objectbase implementation so the envelope writer doesn't have to. However, this is currently a relatively low priority due to lack of manpower.Again, similar difficulties seem inevitable for other enaction mechanisms intended to work with external tools. The questions: Is it possible (or desirable) to support existing tools, particularly tools where retrofitting is impractical? If only new tools are supported, can a relatively simple standard interface be developed and published so these tools can be developed separately by vendors? Would such an interface pre-empt too many design decisions, or would it be feasible for vendors to upgrade their current products?Third, supporting multiple users is hardest of all. The current MARVEL kernel does not provide any facilities for concurrency control. It would be easy to add locking of the entire objectbase, but a more flexible transaction model is needed. We are working on a number of alternative models that we think are promising for incorporation into the MARVEL kernel. Commit-serializability introduces two new transaction operations, split-transaction and join-transaction, that manipulate in-progress transactions to support coordination among multiple users. Participant transactions (AKA participation domains) distinguishes participants in group software development tasks from observers, and relaxes serializability as viewed by participants to permit cooperation.It is essential for enactable process models to support coordination and cooperation among the members of software development teams. There are two sets of questions: First, what are appropriate processes for programming-in-the-many? This is itself an active area of research, and there is certainly no consensus. One opinion, voiced at the previous workshop, is that the community should not be enacting process models until we understand the processes we are modeling. An opposing opinion is that enaction gives the community the capability to experiment with different processes without prematurely making a full scale commitment to a particular process. Assuming agreement with the second view, what process modeling notations and enaction mechanisms can support a reasonable range of cooperative work facilities?The database and operating system communities have agreed on atomic and serializable transactions, which can be implemented using a wide variety of technologies, as the basis for data consistency, failure recovery and concurrency control across their traditional application areas. Can the software engineering community develop an equally all-encompassing “transaction” model? Or is there some characteristic of the software development process such that coordination and cooperation policies will always require special support on a case-by-case basis? If so, what does this say about enaction of process models in general?In summary, MARVEL is implemented and in limited use, it works in some cases, it doesn't work in others, it raises a lot of questions, and both we the MARVEL group and we the software engineering community have a lot more work to do.

The text highlights the challenges of analyzing massive amounts of data, particularly in the context of business processes using process mining. Outliers or irregular behavior in the data can negatively impact processing and clutter process models, leading to less useful paths. The objective is to automatically extract process models from the data, and an automated method for removing irregular behavior from event logs is introduced. This method significantly improves the quality of identified process models and scales well to large datasets. Since the effectiveness of filtering strategies depends on the event log, users can interactively filter activities and directly view the filtered process model from the event log using a slider-based approach. Ultimately, the choice of included activities is left to the user. The method is tested using actual occurrence log collections from enterprise process oversight and hospital environments. The results demonstrate that the newly proposed activity filtering approaches yield process models that are more behaviorally specific compared to conventional frequency-based filtering methods

Preface. Introduction. I: Innovations in Severe Plastic Deformation Processing and Process Modeling. Severe Plastic Deformation of Materials by Equal Channel Angular Extrusion (ECAE) R.E. Goforth, et al. Severe Plastic Deformation of Steels: Structure, Properties and Techniques S.V. Dobatkin. Application of ECAP - Technology for Producing Nano- and Microcrystalline Materials V.I. Kopylov. Severe Deformation Based Process for Grain Subdivision and Resulting Microstructures A.K. Ghosh, W. Huang. Modeling of Continual Flows in Angular Domains B.V. Koutcheryaev. Synthesis and Characterization of Nanocrystalline Tial Based Alloys O.N. Senkov, F.H. Froes. Formation of Submicrocrystalline Structure in TiAl and Ti3Al Intermetallics via Hot Working G. Salishchev, et al. Severe Plastic Deformation Processes Modeling and Workability S.L. Semiatin, et al. The Effect of Strain Path on the Rate of Formation of High Angle Grain Boundaries During ECAE P.B. Prangnell, et al. Thermomechanical Conditions for Submicrocrystalline Structure Formation by Severe Plastic Deformation F.Z. Utyashev, et al. II: Microstructural Characterization and Modeling of Severe Plastic Deformation Materials. Strengthening Processes of Metals by Severe Plastic Deformation. Analyses with Electron and Synchrotron Radiation M.J. Zehetbauer. Size Distribution of Grains or Subgrains, Dislocation Density and Dislocation Character by Using the Dislocation Model of Strain Anisotropy in X-Ray Line Profile Analysis T. Ungar. X Ray-Studies and Computer Simulation of Nanostructured SPD Metals I.V. Alexandrov. An Analysis of Heterophase Structures of Ti3Al, TiAl, Ni3Al Intermetallics Synthesized by the Method of the SphericalShock Wave Action B.A. Greenberg, et al. Structural Changes Induced by Severe Plastic Deformation of Fe- and Co-Based Amorphous Alloys N. Noskova, et al. Structure of Grains and Internal Stress Fields in Ultrafine Grained NI Produced by Severe Plastic Deformation N.A. Koneva, et al. Crystal Lattice Distorsions in Ultrafine-Grained Metals Produced by Severe Plastic Deformation A.N. Tyumentsev, et al. Grain and Subgrain Size-Distribution and Dislocation Densities in Severely Deformed Copper Determined by a New Procedure of X-Ray Line Profile Analysis T. Ungar, et al. Calculation of Energy Intensity and Temperature of Mechanoactivation Process in Planetary Ball Mill by Computer Simulation E.V. Shelekhov, et al. III: Microstructure Evolution During Severe Plastic Deformation Processing. Microstructural Evolution During Processing by Severe Plastic Deformation T.G. Langdon, et al. Characterization of Ultrafine-Grained Structures Produced by Severe Plastic Deformation Z. Horita, et al. Fragmentation in Large Strain Cold Rolled Aluminium as Observed by Synchrotron X-Ray Bragg Peak Profile Analysis (SXPA), Electron Back Scatter Patterning (EBSP) and Transmission Electron Microscopy (TEM) E. Schafler, et al. Influence of Thermal Treatment and Cyclic Plastic Deformation on the Defect Structure in Ultrafine-Grained Nickel E. Thiele, et al. Nanostructure State as Nonequilibrium Transition in Grain Boundary Defects in SPD Condition O.B. Naimark. Texture, Structural Evolution and Mechanical Properties in AA5083 Processed by ECAE L. Dupuy, et al. A TEM-Based Disclination Model for the Substructure Evolution under Severe Plastic Deformation M. Seefeldt, et al. Physical Mesomechanics of Ultrafine-Grained Metals V.E. Panin. Microstructure Evo

In this work, a mathematical model of the laser material processing based upon the heat conduction equation is developed and solved by the finite element method. In this study, the process model is assumed to be in the quasi-steady state and laser beam power distribution to follow Gaussian distribution to get the best simulation of the temperature distribution. The convection effects are included in the two dimensional model. The keyhole concept is used to obtain a better insight into the process. Finite element method is employed to solve the non-dimensionalized governing conduction equation. The effects of the incident laser power, the laser beam diameter, the shielding gas velocity, the beam speed and different type of material are investigated based upon the above model. The laser beam power, laser beam diameter, the moving speed and the type of material are found to have more significant effects in the process. The shielding gas (i.e. the convection) velocity has little influence on the temperature distribution associated with the process. The results from the two-dimensional finite element model are compared with the temperature profiles obtained using a 3-dimensional finite-difference model.In this work, a mathematical model of the laser material processing based upon the heat conduction equation is developed and solved by the finite element method. In this study, the process model is assumed to be in the quasi-steady state and laser beam power distribution to follow Gaussian distribution to get the best simulation of the temperature distribution. The convection effects are included in the two dimensional model. The keyhole concept is used to obtain a better insight into the process. Finite element method is employed to solve the non-dimensionalized governing conduction equation. The effects of the incident laser power, the laser beam diameter, the shielding gas velocity, the beam speed and different type of material are investigated based upon the above model. The laser beam power, laser beam diameter, the moving speed and the type of material are found to have more significant effects in the process. The shielding gas (i.e. the convection) velocity has little influence on the temperature d...

In the previous chapter we presented an information technology reference architecture for FC and PAC. We now describe some Information Technology tools and standards, currently available and under development, which we believe may be important in realizing successful implementations of FC and PAC. Our primary objective in this chapter is to examine our information technology reference architecture for shop floor control systems, and associate with it specific hardware and software tools. We briefly review the most important information technology tools and standards, and give examples of how these tools can be applied in real-life shop floor control systems. Furthermore, we stress the importance of portability, flexibility and inter-operability for shop floor control systems, attributes which we believe are vitally important in a multi-vendor computing environment. The structure of this chapter is as follows: 1 We present an initial overview of information technology, highlighting the importance of flexibility, inter-operability and portability of IT systems. A general computing model is then introduced, and this contains four essential elements required to realize an information technology implementation of shop floor control. These elements are communication systems, data management systems, processing systems and user-interface systems. 2 The main body of the chapter describes the relevant state-of-the-art technologies of the four elements included in the general computing model. At the conclusion of each section, a synthesis of what we believe are the most suitable technologies is presented, in the form a shop floor control model for each particular computing element. Thus, we also present a communication systems model, a data management model, a processing model and an user-interface model for the implementation of FC and PAC systems. 3 Finally, we focus our attention on the emerging object-oriented technology, which holds the promise of highly portable, flexible and interoperable solutions within the domain of shop floor control.

A distributed multi-model-based Management Information System for simulation and decision-making on construction projects

Nowadays, organizations use process-aware information systems to understand and apply rapid changes to their processes. Process mining techniques automatically extract true dimensions of organizational processes including process models from data sets like event logs stored in these information systems. In most studies performed in the area of process model discovery, only information of the event logs is used. However, in this research, a novel method of process discovery is proposed, which uses event logs as well as the information on the data exchange among organizational roles, which is derived from physical generalized flow diagram model. This information formed the basis of a two-layered network that represents handover flow and data exchange flow among organizational roles. Then, by extracting and analyzing motifs existing in this network, five rules are set that map motifs with certain features to logical structures constructing process models. Finally, by integrating those structures, the process model will be discovered. The advantage of the proposed method over the previous ones is that from the business process management viewpoint, it is more efficient in detecting sophisticated structures in the process model. It is also highly resistant to noise. These benefits are derived from the fact that it exerts data exchange information along with event log information. Doing various experiments and evaluation of their results using the F-measure confirmed the superiority of this method to previous ones from the viewpoint of the business process management.

The expansion of drug-related problems urged healthcare organizations to adopt Pharmacoinformatics to signal, analyze and report Adverse Drug Reactions (ADRs). Data for this study have been compiled from local and international sources such as WHO. The study resulted into the development of an intelligent multi-agent decision support system including a process model, a multi-agent architecture and an integrated data processing model with clear description of agent functionalities. The model reflects three main modules: a data capture and update module, diagnosis module and a pharmaceutical care and drug monitoring module. The study also reflected on the practical and managerial environment of the model and the basic considerations to be taken into account. The study also provided some important recommendations.

Fiber optic data transmission has caused revolutionary developments in the current information society. It was also an eye opener for the Oil & Gas industry when fiber optic-based Distributed Temperature Sensing was introduced in the nineties. Temperature profiles over the entire length of the wellbore could suddenly be monitored in real-time to deliver data that is used for troubleshooting and production optimization. Ongoing research in fiber optic sensing technology for applications with extreme operational conditions (such as aerospace or nuclear fusion) will further boost the development of fiber optic multi-parameter sensing systems. Innovations like these will particularly benefit the Oil & Gas industry in situations where conventional electronic sensors are not technically feasible or cost efficient. In multi-parameter sensing systems of the future, different types of fiber optic sensors (e.g. flow, pressure, acoustic, chemical, vibration, gravity) can be manufactured and read out via one single optical fiber. Data from the different types of sensors will be merged and processed via special data-mining algorithms to generate unambiguous information for faster and better decision making. Judging on the speed of developments witnessed today, we believe there will be a second fiber optic sensing revolution in the Oil & Gas industry in the near future. In this paper, we will give some in-house examples of fiber optic innovations from both in and outside the Oil & Gas industry to demonstrate the versatility and potential of fiber optic technology. Introduction Increasing energy demand combined with scarcity means that oil must be produced from new and often more complex reservoirs. These reservoirs may consist of many sections separated by geological faults or the oil may be very viscous, making production more difficult or economically impossible with current technology. This implies that well and production strategies are becoming increasingly complex and require accurate and reliable input for decision making. Maturing assets develop complex ‘time critical’ process dynamics such as production decline, liquid loading and salt precipitation creating the need for real-time monitoring and control. This measurement and control technology must give a more accurate understanding of the key processes involved. It should also improve asset diagnostics to lead to improved production control and recovery strategies without compromising reliability or safety. Furthermore the industry has to deal with increasingly complex environmental and safety regulations and an increasing shortage of expert personnel. We believe that innovations in fiber optic sensing technology have the potential to help better understand the key processes behind decision-making in the oil and gas industry. This insight is based on many projects both inside and outside the oil and gas industry related to monitoring, process modeling and data processing. These new insights are essential to control and optimize the ‘new’ Oil & Gas industry when one considers the challenges that lie ahead. Before we focus on these upcoming fiber optic technologies for the oil and gas industry, we would like to illustrate the versatility and potential of fiber optic technology based on applications from other industries and their applicability to the oil and gas industry. Fiber optic technology is a proven technology but needs to be adapted and modified to the restricting and demanding applications of the oil and gas industry. These applications also give rise to innovations as will be discussed later.

Despite of many criticisms, agile software development (Beck et al., Manifesto for Agile Software Development, http://agilemanifesto.org, [1]) philosophy has been proved to be quite successful to increase the project success rate up to a significant extent. The primary reasons behind the criticism of agile are the strong violation of the traditional disciplined software engineering theories, principles and practices. The goal of this research paper is to establish the fact that agility may also be achieved by following traditional process models especially with BRIDGE (Mandal, 2009 IEEE International Advance Computing Conference (IACC 2009) Patiala, India, [2]) process model. Hence, the aim of this paper is to integrate the agile and traditional disciplined software development process models and establish the compatibility between both the approaches. At the beginning, we have explored the objectives and principles of agile software development. Next, we briefly discussed the BRIDGE process model and further justified that--following BRIDGE process model, the philosophy of agile may also be achieved and conclude that BRIDGE model has both the capability of traditional software development process model as well as of the agile process.

The extract, transform, and load (ETL) process is at the core of data warehousing architectures. As such, the success of data warehouse (DW) projects is essentially based on the proper modeling of the ETL process. As there is no standard model for the representation and design of this process, several researchers have made efforts to propose modeling methods based on different formalisms, such as unified modeling language (UML), ontology, model-driven architecture (MDA), model-driven development (MDD), and graphical flow, which includes business process model notation (BPMN), colored Petri nets (CPN), Yet Another Workflow Language (YAWL), CommonCube, entity modeling diagram (EMD), and so on. With the emergence of Big Data, despite the multitude of relevant approaches proposed for modeling the ETL process in classical environments, part of the community has been motivated to provide new data warehousing methods that support Big Data specifications. In this paper, we present a summary of relevant works related to the modeling of data warehousing approaches, from classical ETL processes to ELT design approaches. A systematic literature review is conducted and a detailed set of comparison criteria are defined in order to allow the reader to better understand the evolution of these processes. Our study paints a complete picture of ETL modeling approaches, from their advent to the era of Big Data, while comparing their main characteristics. This study allows for the identification of the main challenges and issues related to the design of Big Data warehousing systems, mainly involving the lack of a generic design model for data collection, storage, processing, querying, and analysis.

PurposeBusiness process modelling integrates and visualizes relevant information essential for managing day-to-day business operations. It plays a critical role in the design and execution of business transformations. Recognizing the role of process modelling, a large number of modelling languages, methods and techniques have been developed, each offering diverse advantages and having inherent limitations. Traditional and popular process modelling approaches focus on the exact specification of the control flow of business processes, whereas more recent approaches like Subject-oriented Business Process Management (S-BPM) are focused on the communication between process participants. This study aims to provide comparative insights about these two approaches through their experimental application. This study does so by comparing Business Process Model and Notation (BPMN); a control flow approach, with S-BPM; a communication approach, with a specific focus on their suitability for novice modellers.Design/methodology/approachThis paper reports on an exploratory experiment that compares BPMN to S-BPM. Applying cognitive load theory, this study compares the experiences and outcomes of novice process modellers, assessing perceived ease of use, model quality (syntactic and semantic) and modelling efficiency (time to model) across the two approaches.FindingsStudy results show that S-BPM (a communication approach) led to significantly better user performances for process modelling than BPMN (a control flow approach). This study points to how a different modelling approach such as S-BPM could be either considered as an alternative or to complement the more popular control flow approach BPMN. This observation was especially relevant for modelling contexts where domain experts are novice process modellers.Originality/valueThis study provides the first empirical evidence that communication approaches like S-BPM could outperform modelling approaches which are control-flow based (i.e. BPMN), especially when being used by novice process modellers who hold the domain and process knowledge. This study uses this as a springboard to present important considerations for practice and guide future process modelling research.

Recent decades have seen tremendous increases in the quantity of empirical ecological data collected by individual investigators, as well as through research networks such as FLUXNET (Baldocchi et al., 2001). At the same time, advances in computer technology have facilitated the development and implementation of large and complex land surface and ecological process models. Separately, each of these information streams provides useful, but imperfect information about ecosystems. To develop the best scientific understanding of ecological processes, and most accurately predict how ecosystems may cope with global change, integration of empirical and modeling approaches is necessary. However, true integration - in which models inform empirical research, which in turn informs models (Fig. 1) - is not yet common in ecological research (Luo et al., 2011). The goal of this workshop, sponsored by the Department of Energy, Office of Science, Biological and Environmental Research (BER) program, was to bring together members of the empirical and modeling communities to exchange ideas and discuss scientific practices for increasing empirical - model integration, and to explore infrastructure and/or virtual network needs for institutionalizing empirical - model integration (Yiqi Luo, University of Oklahoma, Norman, OK, USA). The workshop included presentations and small group discussions that coveredmore » topics ranging from model-assisted experimental design to data driven modeling (e.g. benchmarking and data assimilation) to infrastructure needs for empirical - model integration. Ultimately, three central questions emerged. How can models be used to inform experiments and observations? How can experimental and observational results be used to inform models? What are effective strategies to promote empirical - model integration?« less

The purpose of this paper is to analyze the processes of classification task by means of the application of the information processing models by Gregg and Simon to the stochastic process models. The result was as follows; 1) Subjects adopted consistently the strategy which made them select a hypothesis from the subset of hypotheses that are consistent with the last stimulus pattern presented to them regardless of the number of attribute-dimensions. 2) As the number of dimensions increased, the deviations between observations and predictions of any models tended to be great in spite of the stationarity of the series of responses and the statistical independence of the intermediate responses.

This paper presents a reference business process model for handling sporadic customer orders in the consumer goods industry. We believe that handling sporadic customer orders due to private label actions of supermarkets as well as strong promotion actions has lately been risen to a major problem of consumer industries in their efforts to streamline their supply chain. Each one of these customer orders has specific packaging requirements and irregularity in demand which creates significant problems to the production/marketing interface. Usually there is difficulty in assigning a reliable delivery date, in pre-calculating customer order costs, and in production planning.