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This paper presents an Kalman Filter Data Fusion methodology and investigation for high dynamics and high precision multi-head angular position encoder. The proposed algorithm based on measurement of four dependent Read Heads and encoder ring for one mechanical shaft of high precision system with electric drive. The global fusion of proposed estimation provide computed value of position and additional...
Lagrangian carotid strain imaging (LCSI) involves estimation of deformation in the carotid artery due to blood pressure variations under cardiac pulsation. Local strain over a cardiac cycle is tracked, which is computationally intensive. We incur long offline processing times for LCSI which becomes a limiting factor for clinical adoption. We report on the computational speedup obtained for a parallelized...
In the current transfer machine for the flexible band, the equipment sometimes stops due to fluctuations in the tension of the flexible band, the readjustment is required at this time and the productivity is reduced. Therefore, in this study, we clarified factors influencing the positioning accuracy of the flexible band, proposed a monitoring method of operating condition, and aimed at the improvement...
Each three-dimensional crystal structure consists of a set of unit cells which parameters comprehensively describe the location of atoms or atom groups in a crystal. However, the problem of ambiguity of unit cell choice significantly limits the application of existing methods of unit cell parameter identification and comparison. The article proposes a new lattice comparison method based on the unit...
The paper presents the simulation results of gene expression sequences clustering within the framework of the objective clustering inductive technology. As experimental data the gene expression sequences of lung cancer patients, which were obtained by microchip experiments, were used. The estimation of the grouping data quality was performed with the use of the internal and external clustering quality...
Advanced Metering Infrastructure (AMI) have rapidly become a topic of international interest as governments have sponsored their deployment for the purposes of utility service reliability and efficiency, e.g., water and electricity conservation. Two problems plague such deployments. First is the protection of consumer privacy. Second is the problem of huge amounts of data from such deployments. A...
In this paper, the BER performance of a soft distance successive cancellation decoder for Polar codes is analyzed in the presence of impulsive noise, modelled using both the Middleton's Class A model and the symmetric alpha-stable model, for impulsive noise channels. This algorithm avoids estimation of the signal-to-noise ratio of the channel, and simplifies the initialization step of the classic...
We introduce a machine learning approach for real life software development effort estimation. Our method uses state of the art developments such as distributed word embeddings in order to create a system that can estimate effort given only basic project management metrics and, most importantly, textual descriptions of tasks. We use an artificial neural network for automating the effort estimation...
Use case analysis has been widely adopted in modern software engineering due to its strength in capturing the functional requirements of a system. It is often done with a UML use case model that formalizes the interactions between actors and a system in the requirements elicitation iteration, and with architectural alternatives explored and user interface details specified in the following analysis...
Good planning and managing software test process require accurate estimation of software test effort. This becomes particularly significant when validation and verification activities are to be performed by an independent organization. This study presents a systematic literature review and a follow up industrial survey, which was performed to investigate the state of the art on software test effort...
Estimating the initial background of a scene is a key prerequisite for several applications in video analytics. In this paper, we present a simple approach that takes into account spatio-temporal motion intensities while estimating the true background. We tested the algorithm on real video sequences from the Scene Background Initialization (SBI) benchmark dataset, and the results show that the algorithm...
Depth map estimation forms an integral part of many applications such as 2D-to-3D creation. There exists various methods in literature for depth map estimation using different cues and structure. Usually, depth information is decoded from these cues at the edges and matting is applied to spread it over neighboring regions. Defocus is one such cue due to its natural existence and does not require any...
Person re-identification (ReID) stands for the task of determining the co-occurrence of individuals across a network of cameras with disjoint viewfields. The relevant literature documents a plausible number of contributions so far. KISS metric learning is an effective ReID method. However, as reported in the existing works, KISS metric learning is sensitive to the feature dimensionality and can not...
Image quality assessment (IQA) plays a crucial role in monitoring quality control in image communication systems, and in benchmarking and optimizing parameters in enhancement algorithms. The full-reference IQA metrics require a good-quality reference image, obtaining which may not be practical in real-life applications. This paper, therefore, proposes a no-reference IQA metric based on the hypothesis...
The paper deals with the contact center modeling with emphasis on the optimal number of agents. The contact center belongs to the queueing systems and its mathematical model can be described by various important parameters. The Erlang C formula tends to be suitable tool for the modeling of QoS parameters of contact centers. In our paper, we propose two parameters: downtime and administrative task...
Manifold causes of image blurring make the no-reference evaluation of realistic blurred images very challenging. Previous studies indicate that handcrafted features suffer from poor representation of the intrinsic characteristics of image blurring and thus blind image sharpness assessment (BISA) is unsatisfactory. This paper explores a shallow convolutional neural network (CNN) to address this problem...
Single-image blind deconvolution is one of the most challenging fields in image processing which restores a sharp image from its blurred version. Nowadays blind deconvolution algorithms have made significant progress. However, the restoration of blurred images with little scale edges and periodic textures is still a hard work. To solve this problem, this paper proposes a new normalized sparse regularization...
In this paper, we consider the nonlinear filtering by using information geometric approach. Under the principle of Bayesian, the filtering problem has been converted to Bayesian estimation. Based on the estimation conditional on the measurement, the posterior probability density functions (PDFs) have constructed a statistical manifold. With the information geometric approach, the nonlinear characteristic...
Deep convolutional neural networks (CNNs) are indispensable to state-of-the-art computer vision algorithms. However, they are still rarely deployed on battery-powered mobile devices, such as smartphones and wearable gadgets, where vision algorithms can enable many revolutionary real-world applications. The key limiting factor is the high energy consumption of CNN processing due to its high computational...
This study aimed to assess the potential of GLAS (Geoscience Laser Altimeter System) LiDAR data to overcome the saturation at high AGB values of existing AGB map on Madagascar (Vieilledent's AGB map [1]). First, spatially distributed estimations of AGB were obtained from GLAS data. Second, the difference between the Vieilledent's AGB map and GLAS derived AGB at each GLAS footprints location was calculated...
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