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Estimation of Distribution Algorithms have proved to be very competitive for solving combinatorial and continuous optimisation problems. However, there are problems for which they have not been extensively developed: we refer to constrained optimisation problems. Existing proposals approach these problems by (i) modifying the sampling strategy of the probabilistic model to allow feasible solutions...
Since Apple introduced the iBeacons in Worldwide Developers Conference (WWDC) 2013, the iBeacon has been rapidly accepted and generalized in the market. For the deployed iBeacons, it is necessary to monitor their status. In this paper, we design a crowd sensing based monitoring framework which combines the moving and static schemas of participants to monitor the real status of iBeacons. In such a...
In this work, we report a study carried out to identify a set of metrics to early estimate the development effort of mobile apps. The applied methodology was inspired by the work of Mendes et al. who addressed a similar problem in the field of web apps. In particular, we extracted an initial set of metrics by analyzing the online quotes forms that companies made available on their websites. Afterward,...
A major goal of computer vision is to enable computers to interpret visual situations — abstract concepts (e.g., “a person walking a dog,” “a crowd waiting for a bus,” “a picnic”) whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. In this paper, we propose a novel method for prior learning and active object localization for...
Intrinsic timing uncertainties present in modern hardware platforms have motivated the use of Extreme Value Theory (EVT) to timing analysis, however, the timing behaviour of a task may not entirely fulfil the necessary assumptions. To deal with this difficulty, randomisation at the hardware level has been proposed as a means of facilitating the use of statistical timing analysis. However, it has been...
Forensic Voice Comparison (FVC) is increasingly using the likelihood ratio (LR) in order to indicate whether the evidence supports the prosecution (same-speaker) or defender (different-speakers) hypotheses. Nevertheless, the LR accepts some practical limitations due both to its estimation process itself and to a lack of knowledge about the reliability of this (practical) estimation process. It is...
The field of signal processing is replete with exemplary problems where the measurements amount to time-delayed and amplitude scaled echoes of some template function or a pulse. When the inter-pulse spacing is favorable, something as primitive as a matched filter serves the purpose of identifying time-delays and amplitudes. When the inter-pulse spacing poses an algorithmic challenge, high-resolution...
As part of an ongoing research into extracting mission-critical information from Search and Rescue speech communications, a corpus of unscripted, goal-oriented, two-party spoken conversations has been designed and collected. The Sheffield Search and Rescue (SSAR) corpus comprises about 12 hours of data from 96 conversations by 24 native speakers of British English with a southern accent. Each conversation...
Supervised speech separation algorithms seldom utilize output patterns. This study proposes a novel recurrent deep stacking approach for time-frequency masking based speech separation, where the output context is explicitly employed to improve the accuracy of mask estimation. The key idea is to incorporate the estimated masks of several previous frames as additional inputs to better estimate the mask...
In this paper we present the INESC Key Detection (IKD) system which incorporates a novel method for dynamically biasing key mode estimation using the spatial displacement of beat-synchronous Tonal Interval Vectors (TIVs). We evaluate the performance of the IKD system at finding the global key on three annotated audio datasets and using three key-defining profiles. Results demonstrate the effectiveness...
This paper presents a method of estimating the geometry of a room and the 3D pose of objects from a single 360 panorama image. Assuming ManhattanWorld geometry, we formulate the task as an inference problem in which we estimate positions and orientations of walls and objects. The method combines surface normal estimation, 2D object detection and 3D object pose estimation. Quantitative results are...
We investigate the precision of attitude estimation algorithms in the particular context of pedestrian navigation with commodity smartphones and their inertial/magnetic sensors. We report on an extensive comparison and experimental analysis of existing algorithms. We focus on typical motions of smartphones when carried by pedestrians. We use a precise ground truth obtained from a motion capture system...
Effort estimation is more challenging in an agile context, as instead of exerting strict control over changes in requirements, dynamism is embraced. Current practice relies on expert judgment, where the accuracy of estimates is sensitive to the expertise of practitioners and prone to bias. In order to improve the effectiveness of the effort estimation process, the goal of this research is to investigate...
Small world characteristics (SWC) have been observed and studied in a wide range of disciplines such as social, biological, electrical and computer networks. However, the significance of SWC in wireless sensor network (WSN) applications has hitherto not been investigated. This work investigates the significance of introducing SWC in a conventional WSN for improving the accuracy of WSN node localization...
The regularization parameter is required in most (if not all) adaptive algorithms, while its role becomes very critical in the presence of additive noise. In this paper, we focus on the regularized recursive least-squares (RLS) algorithm and present a method to find its regularization parameter, which is related to the signal-to-noise ratio (SNR). Also, using a proper estimation of the SNR, we further...
The paper presents the opinions of students at the Electrical Engineering, University POLITEHNICA of Bucharest (UPB) regarding the teaching and assessment methods. The students' opinions depend on various socio-demographic variables discussed. The study is based on a quantitative analysis and it was conducted on 844 students studying Electrical Engineering, during May–July 2016.
Extended Finite State Machines (EFSMs) are widely used to model the behavior of a system. Testing from EFSMs is expressed in terms of generating transition paths and then deriving test data to trigger these paths. However, a transition path may be infeasible, thus it is impossible to generate test data to execute it. In this paper, after generating a set of transition paths that satisfy the requirement-based...
In video background modeling, ghosting occurs when an object that belongs to the background is assigned to the foreground. In the context of Principal Component Pursuit, this usually occurs when a moving object occludes a high contrast background object, a moving object suddenly stops, or a stationary object suddenly starts moving. Based on a previously developed incremental PCP method, we propose...
Users interact with mobile apps with certain intents such as finding a restaurant. Some intents and their corresponding activities are complex and may involve multiple apps; for example, a restaurant app, a messenger app and a calendar app may be needed to plan a dinner with friends. However, activities may be quite personal and third-party developers would not be building apps to specifically handle...
On social media platforms, companies, organizations and individuals are using the function of sharing or retweeting information to promote their products, policies, and ideas. While a growing body of research has focused on identifying the promoters from millions of users, the promoters themselves are seeking to know what strategies can improve promotional effectiveness, which is rarely studied in...
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