waashk/dblp huggingface dataset:
dimensionality reduction for long duration and complex spatio-temporal queries. in this paper we present an approach to mine and query spatio-temporal data with the aim of finding interesting patterns and understanding the underlying data generating process. an important class of queries is based on the flock pattern. a flock is a large subset of objects moving along paths close to each other for a certain pre-defined time. one approach to process a "flock query" is to map spatio-temporal data into a high dimensional space and reduce the query into a sequence of standard range queries which can be presented using a spatial indexing structure. however, as is well known, the performance of spatial indexing structures drastically deteriorates in high dimensional space. in this paper we propose a preprocessing strategy which consists of using a random projection to reduce the dimensionality of the transformed space. our experimental results show, for the first time, the possibility of breaking the curse of dimensionality in a spatio-temporal setting.
using control-flow patterns for specifying business processes in cooperative environments. the representation and execution of business processes have generated some important challenges in computer science. an important related concern is the choosing of the best formal foundation to specify processes behavior, mainly representing control-flow patterns in cooperative environments. the first contribution of this research is the complete definition of the navigation plan definition language (npdl) as an alternative for business process managing in cooperative environments. the second contribution is a complete implementation of control-flow patterns using npdl. these control-flow patterns have been proposed by aalst's group. our experience in applying suggestion of aalst's group to use control-flow patterns as a basis for comparison among control-flow specification languages shows that this comparison method is feasible and the results are useful. the simplicity of npdl representations shows the advantages of npdl as a process specification language. npdl uses a declarative specification (similar to process algebra) to describe the workflow and adds new operators to compensate for the limitations of process algebra and petri nets. npdl also increases the modeling flexibility by allowing the reuse of process expressions in relational data-base systems.
providing context-awareness to virtual file system. in ubiquitous environment, adaptive applications require the context-aware data access. this paper proposes a backward-compatible, context-aware virtual file system (cavfs). users can find a file by the context without remembering full path. since cavfs supports the full backward compatibility, users can even browse hierarchically with the legacy path name, and the legacy applications can access the flies in a context-aware way. we implement cavfs in linux kernel 2.6.7-21. the experiments show that the overhead to maintain the context is reasonably small.
towards secure resource sharing for impromptu collaboration in pervasive computing. access control in mobile and pervasive computing is a complex issue, with many aspects relating to the establishment, management, and enforcement of methods and policies that allow mobile devices to share resources with each other. communication between mobile devices can arise spontaneously, involve the sharing of few resources between heterogeneous platforms, and only need to be maintained for a short time. additionally, the devices often communicate with each other a single time, and have no pre-shared secret or a priori knowledge of the other device. in this paper we propose a secure solution for providing controlled access to local resources in mobile and pervasive computing environments. our solution incorporates demonstrative verification of security credentials, a key-based capability delegation, and easy to use access control features in order to provide simple access with low maintenance costs. it is particularly designed for one-time-only communication between mobile-to-mobile or mobile-to-kiosk devices.
supporting effective unexpected exceptions handling in workflow management systems. this paper proposes a novel architectural framework handling effective unexpected exceptions in workflow management systems (wfms). effective unexpected exceptions are events for which the organizations lack handling strategies. unstructured human interventions are necessary to overcome these situations, but clash with the type of model control currently exercised by wfms. the proposed framework uses the notion of map guidance to orchestrate these human interventions. map guidance empowers users with contextual information about the wfms and environment, enables the interruption of model control on the affected instances, supports collaborative exception handling and facilitates regaining model control after the exception has been resolved. the framework implementation in the open symphony open source platform is also described.
extending the epc with performance measures. the event-driven process chain (epc) is designed for modelling business processes, but does not yet include any means for measuring the performance of a business process. thus, we extend the metamodel of the epc with performance measures to make them conceptually visible. the extensions are tested with an example business process.
fat-miner: mining frequent attribute trees. data that can conceptually be viewed as tree structures abounds in domains such as bio-informatics, web logs, xml databases and multi-relational databases. besides structural information such as nodes and edges, tree structured data also often contains attributes, that represent properties of nodes. current algorithms for finding frequent patterns in structured data, do not take these attributes into account, and hence potentially useful information is neglected. we present fat-miner, an algorithm for frequent pattern discovery in tree structured data with attributes. to illustrate the applicability of fat-miner, we use it to explore the properties of good and bad loans in a well-known multi-relational financial database.
efficient code size reduction without performance loss. for many embedded applications, program code size is a critical design factor for its relationship with limited memory, energy and communication bandwidth. while pursuing better code redundancy elimination in compilation time, people also began to focus on better encoding. some risc processors, such as arm, mips and unicore, support a 32bit/16bit dual-width instruction set. mixed code generation is introduced in expectation of achieving both higher code density from the 16-bit instruction set and good performance from the 32-bit one, with little extra cost. we describe a new fine-grained mixed code generation scheme in this paper. we introduce into the 32-bit isa a new 16-bit mode-changing instruction set which has the following features: firstly, the operation of the instructions are very common in unicore32 programs and are appropriate to be coded into 16 bits; secondly, they can switch the current processor mode while performing their own operations. we implement the mixed code generation at link time in our compilation toolchain. our experiments show that this scheme is successful in better encoding a program's computations to reduce code size without sacrificing performance. in addition, there are little modifications to micro-architecture, ensuring good compatibility with the original instruction set architecture.
exploring olap aggregates with hierarchical visualization techniques. this paper presents an approach to exploring multidimensional data cubes with hierarchical visualization techniques. analysts interact with data in a predominantly "drill-down" fashion, i.e. from coarse grained aggregates towards the desired level of detail. we suggest that visual hierarchies are adequate for mapping the multiscale nature of decomposition as they preserve the results of the entire interaction. we introduce a class of visual structures called enhanced decomposition tree. every tree level is created by a disaggregation step along a chosen dimension, the nodes contain the corresponding sub-aggregates arranged into a chart and the edges are labeled with their dimensional values. various layouts are proposed to account for different analysis tasks. data cubes are queried using a schema-based browser which presents dimensions by the hierarchies of their granularity levels, thus offering an efficient way of generating hierarchical visualizations. multiple data cubes may be explored in parallel along their shared dimensions. the power of our approach is exemplified using a real-world study from the domain of academic administration.
passwords decay, words endure: secure and re-usable multiple password mnemonics. research on password authentication systems has repeatedly shown that people choose weak passwords because of the difficulty of remembering random passwords. moreover, users with multiple passwords for unrelated activities tend to choose almost similar passwords for all of them. many password schemes have been proposed to alleviate this problem, but they either require modification to the password entry and processing infrastructure (e.g., graphical passwords) or they require the user to have some trusted computing power (e.g., smartcard-like portable devices, browser plugins, etc). we propose a scheme that is applicable to any existing system without any modification, as it does not require any form of involvement from the service provider (e.g., bank, brokerage). nor does it require the user to have any computing device at hand (not even a calculator). our approach consists of generating a mnemonic sentence that helps the users remember a multiplicity of truly random passwords, which are independently selected. the scheme is such that changes to passwords do not necessitate a change in the mnemonic sentence that the user memorizes. hence, passwords can be changed without any additional burden on the memory of the user, thereby increasing the system's security. an adversary who breaks one of the passwords encoded in the mnemonic sentence does not gain information about the other passwords. a key idea is to split a password in two parts: one part is written down on a paper (helper card), another part is encoded in the mnemonic sentence. both of these two parts are required for successfully reproducing the password, and the password reconstruction from these two parts is done using only simple table lookups. passwords' renewal requires only the re-generation of the helper card. our scheme resolves the apparent contradictory requirements from most password policies: that the password should be random, and that it should be memorized and never written down. this makes possible passwords that are more secure against an adversary who illicitly gains access to the password file, as a dictionary attack is now unlikely to succeed (the attacker now needs to carry out a more daunting brute force enumerative attack). even if the adversary somehow obtains the helper card, it gets quantifiably limited information about the passwords of the user (so the helper card may be lost or stolen without disaster immediately striking the user). we quantify the time period required for this adversary to successfully crack the password.
maintenance of maximal frequent itemsets in large databases. there have been many studies on efficient discovery of maximal frequent itemsets in large databases. however, it is nontrivial to maintain such discovered itemsets if more and more data is inserted into the database as the insertions may invalidate some existing maximal frequent itemsets and also create some new ones. in this paper, we clearly address the relationships between old and new maximal frequent itemsets and propose an algorithm imfi, which is based on these relationships to reuse previously discovered knowledge. the algorithm follows a top-down mechanism rather than traditional bottom-up methods to produce fewer candidates. moreover, we integrate sg-tree into imfi to improve the counting efficiency, which is faster than those methods based on vertical bitmap database representation. evaluations on imfi have been performed using both synthetic and real databases. preliminary results show that applying imfi is always much faster than an available incremental mfi mining algorithm, especially when it is equipped with sg-tree.
constructing machine emulator on portable microkernel. in this paper, we present a new model of virtual execution environment, a flexible machine emulator with dynamic translator constructed on a portable microkernel. our model offers both high portability and compatibility. moreover, its flexible interface could be reconfigured to support various types of hardware interfaces.
modeling biomedical assertions in the semantic web. we present an enhanced version of an ontological framework called machineprose that is meant to represent the evolving knowledge resulting from biomedical research. this framework bridges the semantic gap between the use of keywords or controlled vocabularies to index articles and the expressive free-text content of research papers. the benefits of the framework are the ability to carry out precise searches to retrieve relevant literature, and novel abilities to provide answers to questions. we illustrate machineprose with a case study of its application to evidence based medicine.
zoning and metaclasses for character recognition. the contribution of this paper is twofold. first we investigate the use of the confusion matrices in order to get some insight to better define perceptual zoning for character recognition. the features considered in this work are based on concavities/convexities deficiencies, which are obtained by labeling the background pixels of the input image. four different perceptual zoning (symmetrical and non-symmetrical) are discussed. experiments show that this mechanism of zoning could be considered as a reasonable alternative to exhaustive search algorithms. the second contribution is a methodology to define metaclasses for the problem of handwritten character recognition. the proposed approach is based on the disagreement among the characters and it uses euclidean distance computed between the confusion matrices. through comprehensive experiments we demonstrate that the use of metaclasses can improve the performance of the system.
regression testing for component-based software via built-in test design. component-based software technology is expected to be an effective and widely used method of constructing software system. however, some specialties of component bring a great challenge for testing the systems built by externally-provided components, especially for regression testing. built-in test design is a fairly effective way to improve component's testability. in this paper, we present an improved regression testing method based on built-in test design for component-based systems. it needs the mutual collaboration between the component developers and users. component developers are responsible for analyzing the affected methods and constructing the corresponding testing-interfaces in the new component version, and then component users can conveniently pick out the subset of test cases for regression testing with these testing-interfaces. through employing preliminary experiments on some medium scale systems, our regression testing method based on built-in test design has been proven to be fairly feasible and cost-effective in practice.
a software framework for automated verification. this paper describes a software framework supporting the automated verification of models. the framework allows analyzing different kinds of behavioral models of software systems and business processes like uml activity diagrams and bpel models. to extend the applicability of the verification tools, a variety of transformation tools have been integrated in the framework.
text classification based on partial least square analysis. latent semantic indexing (lsi) is a favorite feature extraction method used in text classification. since when important global features for all the classes can be determined by lsi, important local features for small classes may be ignored, this leads to poor performance on these small classes. to solve this problem, a novel method based on partial least square (pls) analysis is proposed by integrating class information into the latent classification structure. important features are extracted according to both their descriptive power of document contents as in lsi, and their capacity of discriminating classes. the extracted features are applied to several classification algorithms: svm, knn, c4.5 and smo. experiments on reuters prove that the features extracted by our method outperform those extracted by lsi in all the cases. in particular, the gain obtained by our method is the most apparent on small classes.
an efficient tdma slot assignment protocol in mobile ad hoc networks. because of its ability to provide the collision-free packet transmission regardless of the traffic load, tdma has been applied effectively in ad hoc networks. until now, assuming a stationary ad hoc network, a tdma slot assignment protocol which achieves the high channel utilization has been proposed. in this paper, we extend the protocol to accomodate the dynamic topology change due to the movement of nodes. in our protocol, since each node autonomously detects a change in network topology and assigns a slot to itself, the high channel utilization in the previous protocol can be kept even when nodes in a network move. furthermore, we verify the effectiveness of the protocol by simulation experiments. the results show that our protocol improves channel utilization in comparison to conventional protocols.
component-based version management for embedded computing system design. nowadays, the development of modern computing devices involves a substantial and growing part of software development. a great challenge for engineers is to manage the evolution of a system with several components in the face of mounting complexity due to concurrent hardware and software development. the key limitations of existing version control tools used for a hardware software co-design process include their inadequacy in representing semantics of design models and inability to manage versions of both hardware designs and associated software components in a cohesive manner. thus, it is difficult to track the logical interdependencies between the changes to hardware and software components in an embedded computing system over time. this paper presents an application of a well-known software engineering approach to the management of embedded systems design artifacts. our novel component-based version management mechanism is capable of capturing and versioning the underlying logical contents of components in system design models and their associated software artifacts in a cohesive manner. this paper also illustrates our approach in creating a versioning system, named emvc, for a hardware software co-design process.
towards an automated test generation for the verification of model transformations. it is widely accepted that model transformations play an important role in the mda approach. as for any software, the validation and verification are essential in the life cycle of a model transformation. the proposition of an automatic approach that is based on functional testing techniques for the verification of model transformations reveals three main issues: the automatic generation of test data, the verification criteria, and the definition of the test oracle. the scope of this paper is restricted to the automatic generation of test data issue of the verification process. we first present a background on essential methods for test case generation and we argue their adaptation for the verification of model transformations. for an automated generation of test data we propose a formal language to be used for the specification of model transformations. we also propose a data partitioning technique that focuses on the structure of models in order to take into account the structural aspect of models when generating input test models. our partitioning technique is to be combined with existing techniques to cover the whole characteristics of the value a model.
a cp-lp approach to network management in ospf routing. in this paper, we consider a routing problem related to the widely used open shortest path first (ospf) protocol, which is considered a challenge within the constraint programming (cp) community. we address the special version of ospf which requires unique and symmetrical paths. to solve this problem, we propose a novel hybrid approach which combines cp and linear programming (lp). our approach employs a new global constraint with problem-specific filtering algorithms to efficiently remove inconsistent values from partial solutions. moreover, this constraint employs two lp relaxations which are used to indicate in-feasible partial solutions due either to network capacity constraints, or to protocol-specific routing constraints. we show the efficiency of our complete approach on backbone networks with hundreds of different demands to route.
an olap system for network-constrained moving objects. the continued advances in mobile devices, geo-location wireless sensors and positioning technologies have led to a profusion of moving object (mo) data. however, conventional on-line analytical processing (olap) systems cannot be applied to mo analysis because the position dimension evolves continuously over time. in this paper, we consider the representation of network-constrained mos in olap systems and make the three following contributions: (i) we introduce a logical model to support continuous dimensions and facts. (ii) we propose an efficient data structure to index moving objects. (iii) based on this index structure, we describe an algorithm which optimizes olap queries for analyzing mos.
constraint propagation for loose constraint graphs. in this paper we investigate how to improve propagation-based finite domain constraint solving by making use of the constraint graph to choose propagators to execute in a better order. if the constraint graph is not too densely connected we can build an underlying tree of bi-connected components, and use this to order the choice of propagator. our experiments show that there exist problems where handling biconnected components can substantially improve the propagation performance.
improving the performance of log-structured file systems with adaptive block rearrangement. log-structured file system (lfs) is famous for its optimization for write performance. because of its append-only nature, garbage collection is needed to reclaim the space occupied by the obsolete data. the cleaning overhead could significantly decrease the performance of file system. however, traditional cleaning policies do not consider the storage location where the valid data in the cleaned segments should be placed and rewritten to. in this paper, we propose a new method called r-lfs to dynamically reorganize data in disk to approximate the organ pipe heuristic that can place data in disk optimally. basically, frequently accessed data are dynamically clustered and placed toward the center of disk, whereas less accessed data are moved and placed toward the edges of disk to reduce disk seek time. the essence of r-lfs is that r-lfs takes advantage of the chance of data reorganization during segment cleaning and data writing, no extra overhead is incurred for this data reorganization. besides, because hot data and cold data are in nature separately clustered under r-lfs, cleaning overhead can be substantially reduced as well. performance evaluation under both trace-driven simulation and practical implementation on netbsd/lfs shows that r-lfs can effectively improve the performance of lfs.