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Multifractal analysis is a powerful tool used in signal processing. Multifractal models are essentially characterized by two parameters, the multifractality parameter c2 and the integral scale A (the time scale beyond which multifractal properties vanish). Yet, most applications concentrate on estimating c2 while the estimation of A is in general overlooked, despite the fact that A potentially conveys...
Human tracking across multiple cameras is highly demanded for large scale video surveillance. To successfully track human across multiple uncalibrated cameras that have no overlapping field of views, a system to train more reliable camera link models is proposed in this paper. We employ a novel approach of combining multiple camera links and building bidirectional transition time distribution in the...
Clock jitter is a crucial factor in high speed and high performance application. Traditional jitter measurement method relies on precise and expensive instrumentations. This paper proposes a low cost jitter measurement and separation method. Instead of using traditional time internal analysis equipment, a simple Analog-to-Digital Converter (ADC) is used as the jitter measurement device. The clock...
In this growing world, technologies and methodologies are very vast and are growing at faster pace. Industries and customers prefer to work on high quality product in a very short time and with more efficiency. Customers prefer project that are not prone to faults and work effectively. In order to develop any project, several phases are involved in their development, but approximately half of the...
PMUs are the edifice of wide area monitoring and measurement system. The operation of PMU is essential to monitor and control the dynamic nature of the grid where voltage and current have constantly changing fundamental frequency due to change in load, generation imbalance, transients due to faults etc. Hence grid frequency is continuously varying about its nominal frequency therefore modeling of...
Smooth varying data is hard to classify/divide to separate classes since there is small separation. Large number of close and adjacent poses create smooth varying manifolds. Manual class formation by selecting different data points from entire database into different training classes will affect the error rate in smooth varying data classification. This paper proposes classification of smooth varying...
The emerging three-dimensional integrated circuit (3D IC) provides a promising solution for sustainable computer performance scaling. However, the high cost due to the complex pre-bond/intermediate testing and the low compound yield hinder the commercial adoption of 3D ICs. The defect clustering is found biasing the yield prediction, resulting in an unrealistic cost estimation at the early design...
The item response theory (IRT) provides us not only the abilities of examinees but also the difficulties of items. Adaptive testing using the IRT selects the most appropriate items to examinees automatically, resulting in more accurate ability estimation and more efficient test procedures than the conventional testing. However, the item parameters remain constants even if the features of the examinees...
Anomaly detection starts from a model of normalbehavior and classifies departures from this model as anomalies. This paper introduces a statistical non-parametric approach for anomaly detection that is based on a multivariate extension of the Poisson point process model for univariateextremes. The method is demonstrated on both a synthetic and a real-world data set, the latter being an unbalanced...
Taxicab demand discovering is one of the most fundamental issues of taxicab services. Most of the regions in one city suffer the demand and supply disequilibrium problem. It causes the difficulty in scheduling taxicabs for taxicab companies. It will be solved by modeling the regional demand of taxicabs by using trajectory data. In this paper, we propose a method to model regional taxicab demand. Firstly,...
In this paper we investigate whether human digital fingerprints can be used to estimate human age-groups. To our knowledge, human age-group estimation using digital fingerprints have not been addressed formally. Human age-group estimation can be applied in the areas of online child protection, age based access control or customized services based on estimated age-groups. Motivated by the fact that...
BACKGROUND: Several studies in software effort estimation have found that it can be effective to use a window of recent projects as training data for building an effort estimation model. The previous studies evaluated the use of a window with popular estimation models: linear regression (LR) and estimation by analogy (EbA). Many effort estimation models have been proposed, and the generality of windowing...
Post-fabrication performance compensation and adaptive delay testing are indispensable means for improving yield and reliability of LSIs, The global parameter estimations, such as of threshold voltages, play a key role in maximizing their effectiveness. This paper proposes a novel technique that realizes an accurate device-parameter estimation through Fmax testing framework. In the proposed method,...
An estimation method of a threshold value for electrical interconnect tests is proposed for detecting open defects at interconnects between dies in a 3D IC. Threshold values of a circuit made of our prototyping IC on a printed circuit board are derived by the estimation method. The results show us that resistive open defects whose resistance is larger than 16.1Ω can be detected with a threshold value...
In decentralized detection, the sensors first make a local decision before transmitting it to the fusion center (FC). The optimal design of the sensors' decision rule as well as the fusion rule requires knowledge of the probability distributions of the sensors' observations. This information, however, may not be available prior to deployment. Moreover, these probability distributions may vary over...
Real-time visual identification and tracking of objects is a computationally intensive task, particularly in cluttered environments which contain many visual distracters. In this paper we describe a real-time bio-inspired system for object tracking and identification which combines an event-based vision sensor with a convolutional neural network running on FPGA for recognition. The event-based vision...
This paper proposes a novel approach for automatic estimation of four important traits of speakers, namely age, height, weight and smoking habit, from speech signals. In this method, each utterance is modeled using the i-vector framework which is based on the factor analysis on Gaussian Mixture Model (GMM) mean supervectors, and the Non-negative Factor Analysis (NFA) framework which is based on a...
The real-time audience measurement system consists of five consecutive stages: face detection, face tracking, gender recognition, age classification and in-cloud data statistics analysis. The challenging part of such system is age estimation algorithm on the basis of machine learning methods. The face aging process is determined by different factors: genetic, lifestyle, expression and environment...
We propose a hierarchical regression approach, Dirichlet-tree cascaded Hough forests (DCHF), which is based on deep learning for continuous head pose estimation in unconstrained environment, e.g., poses, illumination, occlusion, low image resolution, expressions and make-up. First, positive facial patches are learned and extracted from facial area to eliminate the influence of noise. Then, in order...
In 1998 NESMA published an alternative approach to establish the functional size of software enhancement projects. The aim of the approach was to be able to use productivity data from software development to estimate software enhancement. This approach has been highly debated, since it is not a pure functional size measurement method in the ISO/IEC 14143 definition. The approach is in use all over...
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