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With the advent of the era of pervasive computing, human dependence on sensors is growing. Such sensor-aware contexts usually possess the characteristics of large-magnitude and uncertainty, so networked devices or systems driven by these contexts cannot get distinct and precise related context information yet, and then lead unable to provide users with satisfied desirable services. In order to solve...
This work is on the balanced truncation of distributed nonstationary linear parameter-varying (NSLPV) systems. These systems are composed of heterogeneous, discrete-time, NSLPV subsystems, formulated in a linear fractional transformation (LFT) framework, interconnected over arbitrary directed graphs, and subjected to a communication latency of one time-step. The proposed method is applied for the...
Logged data is one of the most widespread form of recorded information, since it can be acquired by almost any system and stored at a little cost. Customarily, the interaction logs between the system and a user (or environment) present the structure of a sequential decision process: given a context, the system performs an action and the user provides a feedback about it. This structure is common to...
In this paper, we motivate the usage of natural language processing techniques to detect the uncertainty cues in the software architecture documents. As an initial step of our study, we analyzed three real-world software architecture documents and manually retrieved examples of different types of uncertainties. Based on those examples, we formulated the hypothesis on how the communication of software...
Optimizing the selection of learning resources and practice questions to address each individual student's needs has the potential to improve students' learning efficiency. In this paper, we study the problem of selecting a personalized learning action for each student (e.g. watching a lecture video, working on a practice question, etc.), based on their prior performance, in order to maximize their...
A Dynamic Software Product Line (DSPL) aims at managing run-time adaptations of a software system. It is built on the assumption that context changes that require these adaptations at run-time can be anticipated at design-time. Therefore, the set of adaptation rules and the space of configurations in a DSPL are predefined and fixed at design-time. Yet, for large-scale and highly distributed systems,...
The production planning and control process is performed within complex and dynamic organizations made up of customer expectations, equipment, materials, people, information, and technologies. Changes in both internal and external factors can create a variety of unforeseen events, which make initial plans unfeasible or obsolete during production execution. How to effectively handle the unscheduled...
The number of sensors deployed at each and every place is growing at a faster rate to meet the current needs of modern society. The uninterrupted huge amount of data generated from sensors and other devices in Internet of Things (IoT) is to be captured and inferred into meaningful information. Context-aware computing is one of the key research issues in IoT paradigm and it is evident that it is successful...
In this paper, we study a unit commitment (UC) problem minimizing operating costs of the power system with renewable energy sources. We develop a contextual learning algorithm for UC (CLUC) which learns which UC schedule to choose based on the context information such as past load demand and weather condition. CLUC does not require any prior knowledge on the uncertainties such as the load demand and...
Active learning is an important machine learning problem in reducing the human labeling effort. Current active learning strategies are designed from human knowledge, and are applied on each dataset in an immutable manner. In other words, experience about the usefulness of strategies cannot be updated and transferred to improve active learning on other datasets. This paper initiates a pioneering study...
The global incidence of dengue has grown dramatically in recent decades and about half of the world's population is now at risk. The proper deployment of mobile health teams is one of the tools available to control the mosquitoes population responsible of the illness transmission. The team deployment problem can be casted as a maximal coverage location problem with uncertainty due to the nature of...
This paper considers the problem of solving Quadratic Programs (QPs) in the context of robust Model Predictive Control (MPC) based on scenario trees. A Newton strategy is used in conjunction with dual decomposition, yielding a parallelizable method with a fast practical convergence. In this context, it has been observed that the Hessian of the dual function has an intricate sparsity structure and...
Selecting the most adapted alternative for a new project is a challenging problem because it contains a lot of uncertainty due to lack of information. Moreover, better decision making processes still need to be proposed to help decision makers to select the most effective solution among several alternatives. Although different methods and tools have been developed for this purpose, there is still...
Over the last decades, there has been a growing interest to Service Oriented Computing (SOC) especially in a mobile environement. Web Services are the most common form of services for implementing SOC. Service Composition is to create a new business process by composing several services in order to fulfill business goals that individual services cannot achieve. The massive use of web services in the...
Queries posed by a user over a database do not always return the desired responses. It may sometimes result an empty set of answers especially when data are pervaded with uncertainty and imprecision. Thus, to address this problem, we propose an approach for relaxing a failing query in the context of evidential databases. The uncertainty in such databases is expressed within the belief function theory...
Multiagent patrolling in adversarial domains has been widely studied in recent years. However, little attention has been paid to cooperation issues between patrolling agents. Moreover, most existing works focus on one-shot attacks and assume full rationality of the adversaries. Nonetheless, when patrolling frontiers, detecting illegal fishing or poaching, security forces face several adversaries with...
In this paper, we study a pattern-context-aware scheme for stereo pattern analysis.Depth and texture are chosen as two primary factors for the pattern-context- aware computing.We organize these patterns as a context to analyze.A knowledge-based inference system is built with human experience to model the correlation of the context and processing. The process for the pattern analysis could recognize...
To enable safe motion planning in a dynamic environment, it is vital to anticipate and predict object movements. In practice, however, an accurate object identification among multiple moving objects is extremely challenging, making it infeasible to accurately track and predict individual objects. Furthermore, even for a single object, its appearance can vary significantly due to external effects,...
In the context of swift development of P2P e-commerce, it is critical to defending both customers and sellers from being victimized by probable deception stemming from uncertainties, vagueness and ambiguities that characterize the interactions amongst unfamiliar dealers. Accordingly, credit standing concerning each business partaker plays a decisive part in preventing fraud in P2P transactions and...
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