Array of sensors: A spatiotemporal-state-space model for target trajectory tracking

In this paper, with the objective of tracking the trajectory of multiple mobile targets, a novel spatiotemporal-state-space model is introduced for an array of sensors distributed in space. Under the wideband assumption, the proposed model incorporates the array geometry in conjunction with crucial target parameters namely (i) ranges, (ii) directions, (iii) velocities and (iv) associated Doppler effects. Computer simulation studies show some representative examples where the proposed model is utilised to track the locations of sources in space with a very high accuracy

Multi-photon time-of-flight MLEM application for the positronium imaging in J-PET

We develop a positronium imaging method for the Jagiellonian PET (J-PET) scanners based on the time-of-flight maximum likelihood expectation maximisation (TOF MLEM). The system matrix elements are calculated on-the-fly for the coincidences comprising two annihilation and one de-excitation photons that originate from the ortho-positronium (o-Ps) decay. Using the Geant4 library, a Monte Carlo simulation was conducted for four cylindrical 22Na sources of beta plus decay with diverse o-Ps mean lifetimes, placed symmetrically inside the two JPET prototypes. The estimated time differences between the annihilation and the positron emission were aggregated into histograms (one per voxel), updated by the weights of the activities reconstructed by TOF MLEM. The simulations were restricted to include only the o-Ps decays into back-to-back photons, allowing a linear fitting model to be employed for the estimation of the mean lifetime from each histogram built in the log scale. To suppress the noise, the exclusion of voxels with activity below 2-10 percent of the peak was studied. The estimated o-Ps mean lifetimes were consistent with the simulation and distributed quasi-uniformly at high MLEM iterations. The proposed positronium imaging technique can be further upgraded to include various correction factors, as well as be modified according to realistic o-Ps decay models

Multi-photon time-of-flight MLEM application for the positronium imaging in J-PET

We develop a positronium imaging method for the Jagiellonian PET (J-PET) scanners based on the time-of-flight maximum likelihood expectation maximisation (TOF MLEM). The system matrix elements are calculated on-the-fly for the coincidences comprising two annihilation and one de-excitation photons that originate from the ortho-positronium (o-Ps) decay. Using the Geant4 library, a Monte Carlo simulation was conducted for four cylindrical $^{22}$Na sources of β$^{+}$ decay with diverse o-Ps mean lifetimes, placed symmetrically inside the two JPET prototypes. The estimated time differences between the annihilation and the positron emission were aggregated into histograms (one per voxel), updated by the weights of the activities reconstructed by TOF MLEM. The simulations were restricted to include only the o-Ps decays into back-to-back photons, allowing a linear fitting model to be employed for the estimation of the mean lifetime from each histogram built in the log scale. To suppress the noise, the exclusion of voxels with activity below 2% – 10% of the peak was studied. The estimated o-Ps mean lifetimes were consistent with the simulation and distributed quasi-uniformly at high MLEM iterations. The proposed positronium imaging technique can be further upgraded to include various correction factors, as well as be modified according to realistic o-Ps decay models

Evaluation of Machine Learning Models for Breast Cancer Diagnosis Via Histogram of Oriented Gradients Method and Histopathology Images

Breast cancer is the main death rate from malignant growth worldwide and the most frequently diagnosed type of cancer in females. Machine learning systems have been developed to assist in the accurate detection of cancer. There are numerous methods for cancer detection. But histopathological images are thought to be more precise. In this study, we used the HOG features extractor to extract statistical features from histopathology images of invasive ductal carcinoma. We chose the following images at random from the histopathology images: 100, 200, 400, 1000, and 2000. These statistical features were then used to train several algorithms, including the decision tree, quadratic discriminant analysis, extra randomized trees, gradient boosting, gaussian process classifier, naive bayes, nearest centroid, multilayer perceptron, and support vector machine, to identify whether or not the images depict cancerous or noncancerous growth. The algorithms' performance was evaluated depending on the specificity, accuracy, sensitivity, precision, F1_score, and AUC. The algorithms used worked best when the number of images was set to 100. As the number of images went up, their effectiveness went down

Electrochemically Obtained Insulating and Conducting Polymers and Composites of Acrylonitrile

Electrochemically obtained polyacrylonitrile and a commercial polyacrylonitrile were heat treated to improve their conductivities. The parameters chosen for heat treatment conditions were the temperature, treatment medium (vacuum or air) and, doping agent. The conductivity of all heat treated polymers was measured. The characterization of the heat treated polymers was made by IR analysis. The composite films of polyacrylonitrile with polypyyrole and polythiophene were electrochemically prepared at different compositions. The change in the conductivity of composites was analyzed as a function of the percent composition of the insulating component. IR, DSC, TGA and SEM analyses were used to characterize the polymer composites

Matrix approach for modeling of emission from multilayer spin-polarized light-emitting diodes and lasers

Spin-polarized light sources such as the spin-polarized light-emitting diodes (spin-LEDs) and spin-polarized lasers (spin-lasers) are prospective devices in which the radiative recombination of spin-polarized carriers results in emission of circularly polarized photons. The main goal of this article is to model emitted radiation and its polarization properties from spin-LED and spin-controlled vertical-cavity surface-emitting laser (spin-VCSEL) solid-state structures. A novel approach based on 4 × 4 transfer matrix formalism is derived for modeling of the interaction of light with matter in active media of resonant multilayer anisotropic structure and enables magneto-optical effects. Quantum transitions, which result in photon emission, are described using general Jones source vectors.Web of Science166art. no. 06500

Brain Image Segmentation Based on Fuzzy Clustering

The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not properly illuminated. This paper proposes segmentation of brain tumour image of MRI images based on spatial fuzzy clustering and level set algorithm. After performance evaluation of the proposed algorithm was carried on brain tumour images, the results showed confirm its effectiveness for medical image segmentation, where the brain tumour is detected properly

Immobilization of cholesterol oxidase in a conducting copolymer of thiophene-3-yl acetic acid cholesteryl ester with pyrrole

Cholesterol oxidase has been immobilized in conducting copolymers of thiophene-3-yl acetic acid cholesteryl ester with pyrrole (CM/PPy) and polypyrrole (PPy) via electropolymerization. p-Toluene sulphonic acid was used as the supporting electrolyte. Kinetic parameters (V-max and K-m) and operational stability of enzyme electrodes were investigated. Surface morphology of the films was examined by scanning electron microscope