waashk/dblp huggingface dataset:
a two-dimensional separation of concerns for compiler construction. during language evolution, compiler construction is usually performed along two dimensions: defining new abstract syntax tree (ast) classes, or adding new operations. in order to facilitate such changes, two software design patterns (i.e., the inheritance pattern and the visitor pattern) are widely used to help modularize the language constructs. however, as each design pattern is only suitable for one dimension of extension, neither of these two patterns can independently fulfill the evolution needs during the compiler construction process. in this paper, we analyze two dimensions of concerns in compiler construction and develop a paradigm allowing compiler evolution across these two dimensions using both object-orientation and aspect-orientation. moreover, this approach provides an ability to perform pattern transformation based on pluggable aspects. a simple implementation of an expression language and its possible extension is demonstrated using java and aspectj.
on bounding energy consumption in dynamic, embedded real-time systems. we present a cpu scheduling algorithm, called the <u>e</u>nergy-<u>b</u>ounded <u>u</u>tility <u>a</u>ccrual algorithm (or ebua). ebua is a polynomial-time algorithm that satisfies bounds on system-level energy consumption and activities' accrued timeliness utility. we analytically establish several timeliness properties of ebua. our simulation experiments using amd's (dvs-enabled) k6 processor model confirm the algorithm's effectiveness and superiority.
a dynamic data/currency protocol for mobile database design and reconfiguration. this paper presents flexible protocols for dynamic database design and reconfiguration, enabling mobile database to be designed in such a way that data location, replication and even use semantics can be changed dynamically. in particular, a dual data/currency hoarding and synchronization protocol, a metadata protocol and currency redistribution protocol are proposed. metadata records the changing characteristics of replicas and currencies are dynamically redistributed to fit the target. primaries may be diluted, concentrated and transferred in the system. traditional distributed database is included as home of data. an ad-hoc database may check out its desired data/currency and check them back in when they are no longer accessed by the mobile users. we demonstrate that the flexibility of this approach can significantly improve commit performance under dynamic access and mobility behavior.
indexing continuously changing data with mean-variance tree. constantly evolving data arise in various mobile applications such as location-based services and sensor networks. the problem of indexing the data for efficient query processing is of increasing importance. due to the constant changing nature of the data, traditional indexes suffer from a high update overhead which leads to poor performance. in this paper, we propose a novel index structure, the mvtree, which is built based on the mean and variance of the data instead of the actual data values that are in constant flux. since the mean and variance are relatively stable features compared to the actual values, the mvtree significantly reduces the index update cost. the distribution interval and probability distribution function of the data are not required to be known a priori. the mean and variance for each data item can be dynamically adjusted to match the observed fluctuation of the data. experiments show that compared to traditional index schemes, the mvtree substantially improves index update performance while maintaining satisfactory query performance.
on unit task linear-nonlinear two-cluster scheduling problem. in parallel and distributed processing, tasks are ordinarily clustered and assigned to different processors or machines before they are scheduled. the assignment of tasks to processors is called clustering. the ordering of tasks for execution is called cluster scheduling. the set of tasks is typically modelled as a directed acyclic task graph (dag). as a result of the clustering process, the set of tasks in each cluster either forms a total ordering, called linear, or it doesn't, called nonlinear, with respect to the dag. it has been shown that two-cluster scheduling with one cluster being linear and the other nonlinear is strongly np-hard. in this paper, we develop an exact algorithm to compute an optimal schedule for the above problem in o(e + &alpha;(n)n) time when tasks are restricted to unit tasks, where n is the number of nodes, e is the number of edges, and &alpha;(n) is similar to inverse ack-erman function. we also show that when both clusters are nonlinear, even when tasks are restricted to unit-tasks and task graphs are restricted to those having no path of length more than three, the problem remains np-complete in the strong sense.
enhancing program verifications by restricting object types. object types are abstract specifications of object behaviors; object behaviors are abstractly indicated by object component interdependencies; and program verifications are based on object behaviors. in conventional object type systems, object component interdependencies are not taken into account. as a result, distinct behaviors of objects are confused, which can lead to fundamental typing/subtyping loopholes and program verification troubles. in this paper, we first identify a program verification problem which is caused by the loose conventional object typing/subtyping which is in turn caused by the overlooking of object component interdependencies. then, as a new object typing scheme, we introduce object type graphs (otg) in which object component interdependencies are integrated into object types. finally, we show how the verification problem can be resolved under otg.
computing edit distances between an xml document and a schema and its application in document classification. in this paper, we present an algorithm to find a sequence of top-down edit operations with minimum cost that transforms an xml document such that it conforms to a schema. it is shown that the algorithm runs in o(p x log p x n), where p is the size of the schema(grammar) and n is the size of the xml document (tree). we have also shown that edit distance with restricted top-down edit operations can be computed the same way.we will also show how to use the edit distances in document classification. experimental studies have shown that our methods are effective in structure-oriented classification for both real and synthesized data sets.
mining concept associations for knowledge discovery in large textual databases. in this paper, we describe a new approach for mining concept associations from large text collections. the concepts are short sequences of words that occur frequently together across the text collections. it is these concepts that convey most of the meaning in any language. our goal is to extract interesting associations among concepts that co-occur within the text collections. interesting association between the concepts is mined using association rule mining algorithm. finally we construct directed graph from current rules. the experimental result shows that our approach can efficiently find interesting concept associations in large text collections.
further extensions of fipa contract net protocol: threshold plus doa. being easily understood and implemented for resource allocation or task assignment, fipa contract net protocol (cnp) has been widely applied to kinds of multi-agent system (mas). basing on a typical extension to the original cnp, which was named as contract net with confirmation protocol (cncp), this paper made two further extensions to cnp by the ideas of threshold and degree of availability (doa). cncp enabled the agents to make proposals or accept offers in a continuous time, but it also increased the risk of getting sub-optimal deal or nothing for individual agent. our research is just aiming at relieving this risk. the idea of threshold comes from the fact that: no matter how much proposals one agent sent out, it will get only one task to do at last. by setting a proper threshold, we can save many unnecessary computational costs in making or evaluating proposals. the concept of doa is derived from the principle of maximum expected-utility (meu). with this concept, one agent will evaluate proposals not only by the required costs, it also takes the doa of a participant as an important factor in choosing its best deal, so initiators can act in a more rational way. we also presented an under-consideration idea "deadline", which might become another feasible way to increase system effectiveness and efficiency.
semantic-based information retrieval of biomedical data. in this paper, we propose to improve the effectiveness of biomedical information retrieval via a medical thesaurus. we analyzed the deficiencies of the existing medical thesauri and reconstructed a new thesaurus, called medthes, which follows the ansi/niso z39.19-2003 standard. medthes also endows the users with fine-grained control of information retrieval by providing functions to calculate the semantic similarity between words. we demonstrate the usage of medthes through an existing data search engine.
a uniform meta-model for modeling integrated cooperation. process modeling is a central topic of research on computer supported cooperative work (cscw). uniformity and flexibility in work representation and process enactment are two primary goals. we develop a novel meta-model capable of modeling uniformly a wide range of cooperation scenarios. we will discuss the key elements of the model and its computerized formalism, the cova programming language, and its runtime system. we will describe in this language several typical cooperation scenarios to illustrate how integrated cooperation and other cooperation scenarios can be described and supported with our model.
the t-detectors maturation algorithm based on match range model. negative selection algorithm is used to generate detector for change detection, anomaly detection. but it can not be adapted to the change of self data because the match threshold must be set at first. in this paper, inspired from the maturation of t-cells, a match range model is proposed. base on the model, a novel algorithm composed of positive selection and negative selection is proposed to generate t-detectors and the match threshold is not needed. genetic algorithm is used to evolve the detectors with self-adapted match range. the proposed algorithm is tested by simulation experiment for anomaly detection and compared with the negative selection algorithm. the results show that the proposed algorithm is more effective than the negative selection algorithm and match range is self-adapted.
mediation security specification and enforcement for heterogeneous databases. information sharing among heterogeneous databases requires increasing attention and poses a pressing need. successful protection of information by an effective access control mechanism is a basic requirement for interoperation among heterogeneous data sources. however, most existing work on access control focuses on access control model and security related information, little effort is devoted to exploring access control on the semantic-related heterogeneous databases. no current work resolves the security challenges faced by heterogeneous databases, i.e., context-aware authorization, semantic heterogeneity of databases and policy specification at different points. this paper proposes a mediation security system that secures the information sharing among heterogeneous databases with the promise to meet the above requirements. the proposed system models the flexible access control requirements specific to mediation security while providing uniform access for heterogeneous data sources.
mediation framework modeling and verification by sam. the architecture-level design of mediation systems requires rigorous modeling and analysis techniques to assure the correctness the behaviors of the architecture. the software architecture model (sam) is a formal systematic software architecture specification and analysis methodology that is able to define and analyze different system aspects using different formalisms to improve understandability and reduce complexity. this paper proposes an adaptive mediation framework that provides an easily extensible, decentralized environment for sharing data from heterogeneous databases. we demonstrate how to apply sam to specify the mediation architecture and analyze the temporal properties of the proposed architecture.
image texture classification using datagrams and characteristic views. this paper addresses the problem of image texture classification. a novel texture feature called "characteristic view", which is directly extracted from a kernel corresponding to each texture class, was developed. the k-views template method was used to classify the texture pixels based on these features. the characteristic view concept is based on the assumption that an image taken from the nature scenes, a specific texture class in this image will frequently reveal the repetitions of some certain patterns of features. different "views" can be obtained as features from different spatial locations. the datagram concept is developed in this paper. experimental results using datagrams are provided.
implementation of a dynamic adjustment mechanism with efficient replica selection in data grid environments. the co-allocation architecture was developed in order to enable parallel downloading of datasets from multiple servers. several co-allocation strategies have been coupled and used to exploit rate differences among various client-server links and to address dynamic rate fluctuations by dividing files into multiple blocks of equal sizes. however, a major obstacle, the idle time of faster servers having to wait for the slowest server to deliver the final block, makes it important to reduce differences in finishing time among replica servers. in this paper, we propose a dynamic co-allocation scheme, namely recursive-adjustment co-allocation scheme, to improve the performance of data transfer in data grids. our approach reduces the idle time spent waiting for the slowest server and decreases data transfer completion time. we also provide an effective scheme for reducing the cost of reassembling data blocks.
an approach to secure information flow on object oriented role-based access control model. in this paper, we conclude that confinement problem may occur on the object oriented role-based access control model (orbac). in order to solve the problem, a technique called information flow analysis is proposed. moreover, based on the information flow technique and the principle of mandatory access control principles, a message filtering algorithm and a role set assignment method are developed to deal with the confinement problem on orbac.
nfp-based nesting algorithm for irregular shapes. this paper presents a new 2d irregular-shaped nesting algorithm, which is based on a new nfp (no fit polygon) algorithm and a new piece placement policy named as lowest-gravity-center policy. compared with existing algorithms, the proposed nfp algorithm has lower time-complexity and higher robustness due to the introduction of trace lines. the proposed lowest-gravity-center policy places a piece to the position which has the lowest gravity center based on nfp. compared with the bottom-left piece placement policy, the proposed lowest-gravity-center policy results in a relatively flat boundary for the pieces. the proposed nesting algorithm can deal with pieces with arbitrary rotation and holes. it achieved competitive layout solutions both in nesting pattern height and area-utilization ratio.
on search in peer-to-peer file sharing systems. we consider the problem of information retrieval in a peer-to-peer file sharing system. we assume that peers are unreliable, metadata are sparse, and queries are short. in light of this, the question becomes whether there exists a combination of metadata management and ranking techniques that can consistently improve query results. we try several alternatives, and, through analysis and simulation, show a combination that generally yields the best results.
adaptive page-level incremental checkpointing based on expected recovery time. incremental checkpointing, which is intended to minimize checkpointing overhead, saves only the modified pages of a process. this means that in incremental checkpointing, the time consumed for checkpointing varies according to the amount of modified pages. thus, an efficient interval of checkpointing have to be determined on run-time of a process. in this paper, we present an efficient and adaptive page-level incremental checkpointing facility that is based on the interval determination mechanism for minimizing the expected execution time. our simulation results show that the expected execution time was significantly reduced compared with existing periodic page-level incremental checkpointing.
a fast start-up technique for flash memory based computing systems. flash memory based embedded computing systems are becoming increasingly prevalent. these systems typically have to provide an instant start-up time. however, we observe that mounting a file system for flash memory takes 1 to 25 seconds mainly depending on the flash capacity. since the flash chip capacity is doubled in every year, this mounting time will soon become the most dominant reason of the delay of system start-up time. therefore, in this paper, we present instant mounting techniques for flash file systems by storing the in-memory file system metadata to flash memory when unmounting the file system and reloading the stored metadata quickly when mounting the file system. these metadata snapshot techniques are specifically developed for nor- and nand-type flash memories, while at the same time, overcoming their physical constraints. the proposed techniques check the validity of the stored snapshot and use the proposed fast crash recovery techniques when the snapshot is invalid. based on the experimental results, the proposed techniques can reduce the flash mounting time by about two orders of magnitude over the existing de facto standard flash file system.
dynamic group communication in mobile peer-to-peer environments. this paper presents an approach to integrate publish/subscribe semantics with on-demand multicast in wireless ad hoc networks, providing dynamic group communication with fine-grained subscriptions. a prototype application 'pgm golf forum' is developed, which enables a dynamic publish/subscribe system among the gallery during a golf tournament. dynamic construction of an event dissemination structure to route events from event publishers to subscribers is important, especially to support rapidly changing multi-hop topologies over wireless links. the proposed approach aggregates content-based subscriptions in a compact data format (bloom filters), and odmrp (on-demand multicast routing protocol) is extended to use this context from the middleware-tier to construct an optimized dynamic dissemination mesh. it operates dynamic multicast grouping by aggregated subscriptions applying clustering techniques. cooperation between middleware-tier and network components provides reliable finegrained publish/subscribe by odmrp's mesh topology.
interactive 3d visualization of highly connected ecological networks on the www. food webs describe who eats whom among species within a habitat. these networks depict interlinked food chains and have long been a central ecological paradigm for studying biocomplexity. as food-web data encompasses more species, the network structure of the feeding links among those species results in a highly connected network that is difficult to visualize in 2d. such simple representations often obscure important details critical for understanding the structure and function of ecosystems. graph layout is thus critically important for enhanced understanding of complex food webs. in this paper, we describe 3d visualizations of food webs that use intuitive node placement, minimal edge-crossing and link length, hierarchical node aggregation, and analysis tool integration. we also describe our deployment of "webs on the web" (wow) visualization and analysis tools on the www. these tools will facilitate food-web research, collaboration, and education. given the variety of 3d visualization technologies on the www, our wow visualization pipeline supports diverse formats and adapts to users' preferences by employing xml and a flexible architecture. currently, wow uses xml to semantically markup food-web data (foodwebml), extracts visual information into x3d format, and then uses the information to create a direct display on vrml/x3d browsers or feed a shockwave 3d visualization.
using an object oriented model for resolving representational differences between heterogeneous systems. one of the major concerns in the study of software interoperability is the inconsistent representation of the same real world entity in various legacy software products. this paper proposes an object-oriented model to provide the architecture to consolidate two legacy schemas in order that corresponding systems may share attributes and methods through use of an automated translator. a federation interoperability object model (fiom) is built to capture the information and operations shared between different systems. an automatic wrapper-based translator is discussed that utilizes the model to bridge data representation and operation implementation differences between heterogeneous distributed systems.
semantically enhanced enforcement of mobile consumer's privacy preferences. in such applications as location-based advertising, merchants use consumers' information to send them personalized advertisements. these applications provide convenience to consumers and competitive advantage to merchants. however, the improper use of consumers' information presents a serious threat to their privacy. it is also important to observe that among the motives for the consumers to accept advertisements is the incentive offered by the merchant. therefore, such incentive should become a criterion upon which consumers decide to grant or deny access to their information. we propose modeling mobile consumer preferences including incentive-related preferences in an ontology using the ontology web language (owl) and enforcing these preferences using reasoning techniques. we present modeling of consumer preferences and merchant queries in that ontology and describe how to match them. moreover, we present a prototype implementation and an evaluation study that shows that query size is more significant than the ontology size.
privacy-preserving svm using nonlinear kernels on horizontally partitioned data. traditional data mining and knowledge discovery algorithms assume free access to data, either at a centralized location or in federated form. increasingly, privacy and security concerns restrict this access, thus derailing data mining projects. what we need is distributed knowledge discovery that is sensitive to this problem. the key is to obtain valid results, while providing guarantees on the non-disclosure of data. support vector machine classification is one of the most widely used classification methodologies in data mining and machine learning. it is based on solid theoretical foundations and has wide practical application. this paper proposes a privacy-preserving solution for support vector machine (svm) classification, pp-svm for short. our solution constructs the global svm classification model from the data distributed at multiple parties, without disclosing the data of each party to others. we assume that data is horizontally partitioned -- each party collects the same features of information for different data objects. we quantify the security and efficiency of the proposed method, and highlight future challenges.