Power Grid Frequency Forecasting from μPMU Data using Hybrid Vector-Output LSTM network

The instantaneous balance of electrical supply and demand on the power grid is indicated by the power grid frequency, making it a pivotal variable for power system controls. Accurate frequency forecasting could enable new faster means of frequency management that enhance power system stability. A hybrid vector-output Long Short-Term Memory (LSTM) neural network has been studied using microsynchrophasor data to predict trajectories. The objective of this research is to evaluate the effectiveness of very short time horizon frequency prediction using this method. The proposed model has been trained with over and under-frequency operational limit excursion events as well as normal condition state, with the goal of minimising prediction errors. Training and testing have been conducted using 390,000 datapoints covering 65 frequency events obtained from a distribution grid connected solar farm in England. The results demonstrate this method can provide useful grid frequency projections and shed light on underlying behaviour. Index Terms—Electrical grid frequency, power system stability, time series forecasting, long short term memor

Sustainable Housing for Middle-Income Society in Sri Lanka

Housing is a fundamental human necessity and affects how society interacts with the environment. In the modern era, housing expansions all over the world have significantly increased the number of economic, social, and environmental issues. Making housing constructions in places that are quickly urbanizing more sustainable is a top objective for government agencies, business experts, and research organizations. Managing economic, environmental, and social sustainability factors is referred to as sustainable housing. Major natural resources used in the construction of housing include land, energy, water, and building materials. Minor natural resources used in the process include waste production and air and water pollution. In the community's fight for affordable housing, educated middle-income inhabitants are predicted to be the most susceptible group given expected living standards and monthly income-generating levels. The goals are to explain how the framework for evaluating laws was developed and proven to be valid in order to achieve sustainability in middle-income housing. In order to offer the essential background for developing an interim assessment framework for affordable and sustainable middle-income housing, the research begins by analyzing the current local assessment frameworks and regulations. To evaluate the interim assessment framework, a semi-structured questionnaire survey of business professionals and other stakeholders will serve as the foundation for the secondary study. This intermediate evaluation framework will receive the necessary fine-tuning and industry feedback through discussion and opinions. The interim framework must be transformed into a robust and progressive regulatory structure that enables future success in SH for the majority of middle-class citizens in the nation. The results will next be evaluated in light of Sri Lanka's existing regulatory framework for sustainable middle-income housing. © 2022 The Authors. Published by Department of Estate Management and Valuation, University of Sri Jayewardenepura   Keywords: Sustainable Housing, Middle-income Society, Housing Crisi

Multiple linear regression analysis of factors affecting the consumption

Econometrics provides the researchers with methods, theoretical basements, and procedures that allow the formulation and estimation of economic models that explain the study variable during a reference time period, as well as making predictions about the behavior of the studied reality based on the explanatory variables. The entire process, analyzed from econometrics after having formulated and estimated the model, leads to a very important phase: the statistical validation, which helps the researcher to ensure that the model satisfactorily passes a series of tests. These tests will allow the use of the model not just to explain the behavior of the independent variable under study, but to make predictions based on scenarios of occurrence based on those explanatory variables included in the model, offering a theoretical-practical support to formulate policies related to the studied phenomenon. This research aims to generate the first elements to know the private consumption behavior in India in the period from 2012 to 201

Rhizoctonia in ameliorated and non-ameliorated soils

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Segmentation of sales for a mobile phone service through CART classification tree algorithm

The work consisted of detailing the CRISP-DM method in order to identify optimal groups of customers who are more likely to migrate from a prepaid to postpaid option in order to formulate an improvement plan for in call management by sorting the database. Classification models were applied to analyze the characteristics generated by the purchase of the different services. The CART Classification Tree algorithm. As a result, groups differentiated by probabilities of sales success (migrate from a prepaid to postpaid plan) were found, segments that reflect particular needs and characteristics to design marketing actions focused on the objective of increasing the effectiveness rate, contact information, and sales increase

Allele Frequency–Based and Polymorphism-Versus-Divergence Indices of Balancing Selection in a New Filtered Set of Polymorphic Genes in Plasmodium falciparum

Signatures of balancing selection operating on specific gene loci in endemic pathogens can identify candidate targets of naturally acquired immunity. In malaria parasites, several leading vaccine candidates convincingly show such signatures when subjected to several tests of neutrality, but the discovery of new targets affected by selection to a similar extent has been slow. A small minority of all genes are under such selection, as indicated by a recent study of 26 Plasmodium falciparum merozoite-stage genes that were not previously prioritized as vaccine candidates, of which only one (locus PF10_0348) showed a strong signature. Therefore, to focus discovery efforts on genes that are polymorphic, we scanned all available shotgun genome sequence data from laboratory lines of P. falciparum and chose six loci with more than five single nucleotide polymorphisms per kilobase (including PF10_0348) for in-depth frequency–based analyses in a Kenyan population (allele sample sizes >50 for each locus) and comparison of Hudson–Kreitman–Aguade (HKA) ratios of population diversity (π) to interspecific divergence (K) from the chimpanzee parasite Plasmodium reichenowi. Three of these (the msp3/6-like genes PF10_0348 and PF10_0355 and the surf4.1 gene PFD1160w) showed exceptionally high positive values of Tajima's D and Fu and Li's F indices and have the highest HKA ratios, indicating that they are under balancing selection and should be prioritized for studies of their protein products as candidate targets of immunity. Combined with earlier results, there is now strong evidence that high HKA ratio (as well as the frequency-independent ratio of Watterson's θ/K) is predictive of high values of Tajima's D. Thus, the former offers value for use in genome-wide screening when numbers of genome sequences within a species are low or in combination with Tajima's D as a 2D test on large population genomic samples

Serologically defined variations in malaria endemicity in Pará state, Brazil

BACKGROUND: Measurement of malaria endemicity is typically based on vector or parasite measures. A complementary approach is the detection of parasite specific IgG antibodies. We determined the antibody levels and seroconversion rates to both P. vivax and P. falciparum merozoite antigens in individuals living in areas of varying P. vivax endemicity in Pará state, Brazilian Amazon region. METHODOLOGY/PRINCIPAL FINDINGS: The prevalence of antibodies to recombinant antigens from P. vivax and P. falciparum was determined in 1,330 individuals. Cross sectional surveys were conducted in the north of Brazil in Anajás, Belém, Goianésia do Pará, Jacareacanga, Itaituba, Trairão, all in the Pará state, and Sucuriju, a free-malaria site in the neighboring state Amapá. Seroprevalence to any P. vivax antigens (MSP1 or AMA-1) was 52.5%, whereas 24.7% of the individuals were seropositive to any P. falciparum antigens (MSP1 or AMA-1). For P. vivax antigens, the seroconversion rates (SCR) ranged from 0.005 (Sucuriju) to 0.201 (Goianésia do Pará), and are strongly correlated to the corresponding Annual Parasite Index (API). We detected two sites with distinct characteristics: Goianésia do Pará where seroprevalence curve does not change with age, and Sucuriju where seroprevalence curve is better described by a model with two SCRs compatible with a decrease in force of infection occurred 14 years ago (from 0.069 to 0.005). For P. falciparum antigens, current SCR estimates varied from 0.002 (Belém) to 0.018 (Goianésia do Pará). We also detected a putative decrease in disease transmission occurred ∼29 years ago in Anajás, Goianésia do Pará, Itaituba, Jacareacanga, and Trairão. CONCLUSIONS: We observed heterogeneity of serological indices across study sites with different endemicity levels and temporal changes in the force of infection in some of the sites. Our study provides further evidence that serology can be used to measure and monitor transmission of both major species of malaria parasite

Using Arc Length to Cluster Financial Time Series According to Risk

This article investigates how arc length can be used to partition financial time series according to variability (risk). This technique is predicated on the idea that arc length is an index of volatility, and thus the end result is that safer stocks can be sorted from more risky ones. Performance of arc length is compared with squared returns and absolute returns, two commonly used measures for quantifying the variability of prices. An application involving 30 popular stocks is presented using Maharaj, k-means ++, and correlation-based clustering techniques