Damaged watermarks detection in frequency domain as a primary method for video concealment

This paper deals with video transmission over lossy communication networks. The main idea is to develop video concealment method for information losses and errors correction. At the beginning, three main groups of video concealment methods, divided by encoder/decoder collaboration, are briefly described. The modified algorithm based on the detection and filtration of damaged watermark blocks encapsulated to the transmitted video was developed. Finally, the efficiency of developed algorithm is presented in experimental part of this paper

An efficient P-KCCA algorithm for 2D-3D face recognition using SVM

In this paper, a novel face recognition system for face recognition and identification based on a combination of Principal Component Analysis and Kernel Canonical Correlation Analysis (P-KCCA) using Support Vector Machine (SVM) is proposed. First, the P-KCCA method is utilized to detect and extract the important features from the input images. This method makes it possible to match the 2D face image with enrolled 3D face data. The resulting features are then classified using the SVM method. The proposed methods were tested on TEXAS database with 200 subjects. The experimental results in the TEXAS face database produce interesting results from the point of view of recognition success, rate, and robustness of the face recognition algorithm. We compare the performance of our proposed face recognition method to other commonly-used methods. The experimental results show that the combination of P-KCCA method using SVM achieves a higher performance compared to the alone PCA, CCA and KCCA algorithms

Optimization of all-textile capacitive sensor array for smart chair

All-textile capacitive sensor arrays made of a polyurethane foam, fabric and electrically-conducting yarn were fabricated for a 'smart chair'. Polyurethane foam slab that functioned as a dielectric medium was encased between two pieces of commercially available fabric. The electrically-conducting yarn was used to embroider the capacitor electrodes on both fabric pieces. The completed sensor arrays were investigated under normal compressive load with the targeted pressure range of 2 to 30 kPa for the chair seat and 2 to 8 kPa for the backrest. The sensor capacitance versus normal compressive load exhibited a load/unload hysteresis for all sensor arrays. The hysteresis was modelled with sigmoid function and much narrower hysteresis was observed when all sensors were loaded simultaneously, as opposed to their individual loading, allowing development of a phenomenological model for the former. Among the studied sensor arrays, the array with dimensions of 30 cm 30 cm made of a 10-mm-thick polyurethane foam with density of 18.6 kg/m3 was the most suitable for the following reasons: (a) unloaded sensor capacitance was ~2.7 pF, (b) the sensor location did not affect its response, (c) ~10 kg load applied across individual sensor raised its capacitance by ~12 pF, and (d) 60 kg load applied uniformly across the whole sensor array increased the capacitance by ~5 pF. During the compression of the individual sensors the top fabric affected the sensor's electro-mechanical response and elastic fabric would be favored for applications with non-uniform pressure distribution

Flexible force sensors embedded in office chair for monitoring of sitting postures

Six flexible force sensors, two on the backrest and four on the seat, were embedded in the upholstery of an off-the-shelf office chair to enable non-intrusive monitoring of sitting postures. Besides the sensors, the monitoring platform comprises an Arduino Nano microcontroller with Wi-Fi transmitter, embedded on the chair, a Wi-Fi receiver communicating with a remote server and a Graphical User Interface (GUI) showing real-time readings. Approximately 26,000 observations corresponding to 9 different postures were collected, labelled and classified using supervised machine learning. The results show that only a subset of the 6 sensors is needed for predicting these 9 sitting postures with high accuracy. This opens up the possibility for intelligent, real-time monitoring systems that can improve safety and wellbeing of today’s office workers

A multicentre, prospective, randomised controlled trial to assess the safety and effectiveness of cooling as an adjunctive therapy to percutaneous intervention in patients with acute myocardial infarction: the COOL AMI EU Pivotal

Despite primary PCI (PPCI), ST-elevation myocardial infarction (STEMI) can still result in large infarct size (IS). New technology with rapid intravascular cooling showed positive signals for reduction in IS in anterior STEMI.We investigated the effectiveness and safety of rapid systemic intravascular hypothermia as an adjunct to PPCI in conscious patients, with anterior STEMI, without cardiac arrest.Hypothermia was induced using the ZOLL® Proteus™ intravascular cooling system. After randomisation of 111 patients, 58 to hypothermia and 53 to control groups, the study was prematurely discontinued by the sponsor due to inconsistent patient logistics between the groups resulting in significantly longer total ischaemic delay in the hypothermia group (232 vs 188 minutes; p<0.001).There were no differences in angiographic features and PPCI result between the groups. Intravascular temperature at wire crossing was 33.3+0.9°C. Infarct size/left ventricular mass (IS/LV) by cardiac magnetic resonance (CMR) at day 4-6 was 21.3% in the hypothermia group and 20.0% in the control group (p=0.540). Major adverse cardiac events at 30 days increased non-significantly in the hypothermia group (8.6% vs 1.9%; p=0.117) while cardiogenic shock (10.3% vs 0%; p=0.028) and paroxysmal atrial fibrillation (43.1% vs 3.8%; p<0.001) were significantly more frequent in the hypothermia group.The ZOLL Proteus intravascular cooling system reduced temperature to 33.3°C before PPCI in patients with anterior STEMI. Due to inconsistent patient logistics between the groups, this hypothermia protocol resulted in a longer ischaemic delay, did not reduce IS/LV mass and was associated with increased adverse events

New services development

Dynamic changes in traditional technologies and rising of new technologies call for development of new services. If service providers want to stay on information technologies market, they must keep track with this trend and adjust their services to customer requirements or develop new services. New applications will mainly depend on communication bandwidth and end users ability to handle it. If network providers will be able to ensure necessary bandwidth, there will be nothing that can stop service providers and developers in new service development. People know about growing necessity of new service and ask for them, but they hardly understand that the most important thing for service providers is merchantability and economic return of resources they gave to the development and implementation. By the lack of flexible development environment that is able to develop, test and provide final service for operation, new service development is not easy. There are different new service design procedures for various technological and user areas. This is the reason why this paper provides brief description of new service development procedure from technological and administrative point of view

Convergence performance of adaptive algorithms of L-filters

This paper deals with convergence parameters determination of adaptive algorithms, which are used in adaptive L-filters design. Firstly the stability of adaptation process, convergence rate or adaptation time, and behaviour of convergence curve belong among basic properties of adaptive algorithms. L-filters with variety of adaptive algorithms were used to their determination. Convergence performances finding of adaptive filters is important mainly for their hardware applications, where filtration in real time or adaptation of coefficient filter with low capacity of input data are required

SD LMS L-Filters for Filtration of Gray Level Images in Timespatial Domain Based on GLCM Features

SD LMS L-Filters for Filtration of Gray Level Images in Timespatial Domain Based on GLCM Feature

Local Feature Extraction in the Near Infra-Red Domain for Wildlife Mammals Tracking Purpose

Nowadays, research in area of intelligent transportation system is focused on analysis of traffic flow by computer vision techniques. Keypoint analysis represents detection, modelling and recognition of objects in traffic flow and object tracking as well. The main goal of this paper is to propose new approach to detect and modelling 3D objects that move on road surface. At the beginning, basic methods of object recognition and modelling of 3D object are shortly described. The modified algorithm based on background subtraction and creation of 3D model by depth map is proposed. Finally, the results of developed algorithm are depicted through the last part of this paper