Index Method Research Articles

Development and Validation of the HPLC Method for Simultaneous Quantification of Glucose and Xylose in Sugar Cane Bagasse Extract.

A validated rapid high-performance liquid chromatography (HPLC)-refractive index (RI) method was developed for the identification and quantification of glucose and xylose in hydrolyzed bagasse extract. The separation of compounds was achieved on Eurokat® H column (300 × 8mm, 10μm) at 75°C, using 0.01N sulfuric acid solution as mobile phase and 0.6mL/min as flow rate. The method was validated based on accuracy, precision, linearity, robustness, uncertainty, limit of detection (LOD) and limit of quantification (LOQ). Total chromatographic analysis time per sample was ~11min. Calibration plots were linear over the concentration ranges 11-100μg/100μL for glucose and xylose. The LOD was 0.8ppm and LOQ was 2.5ppm. The high recovery and low relative standard deviation confirm the suitability of the method for determination of glucose and xylose in bagasse extract. The proposed HPLC-RI method was accurate, fast and robust and required less run time due to less analytes retention times and allowed optimal energy consumption owing to lower column oven temperature.

Assessment of the Spatial Distribution of Water Quality for Surface and Groundwater at Bonny Island, Nigeria

The aim of the study was to assess the spatial distribution of water quality for surface and ground water at Bonny Island in Rivers State, Nigeria. Surface and Groundwater samples were collected from 9 sampling locations and analyzed for physicochemical parameters, heavy metals, and petroleum hydrocarbons. The contaminants in the surface and groundwater were measured using a variety of methods. Heavy metals in the water were measured using gas chromatography, PAHs were measured using Atomic Absorption Spectrophotometry (ASS) while THC were measured using HACH DR/890 colorimeter. The water quality index (WQI) was calculated using the Weighted Arithmetic Index Method while Principal Component Analysis was used to understand the distribution of the physicochemical parameters, heavy metals, and petroleum hydrocarbons. The results showed that the WQI for both surface and groundwater samples ranged from 55.22 – 125.39, indicating poor to unfit water quality for consumption. In contrast, a control location away from the industrial activities had good water quality with WQI between 35.19 and 45.77. Principal component analysis revealed that the surface water in the industrial area were contaminated with lead, Poly Aromatic Hydrocarbon (PAHs), Total Petroleum Hydrocarbon which indicate oil and gas activities. High chloride, nitrate and sulphate levels were also observed in surface water close to the NLNG plant. Limiting further contamination of the surface and groundwater can be achieved by constant effluent and plume stack monitoring by regulatory agencies. Industrial stakeholder should set up subsidized clinics to provide treatment for any gastrointestinal illnesses or renal damage suffered by residents.

Modeling the Transmission Dynamics of Tuberculosis in Humans

Tuberculosis (TB) is a major threat to human health particularly in most of developing countries. In this article, we formulate and analyze a deterministic model for the transmission dynamics of pulmonary and extra-pulmonary tuberculosis. The next generation method is employed to find the basic reproduction number R0 which helps to determine whether TB clears or persists in the human population. Global stability of model equilibria is done through Lyapunov functions whereas the normalized forward sensitivity index method is adopted to determine parameters that drive tuberculosis. Analysis shows that both TB free and endemic equilibria exist. The TB free equilibrium is globally asymptotically stable whenever the basic reproduction number R0 < 1 whereas the endemic equilibrium is globally asymptotically stable whenever R0 > 1. Sensitivity analysis shows that the TB infection rate, the fraction of individuals who progress to pulmonary tuberculosis and its induced death drive TB. Numerical results indicate that when there are no interventions, susceptible humans decline significantly with time until when they are attracted to the steady state whereas latently infected, pulmonary and extra-pulmonary TB individuals increase until when they settle at the equilibrium states supporting the analytical results for existence of the endemic equilibrium. In light of these findings, we recommend treating humans infected with pulmonary TB who are carriers of the disease.

Spatiotemporal Distribution Characteristics and Influencing Factors of Freeze–Thaw Erosion in the Qinghai–Tibet Plateau

Freeze–thaw (FT) erosion intensity may exhibit a future increasing trend with climate warming, humidification, and permafrost degradation in the Qinghai–Tibet Plateau (QTP). The present study provides a reference for the prevention and control of FT erosion in the QTP, as well as for the protection and restoration of the regional ecological environment. FT erosion is the third major type of soil erosion after water and wind erosion. Although FT erosion is one of the major soil erosion types in cold regions, it has been studied relatively little in the past because of the complexity of several influencing factors and the involvement of shallow surface layers at certain depths. The QTP is an important ecological barrier area in China. However, this area is characterized by harsh climatic and fragile environmental conditions, as well as by frequent FT erosion events, making it necessary to conduct research on FT erosion. In this paper, a total of 11 meteorological, vegetation, topographic, geomorphological, and geological factors were selected and assigned analytic hierarchy process (AHP)-based weights to evaluate the FT erosion intensity in the QTP using a comprehensive evaluation index method. In addition, the single effects of the selected influencing factors on the FT erosion intensity were further evaluated in this study. According to the obtained results, the total FT erosion area covered 1.61 × 106 km2, accounting for 61.33% of the total area of the QTP. The moderate and strong FT erosion intensity classes covered 6.19 × 105 km2, accounting for 38.37% of the total FT erosion area in the QTP. The results revealed substantial variations in the spatial distribution of the FT erosion intensity in the QTP. Indeed, the moderate and strong erosion areas were mainly located in the high mountain areas and the hilly part of the Hoh Xil frozen soil region.

Research of proton exchange membrane fuel cell degradation index and prediction method for automotive vehicles

Comprehensively describing proton exchange membrane fuel cell (PEMFC) degradation behavior and accurately predicting degradation under dynamic operating conditions have become a prerequisite for automotive PEMFC health maintenance and life extension control. In this paper, a PEMFC comprehensive degradation index that incorporates time-varying physical parameters with multi-scale degradation information is proposed. The nonlinear degradation tendency of exchange current density at dynamic operating conditions is considered in this index. Then a Holt-Winters convolutional neural network (H-W CNN) prediction framework is proposed. The PEMFC reversible degradation features are enhanced by the Holt-Winters smoothing algorithm and a multivariate CNN model is constructed to conduct PEMFC multi-step degradation prediction under insufficient degradation data. Experimental result shows that the degradation index can characterize the comprehensive degradation of PEMFC under dynamic operating conditions. For mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) under 3 h prediction horizon, the H-W CNN prediction framework improves the performance by 38.8%, 38.4%, 37.9% compared to echo state network (ESN). Under 15 to 45 h prediction horizon, the H-W CNN demonstrates better learning potential for PEMFC reversible degradation and degradation trend prediction ability compared with long short-term memory networks (LSTM), ESN d univariate CNN models.

Impact of [formula omitted] theory on the geometry of charged stellar objects

The main objective of this article is to study the viable charged compact stellar structures in f(R,φ,χ) theory, where R, φ and χ denote the Ricci scalar, scalar field and kinetic term, respectively. For this purpose, a static spherical metric with anisotropic matter configuration is considered to analyze the compact stellar structures. We consider a particular model of this modified theory to formulate the explicit expressions of energy density and pressure components that govern the relationship between matter and geometry. The unknown constants in the Finch-Skea solutions are determined by the smooth matching of interior and exterior spacetimes to analyze the configuration of the proposed stellar structures. Physical parameters such as matter variables, energy bounds and equation of state parameters are analyzed to examine the viability of the considered stellar objects. Further, we use sound speed and adiabatic index methods to examine the stability of the compact objects. The rigorous analysis and satisfaction of necessary conditions lead to the conclusion that the stellar objects studied in this framework are viable and stable in the presence of charge.

Tool wear monitoring based on scSE-ResNet-50-TSCNN model integrating machine vision and force signals

Abstract In the realm of mechanical machining, tool wear is an unavoidable phenomenon. Monitoring the condition of tool wear is crucial for enhancing machining quality and advancing automation in the manufacturing process. This paper investigates an innovative approach to tool wear monitoring that integrates machine vision with force signal analysis. It relies on a deep residual two-stream convolutional model optimized with the scSE(Concurrent Spatial and Channel Squeeze and Excitation) attention mechanism (scSE-ResNet-50-TSCNN). The force signals are converted into the corresponding wavelet scale images following wavelet threshold denoising and Continuous Wavelet Transform (CWT). Concurrently, the images undergo processing using Contrast Limited Adaptive Histogram Equalization (CLAHE) and the Structural Similarity Index Method (SSIM), allowing for the selection of the most suitable image inputs. The processed data are subsequently input into the developed scSE-ResNet-50-TSCNN model for precise identification of the tool wear state. To validate the model, the paper employed X850 carbon fibre reinforced polymer (CFRP) and Ti-6Al-4V titanium alloy as laminated experimental materials, conducting a series of tool wear tests while collecting pertinent machining data. The experimental results underscore the model's effectiveness, achieving an impressive recognition accuracy of 93.86%. When compared with alternative models, the proposed approach surpasses them in performance on the identical dataset, showcasing its efficient monitoring capabilities in contrast to single-stream networks or unoptimized networks. Consequently, it excels in monitoring tool wear status and promots crucial technical support for enhancing machining quality control and advancing the field of intelligent manufacturing.

Development and Validation of a Novel Surface Defect Index (SDI) Method for the Effective Quality Evaluation of Concrete Surfaces

Concrete defects have a significant impact on concrete constructions. These defects should be considered not only aesthetic defects but also structural defects. In this study, a novel Surface Defect Index (SDI) method was developed to quantify the defect volume according to liquids’ penetrating properties by applying ready-mixed plaster (RMP). The SDI refers to the volumetric proportion of all apparent and unapparent defects in a given area of concrete, and it is expressed as a percentage of the total volume affected by defects. The proposed SDI method was validated and tested under various controlled defect configurations. Regardless of the specific characteristics of each defect configuration, the SDI method consistently demonstrated a high level of consistency, repeatability, and reproducibility, with coefficients of variation (CVr and CVR) below 5% and with correlation coefficients of R2 = 0.9968. The method succeeded in assessing the surface quality levels through the SDI, demonstrating a significant correlation between this index and the volume of defects. The proposed index was tested on real concrete surfaces, affirming its efficacy in accurately quantifying the volume of surface defects; thus, it can provide an important metric for quality control. Moreover, it provides an excellent evaluation of the quality of concrete surfaces.

Quantifications of service quality factors using the relative importance index method for passenger ferry service in Bangladesh

Service Quality (SQ) of passenger ferries greatly influences passengers' travel experience. The purpose of this article is to identify the passenger ferry's SQ factors and evaluate them using the Relative Importance Index (RII) method. After a thorough review of the literature and passenger interviews, 28 distinct SQ elements are identified, categorised into six major groups, and depicted using the Ishikawa (fishbone) diagram. Different SQ factors are ranked according to their relative importance using the relative importance index method. According to the SQ, the groups and factors are prioritised. Based on the study’s findings, recommendations are made to enhance the passenger ferry's SQ. The factors and groups influencing the SQ (those in need of attention) are discussed.

Personnel development under digital economy conditions

Personnel development under digital economy conditions

MEASURING THE AGRICULTURAL TOTAL FACTOR PRODUCTIVITY OF PROVINCES IN TURKEY USING MALMQUIST INDEX

This study aims to reveal the total factor productivity levels in the agricultural sector in 81 provinces of Turkey by using the Malmquist index method over the period 2009-2019. The results extracted from the Malmquist index findings show that index value changed between 1.186 and 0.952, agricultural productivity increased in 75 provinces and decreased in 6 provinces. In addition, our findings confirm technological change affects the change in agricultural productivity levels in all provinces in Turkey, and that technology is a determining factor in agricultural productivity in all provinces. From a policy perspective, the results suggest that authorities in Turkey should develop and implement technologies that will make the sector productive, to encourage and support infrastructure, research and publication studies on technology. In addition, this research claims that the regional incentive system can be revised and, it can build an incentive system based on performance and efficiency in which provinces or businesses operating in this field are classified according to their productivity.

Assessing Water Quality Index in Kani-Qirzhala Area, Erbil City, Kurdistan Region of Iraq

Groundwater is an essential water source in many areas in the Kurdistan Region of Iraq (KRI). The groundwater can be used for many purposes such as municipal, agricultural, and domestic. The objective of this study is to assess the quality of groundwater in the Kani-Qirzhala area. The study area covers 60 km2, and includes twenty-seven water wells, which have been selected and used to study the water quality parameters in such area. Canadian Council of Ministers for the Environment Water Quality Index method was used to evaluate Water Quality Index and SPSS software version 25 even to study the correlation between Water Quality Index and water quality parameters. The results indicated that the quality of water in most of the wells is fair, except the quality of water in wells 19, 24, and 27 is found to be poor. Well19 is located close to the Erbil landfill site (Kani-Qirzhala) and this poor quality is due to the effect of Landfill site leachate. The Well 24 is in the Erbil store area where the leachate of landfill is discharged to this surrounding area. The quality of water in well 27, on the other hand, was marginal and existed on the eastern side of the study area. The significant correlation revealed a good correlation between WQI and water quality parameters such as (pH, EC, TDS, Ca2+ Na1+, Mg2+, NO3-1, K1+, SO42-, Cl1-, Hardness, Alkalinity, Iron, and Copper).

Investigating the influence of human errors in master-pilot information exchange on maritime accident risk during pilotage

Pilotage-related errors have led to too many accidents in recent years, resulting in significant economic losses and disruptions in global logistics. Despite its importance, Master-Pilot Exchange (MPX) can be overlooked due to several factors. This study focuses on MPX, a standard protocol for information exchange between shipmasters and maritime pilots to ensure safe ship handling. Deficiencies in MPX procedures have been highlighted in various accident reports, emphasizing the need for improvement. This research aims to identify an optimal MPX process, evaluate potential shortcomings, assess their likelihood and severity, and analyse the human factors contributing to these deficiencies. The study utilizes a fuzzy Bayesian Network (BN) to model the MPX process and identify factors that may lead to its failure. It also employs the Success Likelihood Index Method (SLIM) approach to calculate the probability of human errors in the MPX process and identify the performance-shaping factors triggering them. The finding of the Bayesian method shows that the machinery problem and the navigational equipment problem are the two most significant root causes of MPX process failure. According to the SLIM findings, providing details of "the ship's contingency plan", and "navigational information" are the two most significant tasks for this process. Among the identified performance-shaping factors, the degree of teamwork and harmony, experience and knowledge appear to be the three most significant contributors with the highest human error probability (HEP) in mentioned tasks. This study represents a significant contribution to research on master-pilot interactions, addressing a critical aspect of maritime safety.

Analysis of the Occurrent Models of Potential Debris-Flow Sources in the Watershed of Ching-Shuei River

The areas around the Ching-Shuei River saw numerous landslides (2004–2017) after the Jiji earthquake, profoundly harming the watershed’s geological environment. The 33 catchment areas in the Ching-Shuei River watershed and five typhoon and rainstorm events, with a total of 165 occurrences and non-occurrences, were analyzed, and the training and validation were categorized into 70% training and 30% validation. A landslide disaster is deemed, for the purposes of this research, to have taken place if SPOT satellite images taken before and after an incident show a Normalized Difference Vegetation Index difference larger than 0.25, a slope of less than 30 degrees, and a number of connected grids greater than 10. The analysis was carried out using the instability index method analysis with Rogers regression analysis and artificial neural network. The accuracy rates of neural network, logit regression, and instability index analyses were, respectively, 93.3%, 80.6%, and 70.9%. The neural network’s area under the curve was 0.933, indicating excellent discrimination ability; that of the logit regression analysis was 0.794, which is considered good; and that of the instability index analysis was 0.635, or fair. This suggests that any of the three models are suitable for the danger assessment of large post-earthquake debris flows. The results of this study also provide a reference and evidence for specific sites’ potential susceptibility to debris flows.

Investigating the Response of Vegetation to Flash Droughts by Using Cross-Spectral Analysis and an Evapotranspiration-Based Drought Index

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems.

Research on optimal allocation of surface ship formation based on index method and multi-objective programming

In recent times, marine engineers have progressively turned to collaborative efforts involving multiple ships to accomplish intricate tasks at sea and enhance the efficacy of maritime transportation. This trend is also observed in the context of surface ships, where coordinated actions among multiple vessels can enhance combat capabilities. Nevertheless, the assessment of ship formation coordination’s effectiveness has emerged as a significant challenge. Consequently, this research paper presents a quantitative evaluation framework for ship performance indicators and develops a ship formation model grounded in multi-objective constraints that account for the complexities of the marine environment. This paper presents the establishment of a ship evaluation system that encompasses the impact of auxiliary equipment, the ship’s platform, and trained personnel. The study utilizes aircraft carrier battle groups from four distinct countries as case examples to obtain quantitative evaluation results regarding combat performance. Furthermore, the analysis examines the effects of two extreme marine environments on surface ships. The organization of new surface ship formations is conducted based on a multi-objective planning model that is tailored to specific surface ship formations. All kinds of combat performance indexes are better than the formation of this particular surface ship. The experimental results show that the model can integrate different kinds of equipment performance parameters into a unified system and consider the comprehensive factors of equipment, platform and people. According to the requirements of task formation and the limitations of the actual Marine environment, a stable formation can be formed quickly, which can be superior to a specific formation in all aspects. Good results are obtained and the effectiveness of the model is verified.

Analysis of Road Damage Level Using the Pavement Condition Index (PCI) Method on the Surabaya-Gresik Toll Road, East Java

The Surabaya–Gresik toll road is a crucial infrastructure connecting Surabaya City with Gresik Regency. In industrial areas such as Gresik Regency, this toll road is indeed needed to expedite the flow of industrial goods distribution to Surabaya City. The toll road experiences frequent damage, such as alligator cracking, as it is traversed daily by heavy traffic. If the road, as a connecting infrastructure, is damaged, it will impede the flow of vehicles passing through it. Therefore, road maintenance is necessary to ensure optimal service for passing vehicles. In this research, an analysis of road damage on the Surabaya – Gresik toll road seeks solutions for addressing these issues utilizing the method of Pavement Condition Index (PCI). The method involves several stages, including a survey of road conditions, determination of severity levels, assessment of damage, and determination of pavement condition. The survey was conducted in 100-meter segments from KM 10 to KM 14, revealing various types of damage on the toll road, including alligator cracking, bleeding, corrugation, shoving, potholes, and more. Thereafter, an analysis of the severity level and damage assessment was carried out, resulting in an average PCI value of 68, categorized as a "Good" condition. Based on these findings, it is recommended to address this issue through routine maintenance, including repairing minor damage, patching potholes, sweeping, repairing pavement edge damage, sidewalk maintenance, side channel and complementary building drainage, road equipment, and roadside maintenance.

Fluvio-geomorphic change of the Padma-Meghna river course using the NDWI and MNDWI techniques

ABSTRACT This study intends to investigate the fluvial-geomorphic change and erosion-accretion processes of two significant rivers. The 2149 km2 research area’s overall erosion and accretion were depicted using multi-temporal Landsat images and Normalized Difference Water Index, Modified Normalized Difference Water Index methods to measure and investigate change. However, focus has been placed on four unique sections that are prone to erosion, and the bank migration of the section has been measured in order to depict the actual state of erosion. The Padma-Meghna River eroded approximately 11.0, 77.0, and 13.0 km2 between 1973–1978, 1978–1989, and 1989–1994. However, 78.0 and 48.0 km2 of accretion occurred in the years between 1994 and 1999 and 1999 and 2004. Moreover, between 2004 and 2021, the river’s erosional activity was remarkably dynamic compared to deposition. Besides, 64 km2 and 4 km2 of land accretion occurred during 2008–2014 and 2014–2019, while 77 km2 and 68 km2 of land eroded during 2004–2008 and 2019–2021. The overall rates of erosion and accretion are 5.12% and 4.04%, respectively. Statistically, both banks of the Padma River eroded about 2 km from 1973 to 2021. Padma-Meghna confluences are more unstable and susceptible to change. The Meghna’s left bank moved 4.5 km east between Goshairhat and Haimchar in 1989, and in 2008, the river shifted 4.8 km west from the river of 1994. In 1989, it moved 5 km east from a previous location between Goshairhat and Haiderganj, and in 2008, it moved 6.3 km west from the 1989 river. The bank migrated 12 km eastward in 2014 from where it was in 2008 through the bar development. The Mehendiganj Upazila’s eastern side lost more than 7.4 km between 1973 and 2021, and the current major channel is simply 7.4 km west of the 1973 river. The findings of the dynamic changes might be useful to planners, developers, researchers, and government agencies as they develop and put into practice new development initiatives and river basin management.

RisDes_Index: An Index for Analysing the Advance of Areas Undergoing Desertification Using Satellite Data

The proposal for a method of identifying the occurrence of desertification that has a strong association with in situ data leads to more assertive results when analysing the contribution of climate and social and economic factors to advancing the process. This study aimed to develop a methodology called the RisDes_Index to evaluate the evolution of the desertification process based on satellite data. The concept of the RisDes_Index method was based on the reflectance variables of the R, B and G bands, albedo and LAI of the Landsat 5/TM and Landsat 8/OLI satellites. Principal component analysis was used to assess the biophysical basis of the RisDes_Index by associating the results with micrometeorological data, physical and chemical properties, and vegetation cover data collected from five experimental sites in the semi-arid region of Brazil. These sites included one from a seasonally dry forest (i.e., the Caatinga), an agricultural cactus plantation, an area undergoing desertification, and two irrigated sugarcane crops (wetlands), one with and one without straw cover. The RisDes_Index was applied to all pixels of the images from 5 December 1991, 14 November 2001, 20 November 2009 and 6 October 2016 of an important desertification nucleus (DN) in the semi-arid region of Brazil, i.e., the DN of Cabrobó. The proposed RisDes_Index was able to identify areas with significant processes of desertification, which mainly occur in areas of sandy, acidic, bare soils with a high β value (Bowen ratio) and high soil temperature. The results of the RisDes_Index showed that in 5 December 1991, desertified areas comprised 38% of the total area of the DN of Cabrobó, expanding to 51% in 2016. Application of the RisDes_Index confirmed the advance of desertification in the DN of Cabrobó. This was due to a consequent increase in the water deficit and intensified deforestation to increase the areas of livestock farming. The RisDes_Index proved to be a robust method, as its estimation based on simple satellite products exhibited a strong association with biophysical variables of areas with different land uses and degradation levels. Thus, it is suggested that the RisDes_Index be applied in various regions of the world, with the idea of directing action to meet the advance of desertification.

Machining technologies to compute the psychological-financial index

Subject. This article deals with the issues of measuring the emotions of financial decision-makers based on machine learning technologies in finance. Objectives. The article aims to develop a methodology for measuring emotions in the financial sector, algorithms and software based on artificial intelligence for its implementation in finance. Methods. For the study, we used the methods for marking up text data, index method, machine learning methods, computer technologies for natural language processing, methods for assessing emotions with their own rating scale, induction and deduction, and statistical methods for processing observation results. Results. The article reveals the content of methods for comprehensive measurement of the emotions of financial decision-makers. Software tools were created to implement machine learning technologies when computing an emotion measurement index. Conclusions and Relevance. A psycho-financial index based on automatic calculation using new machine learning technologies provides fundamental analysts of financial markets with an analytical tool that brings the forecast result closer to real conditions, when the emerging combinations of traditional and psychological indicators in the markets provide a new interpretation of current events. This improves the quality of analytical work and improves its results. The result can be used in the work of a fundamental analyst of financial markets. The use of new indicators complements and expands the classic analytical tools and improves the quality of market forecasts.