pinecone/core-2020-05-10-deduplication huggingface dataset:
Fused Visualization for Large-Scale Time-Varying Volume Data with Adaptive Particle-Based Rendering

<Book Title>AsiaSim 2014 : 14th International Conference on Systems Simulation, Kitakyushu, Japan, October 26-30, 2014. ProceedingsRecently, there is a strong need for the fused visualization of different objects in many simulation fields, especially for the medical domain (e.g., the fusion of different organs). That is because it is desirable and advantageous to show the different objects and analyze the relationship between them. Nevertheless, such a simulation date is always resulted in a large-scale time-varying volume data, which make the fused visualization even more difficult. To solve this problem, we use a sorting-free rendering technique, Adaptive Particle-based Rendering (APBR), to visualize the large-scale time-varying volume data. Because this method visualizes the volume data by generating opaque particles from the original volume data and projects these particles to the image plane, the visibility sorting is not needed. This makes the fusion of different objects and handling of large-scale volume data is very easy. Moreover, our proposed APBR method can adaptively apply different particle generation process to visualize the volume data based on different viewpoints. This feature can make our system keep an interactive frame rate and also a relatively high image quality. With the APBR, we also develop a time-varying rendering into our system so that the rendering for the large-scale time-varying data also becomes possible. To verify the efficiency, we apply our APBR system to the large-scale blood flow dataset. The experimental results and the user feedbacks show that our system can fuse different objects efficiently while keeping an interactive frame rate and a good image quality, which is very meaningful in the visual analysis
Automated Bias-Correction for Accurate FCD Processing Systems

Within the European research project SimpleFleet, a fleet management system for small and medium enterprises has been developed. GPS traces are collected from equipped vehicles and fed into an FCD processing system to generate traffic data. To estimate the quality of derived traffic data and determine the systematic bias of a FCD processing system a previous method called “self-evaluation” was applied for specific times of day and roads with similar characteristics. With the assumption that the relative bias is the same for corresponding traffic situations, it can be transferred and used to correct results of further computations. Notice that this opens up a convenient road for automated online corrections based on really large amounts of data, rather than on small data sets from costly measurement campaigns
Telematics for the Analysis of Vehicle Fleet Fuel Consumption

Within the European research project SimpleFleet, a telematics system for fleet management business intelligence was developed, delivering live or near-realtime statistics about individual vehicles or the entire fleet. This supports the fleet manager in ad-hoc decisions and in medium and long term improvements. The fleet vehicles (e.g. taxis, delivery vans) are equipped with an On-Board-Unit (OBU) for GPS tracking and data collection from other sensors, e.g., an engine on/off detector. These raw data are sent to a host system and database, being enhanced to Floating Car Data (FCD) using map-matching and routing. Beside other route-related information, consulted fleet operators expressed their interest especially in fuel consumption calculation. For this purpose the German EWS procedure was chosen, providing 2nd degree polynomial functions of the driven speed. Final results for the test in the Athens region are presented, including the comparison of two calculation approaches with different aggregation levels of driven speeds
Managing expectations: runtime negotiation of information quality requirements in event-based systems

© Springer-Verlag Berlin Heidelberg 2014.Interconnected smart devices in the Internet of Things (IoT) provide fine-granular data about real-world events, leveraged by service-based systems using the paradigm of event-based systems (EBS) for invocation. Depending on the capabilities and state of the system, the information propagated in EBS differs in content but also in properties like precision, rate and freshness. At runtime, consumers have different dynamic requirements about those properties that constitute quality of information (QoI) for them. Current approaches to support quality-related requirements in EBS are either domain-specific or limited in terms of expressiveness, flexibility and scope as they do not allow participants to adapt their behavior. We introduce the generic concept of expectations to express, negotiate and enforce arbitrary requirements about information quality in EBS at runtime. In this paper, we present the model of expectations, capabilities and feedback based on generic properties. Participants express requirements and define individual tradeoffs between them as expectations while system features are expressed as capabilities. We discuss the algorithms to (i) negotiate requirements at runtime in the middleware by matching expectations to capabilities and (ii) adapt participants as well as the middleware. We illustrate the architecture for runtime-support in industry-strength systems by describing prototypes implemented within a centralized and a decentralized EBS
Designing Secure Service Workflows in BPEL

This paper presents an approach that we have developed to support the design of secure service based applications in BPEL. The approach is based on the use of secure service composition patterns, which are proven to preserve composition level security properties if the services that are composed according to the pattern satisfy other properties individually. The secure service composition patterns are used for two purposes: (a) to analyse whether a given workflow fragment satisfies a given security property, and (b) to generate com-positions of services that could substitute for individual services within the workflow that cause the violation of the security properties. Our approach has been implemented in a tool that is based on Eclipse BPEL Designer
A look into business process modeling guidelines through the lens of the technology acceptance model

Business process modeling is one of the first steps towards achieving organizational goals in the requirements engineering phase. This is why business process modeling quality is an essential aspect for the development and technical support of any company. Modeling experts rely mainly on their personal experience, and the tacit knowledge. In order to help less experienced modelers, many authors have formulated modeling guidelines as a mean to achieve better model quality. Our research goal is to assess the acceptance of these guidelines for teaching purposes through a survey. To achieve this objective we investigate usefulness, ease of use and the intention to use of a collected set of pragmatic guidelines according to the technology acceptance model by means of a survey amongst Cuban PhD students. Results reveal the "best" and "worst" guidelines as perceived by novice modelers. We also witnessed that perceived ease of use has an important influence on the perceived usefulness, and, at the same time, both influence the novice modelers’ intention to use the guidelines. This implies that to ensure usage of the guidelines by junior modelers, they should be understandable and their utility should be well-motivated.status: publishe
Efficient smoothers for all-at-once multigrid methods for Poisson and
  Stokes control problems

In the present paper we concentrate on an important issue in constructing a
good multigrid solver: the choice of an efficient smoother. We will introduce
all-at-once multigrid solvers for optimal control problems which show robust
convergence in the grid size and in the regularization parameter. We will refer
to recent publications that guarantee such a convergence behavior. These
publications do not pay much attention to the construction of the smoother and
suggest to use a normal equation smoother. We will see that using a Gauss
Seidel like variant of this smoother, the overall multigrid solver is speeded
up by a factor of about two with no additional work. The author will give a
proof which indicates that also the Gauss Seidel like variant of the smoother
is covered by the convergence theory. Numerical experiments suggest that the
proposed method are competitive with Vanka type methods.Comment: The research was funded by the Austrian Science Fund (FWF):
  J3362-N25. The original publication is available at
  http://www.springerlink.co
Optimization of Assembly Line Balancing with Resource Constraint using NSGA-II: A Case Study

Assembly line balancing type-e problem with resource constraint (ALBE-RC) is an attempt to assign the tasks to a minimal number of workstation with minimum cycle time by considering the resource constraint. Due to rapid growth in manufacturing and limited number of resources in industry, all the tasks that used the same resources will be performed in the same workstation such that the precedence relations are not violated. In this work, an implementation of an elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to optimise ALBE-RC case study. An industrial case study was conducted in an electronic company and a product known as HM72A-10 series model has been selected for the case study. The results from the optimization shows that the number of workstations are extensively decreased as well as the number of resources used. The improvement of line efficiency, busy and idle time also indicates that the optimization results are better that the existing one. The validation from industrial expert provides evidence that the proposed method is applicable and can be implemented for line balancing
A hybrid primal heuristic for Robust Multiperiod Network Design

We investigate the Robust Multiperiod Network Design Problem, a
generalization of the classical Capacitated Network Design Problem that
additionally considers multiple design periods and provides solutions protected
against traffic uncertainty. Given the intrinsic difficulty of the problem,
which proves challenging even for state-of-the art commercial solvers, we
propose a hybrid primal heuristic based on the combination of ant colony
optimization and an exact large neighborhood search. Computational experiments
on a set of realistic instances from the SNDlib show that our heuristic can
find solutions of extremely good quality with low optimality gap.Comment: This is the authors' final version of the paper published in:
  Esparcia-Alc\'azar A., Mora A. (eds), EvoApplications 2014: Applications of
  Evolutionary Computation, LNCS 8602, pp. 15-26, 2014. DOI:
  10.1007/978-3-662-45523-4\_2. The final publication is available at Springer
  via http://dx.doi.org/10.1007/978-3-662-45523-4_2. arXiv admin note:
  substantial text overlap with arXiv:1410.585
Fast evolutionary adaptation for Monte Carlo Tree Search

© Springer-Verlag Berlin Heidelberg 2014. This paper describes a new adaptive Monte Carlo Tree Search (MCTS) algorithm that uses evolution to rapidly optimise its performance. An evolutionary algorithm is used as a source of control parameters to modify the behaviour of each iteration (i.e. each simulation or roll-out) of the MCTS algorithm; in this paper we largely restrict this to modifying the behaviour of the random default policy, though it can also be applied to modify the tree policy.This method of tightly integrating evolution into the MCTS algorithm means that evolutionary adaptation occurs on a much faster time-scale than has previously been achieved, and addresses a particular problem with MCTS which frequently occurs in real-time video and control problems: that uniform random roll-outs may be uninformative.Results are presented on the classicMountain Car reinforcement learning benchmark and also on a simplified version of Space Invaders. The results clearly demonstrate the value of the approach, significantly outperforming “standard” MCTS in each case. Furthermore, the adaptation is almost immediate, with no perceptual delay as the system learns: the agent frequently performs well from its very first game
A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link.The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts to a given problem and selects those search logics that appear to be the most appropriate to quickly detect high quality solutions. The resulting algorithm, namely Ensemble of Parameters and Strategies Differential Evolution empowered by Local Search (EPSDE-LS), is evaluated on multiple testbeds and dimensionality values. Numerical results show that the proposed EPSDE-LS robustly displays a very good performance in comparison with some of the state-of-the-art algorithms
Decomposing alignment-based conformance checking of data-aware process models

Process mining techniques relate observed behavior to modeled behavior, e.g., the automatic discovery of a Petri net based on an event log. Process mining is not limited to process discovery and also includes conformance checking. Conformance checking techniques are used for evaluating the quality of discovered process models and to diagnose deviations from some normative model (e.g., to check compliance). Existing conformance checking approaches typically focus on the control-flow, thus being unable to diagnose deviations concerning data. This paper proposes a technique to check the conformance of data-aware process models. We use so-called Petri nets with Data to model data variables, guards, and read/write actions. Data-aware conformance checking problem may be very time consuming and sometimes even intractable when there are many transitions and data variables. Therefore, we propose a technique to decompose large data-aware conformance checking problems into smaller problems that can be solved more efficiently. We provide a general correctness result showing that decomposition does not influence the outcome of conformance checking. The approach is supported through ProM plug-ins and experimental results show significant performance improvements. Experiments have also been conducted with a real-life case study, thus showing that the approach is also relevant in real business settings.Peer ReviewedPostprint (author’s final draft
RelBOSS: A Relationship-Aware Access Control Framework for Software Services

Context-awareness is an important aspect of the dynamically changing environments and the relationship context information brings new benefits to the access control systems. Existing relationship-aware access control approaches are highly domain-specific and consider the expression of access control policies in terms of the relationship context information. However, these approaches are unable to dynamically capture the granularity levels and strengths of the relevant relationship. To this end, in this paper we present a formal Relationship-Aware Access Control (RAAC) model for specifying the relevant relationship context information and the corresponding access control policies. Using the RAAC model, we introduce an ontology-based framework, Rel ationship- B ased access control O ntology for S oftware S ervices (RelBOSS). One of the main novelties of the framework is that it dynamically captures the relationship context information (the type/name, granularity levels and strengths of the relevant relationship). Experiments with a software prototype confirm the feasibility of our framework.Full Tex
Event-based real-time decomposed conformance analysis

Process mining deals with the extraction of knowledge from event logs. One important task within this research field is denoted as conformance checking, which aims to diagnose deviations and discrepancies between modeled behavior and real-life, observed behavior. Conformance checking techniques still face some challenges, among which scalability, timeliness and traceability issues. In this paper, we propose a novel conformance analysis methodology to support the real-time monitoring of event-based data streams, which is shown to be more efficient than related approaches and able to localize deviations in a more fine-grained manner. Our developed approach can be directly applied in business process contexts where rapid reaction times are crucial; an exhaustive case example is provided to evidence the validity of the approach.Peer ReviewedPostprint (author’s final draft
Mining business process deviance : a quest for accuracy

This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot\ud
or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern\ud
mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy
Multi-paradigm process mining: retrieving better models by combining rules and sequences

Business process mining is a well-established field of research which focuses on the automatic retrieval and analysis of process flows. The discovery and representation of these models is based on techniques that come in all shapes and forms. Most notably, procedurally-based
algorithms such as Heuristics Miner have been used successfully for this purpose. Also, declarative process model miners have been proposed, which give other insights into the model by generating rules that apply on the activities. This paper proposes an integrated approach to combining these paradigms to discover process models that contain best of both worlds to enrich insights into the event logs under scrutiny.status: publishe
Augmenting and assisting model elicitation tasks with 3D virtual world context metadata

Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Theories of situated cognition indicate that interactive 3D representations of real work environments engage and prime the cognitive state of the viewer. In this paper, our major contribution is to augment a previous process elicitation methodology with virtual world context metadata, drawn from a 3D simulation of the workplace. We present a conceptual and formal approach for representing this contextual metadata, integrated into a process similarity measure that provides hints for the business analyst to use in later modelling steps. Finally, we conclude with examples from two use cases to illustrate the potential abilities of this approach
Flexible querying for SPARQL

Flexible querying techniques can be used to enhance users' access to heterogeneous data sets, such as Linked Open Data. This paper extends SPARQL 1.1 with approximation and relaxation operators that can be applied to regular expressions for querying property paths in order to find more answers than would be returned by the exact form of a user query. We specify the semantics of the extended language and we consider the complexity of query answering with the new operators, showing that both data and query complexity are not impacted by our extensions. We present a query evaluation algorithm that returns results incrementally according to their ``distance'' from the original query.  We have implemented this algorithm and have conducted preliminary trials over the YAGO SPARQL endpoint and the Lehigh University Benchmark, showing promising performance for the language extensions
Concise Multi-challenge CCA-Secure Encryption and Signatures with Almost Tight Security

International audienceTo gain strong confidence in the security of a public-key scheme, it is most desirable for the security proof to feature a tight reduction between the adversary and the algorithm solving the under-lying hard problem. Recently, Chen and Wee (Crypto '13) described the first Identity-Based Encryption scheme with almost tight security under a standard assumption. Here, "almost tight" means that the security reduction only loses a factor O(λ) – where λ is the security parameter – instead of a factor proportional to the number of adversarial queries. Chen and Wee also gave the shortest signatures whose security almost tightly relates to a simple assumption in the standard model. Also recently, Hofheinz and Jager (Crypto '12) constructed the first CCA-secure public-key encryption scheme in the multi-user setting with tight security. These constructions give schemes that are significantly less efficient in length (and thus, processing) when compared with the earlier schemes with loose reductions in their proof of security. Hofheinz and Jager's scheme has a ciphertext of a few hundreds of group elements, and they left open the problem of finding truly efficient constructions. Likewise, Chen and Wee's signatures and IBE schemes are somewhat less efficient than previous constructions with loose reductions from the same assumptions. In this paper, we consider space-efficient schemes with security almost tightly related to standard assumptions. As a step in solving the open question by Hofheinz and Jager, we construct an ef-ficient CCA-secure public-key encryption scheme whose chosen-ciphertext security in the multi-challenge, multi-user setting almost tightly relates to the DLIN assumption (in the standard model). Quite remark-ably, the ciphertext size decreases to 69 group elements under the DLIN assumption whereas the best previous solution required about 400 group elements. Our scheme is obtained by taking advantage of a new almost tightly secure signature scheme (in the standard model) we develop here and which is based on the recent concise proofs of linear subspace membership in the quasi-adaptive non-interactive zero-knowledge setting (QA-NIZK) defined by Jutla and Roy (Asiacrypt '13). Our signature scheme reduces the length of the previous such signatures (by Chen and Wee) by 37% under the Decision Linear assump-tion, by almost 50% under the K-LIN assumption, and it becomes only 3 group elements long under the Symmetric eXternal Diffie-Hellman assumption. Our signatures are obtained by carefully combining the proof technique of Chen and Wee and the above mentioned QA-NIZK proofs