Filters
total: 251
filtered: 232
-
Catalog
Chosen catalog filters
Search results for: MEMORY SPACE
-
Compressed Projection Bases for Model-Order Reduction of Multiport Microwave Components Using FEM
PublicationThis paper presents a projection basis compression technique for generating compact reduced-order models (ROM) in the FE analysis of microwave devices. In this approach redundancy is removed from the projection basis by means of the proper orthogonal decomposition technique applied to the projected system of linear equations. Compression allows for keeping the size of a reduced-order model as small as possible without compromising...
-
Evaluating Performance and Accuracy Improvements for Attention-OCR
PublicationIn this paper we evaluated a set of potential improvements to the successful Attention-OCR architecture, designed to predict multiline text from unconstrained scenes in real-world images. We investigated the impact of several optimizations on model’s accuracy, including employing dynamic RNNs (Recurrent Neural Networks), scheduled sampling, BiLSTM (Bidirectional Long Short-Term Memory) and a modified attention model. BiLSTM was...
-
Improvement of time difference of arrival measurements resolution by using fractional delay filters in a direct sequence-code division multiple access radionavigation system
PublicationThis study presents a method of improving time measurements resolution in a direct sequence-code division multiple access receiver by using a fine code tracking loop based on fractional delay filtering of a despreading sequence. It briefly describes the structure of a generic digital code tracking loop and the proposed modification which allows to measure time difference of arrival values with the subsample resolution, together...
-
Macromodeling techniques for accelerated finite element analysis
PublicationThis paper deals with the Model Order Reduction applied locally in the Finite Element Method (FEM) analysis. Due to the reduction process, blocks of FEM system matrices associated with selected subregions of the computational domain are projected onto the subspaces spanned by the vectors of suited orthogonal projection basis. In effect, large and sparse FEM matrices are replaced with small and dense ones, called macromodels. This...
-
Fluctuation-Enhanced Sensing (FES): A Promising Sensing Technique
PublicationFluctuation-enhanced sensing (FES) is a very powerful odor and gas sensing technique and as such it can play a fundamental role in the control of environments and, therefore, in the protection of health. For this reason, we conduct a comprehensive survey on the state-of-the-art of the FES technique, highlighting potentials and limits. Particular attention is paid to the dedicated instrumentation necessary for the application of...
-
Evidence for consolidation of neuronal assemblies after seizures in humans
PublicationThe establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as "cellular consolidation" (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation...
-
An automated learning model for twitter sentiment analysis using Ranger AdaBelief optimizer based Bidirectional Long Short Term Memory
PublicationSentiment analysis is an automated approach which is utilized in process of analysing textual data to describe public opinion. The sentiment analysis has major role in creating impact in the day-to-day life of individuals. However, a precise interpretation of text still relies as a major concern in classifying sentiment. So, this research introduced Bidirectional Long Short Term Memory with Ranger AdaBelief Optimizer (Bi-LSTM RAO)...
-
Intracranial hemorrhage detection in 3D computed tomography images using a bi-directional long short-term memory network-based modified genetic algorithm
PublicationIntroduction: Intracranial hemorrhage detection in 3D Computed Tomography (CT) brain images has gained more attention in the research community. The major issue to deal with the 3D CT brain images is scarce and hard to obtain the labelled data with better recognition results. Methods: To overcome the aforementioned problem, a new model has been implemented in this research manuscript. After acquiring the images from the Radiological...
-
DEPO: A dynamic energy‐performance optimizer tool for automatic power capping for energy efficient high‐performance computing
PublicationIn the article we propose an automatic power capping software tool DEPO that allows one to perform runtime optimization of performance and energy related metrics. For an assumed application model with an initialization phase followed by a running phase with uniform compute and memory intensity, the tool performs automatic tuning engaging one of the two exploration algorithms—linear search (LS) and golden section search (GSS), finds...
-
Electromagnetic plane wave scattering from a cylindrical object with an arbitrary cross section using a hybrid technique
PublicationA hybrid technique combining finite-element and mode-matching methods for the analysis of scattering problems in open and closed areas is presented. The main idea of the analysis is based on the utilization of the finite-element method to calculate the post impedance matrix and combine it with external excitation. The discrete analysis, which is the most time- and memory-consuming, is limited here only to the close proximity of...
-
Performance evaluation of parallel background subtraction on GPU platforms
PublicationImplementation of the background subtraction algorithm on parallel GPUs is presented. The algorithm processes video streams and extracts foreground pixels. The work focuses on optimizing parallel algorithm implementation by taking into account specific features of the GPU architecture, such as memory access, data transfers and work group organization. The algorithm is implemented in both OpenCL and CUDA. Various optimizations of...
-
On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
-
On noncausal identification of nonstationary stochastic systems
PublicationIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
-
Interrelated shape memory and Payne effect in polyurethane/graphene oxide nanocomposites
PublicationWe report the fabrication of graphene oxide (GO) based polyurethane (PU) nanocomposites by a simple method of mixing and their shape memory properties at different temperatures. Both the polymer and the filler were synthesized in the laboratory by simple and easy methods – PU by pre-polymer method and GO by improved graphene oxide synthesis method. High molecular level dispersion of GO platelets within the PU matrix and thus good...
-
Development of polyurethanes for bone repair
PublicationThe purpose of this paper is to review recent developments on polyurethanes aimed at the design, synthesis, modifications, and biological properties in the field of bone tissue engineering. Different polyurethane systems are presented and discussed in terms of biodegradation, biocompatibility and bioactivity. A comprehensive discussion is provided of the influence of hard to soft segments ratio, catalysts, stiffness and hydrophilicity...
-
Allergic reactions as a defense of the organism to the influence of implants components made of stainless steel
PublicationDue to the increasing number of cases of hypersensitivity caused by direct contact with metals, as well as the increasing demand for implants in humans all ages numerous studies on the effects of the impact of implant components are being carried out. The paper presents the phenomenon of etiology of allergy in general terms and in relation to the biomaterials used in medicine. There have been characterized in terms of impact on...
-
Allergic Reactions as a Defense of the Organism to the Influence of Implants Components Made of Stainless Steel
PublicationDue to the increasing number of cases of hypersensitivity caused by direct contact with metals, as well as the increasing demand for implants in humans all ages numerous studies on the effects of the impact of implant components are being carried out. The paper presents the phenomenon of etiology of allergy in general terms and in relation to the biomaterials used in medicine. There have been characterized in terms of impact on...
-
Combined Single Neuron Unit Activity and Local Field Potential Oscillations in a Human Visual Recognition Memory Task
PublicationGOAL: Activities of neuronal networks range from action potential firing of individual neurons, coordinated oscillations of local neuronal assemblies, and distributed neural populations. Here, we describe recordings using hybrid electrodes, containing both micro- and clinical macroelectrodes, to simultaneously sample both large-scale network oscillations and single neuron spiking activity in the medial temporal lobe structures...
-
The Distribution of Glucosinolates in Different Phenotypes of Lepidium peruvianum and Their Role as Acetyl- and Butyrylcholinesterase Inhibitors—In Silico and In Vitro Studies
PublicationThe aim of the study was to present the fingerprint of different Lepidium peruvianum tu- ber extracts showing glucosinolates-containing substances possibly playing an important role in preventinting dementia and other memory disorders. Different phenotypes of Lepidium peruvianum (Brassicaceae) tubers were analysed for their glucosinolate profile using a liquid chromatograph coupled with mass spectrometer (HPLC-ESI-QTOF-MS/MS platform)....
-
Remote Spatial Database Access in the Navigation System for the Blind
PublicationThe article presents the problem of a database access in the navigation systems. The authors were among the main creators of the prototype navigation system for the blind - “Voice Maps”. In the implemented prototype only exemplary, limited spatial data were used, therefore they could be stored in the mobile device’s memory without any difficulties. Currently the aforementioned system is being prepared for commercialization - the...
-
Simulation of parallel similarity measure computations for large data sets
PublicationThe paper presents our approach to implementation of similarity measure for big data analysis in a parallel environment. We describe the algorithm for parallelisation of the computations. We provide results from a real MPI application for computations of similarity measures as well as results achieved with our simulation software. The simulation environment allows us to model parallel systems of various sizes with various components...
-
Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...
-
Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
-
Hierarchical Estimation of Human Upper Body Based on 2D Observation Utilizing Evolutionary Programming and 'Genetic Memory'
PublicationNew method of the human body pose estimation based on single camera 2D observation is presented. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, motion cost metric is employed, considering current pose and history of the body movement, favouring the estimates with the lowest...
-
Parallel Background Subtraction in Video Streams Using OpenCL on GPU Platforms
PublicationImplementation of the background subtraction algorithm using OpenCL platform is presented. The algorithm processes live stream of video frames from the surveillance camera in on-line mode. Processing is performed using a host machine and a parallel computing device. The work focuses on optimizing an OpenCL algorithm implementation for GPU devices by taking into account specific features of the GPU architecture, such as memory access,...
-
Real‐Time PPG Signal Conditioning with Long Short‐Term Memory (LSTM) Network for Wearable Devices
PublicationThis paper presents an algorithm for real‐time detection of the heart rate measured on a person’s wrist using a wearable device with a photoplethysmographic (PPG) sensor and accelerometer. The proposed algorithm consists of an appropriately trained LSTM network and the Time‐Domain Heart Rate (TDHR) algorithm for peak detection in the PPG waveform. The Long Short‐Term Memory (LSTM) network uses the signals from the accelerometer...
-
Formulation of Time-Fractional Electrodynamics Based on Riemann-Silberstein Vector
PublicationIn this paper, the formulation of time-fractional (TF) electrodynamics is derived based on the Riemann-Silberstein (RS) vector. With the use of this vector and fractional-order derivatives, one can write TF Maxwell’s equations in a compact form, which allows for modelling of energy dissipation and dynamics of electromagnetic systems with memory. Therefore, we formulate TF Maxwell’s equations using the RS vector and analyse their...
-
Dissecting gamma frequency activities during human memory processing
PublicationGamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not...
-
Tacit Knowledge Sharing and Value Creation in the Network Economy: Socially Driven Evolution of Business
PublicationKey factors which affect competitive advantage in the network economy are innovation, relationships, cooperation, and knowledge. Sharing knowledge is not easy. Companies find it problematic. Presented studies show that the essence of the value creation today is not in sharing explicit but rather tacit knowledge, which is a source of creativity and innovation. Delivering value through knowledge does not only require efficient Transactive...
-
Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublicationThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
-
BIOMATERIALS AND IMPLANTS IN CARDIAC AND VASCULAR SURGERY - REVIEW
PublicationCurrently, on prosthesis in cardiac blood vessels and heart valves are used materials of animal or synthetic origin. For animal materials include, among others pericardial sac in which is the heart. Materials such as this (natural) are characterized by a remarkable biocompatibility within the human body, but their main disadvantage is the relatively low durability. In turn, synthetic materials, which include the austenitic chromium-nickel-molybdenum...
-
Neural networks and deep learning
PublicationIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
-
Ripple oscillations in the left temporal neocortex are associated with impaired verbal episodic memory encoding
PublicationBACKGROUND: We sought to determine if ripple oscillations (80-120 Hz), detected in intracranial electroencephalogram (iEEG) recordings of patients with epilepsy, correlate with an enhancement or disruption of verbal episodic memory encoding. METHODS: We defined ripple and spike events in depth iEEG recordings during list learning in 107 patients with focal epilepsy. We used logistic regression models (LRMs) to investigate the...
-
Runtime Visualization of Application Progress and Monitoring of a GPU-enabled Parallel Environment
PublicationThe paper presents design, implementation and real life uses of a visualization subsystem for a distributed framework for parallelization of workflow-based computations among clusters with nodes that feature both CPUs and GPUs. Firstly, the proposed system presents a graphical view of the infrastructure with clusters, nodes and compute devices along with parameters and runtime graphs of load, memory available, fan speeds etc. Secondly,...
-
A Solution to Image Processing with Parallel MPI I/O and Distributed NVRAM Cache
PublicationThe paper presents a new approach to parallel image processing using byte addressable, non-volatile memory (NVRAM). We show that our custom built MPI I/O implementation of selected functions that use a distributed cache that incorporates NVRAMs located in cluster nodes can be used for efficient processing of large images. We demonstrate performance benefits of such a solution compared to a traditional implementation without NVRAM...
-
A Perspective on Fast-SPICE Simulation Technology
PublicationThis chapter presents an introduction to the area of accelerated transistor-level (‘fast-SPICE’) simulation for automated verification and characterization of integrated circuits (ICs) from technologist’s perspective. It starts with outlining goals, expectations and typical usage models for fast-SPICE simulators, stressing how they differ from regular SPICE tools. It continues with presenting and classifying core technologies typically...
-
An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
-
Dynamical description of quantum computing: generic nonlocality of quantumnoise
PublicationWe develop a dynamical non-Markovian description of quantum computing in the weak-coupling limit, in the lowest-order approximation. We show that the long-range memory of the quantum reservoir (such as the 1/t4 one exhibited by electromagnetic vacuum) produces a strong interrelation between the structure of noise and the quantum algorithm, implying nonlocal attacks of noise. This shows that the implicit assumption of quantum error...
-
Crank–Nicolson FDTD Method in Media Described by Time-Fractional Constitutive Relations
PublicationIn this contribution, we present the Crank-Nicolson finite-difference time-domain (CN-FDTD) method, implemented for simulations of wave propagation in media described by time-fractional (TF) constitutive relations. That is, the considered constitutive relations involve fractional-order (FO) derivatives based on the Grünwald-Letnikov definition, allowing for description of hereditary properties and memory effects of media and processes....
-
Parallel implementation of a Sailing Assistance Application in a Cloud Environment
PublicationSailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions...
-
Improving Clairvoyant: reduction algorithm resilient to imbalanced process arrival patterns
PublicationThe Clairvoyant algorithm proposed in “A novel MPI reduction algorithm resilient to imbalances in process arrival times” was analyzed, commented and improved. The comments concern handling certain edge cases in the original pseudocode and description, i.e., adding another state of a process, improved cache friendliness more precise complexity estimations and some other issues improving the robustness of the algorithm implementation....
-
Survey of Methodologies, Approaches, and Challenges in Parallel Programming Using High-Performance Computing Systems
PublicationThis paper provides a review of contemporary methodologies and APIs for parallel programming, with representative technologies selected in terms of target system type (shared memory, distributed, and hybrid), communication patterns (one-sided and two-sided), and programming abstraction level. We analyze representatives in terms of many aspects including programming model, languages, supported platforms, license, optimization goals,...
-
Decontaminating Arbitrary Graphs by Mobile Agents: a Survey
PublicationA team of mobile agents starting from homebases need to visit and clean all nodes of the network. The goal is to find a strategy, which would be optimal in the sense of the number of needed entities, the number of moves performed by them or the completion time of the strategy. Currently, the field of distributed graph searching by a team of mobile agents is rapidly expanding and many new approaches and models are being presented...
-
Blood Pressure Estimation Based on Blood Flow, ECG and Respiratory Signals Using Recurrent Neural Networks
PublicationThe estimation of systolic and diastolic blood pressure using artificial neural network is considered in the paper. The blood pressure values are estimated using pulse arrival time, and additionally RR intervals of ECG signal together with respiration signal. A single layer recurrent neural network with hyperbolic tangent activation function was used. The average blood pressure estimation error for the data obtained from 21 subjects...
-
Performance Evaluation of Selected Parallel Object Detection and Tracking Algorithms on an Embedded GPU Platform
PublicationPerformance evaluation of selected complex video processing algorithms, implemented on a parallel, embedded GPU platform Tegra X1, is presented. Three algorithms were chosen for evaluation: a GMM-based object detection algorithm, a particle filter tracking algorithm and an optical flow based algorithm devoted to people counting in a crowd flow. The choice of these algorithms was based on their computational complexity and parallel...
-
Magnetoelectric effect in (BiFeO3)x–(BaTiO3)1-x solid solutions
PublicationThe aim of the present work was to study magnetoelectric effect (ME) in (BiFeO3)x–(BaTiO3)1x solid solutions in terms of technological conditions applied in the samples fabrication process. The rapidly growing interest in these materials is caused by their multiferroic behaviour, i.e. coexistence of both electric and magnetic ordering. It creates possibility for many innovative applications, e.g. in steering the magnetic memory...
-
Performance assessment of OpenMP constructs and benchmarks using modern compilers and multi-core CPUs
PublicationConsidering ongoing developments of both modern CPUs, especially in the context of increasing numbers of cores, cache memory and architectures as well as compilers there is a constant need for benchmarking representative and frequently run workloads. The key metric is speed-up as the computational power of modern CPUs stems mainly from using multiple cores. In this paper, we show and discuss results from running codes such as:...
-
A New Type of Macro-Elements for Efficient Two-Dimensional FEM Analysis
PublicationThis letter deals with a model order reduction technique applicable for driven and eigenvalue problems solved using the finite element method (FEM). It allows one to efficiently compute electromagnetic parameters of structures comprising small features that require strong local mesh refinement. The subdomains of very fine mesh are separated from the global domain as so called macro-elements that undergo model reduction. The macro-elements...
-
Accuracy, Memory and Speed Strategies in GPU-based Finite-Element Matrix-Generation
PublicationThis paper presents strategies on how to optimize GPU-based finite-element matrix-generation that occurs in the finite-element method (FEM) using higher order curvilinear elements. The goal of the optimization is to increase the speed of evaluation and assembly of large finite-element matrices on a single GPU (Graphics Processing Unit) while maintaining the accuracy of numerical integration at the desired level. For this reason,...
-
Client-server Approach in the Navigation System for the Blind
PublicationThe article presents the client‐server approach in the navigation system for the blind ‐ “Voice Maps”. The authors were among the main creators of the prototype and currently the commercialization phase is being finished. In the implemented prototype only exemplary, limited spatial data were used, therefore they could be stored and analysed (for path-finding process) in the mobile device’s memory without any difficulties. The...