waashk/dblp huggingface dataset:
defending online reputation systems against collaborative unfair raters through signal modeling and trust. online feedback-based rating systems are gaining popularity. dealing with collaborative unfair ratings in such systems has been recognized as an important but difficult problem. this problem is challenging especially when the number of honest ratings is relatively small and unfair ratings can contribute to a significant portion of the overall ratings. in addition, the lack of unfair rating data from real human users is another obstacle toward realistic evaluation of defense mechanisms. in this paper, we propose a set of methods that jointly detect smart and collaborative unfair ratings based on signal modeling. based on the detection, a framework of trust-assisted rating aggregation system is developed. furthermore, we design and launch a rating challenge to collect unfair rating data from real human users. the proposed system is evaluated through simulations as well as experiments using real attack data. compared with existing schemes, the proposed system can significantly reduce the impact from collaborative unfair ratings.
workflow management for high volume supernova search. observational astrophysics has recently become a data-intensive science after many decades of relative data poverty. as a result, many of the algorithms developed for processing astronomical data, although well established for low-volume data capture, do not scale well to today's high-volume sky surveys and transient searches. specifically, problems may occur with data transfer, workflow management, efficient parallelization, and integration of legacy code. observational astrophysics workflows present computational challenges unique in high performance computing, including 24/7 operations, time-critical processing, and very large numbers of relatively small data files which must all be processed and archived. we present a case study based on sunfall, a distributed, parallel scientific workflow system we built for the nearby supernova factory, the largest data-volume supernova search currently in existence. we describe innovative techniques for data transfer and workflow management, and discuss lessons learned in building a large-scale observational astrophysics workflow management system.
an algorithm for optimal comma free codes with isomorphism rejection. a general algorithm for finding optimal comma-free codes and deriving upper bounds on the minimum redundancy of comma-free codes that implements the idea of isomorphism rejection is presented, together with tables with bounds on the minimum redundancy computed by using this algorithm.
a systematic method for generating quality requirements spectrum. spectrum analysis for quality requirements is useful for measuring and tracking them, but current spectrum analysis largely depends on expertise of each analyst. therefore, it takes a lot of efforts to perform the analysis and is hard to reuse experiences for such analysis. we introduce domain knowledge called term-characteristic map to improve current spectrum analysis for quality requirements. through several experiments, we evaluated the improved method for spectrum analysis.
parameterless outlier detection in data streams. outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). clustering-based outlier detection is a field that aims to cluster data and to detect outliers depending on their characteristics (small, tight and/or dense clusters might be considered as outliers). existing methods require a parameter standing for the "level of outlyingness", such as the maximum size or a percentage of small clusters, in order to build the set of outliers. unfortunately, manually setting this parameter in a streaming environment should not be possible, given the fast time response usually needed. in this paper we propose wod, a method that separates outliers from clusters thanks to a natural and effective principle. the main advantages of wod are its ability to automatically adjust to any clustering result and to be parameterless.
leveraging owl for gis interoperability: rewards and pitfalls. information systems often require combining datasets available in different formats, and geographical information systems are no exception. while semantic technologies have been used before to enable interoperability between relational databases, little research has yet been done for the special case of geographical information systems, despite their applications in active areas of research such as location-based services. in this paper we present an owl-based system for seamless conversion between geographical file formats. while implementing this system we reached the complexity limits of current description logics reasoners and had to design custom algorithms to compute the logical inferences we needed. this process suggested interesting approaches to enable scalable reasoning on the semantic web.
high-level specification of a middleware framework for mobile ad hoc networks: spontaneousware case. the number of distributed applications developed atop mobile wireless ad hoc networks (manet) is rapidly increasing. at the same time, middleware systems that provide services and communication facilities to these applications have become popular. like other distributed environments, the development of middleware systems is not a trivial task. however, this complexity increases when the middleware must execute in a manet due to a dynamic number of members, intermittent connectivity, bandwidth variation, device heterogeneity and so on. in this context, we propose a middleware framework, named spontaneousware, specially designed for aiding developers in the middleware systems development for manet. in order to define a high-level specification for this framework, the requirements and architecture were documented.
practical distributed voter-verifiable secret ballot system. in this paper we propose an end-to-end voter-verifiable system, which is more transparent than existing solutions. its distributed nature permits its use both for supervised voting at a polling place and for online remote voting. we use chaum's blind signatures to ensure voter anonymity. in particular, voters can verify that their votes are recorded exactly as cast, and all ballots can be made public so that anyone can verify the election results. we further address key security issues such as server corruption in the proposed system. the case is made that this can be the basis of a practical voting system.
an empirical study of incorporating cost into test suite reduction and prioritization. software developers use testing to gain and maintain confidence in the correctness of a software system. automated reduction and prioritization techniques attempt to decrease the time required to detect faults during test suite execution. this paper uses the harrold gupta soffa, delayed greedy, traditional greedy, and 2-optimal greedy algorithms for both test suite reduction and prioritization. even though reducing and reordering a test suite is primarily done to ensure that testing is cost-effective, these algorithms are normally configured to make greedy choices with coverage information alone. this paper extends these algorithms to greedily reduce and prioritize the tests by using both test cost (e.g., execution time) and the ratio of code coverage to test cost. an empirical study with eight real world case study applications shows that the ratio greedy choice metric aids a test suite reduction method in identifying a smaller and faster test suite. the results also suggest that incorporating test cost during prioritization allows for an average increase of 17% and a maximum improvement of 141% for a time sensitive evaluation metric called coverage effectiveness.
a destination prediction method using driving contexts and trajectory for car navigation systems. car navigation systems provide the best route to a destination quickly and effectively. however, during daily driving, this information is not necessary since drivers already know the route to the destination very well. in addition, it is time-consuming for drivers to input the destination. thus, our research group has proposed a new car navigation system that provides information related to the destination by predicting the user's destination automatically. we propose the use of a new method that predicts the destination on the basis of the driving trajectory and the contexts in which the user drives. a system that uses our method knows the destination without user interaction and provides information related to the correct destination.
using process mining to business process distribution. service oriented architecture (soa) is by far the most pervasive architecture which includes several building blocks among which orchestration engine is under special focus. although, there are a number of centralized orchestration engines to execute business processes described by bpel language in soa, you may find several decentralized orchestration engines and their purpose is decomposing a bpel process to several software agents to improve quality factors such as adaptability, performance and so forth. as these process distribution methods break a bpel process to its building activities and encapsulate each activity in one agent, it results in producing a lot of agents whose interactions and resource usage would degrade the run-time environment. this paper proposes an intelligent process distribution (ipd) based on a process mining approach in which the selection of activities that should be encapsulated in agents, depends on the previous behavior of process instances. the recommended ipd approach will improve three aspects of system quality. first; is the amelioration of business process adaptability with run-time environment, second; choosing the best agent granularity based on detecting most relevant activities and encapsulating them in agents and third; is decreasing of resource usage due to reduced and improved number of produced agents and messages. furthermore, we proved our method using a mathematical approach.
formalizing the notion of adaptive system behavior. in computer science the notion of adaptive systems has been used in different contexts for many years now. although there is some intuitive, common understanding of the notion, a precise and universally practicable definition is still missing. more precisely, previous definitions fail to strictly differentiate between adaptive and non-adaptive systems. we investigate the intuitions and propose a precise definition that comprises most informal explanations. methodical implications arising from our definition are discussed as well.
impact of function inlining on resource-constrained embedded systems. with the development of computer systems, function inlining schemes were used to reduce execution time while increasing codes. in embedded systems such as wireless sensor nodes, there are extreme limitations on memory space and battery power. this is the reason why function inlining is useful for maximizing memory utilization while minimizing energy consumption of embedded systems. in the previous works, basic inlining schemes were proposed, which were adapted to systems with code memory constraints. however, they were too coarse-grained, and did not evaluate the impact of function inlining in terms of both energy consumption and code memory utilization in actual systems. in this paper, we propose a fine-grained function inlining scheme. we also present the impact of function inlining schemes on resource-constrained embedded systems, in terms of energy consumption and code memory overhead. based on experimental results, we demonstrate that fine-grained function inlining can improve the energy efficiency of embedded systems while maximizing code memory utilization.
a holistic mechanism against file pollution in peer-to-peer networks. content pollution is pervasive in the current peer-to-peer file sharing systems. many previous reputation models have been proposed to address this problem, however, such models strongly rely on the participants' feedback. in this paper, we bring forward a new holistic mechanism which integrates the reputation model, inherent file-source-based information and the statistical data reflecting the diffusion state to defend against pollution attack. first, we deploy a redundancy mechanism to assure that the file requester receives the correct indices that accord with the information published by the file provider. second, we complement the reputation information with the diffusion data to help the file requester select the authentic file for downloading. finally, we introduce a block-oriented probabilistic verification protocol to help the file requester discern the polluted files during the downloading with a low cost. we perform a simulation which shows that our holistic mechanism can perform very well and converge to a high accuracy rapidly, even in a highly malicious environment.
a passive conformance testing approach for a manet routing protocol. in this paper we propose a passive conformance testing technique applied to a mobile ad hoc network (manet) routing protocol, olsr, that is characterized by a dynamically changing topology and lack of centralized management. this makes it necessary to investigate new ways to test complex scenarios and configurations. the work here proposes a formal passive testing method to test the conformance and reliability of the protocol. the method developed has been performed on a real case study showing that the approach can be successful applied and that it allows reducing inconclusive verdicts often observed using other methods.
a real-time message scheduler support for dual-sink mobile ad-hoc sensor networks. this paper designs and measures the performance of a message scheduling scheme for the mobile sensor network employing two sinks. for the purpose of enhancing the successful delivery ratio for time-sensitive sensor messages and also avoiding congestion around the sinks, the proposed scheme keeps their loads different, and makes each sensor node send the urgent message to the low-load sink. for a neutral node, the urgency of a message is estimated by comparing the slack value of the message and slack distribution of overall messages observed at the node. with this information, each node decides the destination of each message. the simulation performed via ns-2 reveals that the proposed scheme, called chop partition, can improve the deadline meet ratio of real-time messages by up to 7.2% for aodv case and 8.2% for dsdv case, compared with the random selection scheme, or even partition, for the given experiment parameters.
exploiting stack distance to estimate worst-case data cache performance. this paper proposes an approach to safely and tightly bounding data cache performance by computing the worst-case stack distance of data cache accesses. our approach can not only be applied to direct-mapped caches, but also be used for set-associative or even fully-associative caches without increasing the complexity of analysis. moreover, the proposed approach can statically categorize worst-case data cache misses into cold, conflict, and capacity misses, which can provide useful insights for designers to enhance the worst-case data cache performance. our evaluation shows that the proposed data cache timing analysis technique can safely and accurately estimate the worst-case data cache performance, and the overestimation as compared to the observed worst-case data cache misses is within 1% on average.
algebraic specification techniques for parametric types with logic-based constraints. mainstream object-oriented languages now offer capabilities of generic types with bounded type parameters, but they typically do not provide support for specifying semantic requirements on the type parameters' methods beyond conformance of signatures. regrettably, even object-oriented assertion languages, such as jml, have nontrivial limitations in this regard. yet many interesting parameterized types require additional semantic features if they are to function as intended. we illustrate the issues with a case study of project scheduling based on the project management institute's generic characterization of task breakdowns. we consider algebraic techniques for instantiating parametric types in such a way that the semantic requirements expressed by logic-based constraints propagate to the instantiating types. these techniques argue for more general bindings of actual type parameters for the formal ones which do not have the restrictions of current programming languages. we show that types equipped with constraints should be viewed as theories, and the bindings as morphisms of types as theories. we translate these software specifications into theories in the pvs specification language. these proposals lead to conclusions about language features for more general, semantic bindings of the actual for the formal type parameters, at least in the assertion languages.
incremental board: a grid-based space for visualizing dynamic data sets. in information visualization, adding and removing data elements can strongly impact the underlying visual space. we introduce a chess board analogy for displaying (projecting) objects from a dynamic set on a 2d space, considering their similarity in a higher dimensional space. our solution is inherently incremental and maintains a coherent disposition of elements, even for completely renewed sets. the algorithm considers relative positions, rather than raw dissimilarity. it has low computational cost, and its complexity depends only on the size of the currently viewed subset, v. thus, a set of size n can be sequentially displayed in o(n) time, reaching at most o(n2) only if viewing the whole set at once. consistent results were obtained as compared to (non-incremental) multidimensional scaling solutions. moreover, the corresponding visualization is not susceptible to occlusion. the technique was tested in different domains, being particularly adequate to display dynamic corpora.
a taxonomy and adversarial model for attacks against network log anonymization. in recent years, it has become important for researchers, security incident responders and educators to share network logs, and many log anonymization tools and techniques have been put forth to sanitize this sensitive data source in order to enable more collaboration. unfortunately, many new attacks have been created, in parallel, that try to exploit weaknesses in the anonymization process. in this paper, we present a taxonomy that relates similar kinds of attacks in a meaningful way. we also present a new adversarial model which we can map into the taxonomy by the types of attacks that can be perpetrated by a particular adversary. this has helped us to negotiate the trade-offs between data utility and trust, by giving us a way to specify the strength of an anonymization scheme as a measure of the types of adversaries it protects against.
a framework of a logic-based question-answering system for the medical domain (loqas-med). question-answering systems that provide precise answers to questions, by combining techniques for information retrieval, information extraction, and natural language processing, are seen as the next-generation search engines. due to the growth and real-world impact of biomedical information, the need for question-answering systems that can aid medical researchers and health care professionals in their information search is acutely felt. in order to provide users with accurate answers, such systems need to go beyond lexico-syntactic analysis to semantic analysis and processing of texts and knowledge resources. moreover, question-answering systems equipped with reasoning capabilities can derive more adequate answers by using inference. research on question answering in the medical and health care domain is still in its inception stage. while several recent approaches to medical question answering have explored use of semantic knowledge, few approaches have exploited the utility of logic formalisms and of inference mechanisms. in this paper, we present a framework for a logic-based question-answering system for the medical domain, which uses description logic as the formalism for knowledge representation and reasoning. as a first step toward building the proposed system, we present semantic analysis and classification of medical questions.
towards a maturity model for corporate data quality management. high-quality corporate data is a prerequisite for world-wide business process harmonization, global spend analysis, integrated service management, and compliance with regulatory and legal requirements. corporate data quality management (cdqm) describes the quality oriented organization and control of a company's key data assets such as material, customer, and vendor data. with regard to the aforementioned business drivers, companies demand an instrument to assess the progress and performance of their cdqm initiative. this paper proposes a reference model for cdqm maturity assessment. the model is intended to be used for supporting the build process of cdqm. a case study shows how the model has been successfully implemented in a real-world scenario.
genqa: automated addition of architectural quality attribute support for java software? non-functional requirements for software systems are typically specified using informal notations such as quality attribute scenarios. further, implementation strategies for such non-functional attributes are frequently common across systems with quite different functional requirements. in such cases, the time invested in implementing these quality attributes could be salvaged, thereby reducing the project lifetime and increasing software quality. in this paper, we present the design and prototype implementation of a tool and associated framework that enables software engineers to effectively capture non-functional requirements, and then automatically generate implementations of these requirements to be added to the application being built. the quality attribute implementations are generated as aspects (aspectj in the prototype) that can be weaved in with the application code (java) with minimal development effort.
formalizing motivational patterns based on colors and their cultural meanings for developing web applications. collaborative work via web tends to increase due to professionals' teams separated by distance and time, demanding more effort and stronger commitment from each person. it is noticed that many times the collaborative work via web is not effective, generating lack of motivation and no engagement, few effective collaboration and no commitment with the results. it should be considered the cultural differences among the team's members, what interfere on each individual's performance, misunderstanding the task (for instance, the adopted vocabulary) and not motivating to reach the goals (for instance, how the environment looks). this research aims at discussing the process of motivational pattern formalizing using common sense knowledge to associate the appropriate colors for the environment to the emotions that these colors can provoke people into engaging, culturally motivating people through significant and appropriate colors in the collaborative environment.