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The architecture of remote Education Resource Center for the students of engineering on the basis of data space is developed. The consolidated data catalog and the query processing schemes in data space are proposed.
The purpose of the paper is to develop methodological bases for assessing vocational aptitude of human-operators of man-machine systems. The model of vocational aptitude and the process of decision-making in the class of hierarchical systems were developed based on the hierarchy analysis method. The experimental research of vocational aptitude assessment for operators of transport-technological machines...
Cloud Computing is storing of data and application on remote servers and accessing them via internet rather than installing and saving them on your personal computers. Growing volume of scientific data sets which are publicly available has made it impractical to move data to desktop for analysis. To solve these issues we require a new computing paradigm. In recent years, cloud computing has grown...
With the goal of increasing the resolution of face images, recent face hallucination methods advance learning techniques which observe training low and high-resolution patches for recovering the output image of interest. Since most existing patch-based face hallucination approaches do not consider the location information of the patches to be hallucinated, the resulting performance might be limited...
When hiding messages in digital images, care needs to be exercised how the embedding changes are executed in or near saturated pixels. In this paper, we consider three different rules that are currently being used that adjust the embedding in saturated pixels and assess their impact on empirical steganographic security of four modern embedding algorithms. Surprisingly, the rules can have a major effect,...
The approximation of nonlinear kernels via linear feature maps has recently gained interest due to their applications in reducing the training and testing time of kernel-based learning algorithms. Current random projection methods avoid the curse of dimensionality by embedding the nonlinear feature space into a low dimensional Euclidean space to create nonlinear kernels. We introduce a Layered Random...
Image super-resolution has gained much attention in these years, while video super-resolution remains almost unchanged. In this paper, we propose a fast super-resolution method for video. We exploit recent development of learning-based technique that achieves state-of-the-art in accuracy and efficiency for image super-resolution. We leverage the temporal coherency of video contents to approximate...
In this paper, we propose a new texture descriptor, completed local derivative pattern (CLDP). In contrast to completed local binary pattern (CLBP), which involves only local differences at each scale, CLDP encodes the directional variation of the local differences of two scales as a complementary component to local patterns in CLBP. The new component in CLDP, with regarded as the directional derivative...
In this paper, we proposed an optimized Sparse Deep Learning Network (SDLN) model for Face Recognition (FR). A key contribution of this work is to learn feature coding of human face with a SDLN based on local structured Sparse Representation (SR). In traditional sparse FR methods, different poses and expressions of training samples could have great influence on the recognition results. We consider...
Plankton image classification plays an important role in the ocean ecosystems research. Recently, a large scale database for plankton classification with over 3 million images annotated with over 100 classes was released. However, the database suffers from imbalanced class distribution in which over 90% of images belong to only 5 classes. Due to this class-imbalance problem, the existing classification...
The recent popularity of smartphones causes significant increase of upskirt filming cases in many countries and regions. To search upskirt images in suspects' IT devices and block them on social media, an effective detector is demanded, but it is neglected by both academic and commercial communities. Three commercial pornographic image detectors and one detector distributed by the U.S. National Institute...
Websites typically include many forms or web elements that allow users to enter and submit data. This data will be eventually executed in the back-end databases. Users can, intentionally or unintentionally enter improper input data that, if reach those back-end databases, may cause some serious security or damaging problems. For proper user interface design as well as for security reasons, it is important...
Facial expression has made significant progress in recent years with many commercial systems are available for real-world applications. It gains strong interest to implement a facial expression system on a portable device such as tablet and smart phone device using the camera already integrated in the devices. It is very common to see face recognition phone unlocking app in new smart phones which...
Ventricular Tachycardia (VT) is a dangerous arrhythmic event which can lead to sudden cardiac death if not detected and taken care of in time. This work uses non-linear features derived from Recurrence Quantification Analysis (RQA) along with Kolmogorov complexity, by analyzing the ECG signals, to train a classifier which can predict VT prior to their onset in remote continuous health devices. Compressed...
In this work, we describe a novel method based on waveform morphology for detecting artifacts in photoplethysmography (PPG) signals and, thus, improve reliability of PPG. By considering inter-individual and measure condition variability, specific parameters are estimated for each record. We introduce a novel metric for comparing pulses, which is the derivative of the correlation coefficient. Then,...
Movement classification from electromyography (EMG) signals is a promising vector for improvement of human computer interaction and prosthetic control. Conventional work in this area typically makes use of expert knowledge to select a set of movements a priori and then design classifiers based around these movements. The disadvantage of this approach is that different individuals might have different...
Accurate classification and recognition of pulmonary nodules is an important and key process of Computer-Aided Diagnosis (CAD) system in lung cancer diagnose. Although it has become an increasingly popular research topic, it remains a lot of scientific and technical challenges. Not only do we lack the accurate and effective algorithm of recognition and classification, but also we have difficulties...
Image Structure Similarity (SSIM) and its extended versions have been successfully used in image quality assessment. In this paper, we propose a similarity metric to evaluate image quality by extracting image sparse structure from natural scene image. A sparse dictionary trained on the data contains the basic elements for representing sparse structures, and it is insensitive to different databases...
Biometrics play a crucial role in establishing an individuals identity. A signature is one of the most widely recognized way to authorize transactions and authenticate the human identity as compared to other electronic identification methods such as fingerprint and retina scans. Due to a huge demand for authentication, fast algorithms need to be assimilated for signature recognition and verification...
In this paper, we study an automatic testing system for public cloud on data security risks. To this end, we first establish a framework based on SOA (Service Oriented Architecture), which provides a capability to proceed data security tests on cloud automatically. Second, based on the framework we implement a cloud security testing system, which includes data confidentiality test and data deletion...
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