UKF based estimation approach for DVR control to compensate voltage swell in distribution systems

AbstractThe Dynamic Voltage Restorer (DVR) is identified as the best solution for mitigation of voltage sag and swell related problems in the much taped distribution system. The compensation performance of the DVR very much depends on its control algorithm. In the paper, an estimation method based on Unscented Kalman Filter (UKF) is proposed for mitigating the voltage swell concern. The proposed UKF based estimation technique is used to assist the control algorithm for generating reference signals of Voltage Source Converter (VSC) of DVR. DVR presents the compensation voltage as output which is included in the connected line. With this estimation method, voltage swell issues are discovered with accuracy and faster performance to retract out the swell problem in sensitivity load linked distribution systems. In MATLAB/Simulink platform the suggested method is executed and its performance is assessed and contrasted with the Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF)

Fuzzy Logic Controller for grid connected Wind Energy Conversion System

The use of renewable power sources, like wind power, has been increased recently due to climatic changes caused by fossil fuels and fast depletion of fossil fuels. This has lead to the tremendous increase in the interconnection of wind turbines to power system grid. This interconnection on a large number in to grid causes problems such as power quality, maintaining system voltage, reactive power compensation, control of grid frequency and aspects of power system grid stability. In this proposed scheme, a fuzzy logic based controller is employed for a STATCOM to improve the power quality. The proposed control scheme supplies the required reactive power to the system and thus relieves the source, leading to Unity Power Factor (UPF) at the source and also it injects currents to reduce total harmonic distortion (THD) to satisfy IEC standard. For extracting the reference currents, an instantaneous reactive power theory based control algorithm is employed. To determine the effectiveness of the proposed fuzzy logic controller, a comparative analysis is also performed with a PI controller and the results have been presented

Efficient reduction of PLI in ECG signal using new variable step size least mean fourth adaptive algorithm

It is very important in remote cardiac diagnosis to extract pure ECG signal from the contaminated recordings of the signal. When recording the ECG signal in the laboratory, the signal is affected by numerous artifacts. Varies artifacts generally degrades the signal quality are PLI, EM, MA and EM. In addition to these, the channel noise also added when transmitting signal from remote location to diagnosis center for analyzing the signal. There are several approaches are used to reduce the noise present in the ECG signal. From the literature it is proven that compared to non adaptive filters, adaptive filters play vital role to trace the random changes in the corrupted signals. In this paper, we proposed efficient Variable step size leaky least mean fourth algorithm and its sign versions for reducing the complexity. These algorithms shows that it gives low steady state error due to least mean fourth and fast convergence rate that is it tracks the input signal quickly because of its variable step size is high at initial iterations of signal compared to the LMS algorithm. The performance of the algorithm is evaluated using SNR, frequency spectrum, MSE, misadjustment and convergence characteristics

Prognóstico de exploração no Chat GPT com ética de inteligência artificial

Natural language processing innovations in the past few decades have made it feasible to synthesis and comprehend coherent text in a variety of ways, turning theoretical techniques into practical implementations. Both report summarizing software and sectors like content writers have been significantly impacted by the extensive Language-model. A huge language model, however, could show evidence of social prejudice, giving moral as well as environmental hazards from negligence, according to observations. Therefore, it is necessary to develop comprehensive guidelines for responsible LLM (Large Language Models). Despite the fact that numerous empirical investigations show that sophisticated large language models has very few ethical difficulties, there isn't a thorough investigation and consumers study of the legality of present large language model use. We use a qualitative study method on OpenAI's ChatGPT3 to solution-focus the real-world ethical risks in current large language models in order to further guide ongoing efforts on responsibly constructing ethical large language models. We carefully review ChatGPT3 from the four perspectives of bias and robustness. According to our stated opinions, we objectively benchmark ChatGPT3 on a number of sample datasets. In this work, it was found that a substantial fraction of principled problems are not solved by the current benchmarks; therefore new case examples were provided to support this. Additionally discussed were the importance of the findings regarding ChatGPT3's AI ethics, potential problems in the future, and helpful design considerations for big language models. This study may provide some guidance for future investigations into and mitigation of the ethical risks offered by technology in large Language Models applications.Las innovaciones en el procesamiento del lenguaje natural en las últimas décadas han hecho posible sintetizar y comprender textos coherentes en una variedad de formas, transformando las técnicas teóricas en implementaciones prácticas. Ambos informan que el software extenso y las industrias como la de los creadores de contenido se han visto significativamente afectadas por el modelo de lenguaje extensivo. Sin embargo, un modelo de lenguaje enorme podría mostrar evidencia de sesgo social, dando riesgos morales y ambientales por negligencia, según las observaciones. Por lo tanto, es necesario desarrollar lineamientos completos para los LLM (Modelos de Lenguaje Grandes) responsables. A pesar de que numerosas investigaciones empíricas muestran que los modelos sofisticados de lenguaje amplio tienen muy pocas dificultades éticas, no existe una investigación exhaustiva y un estudio del consumidor sobre la legalidad del uso actual de modelos de lenguaje amplio. Usamos un método de estudio cualitativo en ChatGPT3 de OpenAI para enfocarnos en resolver los riesgos éticos del mundo real en los modelos actuales de lenguaje amplio para guiar aún más los esfuerzos en curso en la construcción responsable de modelos éticos de lenguaje amplio. Analizamos cuidadosamente ChatGPT3 desde las cuatro perspectivas de sesgo y robustez. De acuerdo con nuestras opiniones expresadas, comparamos ChatGPT3 objetivamente en múltiples conjuntos de datos de muestra. En este trabajo se encontró que una fracción sustancial de los problemas de principios no son resueltos por los marcos actuales; por lo tanto, se han proporcionado nuevos ejemplos de casos para respaldar esto. Además, se discutió la importancia de los hallazgos sobre la ética de la IA de ChatGPT3, los problemas potenciales en el futuro y las consideraciones de diseño útiles para modelos de lenguaje grandes. Este estudio puede proporcionar algunas pautas para futuras investigaciones y mitigación de los riesgos éticos que ofrece la tecnología en grandes aplicaciones de Language Models.As inovações de processamento de linguagem natural nas últimas décadas tornaram possível sintetizar e compreender textos coerentes de várias maneiras, transformando técnicas teóricas em implementações práticas. Ambos relatam que softwares resumidos e setores como criadores de conteúdo foram significativamente afetados pelo extenso modelo de linguagem. Um enorme modelo de linguagem, no entanto, poderia mostrar evidências de preconceito social, dando riscos morais e ambientais por negligência, de acordo com as observações. Portanto, é necessário desenvolver diretrizes abrangentes para LLM (Large Language Models) responsáveis. Apesar do fato de numerosas investigações empíricas mostrarem que modelos sofisticados de linguagem ampla têm muito poucas dificuldades éticas, não há uma investigação completa e estudo de consumidores sobre a legalidade do uso atual de modelos de linguagem ampla. Usamos um método de estudo qualitativo no ChatGPT3 da OpenAI para focar na solução os riscos éticos do mundo real nos atuais modelos de linguagem ampla, a fim de orientar ainda mais os esforços contínuos na construção responsável de modelos éticos de linguagem ampla. Analisamos cuidadosamente o ChatGPT3 a partir das quatro perspectivas de viés e robustez. De acordo com nossas opiniões declaradas, comparamos objetivamente o ChatGPT3 em vários conjuntos de dados de amostra. Neste trabalho, constatou-se que uma fração substancial dos problemas de princípios não é resolvida pelos referenciais atuais; portanto, novos exemplos de casos foram fornecidos para apoiar isso. Além disso, foram discutidas a importância das descobertas sobre a ética de IA do ChatGPT3, possíveis problemas no futuro e considerações de design úteis para grandes modelos de linguagem. Este estudo pode fornecer algumas orientações para futuras investigações e mitigação dos riscos éticos oferecidos pela tecnologia em grandes aplicações de Modelos de Linguagem

IN VITRO ASSESSMENT OF ANTIOXIDANT AND ANTIBACTERIAL ACTIVITY OF GREEN SYNTHESIZED SILVER NANOPARTICLES FROM DIGITARIA RADICOSA LEAVES

Green metallic nanoparticles were creating a new era in the field of green nanotechnology and its applications. Methanolic leaf extract of rare, endemic medicinally important herb, Digitaria radicosa used for the synthesis of silver nanoparticles (SNPs). UV Visible spectrophotometric analysis confirmed the synthesis of green silver nanoparticles indicated by the peak observed at 442nm due to the excitation of surface plasmon resonance in the silver nanoparticles. FT-IR spectroscopic analysis showed the availability of functional groups which may involve in the silver nanoparticles synthesis. X-Ray Diffraction pattern illustrated the characteristic peaks of (111), (122), (231) facets of the centre crystalline and cubic face centred nature of silver nanoparticles. SEM analysis showed that synthesized green silver nanoparticles were of spherical in shape and size of around 90 nm. The free radical scavenging activity of silver nanoparticles were evaluated in vitro by using DPPH scavenging activity, metal chelating activity, reducing power assay and hydrogen peroxide scavenging assays. The antibacterial activity against food borne pathogens such as S. aureus and E .coli were determined by disc diffusion method. The results confirmed that these synthesized green silver nanoparticles identified to have significant in vitro antioxidant potential and good antibacterial activity.Keywords:Green Silver nanoparticles, SNPs, Digitaria radicosa leaf extract, UV Visible spectrophotometry, XRD, FT IR, SEM, in vitro antioxidant assays, antibacterial activity

ESTIMATION OF AMLODIPINE BESYLATE AND IRBESARTAN IN PHARMACEUTICAL FORMULATION BY RP-HPLC WITH FORCED DEGRADATION STUDIES

Objective: To develop and validate a simple, specific, accurate, precise and sensitive reverse phase high performance liquid chromatographic (RP-HPLC) method with forced degradation studies for the simultaneous estimation of amlodipine besylate and irbesartan in the pharmaceutical formulation. Methods: The chromatographic separation of the two drugs were achieved using Enable C 18G column (250 ×4.6 mm; 5 µm) in isocratic mode with mobile phase consisting of sodium acetate buffer (pH 4.0) and acetonitrile (30:70, % v/v) with a flow rate of 0.6 ml/min. Ultraviolet(UV) detection was carried out at 238 nm. The proposed method was validated for linearity, range, accuracy, precision, robustness, limit of detection (LOD) and limit of quantification (LOQ). The tablet formulation was subjected to stress conditions of degradation including acidic, alkaline, oxidative, thermal and photolysis. Results: The retention time for amlodipine besylate and irbesartan were found to be 5.512 and 6.321 min respectively. Linearity was observed over a concentration range 4-32 µg/ml for amlodipine besylate (r2 =0.9999) and 10-70 µg/ml for Irbesartan (r2 =0.9998). The % relative standard deviation (RSD) for Intraday and Interday precision was found to be 0.436 and 0.699 for amlodipine besylate and 0.435 and 0.30 for irbesartan. Amlodipine besylate shown stability towards acidic and thermal whereas in basic, oxidative and photolytic it shown less stability in which it degraded to more extent. Irbesartan shown stability towards thermal conditions whereas in remaining conditions it degrades to more extent especially in oxidative conditions. Conclusion: The developed reverse phase high performance liquid chromatographic (RP-HPLC) method was also found to be simple, precise and sensitive for the simultaneous determination of amlodipine besylate and irbesartan in the tablet dosage form

SILVER NANOPARTICLES FROM TRIANTHEMA PORTULACASTRUM: GREEN SYNTHESIS, CHARACTERIZATION, ANTIBACTERIAL AND ANTICANCER PROPERTIES

ABSTRACTObjective: In this study, silver nanoparticles (SNPs) were synthesized using an aqueous extract of Trainthema portulacastrum and silver ions (Ag+)which have been proven against certain pathogenic bacterial strains and hepatocellular carcinoma (HepG2) cell line.Methods: The bio fabricated nanoparticles were confirmed by surface plasmon resonance which were characterized by biophysical measuresutilizing the ultraviolet-visible spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray, and transmission electron microscope(TEM), Fourier transform infrared spectroscopy, particle size analyzer, and X-ray diffraction. Antibacterial efficacy against Enterobacter aerogens,Proteus mirabilis, Escherichia coli, Staphylococcus epidermis, and Bacillus subtilis. The effect of SNPs tested against HepG2 and NIH/3T3 cell lineexhibits a dose-dependent toxicity.Results and Conclusion: The SEM and TEM images confirmed the presence of spherical and hexagonal shape (0.3-4 μm) of nanocrystalline particleswith the size range of 11.5-29.2 nm. The average particles size of SNPs is 190.3±17.0 nm. Antibacterial activity was carried out by agar well diffusionmethod against different pathogenic bacteria of which B. subtilis showed a significant zone of inhibition 8.66 mm and 12.0 mm for aqueous plantextract and synthesized SNPs. The effect of SNPs tested against HepG2 and NIH/3T3 cell line exhibits a dose-dependent toxicity. In case of HepG2, thecell viability was decreased to 50% (IC50) at the concentration of 173.8±0.84 μg/mL. From the results, it can be concluded that the SNPs fabricatedusing green synthesis method will be a promising candidate in the biomedical field, due to its high bioactive properties.Keywords: Silver nanoparticles, Trainthema portulacastrum, Antibacterial activity, Cytotoxic activity

Identity-Based Blind Signature Scheme with Message Recovery

Blind signature allows a user to obtain a signature on a message without revealing anything about the message to the signer. Blind signatures play an important role in many real world applications such as e-voting, e-cash system where anonymity is of great concern. Due to the rapid growth in popularity of both wireless communications and mobile devices, the design of secure schemes with low-bandwidth capability is an important research issue. In this paper, we present a new blind signature scheme with message recovery in the ID-based setting using bilinear pairings over elliptic curves. The proposed scheme is unforgeable with the assumption that the Computational Diffie-Hellman problem is hard. We compare our scheme with the related schemes in terms of computational and communicational point of view