waashk/dblp huggingface dataset:
message-passing and local heuristics as decimation strategies for satisfiability. decimation is a simple process for solving constraint satisfaction problems, by repeatedly fixing variable values and simplifying without reconsidering earlier decisions. we investigate different decimation strategies, contrasting those based on local, syntactic information from those based on message passing, such as statistical physics based survey propagation (sp) and the related and more well-known belief propagation (bp). our results reveal that once we resolve convergence issues, bp itself can solve fairly hard random k-sat formulas through decimation; the gap between bp and sp narrows down quickly as k increases. we also investigate observable differences between bp/sp and other common csp heuristics as decimation proceeds, exploring the hardness of the decimated formulas and identifying a somewhat unexpected feature of message passing heuristics, namely, unlike other heuristics for satisfiability, they avoid unit propagation as variables are fixed.
a smart clustering algorithm for photo set obtained from multiple digital cameras. the use of digital cameras is prevalent. although the cost of digital photographs is low, managing numerous digital photos is burdensome to most users. an intelligent management tool for digital photos is needed. we propose a novel clustering algorithm for concurrent digital photos obtained from multiple cameras. since previous photo clustering methods can be applied to a single camera, a group of photos obtained from different cameras cannot be classified to meet user preference. we newly define temporal/spatial combined clustering for the set of group photos taken from different cameras to solve this situation. we define a new spatial similarity using block alignment for two independent photos. if a user submits photo clustering that shows preference between spatial and temporal clustering, then we can cluster other photo sets according to the reference clustering characteristics. in this method, the exif metadata plays an essential role. we tested more than one thousand photos taken by tourist groups. the final result was satisfactory compared to previous methods based on temporal (spatial) criteria only.
evaluation of vr medical training applications under the focus of professionals of the health area. this paper presents part of the implementation of a virtual reality (vr) framework, involving the building of an interaction module with support to conventional and non-conventional devices, and the evaluation of a system prototype, considering computational and human aspects. the proposal of the evaluation is to improve the framework, and consequently, the applications generated by it, following ideas and opinions of health's professionals (doctors and students), who are the target public of this project.
symmetric encapsulated multi-methods to abstract over application structure. in object systems, classes take the role of modules, and interfaces consist of methods. because methods are encapsulated in objects, interfaces in object systems do not allow abstracting over where methods are implemented. this implies that any change to the implementation structure may cause a rippling effect. sometimes this unduly restricts the scope of software evolution, in particular for methods with multiple parameters where there is no clear owner. we propose a simple scheme where symmetric methods may be defined in the classes of any of their parameters. this allows client code to be oblivious of what class contains a method implementation, and therefore immune against it changing. when combined with multiple dynamic dispatch, this scheme allows for modular extensibility (but not modular type-checking) where a method defined in one class is overridden by a method defined in a class that is not its subtype. in this paper, we illustrate the scheme by extending a core calculus of class-based languages with these symmetric encapsulated multi-methods, and prove the result sound.
model-based reasoning on the achievement of business goals. business process modeling has been realized as a methodology for the optimization of workflows in enterprises. process models help to formalize the actual workflow by describing the activities that are required to achieve a specific business goal. in order to make business processes compliant with laws and regulations, it is necessary in practice to rewrite them in a way such that they guarantee the compliance with the identified security properties. our research towards automated process rewriting for compliance enforcement has revealed that an essential building block is the ability for reasoning on the achievement of business goals: rewriting is only practically applicable (regardless whether it is performed manually or automatically) if the resulting process still achieves the desired business goals. this paper presents an approach for the automated reasoning on the achievement of business goals based on semantic congruence relations.
situated tuple centres in respect. coordination languages and models can play a key role in the engineering of environment in mas (multiagent systems). in this paper, we take the respect coordination language for programming tuple centres, and extend it so as to govern interactions between agents and environment. in particular, we show how its event model can be generalised to support the management of general environment events and make tuple centres situated. to this end, first a case study is sketched where it is shown how the extended respect can be adopted to coordinate a system for sensing and controlling environmental properties. then the syntax and semantics of the extended version of respect is discussed.
creating a mobile web application platform: the lively kernel experiences. the software industry is currently in the middle of two transitions -- towards web-based software and towards web-enabled mobile devices. in this paper, we summarize our experiences in porting the sun labs lively kernel - an interactive web programming environment developed at sun microsystems laboratories - onto a nokia n810 mobile device. we report our experiences based on two different approaches that were used. first, we ported the system onto a regular web browser running in the mobile device. second, we developed a custom-built native execution environment that provides more direct and extensive access to the underlying resources of the system. based on these experiments, we will discuss the lessons learned as well as provide directions and guidance for future work.
seamless access of home theater personal computers for mobile devices. this paper presents the mompt project, an open source project developed to allow access to multimedia content and to control multiple htpcs remotely using mobile devices. the main contribution in the context of this project is its reference design, which allows the access of htpc functionalities using different technologies, such as upnp and xml-rpc. in this paper the reference design as well as its main components are detailed. also, we describe one developed solution for the mediaportal htpc. it is discussed how it was developed, and the evaluation scenario with mobile devices, more specifically an internet tablet.
softening gcc and regular with preferences. in this paper, we present the soft global constraints &sigma;-gcc and &sigma;-regular which are the soft versions with preferences of well-known global constraints gcc and regular. for each of them, we introduce a new violation based semantic which takes into account preferences and propose algorithms to enforce hyperarc consistency in polynomial time, making use of flow theory.
mapping uml sequence diagram to time petri net for requirement validation of embedded real-time systems with energy constraints. requirements validation is a critical task in any embedded real-time system project. normally, these systems have stringent timing constraints that must be satisfied for the correct functioning, since violation might be catastrophic, such as loss of human lives. in addition, there are systems where energy is another constraint that must also be satisfied. hence, early detection of potential problems may reduce risks of faults propagations from early specification to the final code. this paper presents the mapping process of uml sequence diagram into a time petri net with energy constraints (etpn) so as to validate timing and energy requirements in early phases of the embedded system development life-cycle. besides, the estimates obtained from the model are 95% close to the respective measures obtained from the real hardware platform.
task based visualization of 5d brain eit data. visualization is vital for medical research and clinical applications to interpret information presented in medical imaging data. eit (electrical impedance tomography) is a recently developed medical imaging technique, which is able to collect 5d spectral-temporal-spatial data. visualization of multi-dimensional medical imaging data is still a challenge. making use of the tmdv (task-based multi-dimensional visualization) method and cte (cubic task explore) model, a task based prototype system, eit5dvis, is developed for the visualization of 5d brain eit data in this paper. the evaluation result demonstrates the usability of eit5dvis prototype visualization system and the effectiveness of the tmvd method and cte model for the visualization of multi-dimensional medical imaging data.
key processes to start software process improvement in small companies. to support small software enterprises -- vses-- when they are dealing with the first processes that must be considered as they undertake a project of software process improvement --spi--, we have defined a set of processes which we consider to be of high-priority when initiating the implementation of an improvement project in vses. this paper introduces this set of processes and the way in which they have been obtained, based on the analysis and synthesis of three research works carried out within the context of the competisoft project. it also describes our experience of the application of both the process selection and the prioritization strategy in four vses. the result of implementing the proposal shows that it is feasible to implement it in vses and that it can be done with an expense of effort that is suitable for them.
daraw: a new write buffer to improve parallel i/o energy-efficiency. in the past decades, parallel i/o systems have been used widely to support scientific and commercial applications. new data centers today employ huge quantities of i/o systems, which consume a large amount of energy. most large-scale i/o systems have an array of hard disks working in parallel to meet performance requirements. traditional energy conservation techniques attempt to place disks into low-power states when possible. in this paper we propose a novel strategy, which aims to significantly conserve energy while reducing average i/o response times. this goal is achieved by making use of buffer disks in parallel i/o systems to accumulate small writes to form a log, which can be transferred to data disks in a batch way. we develop an algorithm - dynamic request allocation algorithm for writes or daraw - to energy efficiently allocate and schedule write requests in a parallel i/o system. daraw is able to improve parallel i/o energy efficiency by the virtue of leveraging buffer disks to serve a majority of incoming write requests, thereby keeping data disks in low-power state for longer period times. buffered requests are then written to data disks at a predetermined time. experimental results show that daraw can significantly reduce energy dissipation in parallel i/o systems without adverse impacts on i/o performance.
towards a compositional approach to model transformation for software development. model transformation plays an important role in model-driven software development that aims to introduce significant efficiencies and rigor to the theory and practice of software development. although models may have different notations and representations, they are basically graphs, and model transformations are thus nothing but graph transformations. despite a large amount of theoretical work and a lot of experience with research prototypes on graph-based model transformations, it remains an open issue how to compose model transformations. in this paper, we report our first attempt at a compositional framework for graph-based model transformations using the graph querying language unql. the main idea of unql is that graph queries are fully captured by structural recursion that is suitable for efficient composition. we show that the idea can be applied to graph-based model transformations. we have implemented a prototype of the framework and tested it with several nontrivial examples. our new framework supports systematic development of model transformation "in the large" with the advantage that it can automatically remove inefficiencies arising from their composition.
origami fold as algebraic graph rewriting. we formalize paper fold (origami) by graph rewriting. origami construction is abstractly described by a rewriting system (o, ↬), where o is the set of abstract origami's and ↬ is a binary relation on o, called fold. an abstract origami is a triplet (&pi;, ∽, ≻), where &pi; is a set of faces constituting an origami, and ≻ and are binary relations on &pi;, each representing adjacency and superposition relations between the faces. we then address representation and transformation of abstract origami's and further reasoning about the construction for computational purposes. we present a hypergraph of origami and define origami fold as algebraic graph transformation. the algebraic graph-theoretic formalism enables us to reason about origami in two separate domains of discourse, i.e. pure combinatoric domain and geometric domain r x r, and thus helps us to further tackle challenging problems in computational origami research.
automatic discovery of technology trends from patent text. patent text is a rich source to discover technological progresses, useful to understand the trend and forecast upcoming advances. for the importance in mind, several researchers have attempted textual-data mining from patent documents. however, previous mining methods are limited in terms of readability, domain-expertise, and adaptability. in this paper, we first formulate the task of technological trend discovery and propose a method for discovering such a trend. we complement a probabilistic approach by adopting linguistic clues and propose an unsupervised procedure to discover technological trends. based on the experiment, our method is promising not only in its accuracy, 77% in r-precision, but also in its functionality and novelty of discovering meaningful technological trends.
a framework for text visualization using memory traffic management for mobile devices. graphical user interfaces (guis) of document viewers have gained attention with the increase on the number of mobile applications that uses it. however, mobile devices are still limited in relation to the available functionalities for text exhibition. other limitations of these devices are the memory size, processing capacity and battery. this paper describes a framework for text visualization that safely manages memory traffic for mobile applications that intensively use bitmap font files, such as a document viewer. the main goal is to diversify the functionalities concerning to text exhibition in mobile devices, but also minimizing memory traffic.
planning for remarshaling in an automated container terminal using cooperative coevolutionary algorithms. the productivity of a container terminal is highly dependent on the efficiency of loading the containers onto the vessels. the efficiency of container loading depends on how the containers are stacked in the storage yard. remarshaling refers to the preparatory task of rearranging the containers to maximize the efficiency of loading. in this paper, we propose cooperative coevolutionary algorithms (cceas) to derive a plan for remarshaling in an automated container terminal. cceas efficiently search for a solution in a reduced search space by decomposing a problem into subproblems. our ccea decomposes the problem into two subproblems: one for determining where to move the containers and the other for determining the movement priority. simulation experiments show that our ccea can derive a better plan in terms of the efficiency of both loading and remarshaling than other methods which are not based on the notion of problem decomposition.
a novel approach to detect copy number variation using segmentation and genetic algorithm. among many forms of genomic variations, copy-number variations (cnvs) can be defined as gains or losses of several kilobases to hundreds of kilobases of genomic dna. since many cnvs include genes that result in differential levels of gene expression, cnvs may account for a significant proportion of normal phenotypic variation. some scientists demonstrated that a large portion of overlapping, currently known common human cnvs, were smaller in his dataset. however, previous experimental studies, performed primarily by a-cgh techniques, are limited to detection of cnvs of large-sized cnvs. efficient algorithms for finding small-sized cnvs are essential. in our paper, we propose a novel approach to find small-sized cnvs on a-cgh data which is a sequential 2-dimensional clustering method. the algorithm we propose is robust to some level of noise. and regardless of the size of probes, our algorithm can find cnvs consisting of small number of probes.
fuzzy data modeling based on xml schema. interest in xml has been growing over the last few years and xml has been the de-facto standard of information representation and exchange over the web. however, the real world is filled with imprecision and uncertainty. classical databases have been extended to deal with imprecise and uncertain data. in this paper, we investigate how to incorporate fuzzy data into xml. we identify multiple granularity of data fuzziness in xml. based on possibility distribution theory, we have possibilities associated with elements as well as attribute values of elements in xml. a fuzzy xml data model that addresses all of the fuzziness is developed based on xml schema.
extending passi to model multi-agent systems product lines. multi-agent system product lines (mas-pls) have emerged to integrate software product lines (spls) and agent-oriented software engineering techniques by incorporating their respective benefits and helping the industrial exploitation of agent technology. in this paper, we present a new approach for modeling mas-pls, focusing the domain analysis stage. our approach is based on passi methodology and incorporates some extensions to address agency variability.
implicit relevance feedback for context-aware information retrieval in ubilearning environments. ubiquitous learning (ubilearning) environments heavily employ mobile devices to empower users with mobility and tooling support to learn anytime, anywhere. introducing mobile devices in educational settings imposes constraints on search behavior due to limited resources on these devices such as small screens and restricted input functionalities. targeting this scenario, this paper proposes an architecture for implicit relevance feedback which considers users' work context to expand search queries in order to satisfy information needs with greater precision. evaluation results conducted over a local test collection enriched with contextual features reveal improvements on average precision when compared to a pseudo relevance feedback baseline.
an improved shrinkage estimator to infer regulatory networks with gaussian graphical models. gaussian graphical models (ggms) are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. these models have gained much attention as they encode full conditional relationships between variables, i.e. genes. as a consequence, structure learning of a ggm requires an invertible and well-conditioned covariance matrix. unfortunately, the usual estimator---the sample covariance matrix---is ill-suited in the "small n, large p" setting characteristic of microarray data. as an alternative, [9] proposed a shrinkage estimator that is both statistically efficient and computationally fast. the effectiveness of this estimator in bioinformatics has been illustrated by [12] who successfully used it to infer genetic regulatory networks from microarray data. unfortunately, this improved estimator requires the shrinkage intensity to be estimated from the data, which is problematic in the "small n, large p" setting. indeed, we show that the optimal shrinkage intensity estimator used in [9, 12] is biased. we propose a parametric bootstrap approach to estimate this bias and derive a "bias-corrected" shrinkage estimator. the applicability and usefulness of our estimator are demonstrated on both simulated and real expression data.
cross-layer cooperation between membership estimation and routing. mobile ad hoc networks are characterised by the absence of a centralised infrastructure and node heterogeneity. due to size and mobility requirements of the nodes that make up such a network the protocols employed often must deal with limited bandwith and avoid high power consumption. in classical layered protocol stacks, services are run in isolation. we argue, that in order to save band-with, reduce power and improve performance, various services that are running on a node may co-operate. we have identified two services in particular that can benefit greatly from such a co-operation: the routing protocol, which is responsible for discovering routes between nodes in the system and the membership estimation service, which is responsible for providing an estimation of the current composition of the system. the two services are the fundamental building blocks for distributed algorithms and applications at a higher level. in this paper we show how these two basic protocols can cooperate. the membership estimation service can provide useful information to the routing protocol, whereas routing may aid to maintain the membership estimation updated. we describe an implementation of a cross layer architecture, in which the dynamic source routing protocol (dsr) and our gossip-based membership estimation service share information. we show results of performacne experiments reflecting how this cooperation improves the performance of both services. finally, we identify scenarios in which the interaction is of most benefit.
precise generalized contact point and normal determination for rigid body simulation. modeling contact for rigid body simulation requires accurate determination of time of contact, contact points, and contact normals. existing collision detection methods for rigid body simulation can be grouped into one of three categories: convexity-based discrete methods, a posteriori discrete methods, and continuous methods. our proposed method combines the advantages of all three types: operating on arbitrary geometric representations, running in asymptotic linear time in the number of polyhedral features, having a parameterizable precision (a variation is guaranteed to miss no collisions), and avoiding simplex/simplex tests that are difficult to implement robustly. the algorithm is demonstrated on a pathological example involving both polyhedra and polygon soups.