waashk/dblp huggingface dataset:
a comparative study of techniques to write customizable libraries. code libraries are characterized by feature-richness --- and, consequently, high overhead. the library specialization problem is the problem of obtaining a low-overhead version of library code when the rich feature set is not needed. a version of that problem is this: given a class with certain core functionality and some "optional" features, how can we offer the client a menu of features such that the specific class answering this request is unencumbered by fields or computation not needed for the requested features? this paper presents a comparative study of several approaches to this version of the library specialization problem. we evaluate object-oriented programming, feature-oriented programming, colored ide, aspect-oriented programming, c-style preprocessor directives, and fragment-oriented program generation. we find that all of these techniques have shortcomings.
simsoa: an approach for agent-based simulation and design-time assessment of soc-based it systems. by applying the paradigm of service-oriented computing (soc) to existing it infrastructures, companies aim at increasing flexibility and reducing complexity prevalent in their enterprise it. yet, introducing soa brings forward an soc-specific it complexity that - among other issues - has to be adressed by a company's it service management (itsm). to facilitate an itsm-based assessment of an soc-based enterprise it architecture at design-time, this paper presents an approach for an agent-based soa simulation system: simsoa. by conducting simulation runs, a design-time assessment of an it service architecture with respect to aspects of availability management, service level management and others is supported. this paper outlines the architecture of simsoa and its current state of implementation - and presents an experiment within which the capabilities of simsoa are analyzed against an itsm-related scenario.
an enhanced multi-view video compression using the constrained inter-view prediction. we propose a method that uses the restricted inter-view prediction for multi-view video coding. in the multi-view video, there exists occluded area because of the locations and angle of cameras. this increases the computational complexity, as it still uses both reference pictures for predicting the area which is not shown in the current frame. in this paper, we proposed a method that does not use the interview prediction in cases when macroblocks are occluded. experimental results show that benefits can be obtained compared with the conventional approaches.
a new multimedia synchronous distance learning system: the iva study case. this paper presents an innovative distance learning system named iva (interactive video and audio) which allows users to access video content, from any electronic device with enough processing capability and resources, aiming an ubiquitous application (anytime and anywhere) through synchronous or asynchronous communication. the paper raises and discusses real issues about multipoint multimedia transmission, taking into account adaptation to differnt devices and different networks. the paper also discusses the implemented solutions to overcome the faced problems. the paper's main focus is on live video transmission to many heterogeneous receivers, as this is the application which demands most resources from devices and network.
an implementation of the earliest deadline first algorithm in linux. recently, many projects have been started to introduce some real-time mechanisms into general purpose operating systems (gpos) in order to make them capable of providing the users with some temporal guarantees. many of these projects focused especially on linux for its capillary and widespread adoption throughout many different research and industrial environments. by tracking the kernel release cycle, we propose an efficient earliest deadline first implementation in the form of a patch-set against the 2.6.27 version, that is the latest released one, as of now. our implementation provides the user with the possibility to choose sched_edf as one of the possible scheduling policies for a task, with an enhanced version of the standard algorithm. in fact, we propose a new approach to shared resources' access which, differently from many other previous existing works, does not require the user to specify any parameters about the critical sections every task will enter during its execution.
using geo-spatial session tagging for smart multicast session discovery. ip multicast is increasingly seen as efficient mode of live content distribution in the internet to significantly large subscriber bases. despite its numerous benefits over ip unicast, multicast has not seen widespread deployment over modern networks. network complexity and session discovery issues have plagued ip multicast since its inception. the internet research community is in general agreement to move over to ssm (source specific multicast). with igmp v 3 (internet group management protocol) and ssm, the source discovery burden will rest with the end user. channel discovery is one of the few stumbling blocks remaining to be solved for successful and widespread deployment of multicast. in an earlier work a dns (domain name system) aware multicast session discovery architecture, mdns, has been proposed which is distributed, hierarchical and globally scalable. this paper proposes to leverage the mdns architecture by enabling multicast sessions to be tagged using geographical and spatial information based on the channel contents or service provider location. it further proposes automatic geo-coding of session registration information as the content provider registers session information with mdns. it also provides necessary design changes and gives data models and data structures to support seamless location sensitive session retrieval as part of search query results to be furnished to the end user. the paper includes envisaged scenarios in which geo-tagging would enhance end user experience and would enable smarter query result generation.
autonomous networked robots for the establishment of wireless communication in uncertain emergency response scenarios. during a disaster, emergency response operations can benefit from the establishment of a wireless ad hoc network. we propose the use of autonomous robots that move inside a disaster area and establish a network for two-way communication between trapped civilians with uncertain locations and an operation centre. our aim is to maximise the number of civilians connected to the network. we present a distributed algorithm which involves clustering possible locations of civilians according to their expected shortfall; clustering facilitates both connectivity within groups of civilians and exploration that is based on the uncertainty of these locations. to achieve efficient allocation in terms of time and energy, we also develop a modified algorithm according to which the robots consider the graph that the cluster centres form and follow its minimum spanning tree. we conduct simulations and discuss the efficiency and appropriateness of the two algorithms in different situations.
using probabilistic model checking and simulation for designing self-organizing systems. self-organization is a feasible metaphor for dealing with the growing complexity of today's software systems. self-organization makes desired global system's behavior appear as an emergent property from component local interactions. the corresponding dynamics is usually non-linear so that the adoption of stochastic simulation and probabilistic model checking becomes essential in the early design stage. in this paper, as a reference example, a possible application of such techniques is shown on a problem called collective sort, whose emergent properties were analyzed by relying on the prism probabilistic model checker.
using aspects and dynamic composition to provide context-aware adaptation for mobile applications. mobile systems characterize by dynamic environments, thus requiring adaptive and context aware mechanisms to perceive changes in the execution context and to dynamically adapt to them. we propose a framework for developing adaptive context aware applications which employs aspect-oriented techniques and dynamic composition to modularize the adaptive behavior and to keep apart the application logic from this behavior.
enhanced lattice-based adaptive random testing. adaptive random testing (art) has been proposed to improve the fault-detection capability of random testing (rt). lattice-based art (l-art) is a distinctive art method which generates test cases by systematically placing and then randomly shifting lattice nodes in the input domain. previous studies showed that l-art has a better fault-detection capability than rt, at the same generation cost. test cases of l-art however may be highly concentrated on certain parts of the input domain - a "skewed distribution of test cases". because of this skewed distribution, when failure regions coincidentally reside in the area where l-art selects a high density of test cases, l-art can have a better fault-detection capability than when failure regions are in the low density area. since failure regions can be in any part of the input domain, this dependency of fault-detection capability on the failure region location is undesirable. we have investigated the cause of such skewed test case distributions using l-art. based on our observations, we propose an enhancement to l-art, which not only has a less-skewed test case distribution, but also demonstrates better and more consistent fault-detection capability than the original l-art.
consistent and decentralized orchestration of bpel processes. scalability, consistency and reliability are among the key requirements for orchestration of bpel processes. in addition, system resources should be efficiently utilized. we present a fully decentralized approach to orchestration of bpel processes that achieves high scalability and supports automatic process recovery. the approach is of continuation-passing style, where continuations, or the reminder of the executions, are passed along with asynchronous messages for process orchestration. furthermore, we identify and address two consistency issues that are more challenging for decentralized orchestrations.
formalizing desargues' theorem in coq using ranks. formalizing geometry theorems in a proof assistant like coq is challenging. as emphasized in the literature, the non-degeneracy conditions leads to technical proofs. in addition, when considering higher-dimensions, the amount of incidence relations (e.g. point-line, point-plane, line-plane) induce numerous technical lemmas. in this paper, we present an original approach based on the notion of rank which allows to describe incidence and non-incidence relations such as equality, collinearity and coplanarity homogeneously. it allows to carry out proofs in a more systematic way. to validate this approach, we formalize in coq (using only ranks) one of the fundamental theorems of the projective space, namely desargues' theorem.
collaborative workflow assistant for organizational effectiveness. knowledge intensive process vary widely due to the variation in the specifics of the incoming request and uncertainty in handling and processing that request. traditional management systems with pre-defined workflows are less effective for enabling these kinds of organizational workflows. consequently, less structured tools for ad-hoc collaboration, such as email or activity management systems [8, 16] are used instead because of the flexibility they permit at execution time. however, these ad-hoc collaborative tools are not as capable of capturing best practice knowledge in a manner that is suitable for reuse in similar contexts and future executions of the workflow. we propose to mine knowledge-intensive workflow executions in order to capture and codify best practice knowledge that can be reused to assist and enhance decision making during future executions. we present a model of a dynamic system and a method for knowledge-intensive workflow enactment that captures ad-hoc applications of tacit knowledge as the work is carried out. our framework is illustrated using a critical and commonly occurring process in industry called the architecture life-cycle (alc) management process. this process reviews technological changes made to the installed information technology (it) architectures to meet the evolving requirements of the business. we illustrate how our framework allows participants to locally enhance the alc, by enabling each individual to perform their work in the best way and recording their intentions explicitly using framework mechanisms that relate activities, work products, transitions, and constraints. we illustrate the axioms that filter out best practices that have been observed during executions and feed them back to the collaborators to guide and improve future executions.
automatic product derivation of multi-agent systems product lines. multi-agent systems (mass) development and software product lines (spls) are two consolidated software engineering techniques. recent research work explores the integration between them by proposing new templates and adaptations to document spl variability in the context of mass. however, the automatic product derivation process is not addressed in these works. in this paper, we propose a new extension to our existing model-based product derivation tool, called genarch, in order to enable the automatic instantiation and customization of multiagent systems product lines (mas-pls). a case study illustrates how the proposed extension can be used to derive products (instances) from a mas-pl.
an orthogonal real-time scheduling architecture for responsiveness qos requirements in soa environments. this paper introduces a novel design approach for real-time multi-resource scheduling aimed at ensuring upper-bounded average response time in interactive computer services. by analyzing the properties of conventional heuristics, this work presents a new algorithm which combines resource and queue disciplines in an orthogonal scheduling architecture which extends recent results on stochastic real-time operations with applications on soa and pervasive computing environments. simulation experiments shows how the attributes of the proposed technique can outperform those of conventionally employed alternatives.
fast error-tolerant search on very large texts. we consider the following spelling variants clustering problem: given a list of distinct words, called lexicon, compute (possibly overlapping) clusters of words which are spelling variants of each other. this problem naturally arises in the context of error-tolerant full-text search of the following kind: for a given query, return not only documents matching the query words exactly but also those matching their spelling variants. this is the inverse of the well-known "did you mean: &hellip; ?" web search engine feature, where the error tolerance is on the side of the query, and not on the side of the documents. we combine various ideas from the large body of literature on approximate string searching and spelling correction techniques to a new algorithm for the spelling variants clustering problem that is both accurate and very efficient in time and space. our largest lexicon, containing roughly 10 million words, can be processed in about 16 minutes on a standard pc using 10 mb of additional space. this beats the previously best scheme by a factor of two in running time and by a factor of more than ten in space usage. we have integrated our algorithms into the completesearch engine in a way that achieves error-tolerant search without significant blowup in neither index size nor query processing time.
a method for developing uml state machines. while uml is one of the most used notation for describing a system to build, there are many issues to tackle to develop an appropriate uml model. in this work, we concentrate on the development of state machines describing the behaviour of a class. we show how relevant information can be searched for in the textual description and organized to obtain a behaviour description from which the state machine can be derived. our method is quite systematic and should help to prevent common mistakes in building state machines.
an evaluation of technologies for the pseudonymization of medical data. privacy is one of the fundamental issues in health care today. although, it is a fundamental right of every individual to demand privacy and a variety of laws were enacted that demand the protection of patients' privacy, approaches for protecting privacy often do not comply with legal requirements or basic security requirements. this paper highlights research directions currently pursued for privacy protection in e-health and evaluates common pseudonymization approaches against legal and technical criteria. thereby, it supports decision makers in deciding on privacy systems and researchers in identifying the gaps of current approaches for privacy protection as a basis for further research.
reduced parallel pnn algorithm for pc grid systems. parallel system with distributed memory is a promising platform to achieve a high performance computing with less construction cost. applications with few communications, such as a kind of parameter sweep applications (psa), can be efficiently carried out on such a parallel system, but some applications are not suitable for the parallel system due to a large communication cost. we focus on pnn (pairwise nearest neighbor) codebook generation algorithm for vq (vector quantization) compression algorithm and proposed a parallel version of the pnn algorithm suitable for the parallel system with distributed memory, called "multi-step parallel pnn". however, the computational complexity of the second half of this algorithm increases as the number of worker computers grows, so we apply a tree-distribution implementation to the second half in order to cope with this problem. we call this approach "reduced parallel pnn". we confirm the effectiveness of the reduced parallel pnn by the evaluation of the computational complexity of the algorithm and the experiment executed on a pc cluster system and a pc grid system.
attention driven visual processing for an interactive dialog robot. in this paper we propose an attention-based vision system for the jast interactive dialog robot. the robotic vision system incorporates three submodules: object recognition, gesture recognition and self recognition. the performance boost of our biologically inspired vision system is based on two assumptions: first, generally attention is attracted by regions of high intensity or hue gardients as well as scene dynamics (bottom-up attention attraction), and second, attentioninal focus can be directed by higher level modules, whether volitional or not, in an inhibitory or reinforcing way (top-down attention control). the system proposed in this paper is able to utilize these assumptions and organize its computational efforts accordingly. integrated into an efficient data management architecture, the vision system is capable of continuously publishing results to the cognitive layer of the robot and thus enables operations in realtime. furthermore, the modular system structure and the asynchronous communication paradigm allows for efficient integration of additional modules, be it visual or any other sensory input data. the main contribution of this work is the application of neuroscience findings and biologically plausible theories of attention based visual processing to a real-world robotic setup. here, our experimental results show tremendous speed-ups using either the bottom-up attention attractors or the principle of top-down attention control as input data filters for further visual analysis, reaching the peak in a combination of the two.
rt-replayer: a record-replay architecture for embedded real-time software debugging. recent embedded real-time software tends to be multithreaded and constrained by stringent timing requirements, thus often leading to serious faults depending on the precise timing of thread executions and event occurrences. a promising approach to debugging such complicated software is to log appropriate events during runtime and replay the same software execution based on them. this would allow one to effectively reproduce and track down the sources of faults. unfortunately, previous software-based replayers have not paid much attention to the precise timing of software execution, but largely focused on the relative order of software events. although some hardware-based replayers can provide such precise timing, they generally require a significant cost and are not available in usual development environments. in this paper, we present a software-based replayer, called rt-replayer. rt-replayer is based on two simple but effective software techniques, called virtual timestamps and instruction hooking, which enable faithful reproduction of the original software execution at instruction level accuracy.
discovery of time series in video data through distribution of spatiotemporal gradients. we propose a novel algorithm to extract time series from video to characterize the type of motion embedded in the video. our method relies on describing the motion exposed in a video as a collection of spatiotemporal gradients. each gradient models high variation in the respective region of the video both in space and time with respect to its spatiotemporal neighborhood. rather than obtaining a coarse sampling of the motion by taking one event per frame, we obtain a continuous function by considering all the events that fall in the short-time slicing window of time length equal to the value of the temporal variance. the result is a composed time series that represents the motion in the video independent of rotation and scale. as an empirical demonstration of the viability of our method, we are able to cluster human motions contained in 114 videos into hand-based motions and foot-based motions with the precision of 86.0% and 75.9% respectively.
a session based personalized search using an ontological user profile. within the information overload on the web and the diversity of the user interests, it is increasingly difficult for search engines to satisfy the user information needs. personalized search tackles this problem by considering the user profile during the search. this paper describes a personalized search approach involving a semantic graph-based user profile issued from ontology. user profile refers to the user interest in a specific search session defined as a sequence of related queries. it is built using a score propagation that activates a set of semantically related concepts and maintained in the same search session using a graph-based merging scheme. we also define a session boundary recognition mechanism based on tracking changes in the dominant concepts held by the user profile relatively to a new submitted query using the kendall rank correlation measure. then, personalization is achieved by re-ranking the search results of related queries using the user profile. our experimental evaluation is carried out using the hard 2003 trec collection and shows that our approach is effective.