Matrix Mapping Research Articles

Infrared and visible image fusion via intensity transfer and direct matrix mapping

Infrared (IR) and visible (VIS) image fusion has turned into a research hotspot in image processing due to various applications recently. In this paper, so as to make the resulted images not only retain the thermal object information in the IR images and the background information in the VIS images simultaneously, but also be more in line with human vision, we propose a novel intensity transfer and direct matrix mapping-based fusion method, which we named IT-DMM. Specifically, we formulate such fusion as a minimization problem, and our solution to the problem is a direct matrix mapping from the input images to the resulted image. The weights used in our IT-DMM, which are computed by using spatial saliency map of the IR image, are vital to the performance of the proposed method and are analyzed in detail. Our IT-DMM has high computational efficiency due to the direct matrix mapping and the efficient weight computation method, and thus it has potential practical value. Qualitative and quantitative experiments on eighteen IR and VIS image pairs indicate that our IT-DMM outperforms eleven state-of-the-art image fusion methods in obtaining perceptually better fusion results with almost the same thermal object information in IR images and background information in VIS images.

A Monocular Vision-Based Framework for Power Cable Cross-Section Measurement

The measurements of the diameter of different layers, the thickness of different layers and the eccentricity of insulation layer in the cross-section of power cables are important items of power cable test, which currently depend on labor-intensive manual operations. To improve efficiency, automatic measurement methods are in urgent need. In this paper, a monocular vision-based framework for automatic measurement of the diameter, thickness, and eccentricity of interest in the cross-section of power cables is proposed. The proposed framework mainly consists of three steps. In the first step, the images of cable cross-section are captured and undistorted with the camera calibration parameters. In the second step, the contours of each layer are detected in the cable cross-section image. In order to detect the complete and accurate contours of each layer, the structural edges in the cross-section image are firstly detected and divided into individual layers, then unconnected edges are connected by arc-based method, and finally contours are refined by the proposed break detection and grouping (BDG) and linear trend-based correction (LTBC) algorithm. In the third step, the monocular vision-based cross-section dimension measurement is accomplished by placing a chessboard coplanar with the power cable cross-section plane. The homography matrix mapping pixel coordinates to chessboard world coordinates is estimated, and the diameter, thickness and eccentricity of specific layers are calculated by homography matrix-based measurement method. Simulated data and actual cable data are both used to validate the proposed method. The experimental results show that diameter, minimum thickness, mean thickness and insulation eccentricity of simulated image without additive noise are measured with root mean squared error (RMSE) of 0.424, 0.103 and 0.063 mm, and 0.002, respectively, those of simulated image with additive Gaussian noise and salt and pepper noise are measured with RMSE of 0.502, 0.243 and 0.058 mm and 0.001. Diameter, minimum thickness and mean thickness of actual cable images are measured with average RMSE of 0.768, 0.308 and 0.327 mm. The measurement error of insulation eccentricity of actual cable image is comparatively large, and the measurement accuracy should be improved.

DIFFERENTIAL MULLER-MATRIX MICROSCOPY OF THE PROTEIN FRACTION OF THE VITREOUS BODY PREPARATIONS FOR DIAGNOSTICS OF THE PRESCRIPTION OF DEATH COMING

Objective - to develop a complex of forensic criteria for determining the time since death, using differential Muller-matrix microscopy of the protein fraction of the vitreous body. Material and methods. The vitreous body sampling was conducted from the anterior chamber of the eye in 80 corpses with a previously known time of death from 1 to 24 hours. Subsequently, experimental measurements of the coordinate distributions of the differential element of the polycrystalline structure of biological preparations of the vitreous body were carried out. Results and conclusions. The set of maps and histograms of the distributions of random values of the differential element of the protein fraction of the vitreous layers of the dead with different time since death were studied using the differential Muller-matrix mapping method. The sensitivity range (24 hours) and accuracy (40 minutes) for the Muller differential method with matrix mapping of the protein fraction of the vitreous layers at a certain time since death have been established.

Unsupervised emotion recognition algorithm based on improved deep belief model in combination with probabilistic linear discriminant analysis

Since the initial weight matrix between the last hidden layer of the network and the classification layer is usually generated randomly, the weight matrix does not have the discrimination ability to accurately classify the facial expression recognition, which results in that the features obtained by the weight matrix mapping cannot be guaranteed to be suitable for classification tasks. To solve this problem, a novel linear discriminant deep belief network is proposed in this paper. Firstly, the traditional linear discriminant analysis method is improved, and a new type of inter-class dispersion matrix is designed to solve the rank limitation problem in the traditional Linear Discriminant Analysis Method (LDA). Then, the weight matrix between the last hidden layer and the classification layer of the deep belief network is initialized by the improved linear discriminant analysis method, so that the network is more suitable for the classification task. In the experiments, our proposed deep network obtains respectively the recognition rates of 78.26% and 94.48% on the JAFFE database and the Extended Cohn-Kanade database. In addition, using our proposed algorithm for aggregating linear discriminant analysis into a deep belief network, we were able to produce an accuracy of 81.03% on the challenge test set.

Matrix group integrals, surfaces, and mapping class groups I: U(n)

Since the 1970's, physicists and mathematicians who study random matrices in the GUE or GOE models are aware of intriguing connections between integrals of such random matrices and enumeration of graphs on surfaces. We establish a new aspect of this theory: for random matrices sampled from the group $\mathcal{U}\left(n\right)$ of unitary matrices. More concretely, we study measures induced by free words on $\mathcal{U}\left(n\right)$. Let $F_{r}$ be the free group on $r$ generators. To sample a random element from $\mathcal{U}\left(n\right)$ according to the measure induced by $w\in F_{r}$, one substitutes the $r$ letters in $w$ by $r$ independent, Haar-random elements from $\mathcal{U}\left(n\right)$. The main theme of this paper is that every moment of this measure is determined by families of pairs $\left(\Sigma,f\right)$, where $\Sigma$ is an orientable surface with boundary, and $f$ is a map from $\Sigma$ to the bouquet of $r$ circles, which sends the boundary components of $\Sigma$ to powers of $w$. A crucial role is then played by Euler characteristics of subgroups of the mapping class group of $\Sigma$. As corollaries, we obtain asymptotic bounds on the moments, we show that the measure on $\mathcal{U}\left(n\right)$ bears information about the number of solutions to the equation $\left[u_{1},v_{1}\right]\cdots\left[u_{g},v_{g}\right]=w$ in the free group, and deduce that one can ``hear'' the stable commutator length of a word through its unitary word measures.

Matrix Mapping on Crossbar Memory Arrays with Resistive Interconnects and Its Use in In-Memory Compression of Biosignals

Recent advances in nanoscale resistive memory devices offer promising opportunities for in-memory computing with their capability of simultaneous information storage and processing. The relationship between current and memory conductance can be utilized to perform matrix-vector multiplication for data-intensive tasks, such as training and inference in machine learning and analysis of continuous data stream. This work implements a mapping algorithm of memory conductance for matrix-vector multiplication using a realistic crossbar model with finite cell-to-cell resistance. An iterative simulation calculates the matrix-specific local junction voltages at each crosspoint, and systematically compensates the voltage drop by multiplying the memory conductance with the ratio between the applied and real junction potential. The calibration factors depend both on the location of the crosspoints and the matrix structure. This modification enabled the compression of Electrocardiographic signals, which was not possible with uncalibrated conductance. The results suggest potential utilities of the calibration scheme in the processing of data generated from mobile sensing or communication devices that requires energy/areal efficiencies.

Risk Analysis of Agile Framework in Project Management Exploration Drilling in Oil and Gas Sector

Energy sector in particular of oil and gas industry is the industry that became main income in the State of Indonesia before 2015, but in the same year there was a significant change in oil and gas prices. A more rapid and systematic project management pattern is required using Agile, Agile is a management project pattern that will be implemented in the current decade, using agile activities to make it easier to think, understand and implement prioritization at each stage. In this research will be mapping priority and risk based on expert on determining risk matrix, job priority and risk mapping. The results of this study indicate that subsurface activity is the main sub-project that must be prioritized.

From incomer to insider: The development of the TRANSPEC model - A systematic review of the factors influencing the effective rapid and early career TRANsition to a nursing SPECiality in differing contexts of practice.

ObjectiveShortages in the speciality nursing workforce, both nationally and internationally are driving the need for the development of an evidence-based model to inform recruitment and retention into speciality nursing practice. This study aimed to identify the factors influencing rapid and early career transition into speciality nursing practice.MethodsA comprehensive systematic review of the literature was undertaken using a convergent qualitative synthesis design where results from qualitative, quantitative and mixed methods studies were transformed into qualitative findings. Databases included CINAHL, Medline, Scopus and PsycINFO. Search terms were: nurse, early career, rapid career, transition, specialty, and Medical Subject Heading terms included: professional development and educational, nursing, and continuing. Using validated tools, papers were independently assessed by a minimum of two reviewers.ResultsTwenty-three research articles were included. There were no randomized control trials. Through thematic analysis and matrix mapping of the results, the TRANSPEC model was developed. The model outlines three phases of transition: pre-entry, incomer and insider. There has been little focus on pre-entry with programs being designed at the incomer and insider phases. Impacting on these phases are three concepts: the self (professional and personal), the transition processes (informal and formal) and a sense of belonging. The overarching theme influencing the phases and concepts is the context of practice. Enablers and inhibitors influence successful transition and therefore impact on recruitment and retention. Each nurse’s transition is influenced by time.ConclusionsFor successful transition, the enablers and inhibitors impacting on the three concepts, phases and the context of practice need to be considered when developing any program. It is apparent that while previous studies have focused on the transition processes, such as curricula, the development of the self and a sense of belonging are also essential to successful transition. Further studies should include the pre-entry phase.

Chaotic Multilevel Separated Encryption for Security Enhancement of OFDM-PON

A chaotic multilevel separated encryption (CMSE) scheme is proposed for physical layer security enhancement of orthogonal frequency division multiplexing passive optical network (OFDM-PON). In the proposed scheme, symbols in an OFDM signal are divided into several sub-matrices by matrix mapping and then encrypted by different algorithms selected from a set of alternative encryption algorithms based on 1D logistic chaotic systems separately. The signal processed by this scheme is encrypted at four levels. The four encryption levels depend on a matrix mapping rule, the specific algorithms, the order of used encryption algorithms and the key of each chaotic system. Any one of these conditions is essential for proper decryption. Compared with traditional methods, this scheme adds two new encryption levels and replaces the unique employed algorithm with multiple algorithms, which improves the security of system at the expense of a slightly increased complexity. An encrypted signal transmission of 22.06 Gb/s bit rate is successfully demonstrated over a back-to-back (BTB) system and a 25-km standard single mode fiber (SSMF). The experimental results prove that the CMSE scheme does not deteriorate the system performance and has good security against illegal attacks for future access networks.

Improvement of the Spatial Channel Matrix Mapping and Precoding Algorithm in the Forest Environment

Few studies have been conducted on the forest spatial channel matrix, most of which were conducted by experts and scholars in the field of communications. The mature cellular network channel coding matrix was “transplanted” to the vegetation-covered space, and the effects of the various vegetation dielectric constants, the forest canopy density and other objective factors on the traditional cellular channel were ignored. To overcome this problem, this paper built a relay network that is suitable for forest environments. This network was an effective complement to the existing cellular communication network for expanding the coverage of signals in the forest. On this basis, this paper analysed the multi-antenna relay transmission protocol and proposed an additional spatial channel matching (mapping) matrix between the forward and backward filters. This matrix was designed to consider the effect of the complex forest environment on the channel to reduce the relaying noise power. Then, under the forest cellular relay network topology, a spatial channel matrix structure (based on unitary matrix) that is suitable for the forest environment is proposed. This matrix can be incorporated into various relay protocols and considers the source node preprocessing operation and the destination node equalizer. The forest relay cooperative network that is proposed in this paper can effectively expand the coverage of signals in forest areas; however, due to the inherent limitations of the relay network, many problems will be encountered in practical applications. For example, the precoding scheme that is based on phase correction requires the terminal node to feed the phase correction factor back to the forest base station node; however, the system performance is substantially affected by the feedback accuracy and the arrival delay difference. Due to the uncertain rank of the integrated channel in the forest base station precoding scheme, it was necessary to adapt to a variety of antenna ports, which rendered the design of the precoding codebook highly difficult. In addition, when the number of transmission layers was greater than 1, the local precoding scheme also encountered the problem of inter-layer interference (ILI). Based on a detailed analysis of the shortcomings of the previous scheme and the strategy of partial coherence transmission, this paper proposes an improved algorithm of incoherent joint transmission technology and an improved precoding scheme that are suitable for forest relay systems. The signal that is transmitted by the relay node and the feedback signal is corrected via layer exchange between cells and via phase correction. By changing the layer’s exchange information and phase information, it can be adapted to various forest environments, such as artificial forests, natural forests, and virgin forests. Finally, the outage probability is considered as a performance indicator in the simulation of the forest environment wireless relay system. The theoretical analysis and simulation results demonstrate the satisfactory performance of the proposed spatial channel mapping matrix and the forest relay precoding scheme.

Elementary matrix equivalence and core transformation graphs for Parikh matrices

The introduction of the Parikh matrix mapping by Mateescu et al. in 2001 gave rise to the injectivity problem, that is, the characterization of words having the same Parikh matrix. Certain elementary rewriting rules have been successful in solving this problem for the binary alphabet, yet they do not suffice for the general case. This paper studies these elementary rewriting rules exclusively for the ternary alphabet. Certain labeled graphs, termed as core transformation graphs, are introduced and used to study the structural changes in ternary words upon applications of these elementary rewriting rules. For an arbitrary core transformation graph, all possibilities of the labels on its edges are exhausted and, for each label, the pairs of vertices forming the corresponding edges are characterized. Finally, we obtain results relating core transformation graphs to elementarily matrix equivalent words.

Improving the Nulling Beamformer Using Subspace Suppression.

Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, which may be removed by the TSVD operation. To address this issue we propose a new method, the nulling beamformer with subspace suppression (NBSS). This method, controlled by a tuning parameter, reweights the singular values of the gain matrix mapping from source to sensor space such that components with high overlap are reduced. By doing so, we are able to measure signals between nearby source locations with limited cross-talk interference, allowing for reliable cortical connectivity analysis between them. In two simulations, we demonstrated that NBSS reduces cross-talk while retaining ROIs' signal power, and has higher separating power than both the minimum norm estimate (MNE) and the nulling beamformer without subspace suppression. We also showed that NBSS successfully localized the auditory M100 event-related field in primary auditory cortex, measured from a subject undergoing an auditory localizer task, and suppressed cross-talk in a nearby region in the superior temporal sulcus.

Improved eigensystem realization algorithm and its application on ocean platforms

Based on the matrix mapping theory, an improved eigensystem realization algorithm (ERA), called C/ERA, is proposed in this paper. It rebuilds a Hankel matrix by replacing all elements of each anti-subdiagonal with the arithmetic average of the elements along the anti-subdiagonal, and introduces the concept of using the Frobenius norm (L2-norm) to control the iterations number after implementing the SVD algorithm by the ERA method. With the data associated with a 5-DOF mass-spring-dashpot system and jacket-type platform under impact loading, it is demonstrated that C/ERA has a better capacity of de-noising, and a higher accuracy for low-order modes, and can identify more high-order modes than the ERA method.

Availability assessment of subsea distribution systems at the architectural level

This paper presents a framework for the availability assessment of subsea distribution systems during the functional design (selection) phase. This framework, which also includes all interface elements, can be started at an early stage when the definition of the system architecture is coarse and generic failure data is available and can be refined as more information becomes available, then maintained as the system ages during the operational phase. The main objective is to present a decision tool for selecting the subsea distribution system with the highest advantage in terms of availability at a very early stage of the design. The Design Structure Matrix (DSM) mapping method is used to represent the system's components and their dependencies, which is then enriched with additional reliability data to calculate availability. A case study of an actual subsea distribution system is used to demonstrate the approach.

An Asymmetric Mapping Method for the Synthesis of Sparse Planar Arrays

This study proposes an asymmetric mapping method to design sparse planar arrays with multiple constraints including the aperture, number of elements, and minimum spacing between adjacent elements. Benefiting from two different mapping functions, which are established in this letter, this approach allows one to overcome the limitations of the existing matrix mapping method in terms of flexibility and performances. The numerical validation points out that the proposed method outperforms the matrix mapping method and modified real genetic algorithm in the design of array arrangements.

Synthesis of uniformly excited sparse planar array with multiple constraints

To obtain low peak sidelobe level of the uniformly excited sparse planar array, a modified matrix mapping method is proposed to transform the multi-constraints optimisation problem to the unconstraint. The multiple constraints include the elements quantities, the aperture sizes and the minimum inter-elements spacing. A proportion compression function is established to meet all the constraints. Thus, the infeasible solutions can be excluded from the solutions set during the optimisation process. The simulation results show the effectiveness of the proposed method.

On strongly M-unambiguous prints and Şerbǎnuţǎ's conjecture for Parikh matrices

In the combinatorial study of words, the Parikh matrix mapping was introduced by Mateescu et al. in 2001 as a natural expansion of the classical Parikh mapping. Solving the general injectivity problem of Parikh matrices remains as one of the most sought after triumph among researchers in this area of study. In this paper, we tackle this problem by extending Şerbǎnuţǎ's work regarding prints and M-unambiguity to the context of strong M-equivalence. Consequently, we obtain results on the finiteness of strongly M-unambiguous prints for any finite alphabet. Finally, a related conjecture by Şerbǎnuţǎ is conclusively addressed.

Implementasi Lean Manufacturing Car Body Studi Kasus di PT Inka (Persero)

Means of rail transport in developing countries became major commodities integrated transportation solutions, rail transport is efficient for the number of mass transit. It opens the market potential procurement of railway facilities by PT INKA, both in the domestic market or abroad. As a make to order-based manufacturing started in 2008 with a lot of project exports todeveloping countries, such as Bangladesh, Malaysia and Singapore. PT INKA export market opportunities potentially enough ahead to 2020, but delays in delivery schedule of the train is the main problem is always the case in recent years. Methods of lean manufacturing focuses on identifying and eliminating activities that do not have added value, the first step was the elaboration of a method VSM (value stream mapping) as tools to determine mapping the entire process of production, then weighted 7 waste via a questionnaire and the results of the ranking of waste are translated through the method of RCA (root cause analysis) and then do an analysis matrix mapping tools with value stream analysis tools (VALSAT) and there is a value added value ratio of 60.17% of the 84 activities of production and the total cycle time 29,905 minutes. As a tool to mitigate the improvement of waste carried out the translation of failure mode and effect analysis (FMEA) and of design improvements value stream mapping - future state map can raise the value added ratio to 67.16% consists of 74 processes and production activities 26 795 minutes total cycle time. So this research can increase the productivity and know the activities that do not add value (Non Value Added) in line car body processes and eliminating waste (Waste) as one of the causes of train delays in delivery.

Multivariate geostatistical analysis and source identification of heavy metals in the sediment of Poyang Lake in China

Heavy metals in lake sediment have become a great concern because their remobilization has frequently occurred under hydrodynamic disturbance in shallow lakes. In this study, heavy metals (Cr, Cu, Cd, Pb, and Zn) concentrations in the surface and core sediments of the largest freshwater lake in China, Poyang Lake, were investigated. Geostatistical prediction maps of heavy metals distribution in the surface sediment were completed as well as further data mining. Based on the prediction maps, the ranges of Cr, Cu, Cd, Pb, and Zn concentrations in the surface sediments of the entire lake were 96.2–175.2, 38.3–127.6, 0.2–2.3, 22.5–77.4, and 72.3–254.4mg/kg, respectively. A self-organizing map (SOM) was applied to find the inner element relation of heavy metals in the sediment cores. K-means clustering of the self-organizing map was also completed to define the Euclidian distance of heavy metals in the sediment cores. The geoaccumulation index (Igeo) for Poyang Lake indicated a varying degree of heavy metal contamination in the surface sediment, especially for Cu. The heavy metal contamination in the sediment profiles had similar pollution levels as those of surface sediment, except for Cd. Correlation matrix mapping and principal component analysis (PCA) were used to support the idea that Cr, Pb, and Zn may be mainly derived from both lithogenic and human activities, such as atmospheric and river inflow transportation, whereas Cu and Cd may be mainly contributed from anthropogenic sources, such as mining activities and fertilizer application.

Global Exponential Stability of Impulsive Fuzzy High-Order BAM Neural Networks With Continuously Distributed Delays.

This paper investigates the stability of equilibrium point and periodic solution for impulsive fuzzy high-order bidirectional associative memory neural networks with continuously distributed delays. By applying the inequality analysis technique, -matrix, and Banach contraction mapping principle and constructing some suitable Lyapunov functionals, some sufficient conditions for the uniqueness and global exponential stability of equilibrium point and global exponential stability of periodic solutions are established. In addition, three examples with numerical simulations are presented to demonstrate the feasibility and effectiveness of the theoretical results.