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One of the challenges in IT Service Management is an assessment of an innovation benefit introduced into service delivery on performance of IT System Administrator (SA). The question is especially complex when variability of the service requests load is taken into account. We used the sequential probability ratio test to assess effects of innovation for a case when a load of the service teams is constant...
Known as “the art of strokes”, Chinese calligraphy expresses its aesthetic through the strokes. A calligraphy learner practise the strokes and compose a calligraphic character by the strokes thereafter. Following the same process, the calligraphy robot, Callibot [2] needs to extract the strokes from a character. Therefore, we propose an approach to extract strokes using the geometric properties on...
Dyspepsia is a condition of indigestion and became one of the diseases with a large number of patients in Indonesia. Early detection of Dyspepsia is done to assist in the prevention of the disease. Iridology is a method of early detection in human organs disorders by analyzing the iris patterns. However, the application of Iridology technique often finds difficulties because it requires a high level...
This paper deals with coherent multi-polarization SAR change detection assuming the availability of reference and test images collected from N multiple polarimetric channels. At the design stage, the change detection problem is formulated as a binary hypothesis testing problem and the principle of invariance is used to come up with decision rules sharing the Constant False Alarm Rate (CFAR) property...
This research deals with quantifying the benefits of using the novel Sum Normalized Range Profile (SNRP) over prior art for 1-d feature extraction based classification of maritime vessels. For a fair comparison, classification and feature extraction techniques are maintained the same, for each range profile input. While utilizing SNRP inputs, the automated target recognition engine results indicate...
Handwritten document analysis is a persistent research area nowadays. It has large applications in various image processing domain as human computer interaction, machine translation and automation of reading various scanned images for handwritten fields in forms, postal address on envelopes and amounts in banks checks. The main factor which influence the performance of handwritten text recognition...
Orthogonal experimental design (OED) is a well-known method in statistical experiment which aims to reduce the testing complexity. This paper tries applying OED to reduce the computational complexity in Multiple-input Multiple-output (MIMO) detection. Several times of sorted QR decomposition (SQRD) algorithm are applied firstly to get the diverse solutions. Then a subspace is constructed with the...
One of the most apparent trends in test research and application in recent years has been the increasing application of statistical methods and machine learning. The trend has been driven by factors such as increases in data volume, need to detect subtle defects and need to extend beyond test's traditional sort function to a feedback-providing, yield-learning role. These factors, in turn, reflect...
Several dictionary-based input test data compression methods have been proposed for intellectual property (IP) cores testing. To increase the utilization of the dictionary entries some methods are based on the correction of some bits before the loading of the entries into the scan chains. The coordinates of the bits that should be corrected are sent by the automatic test equipment (ATE), hence, the...
A novel cortical surface registration method is proposed to spatially align inter-subject cortical surfaces by maximizing the similarity of their hierarchical patterns of local functional connectivity extracted from fMRI data. The cortical surface with fMRI data is characterized by functional connectivity information for each vertex of the surface to its spatial neighbors on the cortex sheet at multiple...
In the product development life-cycle of hard-real-time embedded systems, software verification plays a very important role. During verification, a Hardware-In-Loop (HIL) testbed is used to test the key properties of the software, namely, schedulability, concurrency and timeliness, by exercising and monitoring the interfaces of the Design Under Test (DUT). Often, building a testbed to test these properties...
In this paper, we propose an efficient method for generating validation vectors for identifying delay marginalities under increasing levels of process-variations-across die, across wafers, across wafer lots. With the goal of significantly reducing the number of vectors required for validation, we propose an approach for segmenting the full global plus local process variation envelope into sub-envelopes,...
We explore the application of Kernel Support Vector Machines (SVM) to the realm of text messages. Our intent is to classify the author of a text message based on usage patterns present in a training set of text messages. We achieve between 57% and 96% accuracy in determining the author of unknown samples.
Detector adaptation is a challenging problem and several methods have been proposed in recent years. We propose multi class boosted random ferns for detector adaptation. First we collect online samples in an unsupervised manner and collected positive online samples are divided into different categories for different poses of the object. Then we train a multi-class boosted random fern adaptive classifier...
One of the major threats against web applications is Cross-Site Scripting (XSS). The final target of XSS attacks is the client running a particular web browser. During this last decade, several competing web browsers (IE, Netscape, Chrome, Firefox) have evolved to support new features. In this paper, we explore whether the evolution of web browsers is done using systematic security regression testing...
This logo detection system uses a large number of classifiers to capture the variety of appearances exhibited by the logos of this world under a range of viewing conditions (i.e. different view points and presence of occlusion). Each classifier is trained to detect instances of a specific part of a specific logo. Given an image, each detected part instance is used to generate a hypothesis on the extent...
This paper presents a novel method for pattern recognition problem in terms of linear regression. Normally, patterns from a single-object class lie on a linear subspace. Using this concept, we develop a linear model representing a probe image as a linear combination of class-specific galleries. Linear Regression Classification (LRC) algorithm for pattern recognition belongs to the category of nearest...
Clinical depression can be considered as a soft biometric trait that can help to characterize an individual. This mood disorder can be involved in forensic psychological assessment, due to its relevance in different legal issues. The automatic detection of depressed speech has been object of research in the last years, resulting in different algorithmic approaches and acoustic features. Due to the...
This paper provides interesting findings for modeling of a challenging and critical pedagogical issue namely online learning assessment of Multiple Choice Questions (MCQs) analysis and evaluation. More precisely, in fulfillment of that issue's objective, this work suggests using a realistic Artificial Neural Network (ANN) model. That, explicitly, characterized by two learning paradigms: supervised...
In the era of deep sub-micron technology, probability of chip failure has been increased with increase in chip density. A system must be fault tolerant to decrease the failure rate and increase the reliability of it. Multiple faults can affect a system simultaneously and there is a trade-off between area overhead and number of faults tolerated. This paper presents fault tolerant architecture design...
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