Equalization Method Research Articles

To boundary value problems for a generalized hyperbolic equation with two fractional differentiation operators

Boundary value problems for a one-space-dimensional hyperbolic equation with two fractional differentiation operators and variable coefficients are considered. The method of finite differences is used for the approximate solution to the problems posed. Difference schemes for each of the problems are constructed, and by the method of energy inequalities for various relations between the orders of the fractional derivative (α, β) a priori estimates in differential and difference interpretations are obtained. The obtained estimates imply the uniqueness and stability of the solution with respect to the right-hand side and initial data, as well as the convergence of the solution of the difference problem to the solution of the original differential problem. Algorithms for the numerical solution of the problems posed are constructed.

An integrated UAV growth monitoring model of Cinnamomum camphora based on whale optimization algorithm.

To explore an effective analysis model and method for estimating Cinnamomum camphora's (C. camphora's) growth using unmanned aerial vehicle (UAV) multispectral technology, we obtained C. camphora's canopy spectral reflectance using a UAV-mounted multispectral camera and simultaneously measured four single-growth indicators: Soil and Plant Analyzer Development (SPAD)value, aboveground biomass (AGB), plant height (PH), and leaf area index (LAI). The coefficient of variation and equal weighting methods were used to construct the comprehensive growth monitoring indicators (CGMI) for C. camphora. A multispectral inversion model of integrated C. camphora growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. The optimal model was selected based on the coefficient of determination (R2), normalized root mean square error (NRMSE) and mean absolute percentage error (MAPE). Our findings indicate that apparent differences in the accuracy with different model, and the WOA-BPNN model is the best model to invert the growth potential of C. camphora, the R2 of the model test set was 0.9020, the RMSE was 0.0722, and the MAPE was 7%. The R2 of the WOA-BPNN model improved by 18%, the NRMSE decreased by 33%, and the MAPE decreased by 9% compared with the BPNN model. This study provides technical support for the modern field management of C. camphora essential oil and other dwarf forestry industries.

An urban-rural Fringe extraction method based on Combined Urban-rural Fringe Index (CUFI)

In this article, a multi-source data-based method for urban-rural fringe extraction is proposed to solve the problem of insufficiently accurate division of urban-rural fringe, which can conveniently and accurately realise the extraction of the area of urban-rural fringe. The method uses multi-source data such as night light remote sensing images, POI data and high-resolution remote sensing images. We constructed the Combined Urban-Rural Fringe Index (CUFI) model based on the characteristics of NDVI and NTL, POI kernel density value points that change from the city centre to the surrounding area. The calculation of CUFI involves three aspects. The initial step involves processing data, which includes reducing noise in nighttime light images and removing inaccurate information from POI data. The subsequent step involves calculating combined features of NTL and POI kernel density, which includes analyzing the kernel density of POI data, standardizing the results of POI kernel density and nighttime light data, computing NTL & POI indexes using the equal weight combined feature calculation method and reclassifying NTL & POI indexes .The third part involves rejecting misinformation using NDVI. This includes calculating the NDVI index using high-resolution satellite data, rejecting bare land information in the NDVI index using nighttime light data, and reclassifying the processed results. The reclassified results are then multiplied with the reclassification results of the NTL&POI index to obtain the CUFI calculation results. In order to verify the effectiveness and reliability of the method, Tangshan City, Hebei Province was selected as the experimental area, and the method was used to compare and analyse the accuracy with the traditional urban built-up area boundary extraction method. The results show that compared with the traditional method, the extraction accuracy of the CUFI method is higher, reaching 89.51%, which is able to effectively identify urban villages and lakes in the urban area, as well as improving the resolution of extracting Urban-Rural Fringe using NTL& POI methods, and also the urban-rural fringe which has weak night light and fewer POI points, but actually has urban-rural duality attributes Extraction.

Entrepreneurial orientation and digital transformation as drivers of high organizational performance: Evidence from Iraqi private banks

This research investigated how digital transformation affects the relationship between entrepreneurial orientation and organizational performance among private banks in Baghdad, Iraq. The study population consisted of 5,000 individuals holding various positions, including general manager, deputy general manager, department head, section head, and employee. To obtain a representative sample, the researchers employed the stratified equal random sampling method and randomly selected participants. As a result, a total of 406 questionnaires were distributed. However, only 197 questionnaires were valid and suitable for analysis, representing a percentage of 49% of the distributed questionnaires. The primary means of gathering information was through a questionnaire, and the data obtained were analyzed using inferential statistical techniques. The research findings indicated that the different aspects of entrepreneurial orientation, such as being proactive, taking risks, and flexibility, had a significant and beneficial influence on the organization's overall performance and its ability to operate effectively and engage socially. Nonetheless, the innovation aspect did not have a notable impact on the performance of the organization and its related dimensions. In addition, the research indicated that digitalization has a beneficial impact on the relationship between entrepreneurial orientation and the performance of an organization, making it more powerful. The research suggested that private banks operating in Baghdad province ought to promote innovation, foster productive social interactions, enhance their operational efficiency, facilitate digital transformation, and leverage their moderating influence to improve the performance of the organization by boosting entrepreneurial orientation.

ПЕРЕДАЧА ПРАГМАТИЧЕСКОГО ПОТЕНЦИАЛА В ВЫСТУПЛЕНИЯХ ЭКОАКТИВИСТОВ (В ОРИГИНАЛЕ И ПЕРЕВОДЕ)

The article examines the characteristic features of pragmatic meaning implementation in such pragmatically intense texts as eco-activists’ speeches. It also analyzes some variants of their translation in the aspect of reproduction of the original pragmatic potential. It has been found that in most cases the pragmatic potential is realized through an appeal to universal categories that coincide with the general worldview, regardless of the linguistic and cultural background of the audience, such as unity, equality, well-being, and children. In terms of structural and lexical content, the speech units under study do not appear to be of any significant difficulty in translation due to the genre features of public speeches aimed at the wide audience. In this regard, the translation can preserve the exact meaning of the original, have an equal perlocutionary effect and methods of achieving it. Distortion of the pragmatic potential or its loss occurs in the case of culturally marked units present in the original. As a result, the pragmatic potential does not coincide in the original and its translation. However, the percentage of such expressions in our study is relatively low.

Cetacean Optimization Based Medical Image Contrast-Enhancement Technique for Improving Disease Diagnosis in Cardiac MRI

Conventional preprocessing methods in medical imaging can effectively reduce the combination of Gaussian and Impulsive noise, while still maintaining the crucial features such as edges within the images. However, these techniques are found to lag in the optimizing the certain image parameters which play a crucial rule in enhancing the input images and thus may lead to failing in preserving the edges that may adversely affect the early diagnosis of diseases. An attempt has been made to enhance the contrast of cardiac MR (Medical Resonance) images using Cetacean Optimization Algorithm (COA) for improving disease diagnosis. Input cardiac images have been acquired from the free online available databases viz., SCMR consensus and AMRG Atlas. The methodology includes integration of the cost function with contrast measure based on certain metrics to create a newer transformation function. It results in enhanced search pattern using a transformation function in spatial domain and improves the pixel intensity to increase the resolution of an image. The developed algorithm’s performance was evaluated by computing various parameters including peak signal-to-noise ratio (PSNR), structural similarity index measurement (SSIM), mean square error (MSE), and normalized absolute error (NAE). Analysis of the results reveals that the proposed method achieves the highest PSNR (72 dB) and SSIM (0.99) values, along with the lowest NAE (0.16%) and MSE (0.22%) compared to both the particle swarm optimized texture-based histogram equalization (PSOTHE) method and the modified sunflower optimization (MSFO) method. The results indicate that the suggested strategy might improve the intricate details of the input cardiac MRI images. This enhancement can contribute to the efficient identification of cardiac disorder-specific biomarkers.

Sustainable pork production and processing: a step toward empowering tribal women in Northeast India.

This study explores the transformative potential of sustainable pork production and processing as a tool to empower tribal women in the northeast region (NER) of India. The NER is faced with multiple challenges, such as poverty, gender inequality, and poor livelihood methods. Therefore, enhancing sustainable production and processing methods for pork, which is their staple food, presents not only an opportunity for the socio-economic development of the region but also an effective tool for the economic empowerment of tribal women. Through a primary survey of pork value chain actors in Assam, Meghalaya, and Nagaland (the largest producers and consumers of pork in the NER), the study outlines the current practices and barriers to sustainable pork production methods. Although the consumption of pork has remained unchanged and that of processed pork items is on the rise, the production of pork is drastically declining. Therefore, reviving pork production in the NER can be instrumental in building sustainable livelihood models, especially for tribal women in the region. The study explores the effectiveness of a community-based, 'model village approach,' where capacity building around sustainable pork production, processing, and waste management techniques results in the economic empowerment of women. The findings from the post-impact analysis of the capacity-building approach call for policy intervention and the establishment of supportive networks to enhance the growth of a sustainable pork production system across NER, thereby contributing to the attainment of Sustainable Development Goal (SDG) targets proposed by the Indian economy.

Delayed Impulsive Control for Lag Synchronization of Delayed Neural Networks Involving Partial Unmeasurable States.

In the framework of impulsive control, this article deals with the lag synchronization problem of neural networks involving partially unmeasurable states, where the time delay in impulses is fully addressed. Since the complexity of external environment and uncertainty of networks, which may lead to a result that the information of partial states is unmeasurable, the key problem for lag synchronization control is how to utilize the information of measurable states to design suitable impulsive control. By using linear matrix inequality (LMI) and transition matrix method coupled with dimension expansion technique, some sufficient conditions are derived to guarantee lag synchronization, where the requirement for information of all states is needless. Moreover, our proposed conditions not only allow the existence of unmeasurable states but also reduce the restrictions on the number of measurable states, which shows the generality of our results and wide-application in practice. Finally, two illustrative examples and their numerical simulations are presented to demonstrate the effectiveness of main results.

Classification of Pancreatic Cystic Lesions Using ResNet Deep Learning Network in Confocal Laser Endomicroscopy Videos

Accurate classification of pancreatic cystic lesions is crucial to differentiate mucinous lesions of malignant potential. We utilized the ResNet-50 and ResNet-101 network to develop a model for classification of the pancreatic cystic lesions. A total of 50 videos, 13,425 images, from five types of pancreatic cystic lesions and utilize the image rotation and contrast reversal scheme for the training. We adopt a contrast limited adaptive histogram equalization method onto the test video. Our method can automatically classify the feature type and record the prediction results frame by frame. The method has been evaluated on 18 test videos and achieves an accuracy 94% overall.

Primena endoskopa kod ispitivanja motornih vozila

Industrial endoscopes are devices that are intended for visual inspection of inaccessible spaces without disassembling parts or any destructive method. Industrial endoscopes use their own light source, strong enough to illuminate inaccessible spaces where there is no natural or artificial light. Endoscopes are used to inspect pipelines in steam boilers, central openings of turbines, condition of internal parts of generators, surfaces of gears in transmissions, surfaces of cylinders and damage to valves of engines and reciprocating compressors, pressure vessels, position of core transformers, condition of axial compressors, jet engines. In the case of assemblies and parts of modern motor vehicles, where, due to their compact structure, it is not possible to perform inspection and control without complex and expensive disassembly, the application of the endoscope simplifies and significantly lowers the cost of the procedure. Industrial endoscopy began to be applied as a method of control and inspection, with a certain amount of subjectivism. The hardware, and especially the software used in today's endoscopes, has enabled industrial endoscopy to become an exact measurement method. This allows industrial endoscopy to be included in the equal methods of a laboratory accredited according to the SRPS ISO IEC 17025:2017 standard. as repeatability and reproducibility criteria given in the series of standards SRPS ISO 5725:2007. A brief critical review in the application of existing standards, is presented. In conclusion, recommendations related to risk management are given.

Using RAM method for optimal selection of flame retardant nanocomposite material fabrication solution

This study aimed to optimize the selection of manufacturing solutions for flame retardant nanocomposite materials based on polyvinyl chloride (PVC). A total of eight different options were considered. The first option utilized PVC as the base material, and the subsequent options were carried out by adding specific amounts of reinforcing agents, including aluminum hydroxide (ATH) and zinc borate (ZB). The seven following options were denoted by their respective symbols: 5ATH/PVC, 10ATH/PVC, 15ATH/PVC, 5ZB/PVC, 10ZB/PVC, 15ZB/PVC, and 5ATH/5ZB/PVC. The number preceding the symbol of the reinforcing agent represents the percentage of the reinforcing agent added to the PVC material. For example, 5ATH/PVC signifies the addition of 5% of ATH reinforcing agent to the PVC material. To evaluate each option, five different indices were employed. The weight for each index was determined using four different methods, including the Equal method, Entropy method, MEREC method, and LOPCOW method. The RAM method was used to select the best option. The combination of the RAM method and the four weight determination methods generated four different datasets of option rankings. In all four of these datasets, the best and worst options consistently matched. The results indicated that the 15ATH/PVC option was deemed the best, while the pure PVC option was the worst.

A New Equalization Method for Lithium-Ion Battery Packs Based on CUK Converter

A New Equalization Method for Lithium-Ion Battery Packs Based on CUK Converter

Phase Current Equalization Method of IPMSM-based On-board Boost Converter for Electric Vehicles

Phase Current Equalization Method of IPMSM-based On-board Boost Converter for Electric Vehicles

Enhancing Gain Uniformity in WDM Networks Across C and L Bands Through Hybrid Optical Amplifier Integration

This study explores strategies for optimizing EDFA gain in the context of (WDM and DWDM systems. By reviewing recent literature, we investigate various approaches to enhance EDFA performance, considering factors such as input power, pump power, and fiber length. Our analysis covers optimization algorithms, gain flattening techniques, adaptive gain equalization methods, and hybrid amplifier configurations. Additionally, we examine studies addressing nonlinear effects and the allocation of pump power to maximize gain efficiency. Recent advancements, including machine learning-based approaches and novel gain equalization techniques using phase-shifted fiber Bragg gratings, are also discussed. The findings underscore the significance of tailored EDFA gain optimization methods for improving the overall performance and efficiency of WDM and DWDM systems in optical communication networks.

Blind Equalization Method for Ultraviolet Light Scattering Channel Based on Hybrid Neural Network

Blind Equalization Method for Ultraviolet Light Scattering Channel Based on Hybrid Neural Network

Novel Passive Equalization Methods for Lithium-ion Batteries Utilizing Real-Time Internal Resistance Measurements

Novel Passive Equalization Methods for Lithium-ion Batteries Utilizing Real-Time Internal Resistance Measurements

A multi-player game equilibrium problem based on stochastic variational inequalities

<p>In this paper, we studied a generalized Nash equilibrium problem where the constraint conditions were limited to a certain probability. The existence of an equilibrium solution for the vector-valued optimization problem was verified using Ky Fan's inequality and Lusin's theorem, considering the conditions of lower semi-continuity and concavity. Based on the study of the variational inequality method, we proposed a new algorithm to solve the problem. Furthermore, we analyzed the convergence of the algorithm. Finally, we applied the model to examine the economic benefits of digital currency issuance, corroborating the algorithm's effectiveness with a concrete numerical example.</p>

Non-fragile ${H_\infty }$ filter design for uncertain neutral Markovian jump systems with time-varying delays

<abstract> <p>This paper deals with the problem of non-fragile ${H_\infty }$ filter design for a class of neutral Markovian jump systems with parameter uncertainties and time-varying delays. The parameter uncertainties are norm-bounded, and time-varying delays include state and neutral time-varying delays. First, by selecting the appropriate stochastic Lyapunov-Krasovskii functional and using the integral inequality technique, sufficient conditions are obtained to make the filtering error system not only stochastically stabilized, but also mode and delay dependent. Second, by the utilizing linear matrix inequality method, sufficient conditions are obtained for the filtering error system to be stochastically stable and to have a prescribed ${H_\infty }$ performance level $\gamma $. Based on this result, by processing the uncertainty terms, sufficient conditions for the existence of the filter are obtained, and mode-dependent filter parameters are given. Finally, by numerical simulation, the feasibility and validity of the theoretical results are verified.</p> </abstract>

Flammability limits of theoretical azeotropic mixtures consist of R1243zf, RE170 and flame retardants (R13I1, R134a, or R227ea)

3,3,3-trifluoropropene (R1243zf) is a low climate change effect refrigerant that has great development potential. However, R1243zf is flammable and its safety classification is A2 as per ISO standard 817. To reduce its risk of flammability, the method of using mixed refrigerants in practical applications is an effective approach. In this paper, an experimental system was established according to the ASHRAE standard 34 to measure the flammability limits of four azeotropic mixtures containing R1243zf. First, the critical suppression ratio (CSR) of R13I1/R1243zf was tested out that is 0.353. Further measurements were made to determine the lower flammability limits (LFLs) and critical suppression concentrations (CSCs) of three ternary mixtures consisted of R1243zf, thermodynamic performance enhancer (RE170) and flame retardants (R13I1, R134a or R227ea), at various compositions. The experimental non-flammable proportions of R1243zf/RE170/R13I1, R1243zf/RE170/R134a, and R1243zf/RE170/R227ea were 31.81 %, 5.49 %, and 22.42 %, respectively. Besides, a comparison was made between the experimental data and the predicted results by means of three different theoretical methods (the equal effect method, thermal balance method, and group contribution method). The fresh experimental results will provide practical guidance for the applications that utilize the R1243zf blends in low flammability risk.

Performance Study of Multipath Effect in 5G Millimeter-Wave Channel

5G has been essentially a buzzword for several years, but according to the experts, from 2022 onward, there will be an inflection point between network maturity and the availability of 5G. To make 5G a reality, we must minimize all propagation losses. One of the possible factors that reduces the performance of 5G transmission is the multipath effect. In this paper, we investigate the severity of the multipath effect in the 5G millimeter-wave (mmWave) channel and mitigate the multipath effect using adaptive equalization based on the least mean square (LMS) algorithm to improve the performance of 5G wireless signal transmission. A mmWave channel simulator, NYUSIM, provides complete data for all resolvable multipaths in a specific channel configuration. An analysis of bit-error-rate (BER) based on the minimum BER (MBER) and minimum mean square error (MMSE) optimization criterion is performed to measure the improved performance of a 5G data channel simulated under line-of-sight (LOS) and non-LOS (NLOS) paths. A good overall performance of BER based on the MBER and MMSE criteria is attained using the LMS equalization method in a micro-urban area at a maximum data rate of 50 Mbps. For both LOS and NLOS conditions, the increase in data rate to 55.56 Mbps and 62.5 Mbps causes a significant decrease in BER performance. In conclusion, the primary factor affecting the BER performance is the data rate, not the frequency or transmitter-to-receiver distance.