waashk/dblp huggingface dataset:
an efficient dual caching strategy for web service-enabled pdas. pdas have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. however, the most significant step in the evolution of pdas was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity like email, web browsers and maybe most importantly smart/rich clients. being able to host smart clients allows the users of pdas to seamlessly access the it resources (e.g. legacy apps) of their organizations. one increasingly popular way of enabling access to it resources is by using web services (ws) [14]. this trend has been aided by the rapid availability of web service (ws) packages/tools, most notably the efforts of the apache group [1] and ide vendors (e.g., microsoft's visual studio [2], ibm's eclipse [3]). using ide tools and other software packages it is fairly easy for programmers to expose application interfaces and/or consume existing interfaces leading to a gradual replacement of the current web server centric approaches (e.g. asp, jsp, servlets, cgi scripts) with ws centric approach. this paper focuses on the challenges of enabling pdas to host web services consumers and introduces a dual caching approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth.
fast tracking of hierarchical partitions with approximate kl-divergence for geo-temporal organization of personal images. usage of camera-equipped mobile devices raises the need for automatically organizing large personal image collections. we propose here a technique based on a two-level hierarchy of mixture models to automatically organize such a collection with the geo-temporal meta-data attached to each pictures.
reporting leadership patterns among trajectories. widespread availability of location aware devices (such as gps receivers) promotes capture of detailed movement trajectories of people, animals, vehicles and other moving objects, opening new options for a better understanding of the processes involved. in this paper we investigate spatio-temporal movement patterns in large tracking data sets. we present a natural definition of the pattern 'one object is leading others', and discuss how such leadership patterns can be computed from a group of moving entities. the proposed definition is based on behavioural patterns discussed in the behavioural ecology literature. we also present several algorithms for computing the pattern, and they are analysed both theoretically and experimentally.
an architectural co-synthesis algorithm for energy-aware network-on-chip design. network-on-chip (noc) has been proposed to overcome the complex on-chip communication problem of soc (system-on-chip) design in deep submicron. a complete noc design contains exploration on both hardware and software architectures. the hardware architecture includes the selection of pes (processing elements) with multiple types and their topology. the software architecture contains the allocation of tasks to pes, scheduling of tasks and their communications. to find the best hardware design for the target tasks, both hardware and software architectures need to be considered simultaneously. previous works on noc design have concentrated on solving for only one or two design parameters at a time. in this paper, we propose a hardware-software co-synthesis algorithm for a heterogeneous noc architecture. the design goal is to minimize energy consumption while meeting the real-time requirements commonly seen in the embedded applications.
applying genetic algorithms to economy market using iterated prisoner's dilemma. this paper investigates the use of genetic algorithms (ga) to evolve cooperative agents in a competitive market environment using iterated prisoner's dilemma (ipd). our study seeks to follow axelrod's research of computer simulations of the ipd game which is generally regarded as a benchmark for the studies on evolution of cooperation. however, we are of the opinion that his work was a little restrictive and lack of a genuine real-world component. in this paper, we report on a simulation study that attempts to bridge the gap by applying ga to a market model. we examine how well ga could perform against the ipd strategies, and explore the strategic interactions among the agents that represent firms in a coevolving population. we also report on the influence of the genetic operators on the performance of ga. our experimental results show that cooperation can be evolved in such non-cooperative environment using ga. we conclude that with proper tuning of parameters, ga could be extremely useful for optimizing the outcome of an economy market.
distortion-constrained compression of vector maps. an algorithm for lossy compression of vector maps for given error tolerance was developed. the algorithm is based on optimal polygonal approximation and dynamic quantization of vector data. a near optimal distortion-constrained quantizer with step defined by the tolerance level was constructed. the proposed algorithm performed well compared to other approaches.
a mechanism for replicated data consistency in mobile computing environments. mobile computing allows for the development of new and sophisticated database applications. such applications require the reading of current and consistent data. in order to improve data availability, increase performance and maximize throughput, data replication is used. however, due to inherent limitations in mobile and other loosely-coupled environments, the concurrency control and replica control mechanisms must be revisited. this paper proposes a new protocol that guarantees the consistency of replicated data in a mobile computing environment, while provide high data availability and ensure an eventual replica convergence towards a strongly consistent state.
olindda: a cluster-based approach for detecting novelty and concept drift in data streams. a machine learning approach that is capable of treating data streams presents new challenges and enables the analysis of a variety of real problems in which concepts change over time. in this scenario, the ability to identify novel concepts as well as to deal with concept drift are two important attributes. this paper presents a technique based on the k-means clustering algorithm aimed at considering those two situations in a single learning strategy. experimental results performed with data from various domains provide insight into how clustering algorithms can be used for the discovery of new concepts in streams of data.
towards reusable and modular aspect-oriented concurrency control. information systems based on the world wide web increased the impact of concurrent programs. such increase demands the definition of methods for obtaining safe and efficient implementations of concurrent programs, since the complexity of implementation and tests in concurrent environments is bigger than in sequential environments. this work defined guidelines to restructure object-oriented software in order to modularize concurrency control using aspect-oriented programming. those guidelines are supported by a concurrency control implementation that guarantees system correctness without redundant concurrency control, both increasing performance and guaranteeing safety. we define abstract aspects that constitute a simple aspect framework that can be reused to implement concurrency control in other applications. the achieved modularization makes the concurrency control easy to evolve and decreases the complexity of other parts of the software, such as business and data management modules, by decoupling concurrency control code from them.
a randomized knot insertion algorithm for outline capture of planar images using cubic spline. the proposed work, in this paper, is concerned with an efficient technique of curve fitting using cubic splines. the technique has various phases including extracting outlines of images, detecting corner points from the detected outline, addition of extra knot points if needed. the last phase makes a significant contribution by making the technique automated. it uses the idea of knot insertion in a randomized manner. the proposed algorithm is an iterative one. the algorithm proposed is computationally efficient as compared to least square approach.
online resource management in a multiprocessor with a network-on-chip. we propose an online resource allocation solution for multiprocessor systems-on-chip, that executes several real-time, streaming media jobs simultaneously. the system consists of up to 24 processors connected by an aethereal [7] network-on-chip (noc) of 4 to 12 routers. a job is a set of processing tasks connected by fifo channels. each job can be independently started or stopped by the user. each job is annotated with resource budgets per computation task and communication channel which have been computed at compile-time. when a job is requested to start, resources that meet the required resource budgets have to be found. because it is done online, allocation must be done with low-complexity algorithms. we do the allocation in two-steps. first, tasks are assigned to virtual tiles (vts), while trying to minimise the total number of vts and the total bandwidth used. in the second step, these vts are mapped to real tiles, and network bandwidth allocation and routing are performed simultaneously. we show with simulations that introducing randomisation in the processing order yields a significant improvement in the percentage of mapping succdesses. in combination, these techniques allow 95% of the processor resources to be allocated while handling a large number of job arrivals and departures.
web image annotation by fusing visual features and textual information. in this paper, we propose a novel web image annotation method, namely fmd (fused annotation by mixed model graph and decision tree), which combines visual features and textual information to conceptualize the web images. the fmd approach consists of three main processes: 1) construct the visual-based model, namely modelmmg, 2) construct the textual-based model, namely modeldt, and 3) fuse modelmmg and modeldt as modelfmd for annotating the images. the purpose of visual-based annotation model is to objectify the image not only by the global content of the image but also by its local content of composing objects. the textual-based annotation model is to handle the problems of user-specified dependency of keywords and the complex computation due to high dimensionalities in text features. the experimental results reveal that the proposed fmd method is very effective for web image annotation in terms of accuracy through the integration of two different types of features.
enhancing qos metrics estimation in multiclass networks. this paper discusses the problematic of qos monitoring, suggesting the use of on-line multipurpose active monitoring in multiclass networks as a powerful tool to efficiently assist and enhance the control of multiple service levels. to improve the simultaneous estimation of one-way qos metrics, we propose a flexible probing source able to adjust probing patterns to the measurement requirements of each service class, exploring pattern coloring to better sense packet loss. the proof-of-concept provided shows that the proposed solution improves the estimation accuracy of multiple qos metrics significantly, with a reduced probing overhead.
using text search for personal photo collections with the mediassist system. the mediassist system enables organisation and searching of personal digital photo collections based on contextual information, content-based analysis and semi-automatic annotation. one mode of user interaction uses automatically extracted features to create text surrogates for photos, which enables text search of photo collections without manual annotation. our evaluation shows that this text search facility is effective for known-item search.
a computation environment for automated negotiation: a case study in electronic tourism. the automated negotiation topic plays an important role in e-commerce research. however, despite considerable work on automated negotiation, few research efforts have aimed at software engineering facilities such a reuse and flexibility. to address this issue, we propose a novel computation environment for building agents with flexible negotiation strategies to function in various virtual business domains. regarding the negotiation strategies, some decision taking assistance techniques may be used in group, e.g. rule-based reasoning and techniques to machine learning. considering the flexibility of acting in various business domains, a specific agent can be programmed to work in as many business domains as necessary, and essentially, it will also be possible to reconfigure the agent's business domains at execution time. all the experiments in this work were idealized in the terms of a tourism negotiation package. results from these experiments demonstrate effectiveness of our proposal.
mining communities of acquainted mobile users on call detail records. in a telecommunication system, call detail records (i.e., cdrs) are generated automatically for tracking and billing purposes when mobile users having calls. to further investigate the information buried in huge amounts of cdrs, relationship among mobile users can be organized. specifically, communities of acquainted mobile users can be effectively discovered from collected cdrs through our approach proposed in this paper. note that understanding the communities and corresponding calling behaviors are of great importance to telecommunication companies. to conduct proper community mining on cdrs, techniques of data transformation and social network analysis are fully exploited. our study shows that the proposed approach is practically feasible.
his-kcwater: context-aware geospatial data and service integration. the nature of today's geographically and managerially distributed geospatial information sources makes the interoperability across different sources from different organizations difficult. the integration of real-time water quality assurance data with geographic data is even more challenging. in this paper, we present a context-aware geospatial data and service integration framework that is based on the combination of a syntactic model, a semantic model and a pragmatic model using semantic web technologies. this model is context-aware, with the ability to analyze existing dependencies, predict causes and effects and provide context-aware services (which information services are relevant, how to perform the services, how often they are needed, etc). as a proof of concept, we demonstrate the his-kcwater system for supporting users in analyzing real time watershed data, predicting the water quality using hydrologic model simulators, interpreting the results, dynamically forecasting problems and generating alerts about water quality issues.
modeling mirna data. as a sub-type of ncrna genes, micro rna (mirna) produces rna that is implicated in the regulation of gene translation and expression. human diseases can result from alternation in such non-coding rna. building a consolidated mirna database repository thus becomes a crucial element for mirna-related research. we have set up a dual objective in our work: to explore alternative approaches for mirna data modeling, and to consolidate mirna data in an integrated repository for future retrieval and analysis of mirna data. we have explored three approaches for mirna data modeling. for the same source data, we have implemented a relational database (converted from an initial entity-relationship diagram), an xml database, and an integrated xml-relational database. we have also compared their performance on the criteria of query performance and design flexibility. though using entity-relationship modeling of the data provides access to the strength and stability of relational databases, our work concludes that xml information modeling and native xml databases provide geneticists the adaptability and flexibility required to model a complex, constantly changing domain such as mirna research.
a quantitative method for assessing algorithms to remove back-to-front interference in documents. documents written on both sides on translucent paper make visible the ink from one side on the other. this artifact is called "back-to-front interference", "bleeding" or "show-through". the direct binarization of documents with such interference yields unreadable documents. the literature presents several algorithms for suitably removing such artifact. this paper presents a method to assess algorithms to remove back-to-front interference.
how to detect semantic business process model variants? precise modeling of business processes has paved the way to realize process aware information systems that include allocations of resources, communication services, or hardware devices to users. changes in business strategies or new business opportunities may result in modifications of implemented functionalities of information systems and their underlying business process models. the result of these modifications are business process model variants. in this paper, we propose an algorithm for determining linguistic similarities between business process model variants in order to faciliate process redesign.
tube (text-cube) for discovering documentary evidence of associations among entities. user-driven discovery of associations among entities, and documents that provide evidence for these associations, is an important search task conducted by researchers and do-main information specialists. entities here refer to real or abstract objects such as people, organizations, ideologies, etc. associations are the inter-relationships among entities. most current works in query-driven document retrieval and finding representative subgraphs are ill-suited for the task as they lack an awareness of entity types as well as an intuitive representation of associations. we propose the tube model, a text cube approach for discovering associations and documentary evidence of these associations. the model consists of a multi-dimensional view of document data, a flexible representation of multi-document summaries, and a set of operations for data manipulation. we conduct a case study on real-life data to illustrate its applicability to the above task and compare it with the non-tube approach.
a flexible representation of controllers for physically-based animation of virtual humans. in this paper, we propose a representation of controllers that uses high-level sensors and possesses a general and intuitive structure that offers several types of parameters, which can be modified by the animator or automatically. this structure, with the feedback signals provided by its sensors, allows several state machines to act simultaneously on the model, or in a subset of its actuators. the sensors can be optimized, facilitating their definition and use. the representation also permits the animator to define procedures with more general instructions in order to be automatically executed by the controller during the dynamics simulation.
learning rules with negation for text categorization. this paper describes olex, a novel method for the automatic construction of rule-based text classifiers. olex relies on an optimization algorithm whereby a set of (both positive and negative) discriminating terms is generated for the category being learned. such terms are then used to construct a classifier of the form "if term t1 or ... term tn occurs in document d, and none of terms tn--1, &middot; &middot; &middot; tn--m occurs in d, then d belongs to category c". the proposed method is simple and elegant. despite this, the results of a systematic experimentation performed on both the reuters-21578 and the ohsumed data collections show that olex is both effective and efficient.
separation of concerns in translational semantics for dsls in model engineering. development of domain specific languages (dsls) in the context of model driven engineering is gaining more and more popularity. as evolution lies in the heart of every software system, the major requirement for dsls is that they should be modular and resilient to changes. mde-based dsl frameworks should enable a modular specification of language translational semantics and the composition of the modules into languages. ultimately, the availability of such techniques should make the dsl development faster. separation of concerns is a sound software engineering principle used to obtain better modularity, reusability, and adaptability of systems. however, this principle must be supported by proper tools that allow the separation achieved at a conceptual level to be preserved in the language specification. in mde, the mainstream tools for specifying translations are model transformation languages. in this paper we evaluate a class of model transformation languages regarding their applicability for capturing the translational semantics of dsls in a modular way. we found that the concepts in the domain of translational semantics significantly mismatch with the language constructs of the transformation language. we suggest that this problem may be better approached by a domain-specific transformation language.
a phasing mechanism for model transformation languages. in recent years a great effort has been devoted to understanding the nature of model transformations. as a result, several mechanisms to improve model transformation languages have been proposed. phasing has been proposed in some works as a rule scheduling or organization mechanism, but without any detail. in this paper, we present a phasing mechanism a we explain in detail how it can be integrated in a transformation language and when its usage is appropriate. the mechanism we propose can be seen as an internal transformation composition mechanism. first, we motivate the work, and then we describe in depth the mechanism. finally, we show four examples of application and give some conclusions.
a priority assignment strategy of processing elements over an on-chip bus. the number of bus transactions in system-on-chip (soc) grows significantly in recent years. because of different timing constraints for different applications, how to find a proper priority assignment for processing elements (pes) of soc becomes very challenging. in this paper, we first show that the priority assignment problem with one unique priority for each pe is np-complete. when each bus transaction can have one unique priority, we propose an optimal priority assignment algorithm for a given workload. we then propose a priority assignment strategy based on simulated annealing (sa) for pes, where bus arbitration is done in a priority-driven fashion. the objective is to minimize the number of priorities needed for each pe and to satisfy the timing constraints of applications. the experimental results show some encouraging results in priority assignment.
software customization in model driven development of web applications. model driven development (mdd) of complex software systems can require manual adaptations of the generated artifacts. in fact, in order to cope with unforeseen requirements which are not completely satisfiable by means of the involved modeling languages, developer interventions could be needed. the optimal solution to deal with this issue, is based on the expressiveness improvement of the involved metamodels and refinement of the used model transformations. nevertheless, these adaptations are not always possible or cost-effective especially if the new functionalities that have to be introduced affect only the single application being developed. this paper discusses and attempt to hand-tune the generated code by providing an approach supporting its merging with hand written modifications. for this purpose, the behaviour model of the system under study is considered to graphically specify the injection points where the modifications have to occur. the discussions are based on a running example consisting of a simple web application.