dB Values Research Articles

Inverse design of an ultra-compact dual-band wavelength demultiplexing power splitter with detailed analysis of hyperparameters.

Inverse design has been widely studied as an efficient method to reduce footprint and improve performance for integrated silicon photonic (SiP) devices. In this study, we have used inverse design to develop a series of ultra-compact dual-band wavelength demultiplexing power splitters (WDPSs) that can simultaneously perform both wavelength demultiplexing and 1:1 optical power splitting. These WDPSs could facilitate the potential coexistence of dual-band passive optical networks (PONs). The design is performed on a standard silicon-on-insulator (SOI) platform using, what we believe to be, a novel two-step direct binary search (TS-DBS) method and the impact of different hyperparameters related to the physical structure and the optimization algorithm is analyzed in detail. Our inverse-designed WDPS with a minimum feature size of 130 nm achieves a 12.77-times reduction in footprint and a slight increase in performance compared with the forward-designed WDPS. We utilize the optimal combination of hyperparameters to design another WDPS with a minimum feature size reduced to 65 nm, which achieves ultra-low insertion losses of 0.36 dB and 0.37 dB and crosstalk values of -19.91 dB and -17.02 dB at wavelength channels of 1310 nm and 1550 nm, respectively. To the best of our knowledge, the hyperparameters of optimization-based inverse design are systematically discussed for the first time. Our work demonstrates that appropriate setting of hyperparameters greatly improves device performance, throwing light on the manipulation of hyperparameters for future inverse design.

Mango Area Mapping Using Very High-Resolution Satellite Data in Major Blocks of Krishnagiri District, Tamil Nadu, India

A research study was carried out for mapping mango plantation from LISS IV data in the major blocks of Krishnagiri district, Tamil Nadu where there is substantial production of Mango. A very high-resolution satellite data namely LISS IV was acquired and processed with GIS tools. Ground truth data gathered during the survey were utilized to identify significant dB values for mango plantations, which were then used to classify the mango pixels in the study region using supervised classification technique. The Mango area in major blocks of Krishnagiri district was found to be 9077.9 ha during the year 2023. Accuracy assessment and cross validation was done using confusion matrix with the ground truth points collected. The classification resulted with an overall accuracy of 91.2 per cent with a kappa score of 0.62.

Recursive identification of the time-varying frequency parameters of a space solar power satellite using a robust subspace tracking method based on the variable forgetting factor

Considering changes in the structural configuration caused by the rotation of solar panel arrays in space solar power satellites, this study proposes an improved robust recursive subspace tracking algorithm to identify the time-varying modal frequency parameters of the system. In this algorithm, variable forgetting factor and robust weight coefficient are involved to improve the tracking adaptability of time-varying system and decrease the influence of impulsive disturbance. Then, the time-varying pseudo modal frequency parameters are identified using the recursive projection subspace tracking. In the numerical simulations, the influence of the different rotation speeds of the solar panel arrays on the frequency identification results is studied. The computational results for the different rotation speeds reveal that the tracking performance of the proposed algorithm is better than that of the original method for time-varying system. Under the influence of impulsive disturbances, the relative values of the average relative error under the proposed algorithm are approximately 65.9–75.2% less than those under the original algorithm. Additionally, the results reveal that when the rotation speed of the solar panel arrays is time-varying, the proposed algorithm achieves a better tracking performance than the conventional recursive methods by the adjustment of the variable forgetting factor. When the signal-to-noise ratio is 15 dB, the absolute and relative values of the average relative error under the proposed algorithm are less by approximately 6.4% and 64.8%, respectively, under the two reference methods with a fixed forgetting factor.

A prediction error based reversible data hiding scheme in encrypted image using block marking and cover image pre-processing.

A drastic change in communication is happening with digitization. Technological advancements will escalate its pace further. The human health care systems have improved with technology, remodeling the traditional way of treatments. There has been a peak increase in the rate of telehealth and e-health care services during the coronavirus disease 2019 (COVID-19) pandemic. These implications make reversible data hiding (RDH) a hot topic in research, especially for medical image transmission. Recovering the transmitted medical image (MI) at the receiver side is challenging, as an incorrect MI can lead to the wrong diagnosis. Hence, in this paper, we propose a MSB prediction error-based RDH scheme in an encrypted image with high embedding capacity, which recovers the original image with a peak signal-to-noise ratio (PSNR) of dB and structural similarity index (SSIM) value of 1. We scan the MI from the first pixel on the top left corner using the snake scan approach in dual modes: i) performing a rightward direction scan and ii) performing a downward direction scan to identify the best optimal embedding rate for an image. Banking upon the prediction error strategy, multiple MSBs are utilized for embedding the encrypted PHR data. The experimental studies on test images project a high embedding rate with more than 3 bpp for 16-bit high-quality DICOM images and more than 1 bpp for most natural images. The outcomes are much more promising compared to other similar state-of-the-art RDH methods.

Influence of iron content in Fe-based amorphous alloy catalysts on degradation of azo dyes by fenton-like process

Degradation of organic pollutants in industrial wastewater has become one of the biggest problems that are threatening the environment, and correspondingly it is a priority for scientists to find a solution. In this work, we study the effect of the iron content in Fe-based amorphous ribbon catalysts (Fe78+xSi9B13-x, x = 0, 1 and 2) in degradation of Direct Blue 6 (DB 6) azo dye by Fenton-like process. We evaluated the catalytic efficiency by changing experimental conditions with the aim to optimize the degradation performance. The amorphous Fe80Si9B11 ribbon showed the highest catalytic activity with its ability to degrade DB 6 by 94.65% within 15 min Fe80Si9B11 ribbon provides more reactive sites than what generates the most hydroxyl radicals (. OH) and thus increases the degradation reaction. Degradation efficiency can be improved by increasing the reaction temperature and ribbons dosage, a correct amount of H2O2 but decreases with increasing initial pH value and concentration of DB 6. Fe80Si9B11 amorphous ribbons can be reused up to 12 times in optimal conditions, which confirms a good reusability. The excellent performance in catalytic activity and reusability of Fe-based amorphous alloy catalysts will contribute to wastewater treatment.

Quantifying the Rock Damage Intensity Controlled by Mineral Compositions: Insights from Fractal Analyses

Since each rock type represents different deformation characteristics, prediction of the damage beforehand is one of the most fundamental problems of industrial activities and rock engineering studies. Previous studies have predicted the stress–strain behaviors preceding rock failure; however, quantitative analyses of the progressive damage in different rocks under stress have not been accurately presented. This study aims to quantify pre-failure rock damage by investigating the stress-induced microscale cracking process in three different rock types, including diabase, ignimbrite, and marble, representing strong, medium-hard, and weak rock types, respectively. We demonstrate crack intensity at critical stress levels where cracking initiates (σci), propagates (σcd), and where failure occurs (σpeak) based on scanning electron microscope (SEM) images. Furthermore, the progression of rock damage was quantified for each rock type through the fractal analyses of crack patterns on these images. Our results show that the patterns in diabase have the highest fractal dimensions (DB) for all three stress levels. While marble produces the lowest DB value up to σci stress level, it presents greater DB values than those of ignimbrite, starting from the σcd level. This is because rock damage in ignimbrite is controlled by the groundmass, proceeding from such stress level. Rock texture controls the rock stiffness and, hence, the DB values of cracking. The mineral composition is effective on the rock strength, but the textural pattern of the minerals has a first-order control on the rock deformation behavior. Overall, our results provide a better understanding of progressive damage in different rock types, which is crucial in the design of engineering structures.

RBWCI: Robust and Blind Watermarking Framework for Cultural Images

Heritage multimedia, which comprises images, audio, and videos, are precious artifacts of a region. In addition to enabling a better understanding of earlier generations, heritage media provides information about their creative approach, style of living, and diversity of historical and archaeological ideologies. Heritage is an important resource that boosts the local economy, generates sustainable communities, and improves tourism and business sectors. Once heritage images are dissipated to consumers, they may be transmitted through wire/wireless systems, where the data may be accessed by both authorized and unauthorized consumers. With the rapid advancement of technology and 5G networks, establishing an approach that protects cultural heritage media from unauthorized consumers is necessary. This study presents a robust and blind watermarking-framework for cultural images (RBWCI) utilizing the discrete cosine transform domain for ownership verification and copyright protection. The embedding scenario of our technique relies on the difference between coefficients obtained from the two channels of the YCbCr color model. The watermark bit is embedded by taking the difference between two preselected mid-frequency coefficients (Cb-Cr). Moreover, chaotic and deoxyribonucleic acid encryption are employed to ensure double-layer watermark security. The proposed algorithm demonstrates a peak signal-to-noise ratio between 42-43 dB and structural similarity index metric value of approximately 1 for different test images when not under attack. The robustness of the RBWCI was revealed by comparing it with various state-of-the-art schemes, making it suitable for different consumer applications.

Evaluation of Hearing and Auditory Pathways in Fabry Disease Patients

Background Hearing and the auditory pathway are affected in Fabry diseases (FD). There is limited data on hearing and auditory pathways in this population. Therefore, we aimed to investigate auditory functions and auditory pathways using auditory brainstem responses (ABR), otoacoustic distortion emission (DPOAE), pure tone audiometry (PTA), and tympanometry in patients with FD and to compare these results with those of healthy individuals.
 Material and Methods This study included 16 patients with FD (F/M: 8/8, age: 33.5±15.4 years) and 16 healthy controls (F/M: 5/11, age: 33.6±6.3 years). Hearing functions and auditory pathways were assessed with ABR, DPOAE, PTA, and tympanometry.
 Results According to the results of PTA, conductive hearing loss was detected in 4 (25%) of the patients with FD. When the 500-4,000 Hz frequencies were assessed, the bone pathway hearing threshold in both ears was significantly higher in the patients with FD than in the control group (p=0.014 and p=0.014, respectively). When we compared the DPOAE measurements of the patients with FD and the control groups, the dB value measured at 2.8 kHz was significantly lower in the patient group than in the control group (p=0.018). When we compared the ABR measurements, the right ear's 3-5 interpeak latency at 60 dB was significantly lower in the patient with FD than in the control group (1.8±0.3 ms vs 2±0.2 ms, p=0.033).
 Conclusions We found that the hearing loss rate and hearing threshold were statistically significantly higher in FD patients than in the control group. Hearing screening should be systematically performed in these patients.

Nutritional, physical, and sensory properties of fish crackers produced from the head of catfish (Clarias gariepinus)

Catfish heads are a common byproduct of large-scale catfish processing, known for their rich nutritional content. However, despite their potential to be processed into food products such as crackers, catfish heads remain relatively underused. This study aimed to produce crackers made from catfish heads and evaluate the nutritional, physical, and sensory properties of the crackers. After the preparation of catfish head flour (CHF) and catfish head crackers (CHC), the crackers were analysed with various ratios of tapioca flour (TF) to CHF: CHC 0 (100: 0), CHC 1 (90:10), CHC 2 (80:20), CHC 3 (70:30), and CHC 4 (60:40). The examination of the nutritional, physical, and sensory properties showed that the CHF had high protein (30.89% db), calcium (21.83% db), and phosphorus (10.26% db) values, with the CHC 3 having higher protein, calcium, and phosphorus contents than the control group (p<0.05). The CHC 3 also exhibited good colours and textures, in addition to its superiority in all sensory attributes. In light of this analysis, the CHC 3 was indeed the best cracker processing. This study indicates that catfish heads as food ingredients can serve as nutritious crackers preferred by the panelists.

Heterogeneous asymmetric double-layer composite with ultra-low reflection for electromagnetic shielding

In this work, a heterogeneous asymmetric double-layer composite (HADC) consisting of an absorbing layer Fe3O4@reduced graphene oxide (rGO)/waterborne polyurethane (WPU) and a reflecting layer Ni-Co-P@FC (Ni-Co-P coated filter cotton (FC)/PANI@PDMS (polyaniline (PANI) mixed in polydimethylsiloxane (PDMS)) was designed and prepared using a simple chemical plating method and stirred foaming process. In which, the upper Fe3O4@rGO/WPU foam utilizes the combined effects of the porous internal structure and Fe3O4@rGO to achieve superior impedance matching and electromagnetic waves (EMW) absorption performance, while the Ni-Co-P dense conductive network formed by chemical plating process within the bottom layer ensures superior electromagnetic shielding effectiveness (EMI SE). The advantage of heterogeneous asymmetric structure combined with the reasonable distribution of electromagnetic two-component fillers and under the effects of multiple electromagnetic loss mechanisms, the composite structure perfectly overcomes the contradiction between efficient shielding and high absorption. Ultimately, the HADC exhibits a high EMI SE of 36.6 dB and absorption coefficients (A) value of 0.94, showing ultra-low reflection efficiency, which is better than most current shielding materials moreover, the preparation process is simple, with the characteristics of low cost and environmentally friendly. Therefore, this work provides a simple and feasible new idea for the preparation of lightweight, efficient and ultra-low reflection EMI shielding composite structures, which broadens the application of porous structures in the field of electromagnetic shielding.

OPTIMIZATION ASSISTED AUTOREGRESSIVE METHOD WITH DEEP CONVOLUTIONAL NEURAL NETWORK-BASED ENTROPY FILTER FOR IMAGE DEMOSAICING

The natural scenes are captured by digital cameras that adopt a single charged-coupled device (CCD) or Complementary Metal Oxide Semiconductor (CMOS) sensor with a Color Filter Array (CFA). To reconstruct a full color image from the mosaiced CFA image, the missing components of color are recovered by a technique called color demosaicing. This research work introduces Deep Convolution Neural Network (DCNN)-based optimization assisted autoregressive method for image demosaicing. Here, the proposed optimization algorithm, termed Adaptive Autoregressive Water Wave Optimization algorithm (Adaptive Autoregressive-WWO), that is formed by combining Conditional autoregressive value at risk (CAViaR) model and Water Wave Optimization algorithm (WWO). Fusion process is carried out for residual images to generate the final demosaiced image based on entropy measure. Here, the output generated from DCNN is the first residual image. The LPA-ICI filter utilizes the optimization algorithm that generated second order polynomial coefficients to produce the second residual output image. Moreover, this proposed method is evaluated for its performance using metrics, such as Peak signal-to-noise ratio (PSNR) and Second Derivative like Measurement (SDME) and attained the highest PSNR values of 40.379dB and highest SDME values of 50.675dB.

Effect Of Seed Soaking Time In Kno3 On Germination, Vegetative Morphology, And Results Of Bambara Chicken (Vigna Subterranea (L.) Verdcourt)

The The bambara groundnut has the potential to continue to be developed, but the obstacle faced is the very limited availability of bambara groundnut seeds. This is because there are no varieties from the results of breeding that are released and the low quality of the seeds. Low seed quality is caused by slow germination and results in the seed growth process being non-unison, this is influenced by seed dormancy. The purpose of this study was to determine the effect of soaking time in KNO3 on germination, vegetative morphology, and crop yield in the field by measuring seed viability and vigor, vegetative morphology and yield. The research was carried out for 4 months, from June-October 2022 which took place at the Agrotechnology Laboratory of the Muhammadiyah University of Malang and Dadaprejo Land, Batu City. The study was conducted using a simple Completely Randomized Block Design (RKLT) consisting of 10 treatments, and was repeated 3 times. The observed variables included moisture content, DB, PTM, IV, KCT, T50, plant height, number of leaves, leaf shape, leaf color, stem color, pod color, pod shape, number of pods, pod dry weight, number of seeds, dry weight seeds, yield potential, and weight of 1000 seeds. The results showed that the long soaking of seeds in KNO3 did not affect their vegetative morphology. Soaking time of seeds in KNO3 had no significant effect on DB and PTM values, but had a very significant effect on IV values, the number of leaves in the vegetative and generative phases. And it has a significant effect on the height of the KCT, T50, and plant height in the vegetative phase. As for the yield variable, the results showed no significant effect. Soaking time in KNO3 only affected germination, plant height, and number of bambara groundnut leaves.

Long-term impact of organic and conventional farming on soil physical properties under rice (Oryza sativa)-wheat (Triticum aestivum) cropping system in north-western Indo-Gangetic plains

Long-term (13 years) impact of organic and conventional farming on soil physical properties was evaluated under a rice (Oryza sativa L.) – wheat (Triticum aestivum L.) cropping system in a sandy clay loam soil at New Delhi. The treatments included unfertilized control (T1), conventionally managed (T2) and five organic treatments (T3: FYM @ 10 t/ha to rice and wheat, T4: SGM for rice and LGLM for wheat, T5: SGM + BGA for rice and LGLM + Azotobacter for wheat, T6: SGM + FYM for rice and LGLM + FYM for wheat, and T7: SGM + FYM + BGA for rice and LGLM + FYM + Azotobacter for wheat). The application of organic amendments had positive influence on soil physical properties such as saturated hydraulic conductivity (Ks), field capacity (FC) and permanent wilting point (PWP), plant-available water capacity (PAWC), water holding capacity (WHC), distribution of aggregate size fractions, bulk density (Db), and porosity in the 0-15 and 15-30 cm soil layer. A favourable effect of organic amendments was also found on soil strength (at depth 0-70 cm). Even, values related to these properties were significantly affected by the kinds of organic amendments. But, T1 and T2 had no improvement in soil physical properties over the organic ones. Value of Ks decreased with increase in soil depths. T7 and T3 were superior in Ks to other treatments for 0-15 and 15-30 cm soil depths. Volumetric moisture content at FC (θFC) and PWP (θWP) increased with addition of organic amendments and got varying response due to the kinds of organic amendments or their combinations. θFC and θWP were decreased substantially under T1 and T2, because of no addition of organic inputs. As a result of θFC and θWP, PAWC had also signified an improvement under the influence of different organic amendments over T1 and T2. Generally (for both depths), PAWC of T3, T6 and T7 were 17-26% more than T1, T2, T4 and T5. WHC of upper soil layer (0-15 cm) was greater for organic amended plots than plots devoid of organic inputs and lower values were recorded for 15-30 cm soil layer. WHC of T3, T7 and T6 was highest in comparison to plots amended only with (without FYM) green manure, BGA or Azotobacter as well as T1 and T2 for both depths (0-15 and 15-30 cm). A better soil aggregation was observed under organic amended plots for large and small macro-aggregates (LM - >2 and SM-0.25-2 mm) in both soil depths. Lowest value of Db with highest percentage of pore space was noted under T7 than other treatments in both soil layers. Soil strength was significantly lower in organic amended plots than T1 and T2. This study clearly indicated that application of organic inputs especially FYM, improved the soil physical properties, which resulted in better soil aggregation, porosity and soil moisture retention.

Development of a cropping resilient watermarking scheme based on contourlet transform for secure IoT communication

The objective of this work is to propose a robust watermarking method as watermarking techniques are widely used today for preventing image altering and duplication. With the growth of image-based IoT applications nowadays, the need for developing robust digital watermarking techniques is of high demand. In this work, a robust yet highly perceptible watermarking scheme is proposed. The proposed scheme is based on the Contourlet Transform (CT) and Singular Value Decomposition (SVD) as the embedding domain in which the high-frequency components are chosen for embedding. The frequency domain is selected in order to make the watermarking scheme resists image attacks as the watermark is spreaded across different frequency bands in the cover image and hence the possibility of altering all the embedded bands is not possible as it will results in destroying the cover image. On the other hand, the Arnold transformation was used to insure secure IOT communication where the Arnold transform is applied to the binary logo watermark before embedding for a more secure design. In this context, the host image has been decomposed into the first level of contourlet transform and the highest frequency sub-bands are selected for embedding after performing the SVD on those bands where the SVD matrix is chosen to be the embedding domain. Moreover, This work aims to resist the cropping attack on images where PSNR values were above 52 dB and NC values ranged from 0.8 to 0.9 under various types of cropping attacks. In addition, the proposed method demonstrates its ability to resist various geometric and noise attacks such as JPEG compression, histogram equalization, gaussian noising and image brightening. Comparisons with state-of-the-art work demonstrate the proposed scheme's efficienc

Application of nonlinear clustering optimization algorithm in web data mining of cloud computing

Abstract To improve data mining and data clustering performance to improve the efficiency of the cloud computing platform, the author proposes a bionic optimized clustering data extraction algorithm based on cloud computing platform. According to the Gaussian distribution function graph, the degree of aggregation of the categories and the distribution of data points of the same category can be judged more intuitively. The cloud computing platform has the characteristics of large amount of data and high dimension. In the process of solving the distance between all sample points and the center point, after each center point update, the optimization function needs to be re-executed, the author mainly uses clustering evaluation methods such as PBM-index and DB-index. The simulation data object is the Iris dataset in UCI, and N = 500 samples are selected for simulation. The experiment result shows that when P is not greater than 15, the PBM value changes very little, and when P = 20, the PBM performance of all the four clustering algorithms decreased significantly. When the sample size is increased from 50,000 to 100,000, the DB performance of this algorithm does not change much, and the DB value tends to be stable. In terms of clustering operation time, the K-means algorithm has obvious advantages, the DBSCAN algorithm is the most time-consuming, and the operation time of wolf pack clustering and Mean-shift is in the middle. In the actual application process, the number of samples for each training can be dynamically adjusted according to the actual needs, in order to improve the applicability of the wolf pack clustering algorithm in specific application scenarios. Flattening in cloud computing for data clusters, this algorithm is compared with the common clustering algorithm in PBM. DB also shows better performance.

Bandwidth Enhancement of 2x1 Microstrip Array Antena Using Slit Technique for Wireless Communication System

This study proposes a microstrip array antenna with frequency at of 2.3 GHz – 2.5 GHz for various applications, with smaller antena dimensions. The microstrip antenna designed in this study uses a rectangular patch consisting of two patch elements arranged in a linear array. The type of substrate used is FR-4 with a dielectric constant (εr) = 4.3 and a substrate thickness (h) = 1.6 mm. The feeding technique used is indirect feeding using a microstrip line feed. To increase the bandwidth, the antennas are arranged in an array with 50 ohm and 100 ohm microstrip lines. The simulated antenna parameters are return loss value -10 dB, VSWR 2, and gain value. The simulation results of the two-element array design with a substrate size of 123 mm x 65 mm obtained a return loss value of -27.99 dB at a frequency of 2300 MHz, -15.16 dB at a frequency of 2400 MHz, and -29.29 dB. The bandwidth generated in this study is 460 MHz or an increase of up to 283.3% when compared to a 2x1 antenna array without slit. Furthermore, the addition of slits succeeded in reducing the dimensions of 34.43% compared to 2x1 antenna arrays without slits. This antenna is very useful as a wireless communication receiving antena.

Thermal, Acoustic, and Hygrothermal Properties of Recycled Bovine Leather Cutting Waste-Based Panels with Different Compositions

This study aims to investigate the thermo-acoustic and hygrothermal properties of innovative panels made of leather waste produced by a bag factory from a circular economy perspective. Their performance was compared with other residual-based insulation panels. The leather scraps were chipped and three boards were fabricated by means of a mold with different compositions, adding adhesive glue. In order to improve the sustainability aspects, a sample was assembled by using a water-based polyurethane glue, in addition to the two panels with vinyl glue. Panels were tested for thermal, acoustic, and hygrothermal performance. Thermal conductivity values in the range of 0.064–0.078 W/mK at 10 °C were measured depending on the composition and the adhesive. A slight thermal performance deterioration occurs when using the natural water-based glue. The samples were characterized by good performance both in terms of sound absorption coefficient (Noise Reduction Coefficient NRC = 0.21–0.28) and Transmission Loss, up to 59 dB values. Water vapor resistance factor values in the 35–48 range were obtained, close to the values of standard materials, such as expanded polystyrene and polyurethane.

Design of Clustering Techniques in Cognitive Radio Sensor Networks

In recent decades, several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during transmission to a shorter distance while restricting the Primary Users (PUs) interference. The Cognitive Radio (CR) system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm (ASDIC) that shows better spectrum sensing among group of multiusers in terms of sensing error, power saving, and convergence time. In this research paper, the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity. In this research, multiple random Secondary Users (SUs), and PUs are considered for implementation. Hence, the proposed ASDIC algorithm improved the convergence speed by combining the multi-users clustered communication compared to the existing optimization algorithms. Experimental results showed that the proposed ASDIC algorithm reduced the node power of 9.646% compared to the existing algorithms. Similarly, ASDIC algorithm reduced 24.23% of SUs average node power compared to the existing algorithms. Probability of detection is higher by reducing the Signal-to-Noise Ratio (SNR) to 2 dB values. The proposed ASDIC delivers low false alarm rate compared to other existing optimization algorithms in the primary detection. Simulation results showed that the proposed ASDIC algorithm effectively solves the multimodal optimization problems and maximizes the performance of network capacity.

Ionic liquid enables high-performance, self-powered CsPbBr3 perovskite nanonet photodetector.

We fabricated high-quality CsPbBr3 perovskite nanonet films with the assistance of polystyrene spheres, and constructed self-powered photodetectors (PDs) with an ITO/SnO2/CsPbBr3/carbon structure. By passivating the nanonet with different concentrations of 1-butyl-3-methylimidazolium bromide (BMIMBr) ionic liquid, we found that as the concentration of BMIMBr increases, the dark current of the device first decreases and then gradually increases, while the photocurrent remains essentially unchanged. Finally, the PD with 1 mg mL-1 BMIMBr ionic liquid exhibited the best performance with a switch ratio of about 1.35 × 106, a linear dynamic range extending to 140 dB, and responsivity and detectivity values of 0.19 A W-1 and 4.31 × 1012 Jones, respectively. These results provide an important reference for fabricating perovskite PDs.

Segmentation Method of Deterministic Feature Clustering for Identification of Brain Tumor Using MRI

The feature play important role for identification of the region of interest. Different kinds of feature exist, it is also essential to identify the accurate class of the feature., Challenging dataset like MICCAI BraTs brain tumor contains many tumor images. Feature is helpful to detect the region of tumor with some of its characteristic. But due to many images and their information, the issue of data complexity is raised. because the data was found to be complex. Thus, due to the complexity, higher dimension features are reduced to low dimension features. Hence, there is a need for improved feature selection method. Furthermore, it is also essential to enhance the method for the SOM Map for the selection of deterministic feature after the extraction. The goal of the work is not only to select the accurate feature of tumor but also to segment the tumor intensity with the confidence element. The objective under umbrella of this work is to improve the feature selection method by using confidence element of interest through the determination of the best feature using the SOFM with FCM. The method works with the selection of the best features with higher accuracy. Those higher accurate Features are called the deterministic Features. These deterministic features are selected through improved weighted SOM. This improved SOM is further combined with FCM to cluster the Confidence element. Evaluation is made with comparison to ground truth reality images; Results show; DOI is 0.94, JI is 0.91, MSE is 0.058db and PSNR is 17.94db; MSE with small number highlights the performance of method. It can be compared with the state of the art it can be compared from benchmark studies. Values of testing parameter from benchmark studies were JI, DOI, MSE and PSNR: JI value was 31.5%, DOI value was 47.3%, MSE value was 2.5dB and PSNR value was 40dB.A better region of interest is proposed method to determine the confidence element. The average accuracy over the dataset is determined in form of confidence element (ROI), overlap is for complex cases and average value is 94 percent.