Combination Of Filters Research Articles

What are we really decoding? Unveiling biases in EEG-based decoding of the spatial focus of auditory attention

Objective. Spatial auditory attention decoding (Sp-AAD) refers to the task of identifying the direction of the speaker to which a person is attending in a multi-talker setting, based on the listener’s neural recordings, e.g. electroencephalography (EEG). The goal of this study is to thoroughly investigate potential biases when training such Sp-AAD decoders on EEG data, particularly eye-gaze biases and latent trial-dependent confounds, which may result in Sp-AAD models that decode eye-gaze or trial-specific fingerprints rather than spatial auditory attention. Approach. We designed a two-speaker audiovisual Sp-AAD protocol in which the spatial auditory and visual attention were enforced to be either congruent or incongruent, and we recorded EEG data from sixteen participants undergoing several trials recorded at distinct timepoints. We trained a simple linear model for Sp-AAD based on common spatial patterns filters in combination with either linear discriminant analysis (LDA) or k-means clustering, and evaluated them both across- and within-trial. Main results. We found that even a simple linear Sp-AAD model is susceptible to overfitting to confounding signal patterns such as eye-gaze and trial fingerprints (e.g. due to feature shifts across trials), resulting in artificially high decoding accuracies. Furthermore, we found that changes in the EEG signal statistics across trials deteriorate the trial generalization of the classifier, even when the latter is retrained on the test trial with an unsupervised algorithm. Significance. Collectively, our findings confirm that there exist subtle biases and confounds that can strongly interfere with the decoding of spatial auditory attention from EEG. It is expected that more complicated non-linear models based on deep neural networks, which are often used for Sp-AAD, are even more vulnerable to such biases. Future work should perform experiments and model evaluations that avoid and/or control for such biases in Sp-AAD tasks.

Utilization of filter variation and FABA addition in biogas production from palm oil liquid waste to produce electricity

Industrial waste processing is the best step to create a healthy environment. Industrial waste has the potential to be used as biogas, one of which is palm oil liquid waste. Biogas is produced from the fermentation process of palm oil liquid waste with other materials such as sawdust and boiler ash assisted by EM4 as an activiator for bacteria in fermentation. The purpose of this research was to get the best data on the electric power of the variations and replications carried out. Biogas converted to electricity with 3 variations with 3 replication. P1 is 50% biogas and 50% LPG gas filtered using a sulfur filter, P2 is 50% biogas and 50% LPG gas filtered using a boiler scale filter, and P3 is 50% biogas and 50% LPG gas filtered using a combination filter of sulfur and boiler scale. The fermentation process produces biogas of 70,519.167 cm3 at 21 days. The highest average electricity is 242 watts at a sulfur filter, 176 watts at a sulfur and boiler cale filters, and 168,776 watts at a boiler scale filter.

Research on improved black widow algorithm for medical image denoising

Improving the quality of medical images is crucial for accurate clinical diagnosis; however, medical images are often disrupted by various types of noise, posing challenges to the reliability and diagnostic accuracy of the images. This study aims to enhance the Black Widow optimization algorithm and apply it to the task of denoising medical images to improve both the quality of medical images and the accuracy of diagnostic results. By introducing Tent mapping, we refined the Black Widow optimization algorithm to better adapt to the complex features of medical images. The algorithm's denoising capabilities for various types of noise were enhanced through the combination of multiple filters, all without the need for training each time to achieve preset goals. Simulation results, based on processing a dataset containing 1588 images with Gaussian, salt-and-pepper, Poisson, and speckle noise, demonstrated a reduction in Mean Squared Error (MSE) by 0.439, an increase in Peak Signal-to-Noise Ratio (PSNR) by 4.315, an improvement in Structural Similarity Index (SSIM) by 0.132, an enhancement in Edge-to-Noise Ratio (ENL) by 0.402, and an increase in Edge Preservation Index (EPI) by 0.614. Simulation experiments verified that the proposed algorithm has a certain advantage in terms of computational efficiency. The improvement, incorporating Tent mapping and a combination of multiple filters, successfully elevated the performance of the Black Widow algorithm in medical image denoising, providing an effective solution for enhancing medical image quality and diagnostic accuracy.

HGSSA-bi LSTM: A Secure Multimodal Biometric Sensing Using Optimized Bi-Directional Long Short-Term Memory with Self-Attention

Biometric sensing technology has become a frequent element of everyday life as a result of the global demand for information security and safety legislation. In recent years, multimodal biometrics technology has become increasingly popular due to its ability to overcome the shortcomings of unimodal biometric systems. A HGSSA-Bi LSTM (Bi-directional long short-term memory) modal is presented in this paper for multimodal biometric identification. For removal of noise (unwanted) the pre-processing stage is used in the initial stage. An extended cascaded filter (ECF) is used with a combination of median and wiener filter in the pre-processing stage. Then, using the CNN model, feature extraction is utilized to extract features from the processed images. After feature extraction, fusing of feature is used with the aid of discriminant correlation analysis (DCA). Finally, the recognition process is performed by using the novel optimized hunger game search self-attention based Bi-LSTM model (HGSSA-Bi LSTM). The obtained outcome for the developed model is finally compared with other previous approaches such as CNN, RNN, DNN, and autoencoder models and the calculated performance based on accuracy 98.5%, precision 98%, F1-score 97.5%, sensitivity 98.5%, and specificity 99% accordingly.

Simplified Control Method for Unified Power Quality Conditioner (UPQC)

Unified Power Quality Conditioner (UPQC) for harmonic elimination and simultaneous compensation of voltage and current, which improves the power quality offered for other harmonic sensitive loads. UPQC consist of combined series active power filter that compensates voltage harmonics of the power supply, and shunt active power filter that compensates harmonic currents of a non-linear load. In this paper a new control algorithm for the UPQC system is optimized and simplified without transformer voltage, load and filter current measurement, so that system performance is improved. The proposed control technique has been evaluated and tested under dynamical and steady state load conditions using PSIM software. The laboratory prototype experimental results for shunt active filter part are given.

An evaluation of properly operated NSF/ANSI-53 Pb certified drinking water filters in Benton Harbor, MI.

Communities across the United States and particularly in the Midwest continue to grapple with the complications associated with aging infrastructure. This includes the presence of lead (Pb)-bearing plumbing components such as lead service lines, downstream galvanized iron pipes, and Pb/tin solder. The community of Benton Harbor, MI, experienced six Pb action level exceedances between 2018 and 2021, leading to increasing community concern and a request from the state of Michigan for the US Environmental Protection Agency involvement. Between 9 November and 17 December 2021, US EPA Region 5 and Office of Research and Development, along with the state of Michigan, conducted a water filter efficacy and Pb-nanoparticulate (<100 nm) study to evaluate the performance of NSF/ANSI-53 Pb-certified drinking water filters and the presence of nanoparticulate. In this study, a total of 199 properly installed and operated drinking water filters (combination of faucet mounted and pitcher) were tested in their residential locations. One hundred percent of the water filters were found to perform to the standard to which they were certified, with filtered drinking water Pb concentrations below 5 ppb (maximum observed was 2.5 ppb). In addition, Pb particulate was identified; however, discrete Pb-containing nanoparticles were not widely found or identified.

Expanding the genetic spectrum of mitochondrial diseases in Tunisia: novel variants revealed by whole-exome sequencing.

Introduction: Inherited mitochondrial diseases are the most common group of metabolic disorders caused by a defect in oxidative phosphorylation. They are characterized by a wide clinical and genetic spectrum and can manifest at any age. In this study, we established novel phenotype-genotype correlations between the clinical and molecular features of a cohort of Tunisian patients with mitochondrial diseases. Materials and methods: Whole-exome sequencing was performed on five Tunisian patients with suspected mitochondrial diseases. Then, a combination of filtering and bioinformatics prediction tools was utilized to assess the pathogenicity of genetic variations. Sanger sequencing was subsequently performed to confirm the presence of potential deleterious variants in the patients and verify their segregation within families. Structural modeling was conducted to study the effect of novel variants on the protein structure. Results: We identified two novel homozygous variants in NDUFAF5 (c.827G>C; p.Arg276Pro) and FASTKD2 (c.496_497del; p.Leu166GlufsTer2) associated with a severe clinical form of Leigh and Leigh-like syndromes, respectively. Our results further disclosed two variants unreported in North Africa, in GFM2 (c.569G>A; p.Arg190Gln) and FOXRED1 (c.1261G>A; p.Val421Met) genes, and we described the first case of fumaric aciduria in a Tunisian patient harboring the c.1358T>C; p.Leu453Pro FH variant. Conclusion: Our study expands the mutational and phenotypic spectrum of mitochondrial diseases in Tunisia and highlights the importance of next-generation sequencing to decipher the pathomolecular mechanisms responsible for these disorders in an admixed population.

Synchronously tunable combined four-channel ferrite filter

The original design of the synchronously tunable combined four-channel ferrite filter is given. It is a functional unit consisting of four microwave systems of ferrite filters with coupling loops (one such microwave system in each channel) and a common magnetic system for these filters, which ensures their synchronous tuning in the frequency range of 2-4 GHz. The structural solution of the microwave system in the form of a module allows one to obtain both a bandpass ferrite filter and a band-reject ferrite filter. The results of experimental research are provided. They showed that such a four-channel controllable ferrite filter has not only improved design and technological indicators but also a high decoupling between channels. It can be successfully used not only in measuring equipment but also in modern multichannel microwave communication equipment and radar.

Description of the State primary standard for length, velocity, and acceleration units at the oscillating movement of solid body NDETU AUV-04-2019

The article describes the state of metrological assurance in Ukraine, the field of vibration measurements, the composition of the State primary standard for length, velocity, and acceleration at oscillating movement NDETU AUV-04-2019, and its general characteristics and functioning principles. And attention is paid to the key comparisons in which this standard had taken part. The ways of standard upgrading are considered.

Abstract B035: Developing the UValidate platform to measure DNA damage and repair capacity in isogenic donor-derived skin keratinocytes, fibroblasts and melanocyte cell-lines with different Fitzpatrick phototypes

Abstract DNA damage associated with ultraviolet (UV) radiation exposure causes accelerated skin aging and cancer-initiating mutations. Over-the-counter UVA and UVB filters are required in all sunscreens, but transdermal absorption of these compounds have been reported to impair development and reproduction and metabolize into carcinogenic/mutagenic chemical intermediates. To assess the effects of sunscreen active ingredients on UVR-induced DNA damage and repair, we developed a novel high throughput (HTP) screening platform, UValidate, employing mixed populations of isogenic skin cells, exposed to single or combinations of UV filters in the presence of UVB and UVA. UValidate contains a patented LED UVR DNA damage induction system (LUDIS:V3), facilitating programmable precise induction of DNA damage and repair at multiple time points and replicates, using a 96-well configuration capable of simultaneous delivering UVA and UVB. LUDIS:V3 optimization experiments surprisingly revealed that, unlike keratinocytes, skin fibroblasts only repaired UVA DNA damage in conditioned media. We then tested sunscreen active ingredient combinations for their capacity to alter DNA repair and found that: 1) Some sunscreen ingredients, including dioxybenzone, induce a significant increase in DNA damage above endogenous levels. 2) Fibroblasts and keratinocytes respond differently to the treatment protocols. 3) Some sunscreen active compounds contribute to reduction of UVA-induced DNA damage. 4) No sunscreen completely inhibits all UVA DNA damage. We are currently employing the LUDIS:V3 system with HTP comet assays to compare DNA damage and DNA repair capacities, +/- sunscreen active ingredients, of six isogenic sets of primary epidermal keratinocytes (NHEK), melanocytes (NHEM), and fibroblasts (NHDF)` with different Fitzpatrick phototypes I-VI, representative of the diverse American population. These cells were isolated from donor skin samples, and further purified to establish banks of isogenic NHEK, NHEM, and NHDF cell lines. UVA exposure with the LUDIS:V3 and comet assays revealed higher levels of DNA damage in NHEK and NHDF, compared to NHEM, likely due to the UVR-protective effects of melanin in NHEM. Consistently, NHEK with phototype V (from darkly pigmented skin with higher melanin levels) exhibit significantly less UVA-induced DNA damage compared with phototype II NHEK. To create cellular models of dermal disease for DNA repair assays, we have successfully knocked out XPA in multiple NHDF cell lines with different phototypes using a CRISPR-Cas9 KO strategy, as confirmed by immunoblot and NGS sequence analyses. These and other engineered DNA repair-deficient skin cells will be assayed as single or mixed cell-type 2D cultures, with fluorescent labeling allowing for identification of subpopulations in comet and alkaline diffusion assays. This technology addresses the need for better platforms for rapid genotoxicity testing of safer and more effective chemical UV filters to prevent cutaneous carcinogenesis in diverse populations. Citation Format: Dean S. Rosenthal, Elijah Finn, Devin Teehan, Nusrat Islam, Veerupaxagouda Patil, Bonnie Carney, Scott S. Rosenthal, Lucia Dussan, Cynthia M. Simbulan-Rosenthal, Peter Sykora. Developing the UValidate platform to measure DNA damage and repair capacity in isogenic donor-derived skin keratinocytes, fibroblasts and melanocyte cell-lines with different Fitzpatrick phototypes [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr B035.

Application research of interior space design elements based on image processing

In order to quantitatively analyze the application performance of elements in interior space design, a detection method of texture visual features of elements distribution images in interior space design based on image processing and texture edge contour features detection is proposed. A multi-resolution visual information collection model for detecting the texture visual characteristics of element distribution images in indoor space design is constructed, and a visual characteristic identification model for element application configuration in indoor space design is established. Multi-texture grid block area combination design method is adopted to realize the fusion of element application configuration visual images in indoor space design. Through the edge feature detection method of texture grid area, Establish a visual parameter identification model of element application configuration in interior space design, extract the visual information feature quantity of element application configuration in interior space design, adopt Harris corner feature matching method, realize distributed detection of texture edge contour features of element application configuration visual features in interior space design, and fuse detection of high-resolution texture information through combined filtering and collaborative filtering. The collection and optimization of visual features of element application configuration in interior space design are realized, and the distributed detection algorithm of texture edge contour features is adopted to improve the convergence level of detection of texture visual features of element distribution images in interior space design, and the application of elements in interior space design based on image processing is realized. The simulation results show that this method has good resolution and strong visual expression ability in extracting the texture visual features of element distribution images in interior space design, which improves the quantitative analysis ability of elements in interior space design.

Variability and relationships between the size, composition and optical properties of suspended particulate matter in the coastal waters of western Spitsbergen, assessed through measurements of size-fractionated seawater samples

Measurements of inherent optical properties (IOPs) and characteristics of concentration and composition of suspended particles were made on original and size-fractionated surface water samples from Arctic fjords and coastal waters of western Spitsbergen in the Svalbard archipelago, in the summer months of 2021 and 2022. Optical measurements included the spectral scattering coefficient of particles, and spectral absorption coefficients of particles as well as depigmented (non-algal) particles and phytoplankton. Assemblages of suspended particles were characterised by measuring the mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate inorganic matter (PIM), and phytoplankton pigments including chlorophyll a (Chla). All measurements were performed on original (unfiltered) seawater and on size-fractionated samples obtained by filtration using a combination of nylon meshes and membrane filters. This allowed us to determine the contribution of the fractions of very small (VS), small (S) and combined medium and large particles (ML) to the total SPM and Chla, as well as to the total scattering and absorption coefficients. The obtained results: (i) indirectly indicate a clear variability in particle size distributions occurring in the studied marine environment (e.g., the contribution of ML size fraction to SPM (the ratio SPMML/SPM) varied between 0.10 and 0.52); (ii) indicate noticeable differences in composition between size fractions (e.g., the POM/SPM ratio was on average 0.21 for the S fraction, and 0.34 and 0.32 for the VS and ML fractions, respectively); (iii) in most cases indicate that the fraction S had the largest contribution to all analysed spectral optical coefficients, followed by the VS and ML fractions (the average contributions of the S fraction to scattering coefficient of particles and absorption coefficient of particles or depigmented (non-algal) particles were above 0.6 in the entire analysed spectral ranges); (iv) allowed for the identification of statistical relationships between selected characteristics describing changes in particle size and variability of particle IOPs (e.g., we observed statistical relations between SPMML/SPM and the spectral slope of scattering coefficient by particles, as well as SPM-specific coefficients of scattering by particles).

Extraction of silica from sugarcane bagasse ash and its utilization in zeolite 4A synthesis for CO2 adsorption.

Sugarcane bagasse ash (SCBA) is a solid waste containing a high amount of silica (SiO2) and is suitable to utilize as a silica source for synthesizing zeolite NaA. SCBA is typically calcined at high temperatures before silica extraction. The method is not environmentally friendly because it consumes energy and produces CO2. This work demonstrates an alternative extraction method of SiO2 from SCBA by treating it with hydrochloric (HCl) and sodium hydroxide (NaOH) solution. The obtained mixture was separated by paper filter No. 1 (P) and a combination of paper filter and syringe filter (PS). The solution was neutralized by HCl solution, producing silica (SiO2-P and SiO2-PS) with a purity of 98 wt%. Both SiO2 samples and SCBA were utilized to synthesize zeolite NaA for CO2 adsorption. The CO2 adsorption capacities of NaA-P and NaA-PS were 4.30 and 4.10 mmol gadsorbent -1, in the same range as commercial NaA. The capacity is influenced by the total basicity of zeolite. The CO2 adsorption behavior of all samples correlates well with the Toth model. The CO2 adsorption kinetics agrees well with the pseudo-second-order kinetic model. Overall, this work shows the successful extraction of silica via using a direct NaOH solution, yielding high-purity silica sufficient for synthesizing zeolite NaA, a promising adsorbent of CO2.

A New Hybrid Supervisory Control System for Cabinet-Type Firebox Furnaces

In this paper, an intelligent hybrid Industrial Control System (ICS) and a Supervisory Control System (SCS) are proposed to improve the efficiency, safety, availability, and control capabilities of industrial furnaces. The main components of ICS are process control systems and advanced control systems that consist of overheating protection and load control. New soft sensors are designed as a combination of Laguerre filters and an artificial neural network to estimate the surface temperature of the furnace’s tubes, which allows the protection system to adjust fuel flow rate via overriding commands. Model-based fault detection systems are developed to detect faults in the combustion system and fouling in the furnace tubes and prepare features for the supervisory system. The supervisory control system is responsible for interfering between different components, evaluating the situation, and decision making based on the unit status and process conditions. An intuitionistic fuzzy inference system is employed as the core of the supervisory controller to tolerate disturbance and faults by switching the control modes. Test studies using experimental data of the furnace indicate the capability of the proposed monitoring and control system to operate in various loading situations and recover the system from abnormal conditions. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In petrochemical industries, several reports have been issued about the load reduction of fired-heater furnaces imposed by combustion system faults and emergency shutdowns to carry out un-planned repairs due to fouling and wax-formation in tubes. Different activities such as detecting abnormal conditions, identifying faults, and enforcing corrective action can be performed by operators through manual actions. This paper is focused on designing a new supervisory control system (SCS) to be able to recover the fired heater furnace from abnormal conditions and keep running the plant. The SCS evaluates the condition of the unit by acquiring information from main variables, sensors, actuators, operating status of components and utilities, and operator commands. By identifying the root cause of faults, SCS makes decision on recognizing hazard degree, raising alarms, and applying automatic corrective actions.

An investigation of a hybrid solar-mineral disinfection technique using Zeolite and Dead Sea clay

Effluents from water treatment plants (WTP) can often contain a complex mixture of residual micro-contaminants and organisms, not removed during wastewater treatment. A combined trickling filter, activated sludge treatment, ozonation, membrane filtration, and suspended biofilm reactors have been shown to reduce these contaminants in waste effluent but at high capita cost. This study examined an inexpensive method of purifying water, which combines solar water disinfection with natural mineral clays (SOMIN-DIS). The study involved the addition of two types of mineral clays, Zeolite and Dead Sea minerals, to containers of polluted wastewater, at varying concentrations. The containers were then subjected to different durations of sunlight exposure. Then, samples were taken from all of the containers to quantify the overall numbers of Total Coliform, Pseudomonas aeruginosa (P.aeruginosa), and Escherichia coli (E.coli), utilizing the IDEXX system. The findings indicated that incorporating Dead Sea clay and Zeolite into SODIS-treated wastewater decreased the overall number of harmful microorganisms and shortened the disinfection duration, as compared to using natural minerals and solar water disinfection (SODIS) independently. Additionally, the study determined that the most effective concentration of Dead Sea minerals, resulting in the least amounts of harmful microorganisms and shortest purification duration, was 0.001 g/ml. In contrast, the optimum concentration of Zeolite was 0.002 g/ml. In general, the addition of Dead Sea and Zeolite minerals to the wastewater increased the inactivation of bacteria under SODIS from 40% to 65%.

Algorithm for extracting contours of agricultural crops images

Abstract. Currently, identification of crop diseases and their prevention is one of the main problems in the field of agriculture. Conventional visual inspection is a time and money consuming process for farms. Therefore, images taken by unmanned aerial devices or satellites are used to assess the condition of crops, control them and identify diseases. In particular, when identifying crop diseases, it is necessary to first solve the problem of automatic recognition of their type through the image of crops. Usually contour separation algorithms are widely used in the segmentation of objects in the image. This work is aimed at solving the problem of separating the contour of the object, in which algorithms are formed based on Canny, Sobel and Robinson filters, which are considered to be popular and classical methods of contour separation, and their various combinations. In the computational experiments, a set of contour images, whose contours were separated by an expert, was used. Evaluation was performed by comparing the image obtained by applying the combination of filters to the original image and the corresponding contour image pixels separated by an expert. The proposed approach has been tested on a set of plant leaf images and shown to be effective.

Design of multi-ensemble hybrid filtering approach for removal of heart sound from lung auscultations

Successful lung sound extraction from lung auscultations requires precise filters. Lung auscultations include heart and lung sounds. Therefore, the filter design should identify heart sound characteristics. These include periodicity, pitch, frequency, amplitude, etc. Auscultation acquisition sensors are inefficient, so these signals have noise. To get a clean auscultation signal, ambient noise, periodic noise, DC offsets, baseline errors, harmonic noise, etc. must be addressed separately. Data cleaning must maintain a high peak-signal-to-noise ratio without removing desirable signal information. Heart sound patterns are extracted from input auscultations using filter banks on these signals. After heart sound extraction, the output sound sample should only contain lung sounds. Still, heart sound harmonics corrupt output lung sound due to similarities between heart and lung sound patterns. This lowers lung-sound extraction quality and automatic lung-based disease identification efficiency levels. This article proposes a 2-level multi-ensemble filtering model with 43 filters that analyze 15 other parameters to denoise and extract lung sound from lung auscultations to eliminate these drawbacks. Combining LMS, NLMS, and RLS is used for denoising process. For heart sound identification, an ensemble of Savitzky-Golay, FIR equiripple, Butterworth, Chebyshev, Elliptic, and wavelet filters is used. This selective combination of filters improves PSNR by 20% compared to sole filter performance, while signal entropy, crest factor, root mean squared error, kurtosis, etc. also improves for different scenarios.

The JWST Resolved Stellar Populations Early Release Science Program. IV. The Star Formation History of the Local Group Galaxy WLM

We present the first star formation history (SFH) and age–metallicity relation (AMR) derived from resolved stellar populations imaged with the JWST NIRCam instrument. The target is the Local Group star-forming galaxy WLM at 970 kpc. The depth of the color–magnitude diagram (CMD) reaches below the oldest main sequence turnoff with a signal-to-noise ratio = 10 at M F090W = + 4.6 mag. This is the deepest CMD for any galaxy that is not a satellite of the Milky Way. We use Hubble Space Telescope (HST) optical imaging that overlaps with the NIRCam observations to directly evaluate the SFHs derived based on data from the two great observatories. The JWST and HST-based SFHs are in excellent agreement. We use the metallicity distribution function measured from stellar spectra to confirm the trends in the AMRs based on the JWST data. Together, these results confirm the efficacy of recovering an SFH and AMR with the NIRCam F090W−F150W filter combination, and validate the sensitivity and accuracy of stellar evolution libraries in the near-infrared relative to the optical for SFH recovery work. From the JWST data, WLM shows an early onset to star formation, followed by an extended pause post-reionization before star formation reignites, which is qualitatively similar to what has been observed in the isolated galaxies Leo A and Aquarius. Quantitatively, 15% of the stellar mass formed in the first Gyr, while only 10% formed over the next ∼5 Gyr. The stellar mass then rapidly doubled in ∼2.5 Gyr, followed by constant star formation over the last ∼5 Gyr.

Analysis on Improved Gaussian-Wiener filtering technique and GLCM based Feature Extraction for Breast Cancer Diagnosis

Breast cancer is become the most prevailing and fastest growing disease. In medical imaging, the use of machine learning and deep learning algorithms is essential. Classification of the tumor to predict the chemotherapy response for survival is trivial. In this paper, an innovative Gaussian-Wiener filter combination is used for de-noising the MRI images. These pre-processed images with good image quality are selected for tumor detection. On the basis of these pre-processed outputs, important features are extracted to determine the spatial relationship between the image pixels which results in better texture analysis for the tumor images. Analysis is made on the ISPY-2 trial breast MRI database. Results are analyzed which gives better image quality performance for MRI images. The filters and feature extraction method analyzed is used further in the segmentation and optimization process for breast detection and diagnosis to get the best accuracy of nearly 100%. The results also show better texture analysis for extracting features using GLCM based method. Furthermore, the MRI images for these methods used are explained for better performance in the process of breast cancer detection and diagnosis.

Thermoluminescence kinetics in beta-irradiated novel ZnGa2O4:Eu3+ phosphor produced via gel combustion synthesis

Eu3+ doped ZnGa2O4 phosphors with varying dopant concentrations were successfully synthesized using the combustion technique. X-ray diffraction analysis confirmed the consistency of both undoped and Eu3+ doped ZnGa2O4 samples with PDF#38–1240 card structure. The investigation of thermoluminescence (TL) characteristics involved studying TL glow curves in Eu3+ doped ZnGa2O4 samples with different dopant concentrations, employing various optical detection filter combinations. Among these, ZnGa2O4: 2%Eu3+ and the IRSL-TL wide blue band (wbb) proved to be the optimal sample and ideal detection filter pairing for identifying TL features. Following preheating experiments, the TL maximum was observed at around 190 °C, with a heating rate of 2 °Cs−1. The dose-response experiment for ZnGa2O4:2%Eu3+ exhibited satisfactory linearity, with a coefficient of b = 0.988 and an R2 value of 0.989 for doses up to 100 Gy. Moreover, for the dose range of 200–500 Gy, a sublinear relationship was maintained, with a coefficient of b = 0.31 and an R2 value of 0.988. Hoogenstraaten's method, along with the initial rise method and the Tm-Tstop experiment, was also employed in conjunction with a glow curve fitting package. This comprehensive approach facilitated the determination of the number of peaks, trap structure, and kinetic parameters within the thermoluminescence glow curve. Glow curve deconvolution using specialized software revealed the presence of five well-isolated and overlapping TL glow peaks, achieving a figure of merit (FOM) value of 1.39.