Temporal Analysis Research Articles

Temporal Complementarity Analysis of Wind and Solar Power Potential for Distributed Hybrid Electric Generation in Chile

We evaluate the temporal complementarity in daily averages between wind and solar power potential in Chile using Spearman’s correlation coefficient. We used hourly wind speed and solar radiation data for 176 geographic points from 2004 to 2016. The results allow us to identify four zones: Zone A1 on the coast and in the valleys in the north of Chile between latitudes 18° S and 36° S, with moderate positive correlation; Zone A2 in the north Andes between latitudes 25° S and 33° S, with weak negative correlation; Zone B in the center-south part of the country between latitudes 36° S and 51° S with moderate negative correlation; and Zone C in the south, between latitudes 51° S and 55° S with null or weak positive correlation. On the one hand, the interannual analysis shows that Zone A1 keeps uniform correlation values with negative asymmetry, i.e., higher correlation values. On the other hand, there is positive asymmetry in most of the years in Zone A2, i.e., lower (or negative) values of correlation. Zone B shows an interannual oscillation of the median correlation, while Zone C shows a larger dispersion in the interannual results. Significance analysis shows that 163 out of the 176 points are statistically significant, while Zones A1, A2, and B have significant correlations, with Zone C being marginally significant. The results obtained are relevant information for further studies on the location of hybrid generation facilities. We expect our methodology to be instrumental in Chile’s energetic transition to a 100% renewable generation matrix.

Female genital mutilation: trends, economic burden of delay and basis for public health interventions.

The practice of female genital mutilation (FGM) is a health and social problem. Millions of girls and women have undergone FGM or will soon, and more information is needed to effectively reduce the practice. The aim of this research is to provide an overview of the FGM trendlines, the inequality of its prevalence, and the economic burden. The findings shed light on 30-year trends and the impact of the pandemic on planned efforts to reduce FGM which helps with public health interventions. Temporal trend analysis, and graphical analysis were used to assess the change and inequality over the last 30 years. We included 27 countries in which FGM is prevalent. We calculated the extra economic burden of delayed interventions to reduce FGM like COVID-19. For the 27 countries analyzed for temporal trendlines, 13 countries showed no change over time while 14 had decreasing trends. Among the 14, nine countries, Uganda, Togo, Ghana, Benin, Kenya, Nigeria, Central African Republic, Chad, and Ethiopia had high year-decrease (CAGR - 1.01 and - 10.26) while five, Côte d'Ivoire, Egypt, Gambia, Djibouti, and Mali had low year-decrease (CAGR>-1 and < 0). Among these five are the highest FGM prevalence similar distribution regardless the wealth quintiles or residence. There is an economic burden of delay or non-decline of FGM that could be averted. Findings indicate that some countries show a declining trend over time while others not. It can be observed that there is heterogeneity and homogeneity in the FGM prevalence within and between countries which may indicate inequality that deserves further investigation. There is considerable economic burden due to delays in the implementation of interventions to reduce or eliminate FGM. These insights can help in the preparation of public health interventions.

Temporal and Spatial Analysis of Coupling Coordination in Beijing–Tianjin–Hebei Urban Agglomeration: Ecology, Environment and Economy

With the rapid growth and development of urban areas, the economy has often been prioritized at the expense of the environment and ecological systems. However, it is essential to delve deeper into the relationship between the economy and the ecological environment. Therefore, this study introduces a comprehensive evaluation system that encompasses economic, ecological, and environmental factors in the Beijing–Tianjin–Hebei urban agglomeration in China. The Criteria Importance Through Inter-criteria Correlation (CRITIC) method is utilized to determine the weights of various indicators, and coupling as well as coupling coordination models are employed to investigate the spatiotemporal trends and interrelationships of the three factors. The results indicate that the economic development index has displayed a consistent uptrend since 2000, with the economic development index from 2015–2020 increasing by approximately four times compared to 2000–2005. The ecological status index has also increased in the last five years, with a rise of about 0.05 from 2015–2020 compared to 2000–2005. The environmental status index has fluctuated but generally increased, with a rise of approximately 5.6 times from 2015–2020 compared to 2000–2005. The coupling degree of the Beijing–Tianjin–Hebei urban agglomeration is relatively high, with intense coupling from 2005–2020, and moderate coupling from 2000–2005. Furthermore, the coupling coordination has continuously improved from mild maladjustment to barely coordinated from 2000 to 2020, indicating the enhancement of the coupling coordination of the three factors. It is crucial to acknowledge that there exists spatial heterogeneity in both the coupling degree and coupling coordination degree. This heterogeneity stems from the uneven progress in economic development, ecological conditions, and environmental status across various cities. Additional endeavors are required to foster the harmonized advancement of these factors across the entire region.

An inflection point-based method for estimating metrics of mangrove phenology combining climatic factors and Landsat NDVI time series

Abstract The present research evaluated the prospects of utilizing rainfall and temperature combined with Landsat-8 derived HANTS (Harmonic ANalysis of Time Series) reconstructed NDVI for estimating the metrics of the mangrove phenology. The selected period of the study was from 2013 to 2020 for the Pichavaram mangroves of Tamil Nadu. The NDVI and ERA5 (ECMWF Re-Analysis) datasets of rainfall and temperature were the input datasets for developing the new algorithm. The ‘z-score sum’ provided a measure of the cumulative impact of rainfall and temperature, displaying its most negative value coinciding with the peak positive value of the NDVI time series datasets. The algorithm developed for phenological metrics estimation identified the common inflection points of the z-score sum and NDVI curves. The temporal analysis of metrics revealed the average Length of Season (LoS) as 230 days. The metrics also identified the drought year 2016 with the shortest LoS and the least Gross Primary Productivity (GPP) values. The analysis showed the influences of the preceding year’s monsoon rainfall on the GPP values of the later part of the phenological cycle. The temperatures during the days of PoS were found to be the optimum temperature for the growth of mangroves.

Construction of the Chinese Route of Industrial Heritage Based on Spatial and Temporal Distribution Analysis

In the context of cultural routes, in order to achieve overall protection of industrial heritage, the European Route of Industrial Heritage (ERIH) was established to organize and promote the entire European industrial heritage. The conservation and utilization of Chinese industrial heritage are currently dominated by individual cases, which limits their potential to contribute to regional sustainable development. There is an urgent need of a conservation system at the regional or national level, to ensure that Chinese industrial heritage conservation effectively contributes to regional sustainable development. This study considers the industrial heritage of China built between 1840 and 1978 to establish the Chinese Industrial Heritage GIS Database (CIHGD). The analysis shows that the distribution of China’s industrial heritage is mainly concentrated in the eastern and southern coastal areas, and the industrial heritage has formed three key regions, 14 key cities, and important railway and water systems located in eastern China. The CRIH facilitates the holistic conservation of China’s industrial heritage and provides basic data for future research on China’s industrial heritage. The objective of this study is to promote the establishment of an information-based management system for industrial heritage in China, and to explore the value evaluation, protection system, and regional tourism of industrial heritage from a national perspective in China.

Integrated metabolomic and transcriptomic analyses provide insights into regulation mechanisms during bulbous stem development in the Chinese medicinal herb plant, Stephania kwangsiensis

BackgroundStephania kwangsiensis Lo (Menispermaceae) is a well-known Chinese herbal medicine, and its bulbous stems are used medicinally. The storage stem of S. kwangsiensis originated from the hypocotyls. To date, there are no reports on the growth and development of S. kwangsiensis storage stems.ResultsThe bulbous stem of S. kwangsiensis, the starch diameter was larger at the stable expanding stage (S3T) than at the unexpanded stage (S1T) or the rapidly expanding stage (S2T) at the three different time points. We used ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and Illumina sequencing to identify key genes involved in bulbous stem development. A large number of differentially accumulated metabolites (DAMs) and differentially expressed genes (DEGs) were identified. Based on the differential expression profiles of the metabolites, alkaloids, lipids, and phenolic acids were the top three differentially expressed classes. Compared with S2T, significant changes in plant signal transduction and isoquinoline alkaloid biosynthesis pathways occurred at both the transcriptional and metabolic levels in S1T. In S2T compared with S3T, several metabolites involved in tyrosine metabolism were decreased. Temporal analysis of S1T to S3T indicated the downregulation of phenylpropanoid biosynthesis, including lignin biosynthesis. The annotation of key pathways showed an up-down trend for genes and metabolites involved in isoquinoline alkaloid biosynthesis, whereas phenylpropanoid biosynthesis was not completely consistent.ConclusionsDownregulation of the phenylpropanoid biosynthesis pathway may be the result of carbon flow into alkaloid synthesis and storage of lipids and starch during the development of S. kwangsiensis bulbous stems. A decrease in the number of metabolites involved in tyrosine metabolism may also lead to a decrease in the upstream substrates of phenylpropane biosynthesis. Downregulation of lignin synthesis during phenylpropanoid biosynthesis may loosen restrictions on bulbous stem expansion. This study provides the first comprehensive analysis of the metabolome and transcriptome profiles of S. kwangsiensis bulbous stems. These data provide guidance for the cultivation, breeding, and harvesting of S. kwangsiensis.

Impact of the chips act on the GVC participation of China's electronics industry

PurposeIn this paper, we evaluated the impact of the US “Chip Act” on the participation of the Chinese electronics industry in the global value chain based on the dynamic CGE model. This is a meaningful attempt to use the GTAP-VA model to analyze the electronics industry in China.Design/methodology/approachWe employ a Dynamic GTAP-VA Model to quantitatively evaluate the economic repercussions of the “Chip Act” on the Chinese electronic industries' GVC participation from 2023 to 2040.FindingsThe findings depict a discernible contraction in China’s electronic sector by 2040, marked by a −2.95% change in output, a −3.50% alteration in exports and a 0.45% increment in imports. Concurrently, the U.S., EU and certain Asian economies exhibit expansions within the electronic sector, indicating a GVC realignment. The “Chip Act” implementation precipitates a significant divergence in GVC participation across different countries and industries, notably impacting the electronics sector.Research limitations/implicationsThrough a meticulous temporal analysis, this manuscript unveils the nuanced economic shifts within the GVC, substantially bridging the empirical void in existing literature. This narrative accentuates the profound implications of policy regulations on global trade dynamics, contributing to the discourse on international economic policy and industry evolution.Practical implicationsWe evaluated the impact of the US “Chip Act” on the participation of the Chinese electronics industry in the global value chain based on the dynamic CGE model. This is a meaningful attempt to use the GTAP-VA model to analyze the electronics industry in China.Social implicationsThe interaction between policy regulations and global value chain (GVC) dynamics is pivotal in understanding the contemporary global trade framework, especially within technology-driven sectors. The US “Chips Act” represents a significant regulatory milestone with potential ramifications on the Chinese electronic industries' engagement in the GVC.Originality/valueThe significance of this paper is that it quantifies for the first time the impact of the US Chip Act on the GVC participation index of East Asian countries in the context of US-China decoupling. With careful consideration of strategic aspects, this paper substantially fills the empirical gap in the existing literature by presenting subtle economic changes within GVCs, highlighting the profound implications of policy regulation on global trade dynamics.

Advancements in Satellite Remote Sensing for Predicting Large-Scale Wildfire Risks: An Image Processing Algorithmic Framework

With the escalation of global warming and human activities, large-scale wildfires have become increasingly frequent, posing significant threats to both ecological environments and human societal safety. Satellite remote sensing technology plays a pivotal role in wildfire monitoring and risk assessment, providing extensive geographical coverage and continuous monitoring capabilities. Traditional methods for predicating wildfire risk, however, face limitations in processing large-scale remote sensing data, especially in cloud detection and temporal information analysis. In response to this challenge, a novel set of image processing algorithms has been developed to enhance the efficiency and accuracy of wildfire risk prediction. Initially, a cloud detection and removal algorithm based on deep learning is introduced. This algorithm effectively identifies and eliminates cloud interference in remote sensing images, thereby significantly improving the quality and usability of image data. Subsequently, a temporal information capturing technique is proposed, capable of processing vast amounts of remote sensing data and extracting time series features. This technique provides robust data support for wildfire risk prediction. The application of these technologies not only improves the efficiency of the data processing workflow but also enhances the timeliness and accuracy of the prediction model, holding significant practical importance for guiding actual wildfire prevention and response measures.

Dynamic dependency between health-care sector and Islamic industry: before, during and after COVID-19 lockdown evidences

Purpose This study aims to empirically explore and compare the dynamic dependency between health-care sector and Islamic industries before, during and after the COVID-19 pandemic. Design/methodology/approach Time-varying student-t copula is used for before, during and after COVID-19 periods. The data used are the daily frequency price series of the selected markets from February 2017 to October 2023. Findings Empirical results found strong evidence of significant impact of the COVID-19 pandemic on the dependence structure of the studied indexes: Co-movements between various sectors are certain. The authors assist also in the birth of new dependence structure with the health-care industry in response to the COVID-19 crisis. This reflects the contagion occurrence from the health-care sector to other sectors. Originality/value By specifically examining the Islamic industry, this study sheds light on the resilience, challenges and opportunities within this sector, contributing novel perspectives to the broader discourse on pandemic-related impacts on economies and industries. Also, this paper conducts a comprehensive temporal analysis, examining the dynamics before, during and after the COVID-19 lockdown. Such approach enables an understanding of how the relationship between the health-care sector and the Islamic industry evolves over time, accounting for both short-term disruptions and long-term effects. By considering the pre-pandemic context, the paper adopts a longitudinal perspective, enabling a deeper understanding of how historical trends, structural factors and institutional frameworks shape the interplay between the health-care sector and the Islamic industry.

Long-term radiological assessment of a Mediterranean freshwater ecosystem surrounding a nuclear power plant.

The radionuclide concentration of man-made radionuclides on non-human biota in freshwater ecosystems has been extensively studied in environments affected by the Chernobyl and Fukushima accidents, in both humid continental and subtropical climates, respectively. However, there are very few studies that assess the long-term effects of operating nuclear facilities in Mediterranean environments. In the present study, a temporal analysis of the impact on carp, cattail, and bulrushes in the cooling pond of the currently operating Almaraz nuclear power plant was investigated for the period 2000-2020. The results do not show a general trend in man-made radionuclide concentrations. Instead, depending on their availability and the type of organism, trends decrease over time. This is also reflected in the effective half-lives obtained, which are lower than the physical half-life for some radionuclides. Transfer coefficients for the main man-made radionuclides detected were obtained, and it was found that these were significantly lower than the typical ranges found for benthic fish and vascular plants in freshwater ecosystems. Finally, the internal and external doses received by the carp have been evaluated using ERICA tool, and it has been observed that the main contribution to the total dose is due to the internal dose (0.65-7.04) × 10-4µGy/h.

Spatial–Temporal Pattern Analysis and Development Forecasting of Carbon Stock Based on Land Use Change Simulation: A Case Study of the Xiamen–Zhangzhou–Quanzhou Urban Agglomeration, China

The spatial–temporal distribution and evolution characteristics of carbon stock under the influence of land use changes are crucial to the scientific management of environmental resources and the optimization of land spatial layout. Taking the Xiamen–Zhangzhou–Quanzhou urban agglomeration in the southeastern coastal region of China as an example, based on seven land use types from 1990 to 2020, including cultivated land, woodland, and construction land, we quantitatively investigate the spatial–temporal patterns of carbon stock development and the spatial correlation of carbon stock distribution. Additionally, two scenarios for the development of urban and ecological priorities in 2060 are established to investigate the effects of land use changes on carbon stock. The results indicate that (1) the research area has formed a land use spatial pattern centered around urban construction in the eastern bay area, with the western forest area and coastal forest belt serving as ecological barriers. Carbon stock is influenced by land use type, and the distribution of total carbon stock exhibits a spatial aggregation phenomenon characterized by “low in the southeast, high in the north, and medium in the center”. (2) Distance of trunk and secondary roads, elevation, slope, watershed borders, population size, and gross domestic product (GDP) factors are the main drivers of the growth of land use types. The primary causes of the reduction in carbon stock are the widespread conversion of cultivated land, woodland, and grassland into construction land, as well as water and unused land. (3) In 2060, there will be a decrease of 41,712,443.35 Mg in the urban priority development scenario compared to 2020, and a decrease of 29,577,580.48 Mg in the ecological priority development scenario. The estimated carbon stock under the two scenarios varies by 12,134,862.88 Mg. The average carbon storage of Zhangpu County, Quangang County, and Jimei County is expected to rise by one level under the ecological protection scenario, indicating that the vast forest area can become a potential area to maintain carbon stock. It is crucial to encourage the coordinated development of peri-urban agroforestry and ecological barriers, as well as to establish a harmonious spatial pattern of land use and carbon stock at the scale of urban agglomerations.

City-forming role of the Metro in Warsaw

The article analyses the continuous transformations in the spatial development of the western part of Warsaw from 2001 to 2022. The study utilises cartographic materials and temporal analysis, considering pedestrian travel times to planned metro stations in the Bemowo district. An investment analysis of single and multi-family buildings was conducted throughout the Bemowo district and near metro stations. The analysis is based on four time intervals to determine the speed and nature of changes and their impact on land development. The selected analysis periods are 2001–2005, 2005–2010, 2010–2016, and 2016–2022. In 2022, the construction of the last section of the second metro line commenced. The results indicate that the total number of buildings constructed in Bemowo within 833 m of the metro station increased by 298 between 2001 and 2022, representing a growth of 64.5 %. During the same period, the building area increased by 1,237,405 m2, corresponding to a growth of 136.2 % relative to the existing area. The highest increase in the number of new multi-family buildings was observed after 2016, providing evidence of the alignment of the construction and the second metro line station with the transit-oriented development (TOD) concept in the western part of Warsaw.

Temporal analysis of factors affecting injury severities of expressway rear-end crashes during weekdays and weekends

ABSTRACT High fatality rates in frequent rear-end crashes have underscored significant safety concerns in China. This study aims to explore the mechanisms and determinants of rear-end crashes, with a particular focus on the factors influencing crash severity during weekdays and weekends (W-W). Employing the Random Parameter Logit Model (RPLM) to account for variability in data, we analyzed W-W rear-end crashes on the Beijing-Shanghai Expressway in Jiangsu province from 2017 to 2019, considering three severity levels: no injury, minor injury, and severe injury. Our comprehensive analysis covered variables from temporal, roadway, vehicle, crash, and environmental categories, alongside calculating the marginal effects of each significant variable on crash severity. Findings reveal temporal instability over the three-year period and notable differences in W-W crash severity. Out of all variables, four displayed random parameter characteristics, indicating potential interactions that influence crash outcomes. Specifically, our results indicate that rear-end crashes involving three or more vehicles on bridges are more likely to result in casualties. Interchange segments typically saw no injuries in two-vehicle crashes. Speeding during winter or on sunny days significantly increases the risk of injuries and fatalities. Furthermore, rear-end crashes in interchange areas during winter are particularly prone to causing injuries. These findings offer guidance for the development of effective safety countermeasures targed at different pediods.

Fostering Environmental Awareness Through Eco-Literacy in Novels: A Bibliometric Review

Due to rising worldwide environmental issues, eco-literacy and environmental consciousness have received emphasis in recent years. This phenomenon implicitly suggests that novels can significantly elucidate intricate ecological concepts. This study aims to uncover the underlying currents that shape the discourse around eco-literacy in novels and their influence on societal perceptions of the environment. This study used Scopus and Web of Science (WoS) databases to gather and analyse datasets. ScientoPy and VOSviewer were then used to analyse the retrieved datasets. This study found that temporal trend analysis showed a gradual increase in research production, notably after 2005, showing a growing interest in the connection between eco-literacy and novel studies. The prevalence of keywords such as “environmental education”, “eco-criticism”, and “environmental communication” demonstrates the significance of literature as a tool for cultivating environmental awareness, critical analysis, and effective communication in novels. This study contributes to the field by comprehensively evaluating the temporal patterns, thematic themes, and collaborative networks within eco-literacy domains and new research.

Land Use, Built-Up, and Vegetation Index in North Halmahera Regency through Spatio-Temporal Analysis

Monitoring land use, buildings, and vegetation index of ecotourism areas in North Halmahera can support planning space utilization in urban areas for tourist areas as the concept of land use management and urban planning. This study offers ideas for analyzing the distribution of buildings, vegetation index, and land use in the mangrove ecotourism area of North Halmahera Regency using the spatio-temporal analysis method. The spatio-temporal analysis method comprises several stages: data selection, preprocessing, data integration, spatial analysis, temporal analysis, spatio-temporal analysis, data visualization, interpretation and understanding, and data visualization. The results of this study show that changes in the livelihood strategy of local people, from farmers and fishermen to traders, also affect land use patterns, from agricultural activities to economic activities, which triggers an increase in the number of buildings for production activities to product distribution. The implications of these findings on ecotourism development programs and policies and infrastructure development in the North Halmahera Regency are to consider community livelihoods and space or land use behavior in ecotourism areas based on vegetation, soil, and building index values. Thus, the intensification of building distribution and changes in vegetation index values from 2013-2023 reflect changes in people's livelihood strategies from agrarian activities to trade and from fishermen's activities to tourism transportation service providers.

Simultaneous and observations of the ultraluminous source NGC 4190 ULX-1

We present an X-ray analysis of three different XMM-Newton observations together with simultaneous and observations of the ultraluminous X-ray source NGC 4190 ULX-1. Our goal is to constrain the structure of the accretion disk and the geometrical properties of the source. We performed temporal and spectral analyses in the 0.4--30 keV energy range in which the source is significantly detected in dedicated XMM-Newton and NuSTAR observations. The temporal analysis shows no flaring activity in the light curves. No pulsation is detected throughout. The source exhibits a typical ULX spectrum, which can be fitted with two thermal blackbody components plus a Comptonization tail at high energies. The luminosity-temperature ($L-T$) relation of each thermal spectral component is consistent with the $L $ relation expected from an advection-dominated supercritical disk. We interpret these results as a super-Eddington accreting black hole seen almost face-on. A dense wind ejected from the disk obscures the central source, and a hot electron plasma is evacuated through the funnel formed above the hole. Geometric beaming is responsible for the ULX soft emission, whereas the hard tail is the result of the Comptonization of soft photons by the electrons ejected through the funnel.

Grid Planning Method of Medium Voltage Distribution Network Including Distributed Power Sources based on Timing Characteristics

Aiming at the problems of unbalanced load distribution of feeders and low utilization rate of system resources in existing medium voltage(MV) distribution network planning, it is difficult to meet the requirements of future grid construction, Propose a grid planning method of MV distribution network including distributed generator(DG) based on timing characteristics. Firstly, based on the existing grid planning achievements and temporal characteristics analysis, the grid structure and planning strategy of the MV distribution network are formed. Secondly, based on the network planning strategy, establish a dual level planning model for both internal and external distribution networks. The inner model uses comprehensive performance indicators as fitness functions to solve the optimal division of the distribution network grid, while the outer model calculates the distributed power capacity configuration of each grid with the goal of maximizing the consumption of DG. Then, based on the established dual layer planning model for the distribution network, genetic algorithms and self programming algorithms are used to solve the model by interconnecting the internal and external layers. Finally, the practicality and effectiveness of the proposed model and method were verified through practical examples combined with evaluation indicators.

Spatial and temporal differences and convergence analysis of multidimensional relative poverty in ethnic areas.

Reducing multidimensional relative poverty is one of the important issues in the current global poverty governance field. This article takes 12 ethnic regions in China as the research object and constructs a multidimensional relative poverty measurement system. The calculated multidimensional relative poverty index is decomposed according to provinces, cities, dimensions, and indicators. Then, the Dagum Gini coefficient and convergence analysis are used to analyze spatiotemporal heterogeneity and convergence characteristics. The results show that the multi-dimensional relative poverty situation of various provinces in ethnic minority areas has improved from 2012 to 2021, among which Tibet province is the most serious and Shaanxi is the best. According to the analysis of convergence, it was observed that there is no σ-convergence of multidimensional relative poverty in ethnic areas in general, and there is absolute β-convergence in general and in the southwest and northwest regions, and there is no absolute β-convergence in the northeast region. Based on this, policy recommendations for reducing multidimensional relative poverty are proposed at the end of the article. Compared with previous studies, this article focuses on ethnic regions that are easily overlooked. Starting from the dimensions of economy, social development, and ecological environment, the poverty measurement system has been enriched.

Review on Human Pose Estimation using AI Fitness Tracker

Human pose estimation, a fundamental computer vision task, has witnessed significant advancements with the advent of deep learning techniques. This paper provides an overview of recent developments in human pose estimation, focusing on the application of convolutional neural networks (CNNs) and recurrent neural networks (RNNs). We explore the distinctions between 2D and 3D pose estimation, highlighting the challenges and solutions for each. The paper discusses the various techniques for single-person and multi-person pose estimation, as well as the trade-offs between part-based and holistic approaches. Additionally, we delve into the real-time and offline aspects of pose estimation and the significance of temporal analysis in videos. Lastly, we touch on the translation of 2D pose information into 3D space. This review underscores the practical implications of human pose estimation in diverse fields such as sports analysis, healthcare, surveillance, and entertainment. The dynamic nature of this field, fueled by ongoing research and technological advancements, promises to unlock new possibilities for human-computer interaction, augmented reality, and beyond. This abstract provides an overview of the paper's focus on deep learning in the context of human pose estimation and highlights the key aspects of the field. You can further tailor it to your specific paper or presentation needs. Keywords: Human pose estimation, camera, Artificial intelligence, Machine learning

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Currently, the Water Quality Index (WQI) model becomes a widely used tool to evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the simplest mathematical tools that can assist water operator in decision making in assessing the quality of water and it is widely used in the last years. The water quality analysis and prediction is conducted for Johor River Basin incorporating the upstream to downstream water quality monitoring station data of the river. In this research, the numerical method is first used to calculate the WQI and identify the classes for validating the prediction results. Then, two ensemble and optimized machine learning models including gradient boosting regression (GB) and random forest regression (RF) are employed to predict the WQI. The study area selected is the Johor River basin located in Johor, Peninsular Malaysia. The initial phase of this study involves analyzing all available data on parameters concerning the river, aiming to gain a comprehensive understanding of the overall water quality within the river basin. Through temporal analysis, it was determined that Mg, E. coli, SS, and DS emerge as critical factors affecting water quality in this river basin. Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. Finally, an ensemble-based machine learning model is designed to predict the WQI using three parameters. Two ensemble ML approaches are chosen to predict the WQI in the study area and achieved a R2 of 0.86 for RF-based regression and 0.85 for GB-based ML technique. Finally, this research proves that using only the biochemical oxygen demand (BOD), the chemical oxygen demand (COD) and percentage of dissolved oxygen (DO%), the WQI can be predicted accurately and almost 96 times out of 100 sample, the water class can be predicted using GB ensembled ML algorithm. Moving forward, stakeholders may opt to integrate this research into their analyses, potentially yielding economic reliability and time savings.