Fault injection was initially developed in the context of hardware faults. Traditional fault injection techniques can emulate transient and permanent hardware faults using simple bit-flip or stuck-at models. The need for SFI arose with the emergence of software faults as a major cause of system failures, leading to the development of several SFI approaches. The […]
CLASSIFICATION OF ANALYSIS- CLUSTERING PATTERN DISCRIMINATIVE ALGORITHMS
A natural environment, the high dimensional measurement signals, lying in the F-dimensional measurement space, usually represent patterns residing in a much lower, D- dimensional subspace embedded in the ambient measurement space. Subclass discriminant analysis (MSDA) and restricted Gaussian model is first presented, and then two further discriminant analysis (DA) methods, fractional step MSDA (FSMSDA) and […]
API Change-Rule at a Method-Header Level using a wild card pattern-matching operator
The developers often inspect program differences between two versions. A team lead reviews modifications done by her team members to check whether the intended change is implemented correctly. Questions developers ask about code changes are often of the following style. To enable developers to reason about program differences at a high level and to help […]
FoCUS Modules of Index And Thread URL Detection
Internet forums are important platforms where users can request and exchange information with thers. The TripAdvisor Travel Board is a place where people can ask and share travel tips. Due to the richness of information in forums, researchers are increasingly interested in mining knowledge from them. To harvest knowledge from forums, their contents have to […]
Cluster consensus in discrete-time networks of multi-agents with inter-cluster nonidentical inputs
The multi-agent systems have broad applications. The consensus problems of multi-agent systems have attracted increasing interests from many fields, such as physics, control engineering, and biology. In network of agents, consensus means that all agents will converge to some common state. A consensus algorithm is an interaction rule how agents update their states. The consensus […]
A Quantitative Approach to Input Generation in Real-Time Testing of Stochastic Systems
The testing process, an implementation is exercised under controlled conditions with the intent of observing deviations with respect to the expected behavior. The development of reactive and real-time systems, this often relies on the execution of test-suites derived from abstractions that focus on finite-state and timed behavior, with the aim of revealing defects related to […]
Predicate in Euclidean space and road networks
A large amount of data is an important operation in a wide range of domains. Felipe et al. has recently extended its study to spatial databases, where keyword search becomes a fundamental building block for an increasing number of real-world applications, and proposed the IR2-Tree. A main limitation of the IR2-Tree is that it only […]
Safe and preserve personalization in module-based data management
In many application domains (e.g., medicine or biology), comprehensive schemas resulting from collaborative initiatives are made available. For instance, SNOMED is an ontological schema containing more than 400.000 concept names covering various areas such as anatomy, diseases, medication, and even geographic locations. Such well-established schemas are often associated with reliable data that have been carefully […]
Prevent re-identification attacks by adversaries with immediate neighborhood structural knowledge
The publication of social network data entails a privacy threat for their users. Sensitive information about users of the social networks should be protected. The challenge is to devise methods to publish social network data in a form that affords utility without compromising privacy. Previous research has proposed various privacy models with the corresponding protection […]
Social science and energy efficiency instantiation human behavior modeling
One seeks to develop predictive models to map between a set of predictor variables and an outcome. Statistical tools such as multiple regression or neural networks provide mature methods for computing model parameters when the set of predictive covariates and the model structure are pre-specified. Recent research is providing new tools for inferring the structural […]
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