Average Intensity Values Research Articles

New color channel driven physical lighting model for low-light image enhancement

Outdoor imaging systems, affected by low-light conditions, generally produce low-quality images with poor visibility. Low-quality images can directly influence high-level tasks such as surveillance and autonomous navigation systems. Enhancing the images captured under inadequate lighting conditions aims to generate higher visual quality in these images. However, current low-light enhancement methods may result in color unnaturalness, information loss, and strange artifacts. We propose a new color channel-driven physical lighting model (NCC-PLM) to respond to these issues to improve image quality. More concretely, we first apply a gamma correction to the input image according to its darkness degree, which is determined by its average intensity value. Then, we introduce a new color channel prior to estimate the environmental light (EL) and light scattering attenuation rate (LSAR). Finally, the enhanced image is obtained through the estimations and physical lighting model. Experimental results on various datasets demonstrate the proposed method's effectiveness and superiority over the compared methods both visually and qualitatively. Specifically, we enhance the visual quality of low-light images by revealing intricate details and maintaining color consistency, leading to a natural appearance.

Noninvasive quantitative ultrasound fatty liver evaluation of hepato-renal index in pediatric patients using 3D-slicer

AimHepato-renal index (HRI) calculated by ultrasound images has been shown to be an effective, noninvasive tool to screen patients with steatosis. The aim of this study was to non-invasively explore a new method for the calculation, directly on DICOM images, of HRI in pediatric patients using 3D Slicer, a free and open-source software for medical image analysis, especially used for artificial intelligence data annotation. Previous studies in literature were based on non-medical image format (such as png and tiff) and analyzed by using ImageJ, a popular image analysis software.Materials and methodsDICOM images were collected retrospectively between November 2022 and December 2023 at a tertiary institution on any patient under 18 years referred to US assessment of suspected steatosis. The HRI was measured on sagittal images with a clear visualization of both the liver and the kidney by 3D Slicer. The HRI was calculated as the ratio of average pixel intensity values between the two ROIs. Also, we correlated the index with the qualitative operator assessment grade of steatosis made by two expert radiologists with more than 15 years of experience.Results49 patients (59% male, age 11.6 ± 2.6 year) were recruited. Of these, 29 (59%) had qualitative ultrasound confirmation of the diagnosis. The Bland–Altman plots showed a good agreement between the HRI indexes calculated with the standard tool ImageJ and 3D Slicer. Furthermore, the quantitative HRI calculated by the two software showed a correlation (Spearman’s coefficient = 0.52, P < 0.0001) with the qualitative operator measurement.ConclusionsFor the first time, an estimation of HRI directly on DICOM images was executed by using 3D Slicer, obtained quantitative information directly from clinically approved image format.

Pain intensity profile after a single injection of the peptide analgesic taphalgin in traumatology and orthopedic patients: prospective observational cohort study

INTRODUCTION: Multimodal analgesia is the main management strategy for postoperative pain. One component of this approach is opioid agonists. OBJECTIVE: Assessment of pain intensity profile after a single administration of the new selective µ1-opioid receptor agonist taphalgin in traumatology and orthopedic patients. MATERIALS AND METHODS: This prospective observational program analyzed data from 100 patients whom were prescribed the drug taphalgin for pain relief after traumatological and orthopedic surgery. All patients were treated with 50 mg dexketoprofen when moderate pain appeared after surgery. If the pain reached moderate or high intensity again, 4 mg of taphalgin was administered subcutaneously and then the change in pain intensity at rest and during movement was observed after 15, 30, 45, 60 min, as well as 2 and 4 h, using numerical rating scale (NRS). In this study physicians’ satisfaction by taphalgin was estimated. Satisfaction was assessed using Likert scale, where 1 — very bad, 2 — unsatisfactory, 3 — satisfactory, 4 — good, 5 — excellent. Repeated measures analysis of variance and dependent samples t-test were used for statistical analysis. The critical level of significance for accepting significant differences was set at 0.05. RESULTS: The average value of pain intensity before drug administration at rest was 5.9 ± 0.5 points and pain in movement was 8.4 ± 0.8 points. After just 15 min, significant pain reduction was achieved to 4.9 ± 0.8 and 7.3 ± 1.1 points (p &lt; 0.001), respectively, after 30 min — to 3.6 ± 1.1 and 5.7 ± 1.1 points (p &lt; 0.001), respectively, and after 60 min — to 2.2 ± 0.8 и 4.2 ± 0.8 points (p &lt; 0.001), respectively. Doctor’s satisfaction with treatment showed that a positive assessment was given in 83 % of cases, and complete dissatisfaction was revealed in 1 % of cases. Impotently, no observations of respiratory depression or postoperative nausea and vomiting syndrome have been recorded. CONCLUSIONS: The drug taphalgin is an effective analgesic for the postoperative period in traumatology and orthopedics.

386 The Analysis of N-glycans and Collagen to Predict Prostate Adenocarcinoma Outcome

OBJECTIVES/GOALS: Distinguishing indolent from aggressive prostate cancer and early identification of men at risk of developing aggressive, metastatic disease is of great importance. We aim to explore the relationship between N-glycan and collagen composition in prostate tumor tissue and the long-term outcome of the disease. METHODS/STUDY POPULATION: Matrix assisted laser desorption/ionization mass spectrometry can be utilized to characterize N-glycan profiles in formalin fixed paraffin embedded tissues. Collagen may also be characterized using ECM-targeted collagenase MALDI imaging. These approaches were used to analyze prostatectomy samples with different clinical outcomes. Tissue microarrays containing tissues from 75 non-progressors (no evidence of disease; NED) and 50 metastatic cases (MET) were examined. From a combined list of 90 N-glycans and 500 collagenase peptides, the average AUC intensity value for each glycan and collagen peptide was extracted and assessed as a predictor of metastatic progression. Ancestral informative markers were analyzed and polygenic hazard risk scores were generated for samples as well. RESULTS/ANTICIPATED RESULTS: Three N-glycans and three collagen peptides were found to discriminate between NED and MET cases with statistical significance. The best performing N-glycan was Hex6HexNAc6Fuc1 with an AUC of 0.77 (p&lt;0.001). While the best performing collagen peptide was COL1A2 with an AUC of C 0.77 (p&lt;0.001). DISCUSSION/SIGNIFICANCE: Both a collagen peptide and N-glycan were discovered as promising biomarkers to predict metastasis. Future validation studies are needed to confirm biomarker potential and to determine if the addition of these biomarkers can strengthen current genomic classifier’s ability to predict metastatic prostate cancer.

Development of an Intelligent Imaging System for Determining Maturity of Copra Flesh in Coconuts Using Shape and Texture Extraction

Copra is dried coconut meat that is used to produce coconut oil. According to the Central Statistics Agency (BPS), Indonesia's copra production in 2020 reached 2.3 million tonnes. This is one form of the process of improving the economy of people living on the coast. This research was conducted to educate farmers in determining the level of maturity of the copra meat produced. This research was conducted using an extraction method that involves colour extraction and texture extraction. the method is used to provide convenience in seeing the level of maturity of the two characteristics of copra obtained in the field, namely texture and colour. The process obtained in the training with one of the images used as a test image in colour extraction produces area, perimeter, metric and eccentricity values in label 3 with values of 651.00, 184.69, 0.24 and 0.89. while in the feature extraction method the results are obtained with an average intensity value of 243.31, standard deviation of intensity 39.76 and entropy value of the tested image 4.57. The method is able to perform a detection process so that it can determine the level of maturity of copra seen from the existing types of copra such as asalan copra, regular copra, black copra and wet copra, each of which provides different functions in the copra processing stage. The process will be carried out using KNN which is seen from all test data and training data stored after the detection process. The results of the process carried out using digital images involving the extraction method for detection and KNN for classification are able to provide the right value. This is evidenced by the better accuracy value of 98%.

A High-Efficiency Satellite Image Classification Method for Real-Time Application Using Augmented Incremental Transfer Learning

Researchers have put forth a range of models for processing satellite images, each with distinct data formats and processing requirements. One limitation arises from variations in the forms of modules, such as the image capturing and feature extraction modules, impacting accuracy and scalability in real-time scenarios. This passage introduces and explores a pioneering very competent temporal engine crafted specifically for classification of real-time satellite images. The proposed approach utilizes augmented incremental transfer learning, aiming to mitigate the limitations associated with diverse processing requirements. This approach involves capturing real-time satellite data through Google’s Earth Engine and subsequently processing it using a Convolutional Neural Network (CNN) based on transfer learning. The CNN employs backscatter coefficient analysis, utilizing coefficients derived from Precision Image's average intensity value across a distributed target. By integrating incremental learning and CNN for classification, the model achieves an impressive average accuracy of 98.06% in detecting crop type and severity of damage. Comparative analysis with state-of-the-art approaches reveals the superiority of the proposed model. It outperforms existing models by 5% in accuracy, showcasing its efficacy in satellite image processing and classification.

Environmental performance driven optimization of urban modular housing layout in Singapore

ABSTRACT With the growing size of cities and the need to renew residential areas, architects are calling for more efficient use of already settled areas. This paper presents a performance-driven architectural design (PDAD) workflow for shape generation and genetic optimization based on environmental data, using public housing in the Singapore region as a case study. It integrates three-dimensional cellular automata, parametric performance simulation, genetic optimization algorithms, and hierarchical clustering algorithms. The results show that the average value of Useful Daylight Illuminance (UDI) is 85.19%, the average value of Energy Use Intensity (EUI) is 159.41 kWh/m2, and the average value of Predicted Mean Vote (PMV) is 0.64 for the optimal set of solutions produced after genetic optimization. The optimal solution set was further classified into 4 categories by a hierarchical clustering algorithm and was visualized for further evaluation and selection by the architect. The study helps architects to integrate data analysis results with human decision-making as a design research method in the early stages of design and leads to further discussion on bottom-up design approaches in the urban renewal process.

Влияние метеофакторов на среднесуточную интенсивность городского острова тепла Екатеринбурга

Urban heat island (UHI) intensity in the surface air temperature field is equal to the difference between temperatures (averaged for the period under consideration) in the city and in the immediate rural surroundings. Using multi-regression analysis, We investigated the meteorological factors determining the mean daily UHI intensity based on observational data at weather stations in Yekaterinburg and the village of Verkhneye Dubrovo in 2020–2022. The average value of an UHI intensity in May-September equals to 0.94 °C with a standard deviation of daily mean values of 0.71 °C. The multiple linear regression model includes the difference in the relative humidity of the atmosphere in the city and the village, the weather factor determined by wind speed and cloudiness, and atmospheric pressure. This “summer” model describes 60 % of the observed UHI variance. In December-March, the average UHI intensity equals to 0.81 °C with a standard deviation of mean daily values of 0.82 °C. The regression model includes only the weather factor explaining 27 % of the UHI variability. It is concluded that the UHI intensity in Yekaterinburg is primarily determined by solar radiation and various properties of urban and rural surfaces (albedo, emissivity, thermal properties of soils). They determine the maximal UHI intensity that is realized only in “ideal” weather (weather factor ~1). Deviations from “ideal” conditions described by meteorological factors only reduce the maximal UHI intensity. In winter, heat leaks from buildings and heating networks weakly dependent on the meteorological factors make an additional contribution to the UHI intensity.

Efficient Image Encryption via 2D Logistic Chaos Mapping: Strengthening Security with Pixel-Level Dynamics

This study presents an innovative image encryption algorithm anchored on the two-dimensional Logistic chaotic system, designed to address the limitations of traditional methods in terms of speed and security. The algorithm employs pixel shifting and scrambling, coupled with a segmented grayscale value substitution, to achieve a high level of security with strong key sensitivity and robust resistance to both differential and statistical attacks. Experimental validation demonstrates its superiority with fast encryption speeds, as evidenced by an encryption time of 0.2136 seconds for a 256×256 color image, and an entropy close to its ideal value, indicating excellent randomness. This method also exhibits high performance in resisting differential attacks, with Number of Pixels Change Rate (NPCR) and the Unified Average Changing Intensity (UACI) values nearing their optimal expected values. The integration of Quantum Key Distribution (QKD) is suggested for future work to enhance security against quantum computing threats, solidifying the algorithm’s potential as a leading solution for the image encryption.

Metaphorical Expression of Emotions in Modern Music Composition Based on Emotional Calculations

Abstract In this paper, audio and lyrics features of music are fused from the audio and lyrics attributes of modern music tracks to obtain a joint representation of music. The features such as tempo, directionality, average value of intensity, beat, and change of rhythm of each musical segment are extracted from the main audio track to form the music feature vector. Subsequently, the music was separated into multiple segments with distinct emotions, and the emotional expression of modern music was evaluated using the Hevner emotion model. Finally, the note extraction performance of this paper’s model is analyzed, and the spectral contrast features of different music pieces and the emotional expression of music pieces under different features are explored. The results show that the pitch patterns of sad emotions are mostly distributed in the range of 0.5-0.55, and the values of the pitch patterns of angry music are basically larger than 0.55. The mean values of the spectral entropy of joy and calmness are mostly distributed in the range of 0.5-0.7, and the sad emotions are mostly in the vicinity of 0.7, while the mean values of the spectral entropy of angry emotions are larger than 0.8.

LIGHTING STUDY IN CLASSROOM AT MTS AL MUTTAQIN PLEMAHAN KEDIRI

Lighting is very important in the classroom. The layout or orientation, window openings and area of the building must be considered so that sunlight entering the classroom can meet the standart. The purpose of this study was to find out how much light intensity is in the classroom and whether it is in accordance with SNI standards, so that it is comfortable for learning. This research method uses qualitative methods by observing interviews and quantitative methods by using simulations. The results showed that first grade class has an average of 1000 lux for 08.00 AM however, towards 12.00 PM the intensity of incoming light decreases to an average of 100 lux. Second grade has an average of 500 lux for 08.00 AM but towards 12.00 PM the intensity of incoming light decreases until it has an average of 100 lux. Grade three has an average of 300 lux at 14.00 PM and towards 16.00 PM the light intensity only decreases slightly so that it has the same average. The results of the interviews showed a lack of lighting during learning activities. The conclusion is that the average intensity value in the class measured is sufficient, but the distribution is uneven, so artificial lighting is needed.

Organic carbon storage and accumulation characteristics of peatlands in the Changbai Mountains, China

AbstractPeatlands are important carbon pools and stable carbon sinks in terrestrial ecosystems. Studying carbon storage and accumulation characteristics can provide a scientific basis for the conservation and restoration of peatlands. Based on the 2014–2015 survey of the Jilin Provincial Forestry Department on the carbon storage of peatlands in the Changbai Mountains, the surveyed 865 peatlands have a total area of 22,900 hm2 and carbon storage of 18,753,300 tons. There are 275 medium‐sized organic carbon (OC) stocks of peatlands (10000–100,000 tons) in this area, and their carbon storage accounts for 41.3% of the total reserves. The peatland carbon in this area is mainly distributed in the Yanbian Korean Autonomous Prefecture, valleys and the lava platform are the most important geomorphological basis for peatland deposits. The Mudanjiang River Basin has the largest carbon storage and it is dominated by a nutrient‐rich peatland. Peatlands in the Changbai Mountains formed and developed since the Holocene, and the carbon accumulation intensity is different in each stage. The average carbon density of peatlands in this area was 69.74 kg/m3 with an average value of 81.77 kg/m2 for OC accumulation per unit area. The average value of the carbon cumulative intensity of peatlands was 164.43 ton/km2 and the carbon accumulation rate of peatlands was 38.96 g/(a m2).

A-364 The Utility of the Highly Sensitive Detection System for Immunochromatographic Assay by Addition of MPC polymer

Abstract Background Immunochromatographic assay (ICA) is frequently used as a point-of-care testing (POCT) in the field of infectious diseases, but it has a problem of low detection sensitivity. Many interfering substances in ICA test materials have been reported to case a decrease in detection sensitivity. For the purpose of increasing the sensitivity of ICA, bovine serum albumin or a polymer with phosphorylcholine groups (MPC polymer) has been used as an additive to a sample diluent. In this study, we evaluated the usability of the sensitizing effect for the addition of MPC polymer with a serum-based HBs antigen test kit. Methods A 2-fold dilution series of a commercially available control serum (Infectrol D, SeraCare Life Sciences, Inc. manufacturer's reference value 108.674 IU/mL) containing 0.05%, 0.10%, 0.5% of several MPC polymers (Biolipidure® from NOF Corporation) as final concentration were prepared with HBs antigen negative serum. The optimal type of MPC polymer and the concentrations added to the sera were determined by comparing the color intensity of their test lines in the evaluation of each test sample with a commercially available test kit (Quick Chaser® from MIZUHO MEDY Co., Ltd.). The color intensities of the test lines were quantified with an immunochromatographic reader. In addition, the correlation of two different test kits (ESPLINE® from FUJIREBIO and Quick Chaser® from MIZUHO MEDY Co., Ltd.) was evaluated with sera obtained from HBs antigen-positive patients regarding the three types of MPC polymer which were improved the detection sensitivity in the evaluation with the control serum. The measurements were performed in triplicate after 0.5% of MPC polymer as final concentration was added to each diluted serum. Results Antigen amount for diluted sera with MPC polymer were determined by CLEIA method, and no difference in the antigen amount was observed regardless of the addition or the types of MPC polymer. In addition, the color intensity in each dilution series was compared to the cutoff value, which is average value of the color intensity of negative control serum without MPC polymer. In the evaluation with control serum, the test line in the case without MPC polymer enabled to detect up to 2-fold diluted control serum while the test line in the case with MPC polymer enabled to detect up to 32-fold diluted control serum. The addition of MPC polymer in the evaluation with sera obtained from HBs antigen-positive patients was also confirmed that the detection sensitivity enhanced up to 8-fold higher in ESPLINE® and up to 4-fold higher in Quick Chaser®. Conclusion The color intensity of the test line enhanced by the addition of MPC polymer. In particular, when the highly hydrophilic and anionic MPC polymer was added, the test line was detected narrower and darker, and we believe that the increased color intensity resulted in improved sensitivity. By considering the influence of interfering substances in clinical materials and the physical properties of the MPC polymer (hydrophobicity, molecular size, etc.), it is expected that the sensitivity of the ICA will be increased to be more suitable for clinical materials.

Analysis of faculty of electrical engineering and informatics building energy use intensity in pardubice, czech

The investigation focused on analyzing the energy usage patterns of the Faculty of Electrical Engineering and Informatics in Pardubice. The recorded energy consumption data were examined and discussed. The average heating energy consumption in the Faculty of Electrical Engineering and Informatics building in 2020, 2021, and 2022 is 686.45 MWh or 57% of the total energy equivalent value. Meanwhile, the average electricity consumption in the building during the same period is 518.97 MWh or 43% of the total energy equivalent value. The average fluctuation in heating energy consumption used in the Faculty of Electrical Engineering and Informatics building tends to increase by 2.9% per year, while the average fluctuation in electricity consumption tends to increase by 3.3% per year. According to the findings, the average comprehensive energy consumption per unit area in the building was 146,03kWh/m2. It was the sum of the energy use intensity for heating and the energy use intensity for electricity. The average energy use intensity value for heating in the building was 83.16 kWh/m2, while the average energy use intensity value for electricity was 62.78 kWh/m2.

Identifikasi Karakteristik Accumulator Menggunakan Citra Termal Berbasis Pengolahan Citra

Batteries are an important part of the power generation system, both solar power plants and motorized vehicle electrical systems. Battery capacity is something that must be considered for these various activities, because a decrease in battery capacity results in disruption of power distribution to users. The battery in this study is a battery or accumulator. The sample image is obtained using a thermal camera to determine the characteristics of the battery based on color. The basis for identifying characteristics is obtained by separating the RGB color components in the thermal image. Each color component will calculate the average pixel intensity value and see the difference in the resulting value. The results showed that the distinguishing characteristic between the sampling conditions was that the green pixel intensity mean value when the battery was being charged was higher than the condition of the battery before being charged and the condition of the battery when it was loaded. The average value when the battery is on the power side is 107 pixels green, while the average value when the battery is before charging is 81 pixels green and when the battery is loaded the average green value is 82 pixels.

Is There a Relationship between Increased Land-Use Intensity and the Rise in PM2.5 Pollution Levels in the Yangtze River Economic Belt, China (2000–2021)?

With the rapid urbanization and industrialization of the past few decades, environmental issues have become increasingly prominent, and air pollution in the form of PM2.5 has become a major concern in China. The Chinese government has recognized the severity of these environmental challenges and has placed great emphasis on protecting the environment while promoting economic growth. This study utilizes remote sensing technology to analyze the spatio-temporal evolution characteristics of the decoupling between land-use intensity and PM2.5 in the Yangtze River Economic Belt (YREB) using 2000–2021 series of PM2.5 and land-use-change data, with the Mean Center Change analysis and the Tapio Decoupling Model. This study attempts to analyze the causes of change from the perspectives of economic development stage and policy execution. The study found that the average PM2.5 level decreased by 11.77 μg/m3 during this period, with high levels concentrated in urban areas and low levels found in less developed regions. The central trajectory of the land-use intensity shifted southeast, indicating a consistent trend in urbanization and industrialization in that direction. Meanwhile, the average land-use intensity value increased by 0.19, with the highest values concentrated in urban areas. A total of 71.12% of the regions in the YREB exhibited strong negative decoupling or negative decoupling between land-use intensity and PM2.5 levels, suggesting rapid urbanization and industrialization with a decrease in PM2.5 levels. These findings provide insight into the dynamic relationship between economic development, urbanization, and PM2.5 in China’s Yangtze River Economic Belt.

PSEUDO RANDOM KEY GENERATOR USING FRACTAL BASED TRELLIS CODED GENETIC ALGORITHM FOR IMAGE ENCRYPTION

Cryptographic applications such as online banking, and securing medical and military data require the usage of random keys, which should remain unpredictable by adversaries. This paper focuses on the strengths and limitations of the techniques and algorithms that are used in the generation of random keys and a new method to generate random keys is proposed using fractals. Fractals are generated using the Sierpinski triangle and fed as input for Non-Deterministic Finite Automata (NDFA) to generate an Initial Vector (IV). Trellis Coded Genetic Algorithm (TCGA) code generator generates seed value using IV as input. Pseudo-Random Key Generator (PRKG) generates a Session Key matrix (SKM) using a seed value. Images are encrypted using SKM to generate cipher images. The randomness of the TCGA code is tested using entropy measure and efficiency based on NIST Tests. SKM with high entropy value is used for image encryption. The Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI) values are used for calculating the randomness of cipher images.

Color Image Encryption Algorithm Based on a Chaotic Model Using the Modular Discrete Derivative and Langton’s Ant

In this work, a color image encryption and decryption algorithm for digital images is presented. It is based on the modular discrete derivative (MDD), a novel technique to encrypt images and efficiently hide visual information. In addition, Langton’s ant, which is a two-dimensional universal Turing machine with a high key space, is used. Moreover, a deterministic noise technique that adds security to the MDD is utilized. The proposed hybrid scheme exploits the advantages of MDD and Langton’s ant, generating a very secure and reliable encryption algorithm. In this proposal, if the key is known, the original image is recovered without loss. The method has demonstrated high performance through various tests, including statistical analysis (histograms and correlation distributions), entropy, texture analysis, encryption quality, key space assessment, key sensitivity analysis, and robustness to differential attack. The proposed method highlights obtaining chi-square values between 233.951 and 281.687, entropy values between 7.9999225223 and 7.9999355791, PSNR values (in the original and encrypted images) between 8.134 and 9.957, the number of pixel change rate (NPCR) values between 99.60851796% and 99.61054611%, unified average changing intensity (UACI) values between 33.44672377% and 33.47430379%, and a vast range of possible keys &gt;5.8459×1072. On the other hand, an analysis of the sensitivity of the key shows that slight changes to the key do not generate any additional information to decrypt the image. In addition, the proposed method shows a competitive performance against recent works found in the literature.

Expansion and optimization of ammonia import to the Republic of Korea for electricity generation

Ammonia is considered a promising energy source for achieving carbon neutrality because it is carbon-free. This study aims to evaluate the feasibility of ammonia-based power generation by conducting techno-economic and carbon footprint analyses of an integrated ammonia decomposition and phosphoric acid fuel cell system. Using a commercial process simulator, the power generation process is designed to reveal an energy efficiency of 46.7% and an upper limit for the ammonia price to compete with industrial electricity prices is identified as 421.3 $ tNH3–1 through economic analysis. Furthermore, the study establishes five different scenarios for ammonia import from the top ten exporting countries to the Republic of Korea (KOR), according to historical data, for optimization. Ammonia import is optimized in terms of exporting countries and quantities to satisfy the ammonia price while minimizing overall emissions using the Monte Carlo method for ammonia production costs and carbon dioxide emissions in each nation. The results show that carbon intensity falls within the range of 0.707–0.736 kgCO2-eq kWh−1, which exceeds the 20-year average value of carbon intensity in KOR if carbon-based ammonia is solely imported. However, the system can be competitive in terms of both economic and environmental aspects if the carbon–neutral ammonia ratio is over 78% (more than Scenario 4). In conclusion, this study statistically investigates the optimization results focusing on major ammonia export countries, identifies the trend of carbon intensity in the scenarios, and provides guidelines for reducing overall carbon intensity by considering the production, transportation, and utilization of ammonia.

A Histogram Analysis of the Pixel Grayscale (Luminous Intensity) of B-Mode Ultrasound Images of the Subcutaneous Layer Predicts the Grade of Leg Edema in Pregnant Women.

The technique most widely used to quantitatively measure leg edema is only a pitting edema method. It has recently become possible to digitize B-mode ultrasound images and accurately quantify their brightness using an image-analysis software program. The purpose of this study was to find new indices of the grade of leg skin, to study whether or not analyses of the subcutaneous layer of leg skin on ultrasound images using image-editing software program can be used to evaluate it and to digitize it. Images of 282 subcutaneous layers of leg skin in 141 pregnant women were obtained using a B-scan portable ultrasound device. Rectangular photographs (vertical: skin thickness; horizontal: width of probe) were obtained using an image-editing program, and the luminous intensity (pixel grayscale: 0-255) and thickness of the skin were calculated using a histogram. We investigated the correlation between these parameters and the grade of pitting edema (0-3). There was a significant positive correlation between the grade of pitting edema and the average luminous intensity value, its standard deviation, and the skin thickness (ρ = 0.36, ρ = 0.22, ρ = 0.51, p < 0.0001, respectively). In particular, there was strong positive correlation between the grade of pitting edema and both the total number of pixels in a rectangle × (multiplied by) the average luminous intensity value and the total number of pixels in a rectangle × the standard deviation of the average luminous intensity value (ρ = 0.58 and ρ = 0.59, p < 0.0001, respectively). We could quantitatively evaluate the grade of leg edema by analyzing ultrasound photographs of the subcutaneous layer of the leg skin using an image-editing software program and found new indices to digitize it.