Brightness Intensity Research Articles

Kadar Air dan Warna Penyedap Alami Jamur Tiram (Pleurotus Ostreatus) Berdasarkan Perlakuan Awal (Pre-treatment)

Flavoring seasonings are food additives added with the aim of increasing flavor(palatability) and covering up deficiencies in food in terms of taste. The natural glutamatecontent of mushrooms has the potential to be used as a flavoring ingredient, one of which isoyster mushrooms. The quality of natural flavoring of oyster mushrooms is determined by theformula of the ingredients and the way they are produced. The drying process can affect thewater content and color of seasoning. This study aims to determine the water content and natural flavoring of oystermushrooms based on initial treatment. This study was an experimental study using aCompletely Randomized Design with 6 treatment trials (non-blanching, blanching, sodiumbisulfite immersion, citric acid immersion, blanching + sodium bisulfite immersion, andblanching + citric acid immersion), and 3 test replications. The moisture content test wasperformed by the AOAC oven method and color analysis was measured using Konica MinoltaCR-10 Color Reader. Observational data were analyzed using univariate analysis. The results showed that the initial treatment had a tendency to increase water content.Moisture content for all samples based on pretreatment meets the quality criteria for dryproducts that is 10%. The results of the color analysis showed an increase in the value of eachtreatment but did not show any real difference in color. The treatment using sodium bisulfiteimmersion and blanching showed an increase in brightness intensity and a good chroma valuecategory compared to the control value. Based on Hue value in each treatment has the samecolor scheme, namely yellow – red. OKeywords: Oyster mushroom, Water Content, Color, Pre treatment, blanching

Multisensor Image Fusion for Automated Detection of Defects in Printed Circuit Boards

This paper presents multisensor image fusion of polarization and infrared imaging to detect defects in printed circuit boards (PCBs). Many existing automated optical inspection techniques rely on visible imaging sensors. However, collected images suffer from uneven brightness levels due to the influence of lighting environment, which may significantly affect detection accuracies. Polarization information characterizes material types, surface roughness, and geometric shape of an object. Thermal infrared imaging reveals heat radiation difference between the defect region and the background. Polarization and infrared imaging are not sensitive to background illumination and contrast. In this paper, we utilize polarization information as well as infrared imaging to detect the defects in PCBs that conventional optical inspection techniques cannot easily detect. We design a multi-source image acquisition system to simultaneously acquire brightness intensity, polarization, and infrared intensity. Then a Multisensor Lightweight Detection Network (MLDN), trained on the PCB dataset collected, fuses polarization information and the brightness intensities in the visible and thermal infrared spectra to detect defects in challenging lighting conditions. Experiment results show that the proposed network outperforms the state-of-the-art automated optical inspection techniques in terms of mean average precision.

Cortical mechanisms of visual hypersensitivity in women at risk for chronic pelvic pain.

Increased sensory sensitivity across non-nociceptive modalities is a common symptom of chronic pain conditions and is associated with chronic pain development. Providing a better understanding of the brain-behavior relationships that underlie multimodal hypersensitivity (MMH) may clarify the role of MMH in the development of chronic pain. We studied sensory hypersensitivity in a cohort of women (n = 147) who had diary confirmation of menstrual status and were enriched with risk factors for chronic pelvic pain, such as dysmenorrhea and increased bladder sensitivity. We administered 2 experimental tasks to evaluate the cross-modal relationship between visual and visceral sensitivity. Visual sensitivity was probed by presenting participants with a periodic pattern-reversal checkerboard stimulus presented across 5 brightness intensities during electroencephalography recording. Self-reported visual unpleasantness ratings for each brightness intensity were simultaneously assessed. Visceral sensitivity was evaluated with an experimental bladder-filling task associated with early clinical symptoms of chronic pelvic pain. Visually evoked cortical activity increased with brightness intensity across the entire scalp, especially at occipital electrode sites. Visual stimulation-induced unpleasantness was associated with provoked bladder pain and evoked primary visual cortex activity. However, the relationship between unpleasantness and cortical activity was moderated by provoked bladder pain. These results demonstrate that activity in the primary visual cortex is not greater in individuals with greater visceral sensitivity. We hypothesize that downstream interpretation or integration of this signal is amplified in individuals with visceral hypersensitivity. Future studies aimed at reducing MMH in chronic pain conditions should prioritize targeting of cortical mechanisms responsible for aberrant downstream sensory integration.

Compact ultracold neutron source concept for low-energy accelerator-driven neutron sources

The concept of a small-scale, pulsed-proton accelerator-based compact ultracold neutron (UCN) source is presented. The essential idea of the compact UCN source is to enclose a volume of superfluid \(^{4}\hbox {He}\) converter with a supercold moderator in the vicinity of a low-radiation neutron production target from (p, n) reactions. The supercold moderator should possess an ability to produce cold neutron flux with a peak brightness near the single-phonon excitation band of the superfluid \(^{4}\hbox {He}\) converter, thereby augmenting the UCN production in the compact UCN source even with very low intensity of neutron brightness. The performance of the compact UCN source is studied in terms of the UCN production and thermal load in the UCN converter. With the proposed concept of the compact UCN source, a UCN production rate of \(P_\mathrm{{UCN}}=80\,\hbox {UCN/cm}^{3}/\hbox {s}\) in the UCN converter could be obtained while maintaining thermal load of the superfluid \(^{4}\hbox {He}\) and its container at a level of \(22~\hbox {mW}\). This study shows that the compact UCN source can produce a high enough density of UCNs at a small-scale, low-energy, pulsed-proton beam facility with reduced efforts on the cooling and radiation protection.

Fluorescence Thermometry Based on PL Spectra and PL Image from Ti Doped Al2O3

Temperature dependences of photoluminescence (PL) from Ti doped sapphire (Ti doped Al2O3) crystals peaking at λ = 725 nm is evaluated for a fluorescence thermometry application. PL intensity from Ti doped sapphire decreases with temperatures increasing from 20 to 250 oC. 2-dimensional (2-D) PL images were observed from Ti doped sapphire using a CCD camera under a blue LED illumination. Brightness (intensity of red signal) of the PL image decreases linearly with temperature as is seen in PL peak intensity. The tendency of the temperature change of the PL peak intensity, intensity ratio, and full width at the half maximum (FWHM) of PL peak, and the brightness of the PL image from Ti doped Al2O3 are found to be useful for a fluorescence thermometry.

Methodology for determining radiation dose distribution of strontium-90 applicators for veterinary intraoperatory betatherapy

Betatherapy is a modality within brachytherapy that uses beta radiation applicators, which are used in the treatment of superficial injuries. With the advancement of therapeutic techniques, new clinical protocols in veterinary medicine will be established. In this sense, betatherapy appears as an important option for performing radiotherapy procedures and, consequently, further studies are necessary to define the clinical oncological protocols. Therefore, the aim of this study was to present a methodology for determining the dose distribution of beta radiation from strontium-90 (90Sr) applicators for use in intraoperative radiotherapy in veterinary medicine. Planar radiation dose distributions from three 90Sr applicators were analyzed using radiographic films, which were exposed to beams from sources at different exposure times. The optical density (O.D.) of the radiation field was verified with a digital densitometer. After scanning the films, using the ImageJ software, the brightness intensities (BI) for the radiation exposure fields were measured. The analysis of the radiation dose distribution of the betatherapy applicators, produced results similar to those already described in the literature. The use of the ImageJ software, as well as the O.D. obtained, helped in the analysis of dosimetric studies. The behavior of the dose-effect curves provided a better understanding of the homogeneity of the radiation field in the treatment plan and, therefore, the radiation dose distributions in the treatment fields indicate the use of these types of applicators in veterinary radiotherapy procedures.

Retinal disease identification using upgraded CLAHE filter and transfer convolution neural network

Retinal tissue plays a crucial part in human vision. Infections of retinal tissue and delayed treatment or untreated infection could lead to loss of vision. Additionally, the diagnosis is prone to errors when huge dataset is involved. Therefore, a fully automated model of identification of retinal disease is proposed to reduce human interaction while retaining its high accuracy classification results. This paper introduces an enhanced design of a fully automatic multi-class retina diseases prediction system to assist ophthalmologists in making speedy and accurate investigation. Retinal fundus images, which have been used in this study, were downloaded from the stare website (157 images from five classes: BDR, CRVO, CNV, PDR, and Normal). The five files were categorized according to their annotations conducted by the experienced specialists. The categorized images were first processed with the proposed upgraded contrast-limited adaptive histogram filter for image brightness enhancement, noise reduction, and intensity spectrum normalization. The proposed model was designed with transfer learning method and the fine-tuned pre-trained RESNET50. Eventually, the proposed framework was examined with performance evaluation parameters, recorded a classification rate with 100% sensitivity, 100% specificity, and 100% accuracy. The performance of the proposed model showed a magnificent superiority as compared to the state-of-the-art studies.

IMAGE QUALITY IMPROVEMENT USING IMAGE PROCESSING METHOD IMAGE BRIGHTNESS CONTRAST AND IMAGE SHARPENING

The ability of computers that are increasingly reliable in various fields, especially in helping the image processing sector through improving image quality, is very much felt so that the empowerment of computers at any time needs to be improved. Image quality improvement can be made with various techniques, including Image Quality Improvement with Image Brightness and Image Sharpening methods. The process begins with capturing the image and then continues with increasing the intensity of brightness, image contrast and sharpening. Image processing results are indicated by changes in the resulting image and changes in the image histogram

Intelligent Street Lighting Energy-Saving System Based on Climate Conditions and Vehicle’s Movements

The huge amount of electric power and cost associated with street lighting has raised the need to investigate both cost issues and environmental concerns. Cities worldwide are increasingly investing in energy-efficient street lighting systems. Modern street lighting technology can lower energy consumption as well as operation and maintenance costs significantly. In addition, bright street lighting can reduce accidents and crime rate in the area. Street lighting is an essential public service that provides a significant factor contributing to the quality of life and productivity of people workforces. This paper proposes an intelligent and energy-efficient traffic sensing system based on the widely distributed street lights. It is intended to observe vehicle’s movement on the road and turn ON a block of street lights ahead of vehicle whenever needed. As the vehicle passes by, the system turns OFF the trailing lights. The brightness (intensity of light) of the street light is adjusted based on the surrounding using LDR sensor. Hence, the street lights will be switched ON in the evening around sunset when a vehicle passes by, and switched OFF in the morning after sunrise when there is sufficient light on the streets. In addition, the proposed system will control the intensity level of the street light using the LDR sensor. The Proteus Software Simulation of the proposed system was performed and tested. Then a hardware prototype was designed and implemented to evaluate the performance of the proposed system. This technology can save significant costs and energy.

RDH-based dynamic weighted histogram equalization using for secure transmission and cancer prediction

Image contrast enhancement is a prerequisite and plays a very important role in many image processing field like medical imaging, face recognition, computer-vision, and satellite imaging. In this paper we proposed reversible data hiding based Limited Dynamic Weighted Histogram Equalization techniques for Abnormal Tumor regions which improve the contrast, transmit the hidden secret information, preserve its brightness intensity and original appearance of the image. We have implemented Otsu’s method to segment the input image into two sub-histogram regions of interest (ROI) and non-region of interest; furthermore, the sub-histograms ROI region equalized independently without of over-enhancement and any loss of hidden and diagnostic data. Our proposed method is more efficient to precisely preserve the brightness of the image and extract the secret information with contrast image reversibly; besides, different classifiers are used to classify the brain cancer to check the performance of our proposed method.

A method for non-contact determination of the amplitude of deformation of accumulated operational damage to a metal structure

It has been shown that to study the kinetics of operational damage to materials and structural elements, it is necessary to develop modern means and methods for diagnosing damage occurring in laboratory samples and structural elements. In this paper, in order to determine the deformation state of the surface layer of a structural material, using austenitic steel samples as an example, we used the method of optical measurement of microplastic deformation, which is based on the correlation between the energy of a coherent light source reflected by the surface of a metal polycrystal and the amplitude of microplastic deformation of the deformed surface. According to this method, the local area of the material sample surface under investigation is irradiated at certain stages of loading with coherent light beams with a wavelength that corresponds to the scale of localization of microplastic deformations of the sample surface. An optical system is used to generate an image of the speckle-modulated beam, which has the parameters of the deformed surface relief. As a measure of the depth of the deformation relief, the integral value of the image brightness intensity parameter is used as the ratio of the number of light pixels to the total number of pixels in the specklegram image. As a result of the analysis of the statistical parameters of the specklegram, which correlate with the characteristics of the state of microplastic deformation of the surface of austenitic steel samples, the characteristic parameters of the scattered damage to the structure of discrete deformations of the surface of a metal polycrystal were determined. On the basis of the experimental data obtained, the regularities of the influence of static and cyclic deformation on the shape of the distribution of discrete surface properties were revealed. In particular, as a result of analyzing the statistical characteristics of the correlation diagrams, a linear dependence of the parameters of the distribution of discrete properties of the deformed surface relief on the loading factor was obtained.

A method based on ejector technology to suppress the infrared radiation of the special vehicle exhaust gas

In this study, a method based on ejector technology is proposed to effectively suppress the infrared radiation associated with the exhaust gas of special vehicles such as tanks, armored vehicles, and missile carriers. These vehicles emit exhaust gases at very high temperatures. First, a mathematical model of the exhaust pipe was established for the exhaust system of a certain type of special vehicle. Then, the 3-D flow field outside the exhaust pipe was numerically simulated using FLUENT 6.3 software. Thus, the temperature, pressure, and density of the exhaust-gas-flow field before and after adopting the proposed ejector technique were obtained. Second, the statistical narrowband model based on the Lorentzian profile was used to determine the average absorption coefficient of a narrow band. Then, the finite volume method was used to solve the radiation transfer equation in the gaseous medium. Finally, the spectral radiation brightness and mid-infrared radiation intensity distribution of the exhaust gas before and after adopting the ejector technique were obtained. Results show that the proposed method considerably decreased the infrared radiation intensity of the exhaust gas by approximately 70%. Thus, using the proposed ejector technology, the infrared radiation associated with the exhaust system of special vehicles can be effectively suppressed.

Edge detection of noisy digital image using optimization of threshold and self organized map neural network

The purpose of this research is to find a suitable method for detecting the edges of noisy digital images by eliminating the noise effects. The image will be partitioned into equal partitions and the initial threshold of that image partition will be calculated. By applying all these thresholds into the self-organized map (SOM) neural network input optimized for learning and training based optimization algorithm (TLBO), threshold clustering will be performed. The partitioned image will be edge detected by entropy method. Choosing the threshold for image segmentation is of great importance. The mean of the brightness of digital noise images is not a good representative of the initial threshold. Noise causes the mean intensity of the brightness to take distance from the main range of the intensity of the image so the resulting edge detected image will be severely noisy and truncated. By determining the highest frequency of brightness intensity instead of the mean brightness, the above-mentioned weaknesses will be eliminated. This method outperforms many current methods, such as Tsallis entropy, Singh and Kiani and even Canny Edge Detection which demonstrates the effectiveness of the proposed method, In the Table 1 the PSNR of image 5 of the proposed method is 61.4896, but Singh method which is 55.61, Tsallis method which is 53.9234, Kiani method which is 53.9315 the proposed method is less than the other methods.

Contrast Enhancement Using Inverted Gaussian Histogram Specification Technique

Contrast enhancement has become a vital process in improving the human perception as well as machine perception, due to the enormous application of digital imaging techniques in various fields like medical, aerospace, agriculture, machine vision, automation, surveillance, etc. During contrast enhancement by various existing techniques, the advent of adverse side effects like brightness degradation, intensity saturation and appearance of artifacts in the enhanced images is a critical issue, which needs more research attention. In this paper, an inverted Gaussian histogram specification technique for contrast enhancement of differently skewed images is proposed, in which the pixel concentration on either side of the histogram is increased to overcome the drawbacks in the existing methods. The proposed technique uses parameters like mean, standard deviation and inversion constant to generate various inverted Gaussian specified histograms. Further, transformation and objective functions are used to identify the best desired histogram so as to obtain the best enhanced image for the given image. The performance of the proposed method is compared with other existing techniques on the images taken from various standard databases. The experimental results show that the proposed technique is best suitable for contrast enhancement of images with differently skewed histograms.

Estimation and evaluation of pseudo-CT images using linear regression models and texture feature extraction from MRI images in the brain region to design external radiotherapy planning.

The aim of this study is to construct and evaluate Pseudo-CT images (P-CTs) for electron density calculation to facilitate external radiotherapy treatment planning. Despite numerous benefits, computed tomography (CT) scan does not provide accurate information on soft tissue contrast, which often makes it difficult to precisely differentiate target tissues from the organs at risk and determine the tumor volume. Therefore, MRI imaging can reduce the variability of results when registering with a CT scan. In this research, a fuzzy clustering algorithm was used to segment images into different tissues, also linear regression methods were used to design the regression model based on the feature extraction method and the brightness intensity values. The results of the proposed algorithm for dose-volume histogram (DVH), Isodose curves, and gamma analysis were investigated using the RayPlan treatment planning system, and VeriSoft software. Furthermore, various statistical indices such as Mean Absolute Error (MAE), Mean Error (ME), and Structural Similarity Index (SSIM) were calculated. The MAE of a range of 45-55 was found from the proposed methods. The relative difference error between the PTV region of the CT and the Pseudo-CT was 0.5, and the best gamma rate was 95.4% based on the polar coordinate feature and proposed polynomial regression model. The proposed method could support the generation of P-CT data for different parts of the brain region from a collection of MRI series with an acceptable average error rate by different evaluation criteria.

Preflare Dynamics of Microwave and Ultraviolet Emission in Active Regions of the Sun

This paper is a study of the spatial dynamics of microwave emission (data from the Nobeyama Radioheliograph) from two active regions NOAA 12673 and NOAA 11261 for several hours prior to powerful class M x-ray flares. The spatial distribution of the radio brightness and emission intensity in certain parts of the active region is found to be highly nonstationary. Data in the ultraviolet (AIA/SDO) are also used for studying the fine structure of the active emission sources. It is shown that the spatial dynamics of the microwave sources correlates well with the position and appearance of bright ultraviolet (UV) loops in the 94 A line, i.e., with magnetic loops where the plasma is heated to high temperatures ~107 K. A combined analysis of the UV and radio emission charts with magnetic field charts (HMI/SDO) for NOAA 12673 shows that the highly nonstationary behavior of the microwave sources develops simultaneously with the ignition of a system of intersecting UV loops (X-structures). It is also shown that the bright UV loops and microwave sources arise in the area where new magnetic fluxes emerge.

Depth Estimation for Local Colon Structure in Monocular Capsule Endoscopy Based on Brightness and Camera Motion

SUMMARYWe present a 3D reconstruction method using brightness and camera motion estimation for registering local colon structure in colonoscopy. The proposed method is based on reverse projection from 2D fold contours to 3D space, motion estimation from 3D reconstructed points between neighboring frames, and model registration to reconstruct the fold structure. On the synthetic colon, the average percentages of the reconstructed depth error and circumference error are about 14.2% and 15.2%, respectively. The accuracy is enough for the navigation and control in capsule robot. This work demonstrates that the proposed method is superior to the methods using single-frame-based brightness intensity.

Curcumin addition in diet of laying hens under cold stress has antioxidant and antimicrobial effects and improves bird health and egg quality.

Curcumin is an herbal component with several biological properties, and we highlight here the thermal stability, antioxidant and anti-inflammatory activity. We determined whether curcumin supplementation in the diets of laying hens under cold stress and naturally infected with Escherichia coli would control infection, and would have positive effects on overall health, as well as egg production and quality. We allocated 36 chickens that had been naturally infected with E. coli into two groups, with six replicates and three chickens per repetition: control group and curcumin group (200mg curcumin/kg). The experimental period lasted 42 days, and fecal, blood and egg samples were collected at 1, 21 and 42 days We found that feces and eggs had lower total bacterial counts, E. coli counts and total coliform counts in the curcumin group at 21 and 42 days. In fresh eggs, the brightness and yellow intensity (b+) were significantly higher in the curcumin group. In stored eggs, higher specific gravity, albumen height and lower yolk pH were observed in the curcumin group. Fresh eggs collected and stored on day 42 showed lower levels of lipid peroxidation in the curcumin group, while the total antioxidant capacity in the stored eggs was significantly higher in the curcumin group. The curcumin group showed lower total leukocyte counts as a result of lower numbers of neutrophils and lymphocytes, as well as lower levels of total protein, alkaline phosphatase and alanine aminotransferase. Lower serum lipoperoxidation at 42 days was observed in the curcumin group, probably because of the higher activity of glutathione peroxidase and glutathione transferase in other words, because of antioxidant stimulation. Taken together, our findings suggest that curcumin supplementation in laying hens under cold stress and with colibacillosis has positive effects on infection control because of antioxidant stimulation.

On the Effects of Constitutive Properties and Roughness of a Hard Inclusion in Soft Tissue on B-mode Images.

We perform finite element modeling of pulse-echo ultrasound of a hard inclusion in a soft tissue to gain a better understanding of B-mode image brightness characteristics. We simulate a pressure wave emitted by an ultrasound transducer through the inclusion-tissue medium by prescribing suitable boundary conditions, and collect the scattered wave response to simulate the behavior of the transducer array used for pulse-echo ultrasound. We form B-mode images from simulated channel data using standard delay and sum beamforming. We establish the accuracy of the finite element model by comparing the point spread function with that obtained from Field II ultrasound simulation program. We also demonstrate qualitative validation by comparing the brightness characteristics of rough and smooth surfaced circular inclusions with experimental images of a cylindrical metal tool immersed in a water tank. We next conduct simulation studies to evaluate changes in B-mode image brightness intensity and contrast related to different constitutive properties, namely, compressibility of the inclusion, impedance contrast between the host and inclusion, and surface roughness of the inclusion. We find that the intensity observed behind a hard inclusion in the axial direction is strongly affected by the compressibility and roughness of the inclusion. Also, the perceived width of the stone based on the intensity is greater for rougher stones. Our study indicates that imaging of compressible inclusions may benefit from targeted B-mode image forming algorithms. Our modeling framework can potentially be useful in differentiating hard inclusions from surrounding parenchyma, and for classifying kidney stones or gallstones.

Kualitas Perairan Situ Lebakwangi, Bogor

Water pollution that occurs due to various human activities in Situ Lebakwangi's cause of water quality decrease based on Government Regulation Number 82 of 2001 about Water Quality Criteria. The purpose of this research is to know the water quality of Situ Lebakwangi based on physical, chemical, and biological (coliform bacteria) factors. This research was conducted in Situ Lebakwangi, Bogor in January 2015. Physical factor parameters are temperature, dissolved oxygen (DO), pH, total dissolved solids (TDS), electrical conductivity (EC), five days of biological oxygen demand, brightness and light intensity. Research results show that the physical condition of Situ Lebakwangi is conformed with environmental quality standard class II.Temperature of Situ Lebakwangi range is 29,2-30,2 ˚C, DO 4,8-6,2 ppm, TDS 53,7-58,7 ppm, BOD 5 1,6-3,1 ppm, EC 112-118 mS/cm, and pH 6,6-8,8. The measurement result shows that total bacteria exceed the environmental quality standard 1,0 x 10 3 CFU/ml, except in the six-station. Pollutant bacteria E. coli was not found in the 6 th station. All of the stations can not found pathogenic bacteria Salmonella sp. Coliform bacteria in five and six stations exceeds the environmental quality standard, which is 5,0 x 10 3 . All observed physical factor parameters were in conformable with PP 82 of 2001 about Water Quality Criteria, but for biological parameters (total bacteria and total coliform) were not. Based on these results, aquatic of Situ Lebakwangi can not be used for water recreation facilities, freshwater fish cultivation, livestock, water to irrigate crops, and other uses that require the same water quality.