Information processing of classification task

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

Information seeking during the COVID-19 pandemic: Application of the risk information seeking and processing model

Using national online panel survey data (N = 1,000) in South Korea, this study applied the Risk Information Seeking and Processing (RISP) model to examine how people are motivated to seek information about obesity. We added autonomous motivation and health consciousness to the RISP model to investigate their association with health information seeking behavior about obesity. We proposed that information seeking is influenced by information insufficiency, autonomous motivation that is associated with health consciousness, and negative affective response that is related to subjective norm and risk perception. Using structural equation modeling analysis, this study largely supported our hypotheses. The results revealed associations among the socio-psychological variables that predict information seeking behavior on obesity. We found that information insufficiency, autonomous motivation, and negative affective responses appeared to be strong predictors in seeking obesity-related information. These findings have practical implications for health communication efforts in an emerging obesity risk country.

Traditional LiDAR post process is centralized. In centralized process model, data, process module and workflow can only be accessed within specific platform. This results in interoperability problem ranging from data sharing to functionality and workflow reuse. To tackle this problem, this paper proposes distributed process model for LiDAR post process. The distributed process model consists of interoperability solution on three aspects: data, process module and workflow. According to experiment, distributed LiDAR process model overcomes problems mentioned above. The process model and interoperability solution proposed in this paper can serve as reference to other geo-processing application.

This study applies the risk information seeking and processing (RISP) model to examine how information processing influences individuals’ support for climate change mitigation policy. Perceived issue salience, attitude toward climate information, and systematic processing are positively related to policy support, whereas heuristic processing is not a significant predictor. The direct and indirect relationships illustrated in the model help expand the utility of the risk information seeking and processing model to address policy support. From an applied perspective, this study suggests important pathways to encourage systematic processing of information related to climate change, which may lead to increased public support for mitigation policies.

Modern information technology makes it possible to redesign the ways people work. In the future, machines can carry out intelligence-requiring tasks, which previously were done by people. It is thus good to develop methodologies for designing intelligent systems. An example of such methods is cognitive mimetics, i.e. imitating human information processing. Today, machines cannot by themselves navigate in archipelagos. However, the fact that people can take care of ship steering and navigation means that there is an information process, which makes it possible to navigate ships. This information process takes place inside the minds of navigating people. If we are able to explicate the information processing in the navigator’s mind, the knowledge of it can be used in designing intelligent machines. Replicating physical objects and industrial processes by means of digital computers is called digital twinning. Digital twins (DTs), which are digital replicas of physical systems and processes, have recently become tools for working with complex industrial processes. A crucial question for DTs is should human actions be added to them? As the answer is positive, such models of human information processing can be called human digital twins (HDTs). The knowledge of human tacit and explicit information processes can be represented by human digital twins. Models can be used in the search for a deeper understanding of human intelligent information processes. Human digital twins can thus be used as methodological tools in cognitive mimetics. In our present study, we modeled paper machine operators’ thinking. Specifically, we developed an ideal-exception-correction (IEC) model for paper operators’ control logic. The model illustrates how research and HDT-modeling can be used for explicating the subconscious or tacit information processing of people for the design of intelligent systems. In this article a model for design processes using cognitive modelling will be suggested. The concepts of cognitive mimetics and human digital twins enable us to outline a model for using the long tradition of simulating human thinking as a tool in designing intelligent systems.

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

Accelerated degradation test (ADT) has become an efficient approach to evaluate the reliability for highly reliable products. However, when modeling accelerated degradation data with degradation models, it is difficult to exactly figure out the changing rules of parameters with stress variables varying. At present, the changing rules are mainly assumed according to engineering experience or subjective judgements, which probably results in inaccurately extrapolating the reliability. To figure out the changing rules of parameters with stress variables varying, the acceleration factor constant principle and its application under ADT are studied in the paper. It is well known that the acceleration factor between any two different stress levels should be a constant under an effective ADT. For each degradation model, its parameters should obey special changing rules to satisfy that the acceleration factor maintains a constant throughout an ADT. Taking three extensively used stochastic process models as examples, including Wiener process model, gamma process model, and inverse Gaussian process model, the method of deducing the changing rules of the parameters according to the acceleration factor constant principle was demonstrated. A simulation test was conducted to validate the deduced changing rules of the parameters for the three stochastic process models. An illustrative example involving self‐regulating heating cables was used to illustrate the application of the acceleration factor constant principle under ADT. Results indicate that the acceleration factor constant principle offers an appealing and credible approach to help model accelerated degradation data. Copyright © 2016 John Wiley & Sons, Ltd.

There are many types of intelligent systems used in modeling the information processing at the human brain level. The information processing is divided into two major parts: first part represents the information processing at the microstructure level (represented by sensory processes) and second part represents the information processing at the macrostructure level (represented by reasoning, memory and problem solving). In this context, the neural networks are used for model the first part of learning process - the primary stage of this and expert systems are used for model the second part of learning process - the final stage of this. So, the information processing is model by a complex system which contains many intelligent control systems: neural network, expert system and hybrid intelligent systems

The dynamic model of situated cognition (DMSC) is a descriptive model of information processing and information flow on the battlefield. This model illustrates the relationship between technological systems and human perceptual and cognitive processes and provides an effective framework within which to view information flow in a complex system. This research applies dynamical system modeling and control theory approaches to model the DMSC mathematically, represent decision maker feedback as input to the mathematical model, and represent the process by which the enormous amount of collected information is filtered, fused, and reduced to the relatively small subset of information a decision maker ultimately sees, toward the end of making this process more effective and efficient. The end result is a computational model of the information flow process, enabling decision makers to assess strengths and weaknesses in information processing system design.

Advanced organizational processes today require many process-relevant artifacts to be formally represented in process models. As these processes become more complex, process designers face the challenge of maintaining high comprehensibility while adequately visualizing process-relevant information. Modularization has been introduced to address the increasing complexity and information overload of process models, tackling this issue. While research acknowledges the importance of process model comprehensibility in order to benefit from the merits of such models, there still needs to be more clarity about the benefits of process model modularization. Recent research has focused on the human visual system and investigated visual behavior in the context of process model literacy. Continuing this branch of research, this paper analyses gaze behavior when comprehending modularized process models. A follow-up eye-tracking study was conducted to comprehend differently modularized BPMN 2.0 process models (i.e., vertical, horizontal, orthogonal). The results indicated that process model readers comprehend modularization approaches differently. Vertical modularization was perceived as the best comprehensible approach, whereas horizontal received the least acceptance. Considered eye movement performance measures confirm prior observation that attention is deployed more effectively in vertical modularization. Based upon the findings, the paper proposes a revised theoretical model from prior work that relates visual tasks to the execution of visual routines, explaining comprehension and information processing in modularized process models. The theoretical model elaborates how the visual system process and comprehends information obtained from modularized process models. Furthermore, the paper derived implications for modeling and practical applications, pointing out solid representational points and shortcomings of each modularization approach regarding how modularized process models are read and comprehended.

This study integrates cultural theory of risk into the risk information seeking and processing model in the context of particulate air pollution in South Korea. Specifically, it examines how cultural worldviews (hierarchy, individualism, egalitarianism, and fatalism) influence the way people interpret risk about an environmental risk, which may in turn promote or deter their information seeking and processing about the risk. An online survey (N = 645) showed that egalitarianism was positively associated with perceptions of societal and personal risks, affective responses toward the risk, and informational subjective norms. Perceived societal risk, in particular, mediated the effect of egalitarianism on information insufficiency. Moreover, cultural worldview was a significant moderator of the relationships between information insufficiency and risk information seeking and processing. The positive relationship between information insufficiency and information seeking grew stronger with increasing egalitarianism. In contrast, the negative relationship between information insufficiency and heuristic processing was strengthened with increasing hierarchy. This study extends prior theories and models in risk communication by addressing the roles of cultural worldview, an important individual difference factor in interpreting environmental risks.

What nucleic acids cannot do: a model for information processing in protein molecules

With green and smart manufacturing emergence and development, effective conduct with End of Life (EOL) products is an extremely important and hot research topic. Disassembly line design is a fundamental and complex problem in EOL product recycling and remanufacturing, especially when considering uncertainty. In this paper, we investigate a disassembly line balancing problem (DLBP) with stochastic task processing time to minimize the cycle time. We focus on selecting alternative task processes, determining the number of open workstations and assigning operational tasks to the workstations. A joint chance-constrained programming is proposed and we adopt a distribution-free method, which is based on Markov Inequality, to approximate the chance constraints as the distribution is difficult to fully estimated. Risk-neutral model may provide solutions that perform poorly while considering uncertainty. Therefore, a risk-averse measure called Conditional Value-at-Risk (CVaR), which is rarely used in the DLBP, is considered in this paper to incorporate decision makers’ perspectives. To the best of our knowledge, we are the first to consider risk-averse model in DLBP with minimizing cycle time under uncertain task processing time. Finally, computational experiments are conducted and give the impacts by testing different risk levels and confidence levels.