Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacological evaluation of Parkia speciosa Hassk . for antioxidant , anti-inflammatory , anti-diabetic and anti-microbial activities in vitro

Copyright: © Author, This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial No Derives License, which permits use and distribution in any medium, provided the original work is properly cited, the use is noncommercial and no modifications or adaptations are made. Parkia speciosa Hassk. (Petai or Stink bean, Family Fabaceae) is a traditionally consumed medicinal plant for liver disease, oedema, kidney inflamemation, diabetes and as an anthelmintic. The phytochemical analysis of seeds of P. speciosa in water, methanol and hydromethanolic (1:1) extracts revealed the presence of carbohydrates, amino acid, alkaloids, saponins, tannins, flavonoids, terpenoids, glycosides, xanthoproteins and phenols. In vitro antioxidant capacity by linear regression analysis was measured by assaying DPPH radical and H2O2 scavenging capacities. Their respective IC50 values were found to be 315.75 μg/ml and 166.63 μg/ml. The hydromethanolic extract gave total phenolic, total flavonoids and FRAP values of 13.54±0.0163 mg GAE/g, 5.46±0.011 mg/g QE/g and 1.9 mM FeSO4 respectively. The IC50 values for in vitro anti-inflammatory activities were evaluated by the following assays: lipoxygenase inhibition (IC50 = 493.34μg μg/ml), proteinase inhibition (IC50 = 1142.3 μg μg/ml) and RBC membrane stabilization (IC50 = 67.01 μg μg/ml) at different concentrations using aspirin as control. Studies were also carried out to assess the anti-diabetic potential by assaying the ability of the plant to inhibit pancreatic lipase and amylase activities. The % inhibition at 500 μg/ml of the plant extracts were found to be 89.5% (for lipase) and 79.2% (for amylase). Antimicrobial activity of the extracts was studied against common pathogens (S. aureus, E. coli, P. aeruginosa and K. pneumoniae). The zone of inhibition was observed using well diffusion method.
Automatic domain module extraction using SVM machine learning approach from electronic textbooks

-In recent days, Technology-Supported Learning Systems (TSLSs), such as Intelligent Tutoring Systems (ITSs), Adaptive Hypermedia Systems (AHSs), and especially, Learning Management Systems (LMSs) are being extensively used in many studious institutions and becoming necessary for learning. The Domain Module is measured the core of any TSLSs as it represents the data about a topic matter to be communicated to the learner. In the existing system, a DOM-Sortze is a system that uses NLP techniques, heuristic analysis, and ontologies for the semiautomatic structure of the Domain Module from electronic textbooks. But in this system, still lack in the identification of pedagogical relationships. This is needed to improve in this system. In other words, DOM-Sortze system is not able to including the new rules of the pedagogical relationships. To overcome this issue, using learning techniques to learn the new rules in the pedagogical relationships. In our proposed system, we are proposing the SVM (support vector machine) learning approach intended for learning process. Our machine learning methods are used to infer new rules in order to improve the identification of pedagogical relationships or the DRs in the electronic textbooks.
REDUCTION OF ACTIVE POWER LOSS BY CHAOTIC SEARCH BASED ARTIFICIAL BEE COLONY ALGORITHM

This paper presents Chaotic Search Based Artificial Bee Colony Optimization Algorithm (CSABC) for solving the optimal reactive power problem. Basic Artificial Bee Colony algorithm (ABC) has the advantages of strong robustness, fast convergence and high flexibility, fewer setting parameters, but it has the disadvantages premature convergence in the later search period and the accuracy of the optimal value which cannot meet the requirements sometimes. In this paper the Chaotic Local Search method is applied to solve the reactive power problem of global optimal value. The premature convergence issue of the Artificial Bee Colony algorithm has been improved by increasing the number of scout and rational using of the global optimal value and Chaotic Search. The proposed Chaotic Search Based Artificial Bee Colony Optimization (CSABC) algorithm has been tested in stand IEEE 30, 118bus & practical 191 Indian utility test systems. The results show that the proposed algorithm performs well in reducing the real power loss and prevent premature convergence to high degree with rapid convergence.
A New Optimization Algorithm for SolvingOptimal Power Flow

This paper States a new and well-Organized method for solving optimal power flow (OPF) problem in power systems. In the proposed approach, Artificial Bee Colony (ABC) algorithm is hired as the main optimizer for optimal adjustments of the power system control variables of the OPF problem. Unique objective functions such as Minimization of fuel costs, total active power loss, improvement of voltage profile, enhancement of voltage stability and all emission cost are selected for this graciously constrained nonlinear non-convex optimization problem. The strength and effectiveness of the proposed method is tested with the Institute of Electrical & Electronic Engineering 30 bus system, and the test results are assessed with the results found by other experimental methods reported in the pamphlets newly. The simulation results attained show that the ABC algorithm provides accurate solutions for any type of the objective functions.
Design & Analysis of Hybrid Micro Grid with DC Connection at Back to Back Converter

A micro grid is a localized grouping of electricity generation, energy storage, and loads that normally operate connected to a traditional centralized grid (macro grid). This single point of common coupling with the macro grid can be disconnected. The micro grid can then function autonomously. Generation and loads in a micro grid are usually interconnected at low voltage. From the point of view of the grid operator, a connected micro grid can be controlled as if it were one entity. Micro grid generation resources can include fuel cells, wind, solar, or other energy sources. The necessity of an AC or DC micro grid is governed by available micro sources and connected loads. A hybrid structure can ensure a sustainable configuration blending both the forms. In this paper, a hybrid micro grid structure for a grid connected micro grid with DC connection at back to back (B2B) converters is proposed. While a B2B connection between two AC systems could bestow a reliable, isolated and efficient coupling,an extra DC bus connection can facilitate use of the DC micro sources. The DC bus can supply the local DC loads and can also trade part of the power with the AC grids. The voltage support at the DC link (of the B2B converters) can be used for the DC bus formation. Different power management strategies with fixed power references or decentralized power distribution in AC/DC sides are proposed and validated with simulations in MATLAB.
Raspberry Pibot Manipulated for Multi

In today's world, everyone is worried about their safety due to increase in crime rate. This has led to an increase in the importance of surveillance systems. In this project, raspberry pi serves as the heart of the robot which in turn is used to implement the real surveillance system possible within a local network. The major factor enhanced in this project is the skid steered mechanism manipulated over the motor controlling the robotic movement. This particular mechanism has the major role in imparting an equilibrium movement of the robot in the rough terrain. Depending on the obstacles identified in the area the pibot maintains the area map and also update its frequency as per the obstacles encountered. Further the environmental conditions monitored by the sensor unit will benefit in obtaining a clear idea of the remote area . A single camera is installed on a robot and the robot can move in all directions to take photos in different angles. The Pi has the capability of installing and processing high resource software's which makes it possible to accomplish the objectives streaming & controlling the robot. The live streaming is proficient by using the mjpeg streamer and the server-client model is made using java.
Effect of Nitrogen Levels on Yield, Competitive,

Intercropping is one of the most common practices used in sustainable agricultural systems which have an important role in increasing the productivity and stability of yield in order to improve resource utilization and environmental factors Hashemi et al. [1]. Therefore, intercropping became an attractive strategy for increasing productivity and labour utilization per unit area of available land and to intensify land use in the southern highland region Ibb (Yemen) in the last decades. Intercropping cereals and legumes is also important due to some potential benefits including the enhancement of forage quality through the complimentary outcome of two or more crops grown instantaneously on the same part of land Hamdollah (2012) and high productivity and profitability Yildirin & Guvence [2].
A LITERATURE SURVEY: EDUCATIONAL DATA MINING AND WEB DATA MINING

: Data Mining (DM) is extracting information from large set of data and obtaining meaningful results from it. Data Mining has evolved into diverse fields which requires development of data collection, creation, data management (including data storage retrieval and database transaction processing) and advanced data analysis (data warehousing and mining). This paper explains about two of Data Mining fields : Educational Data Mining (EDM) and Web Data Mining (WDM). Educational Data Mining (EDM) is an emerging field of data mining which applies various data mining algorithms for betterment of students and improving quality of student courseware. Web Data Mining (WDM) is a technique used to crawl through various web resources to collect information which an individual or a company use to promote business. In this survey, different published research papers on methodologies used in EDM and WDM are compared. Also, it gives an insight into techniques used in EDM and WDM.
An Ameliorated Methodology to Eliminate Redundancy in Databases Using SQL

Today, there is an exponential growth in the amount and variety of data stored in the form of databases. Data Cleaning is an inevitable problem when combining data from various distributed and commercial databases. Duplication elimination is an integral part of data integration and cleaning. While many frameworks and approaches exist to identify, merge and eliminate duplicates in the databases that relies on ad hoc solutions. We propose a complementary approach to eliminate redundancy in databases using Structured Query Language (SQL). SQL is the fourth generation database language and has statements for data definition, query and update. Today, most relational and commercial databases support SQL. This work is done by using SQL statements to eliminate redundant data in the relational databases. This new methodology can be easily embedded into any application programs which support database approaches.
A study on antioxidant activity, phenol, and flavonoid content of seedpod of Nelumbo nucifera Gaertn

Nelumbo nucifera (NN) Gaertn. (Family: Nelumbonaceae) commonly known as Indian lotus, a perennial aquatic plant been extensively used for nutritional and traditional medicinal purpose by people in many parts of the world. [1] Nelumbo is represented by only two species, NN and Nelumbo lutea. NN is widely distributed in Southeast Asia and in India, it occurs from Kashmir in north to Kanyakumari in south. [2] NN commonly known as American lotus is distributed in North and South America. [3]
Automatic Keyword Extraction for Text Summarization in Multi-document e-Newspapers Articles

Summarization is the way towards lessening the content of a text file to make it brief that holds all the critical purposes in the content of original text file. In the process of extractive summarization, one extracts only those sentences which are the most relevant sentences in the text document and that conveys the moral of the content. The extractive summarization techniques usually revolve around the idea of discovering most relevant and frequent keywords and then extract the sentences based on those keywords. Manual extraction or explanation of relevant keywords are a dreary procedure overflowing with errors including loads of manual exertion and time. In this paper, we proposed a hybrid approach to extract keyword automatically for multi-document text summarization in e-newspaper articles. The performance of the proposed approach is compared with three additional keyword extraction techniques namely, term frequency-inverse document frequency (TF-IDF), term frequency-adaptive inverse document frequency (TF-AIDF), and a number of false alarm (NFA) for automatic keyword extraction and summarization in e-newspapers articles for better analysis. Finally, we showed that our proposed techniques had been outperformed over other techniques for automatic keyword extraction and summarization.
THE EFFECTIVENESS OF CHRONOTHERAPY IN HYPERTENSIVE PATIENTS WITH AN INSUFFICIENT DEGREE OF SLEEP-TIME DIASTOLIC BLOOD PRESSURE

The violation of daily blood pressure (BP) profile is one of the predictors of cardiovascular (CV) morbidity and mortality in patients with arterial hypertension (AH). It is determined by ambulatory BP monitoring (ABPM). The aim of the study was to assess the impact of the chronotherapeutic approach on the level of systolic blood pressure (SBP) and diastolic blood pressure (DPB) and daily BP profile in patients with AH with insufficient degree of sleep-time relative DBP decline. The study included 28 patients with AH with nondipper DBP daily profile in age from 52 to 78 years old. The participants were divided onto two groups. Group 1 included 14 patients, who take all antihypertensive drugs in the morning, group 2 included 14 patients who takе at least one antihypertensive drug at bedtime. All patients underwent 24-hour blood pressure monitoring using the computer system «Cardiosens» (KhAI Medica, Ukraine, with the oscillometric method of BP measurement) when enrolling in the study and after 3 months. The type of SBP and DBP diurnal profile, the mean values of SBP, DBP and hyperbaric indices were determined and compared between groups 1 and 2 at each visit, as well as within groups between visits. The results showed that morning taking of antihypertensive drugs in patients with AH with insufficient degree of DBP decline influences more on SBP while evening taking – on DBP. It was concluded that violation of DBP daily profile in medication therapy of patients with insufficient degree of DBP decline should be provided along with violation of SBP daily profile.
Copy move forgery detection by matching triangles of key points via multi-scale analysis and voting processes

:- One of the most common type of tempering the digital images is copy image forgery. As this work gives a new approach for detecting copy image forgery. As earlier detection methods are used for copy image forgery that basically use block matching approaches that firstly divide the images into overlap blocks and then find out the similar ones. As in this paper hybrid approach is used with new algorithm for detection and localization of accurate copy image forgery which is based on multi scale analysis. As novel hybrid approach compare single points or triangles instead of blocks, and can fastly match the nearest neighbor by patch matching. This algorithm is adapted for achieve high robustness with rotation and scaling changes. The interest points are extracted from the image and are clustered in a triangle shape. After that a multi scale image is constructed now the generated group is examined using descriptor that is strongly robust to scaling and rotation and partially to compression. This paper deals with increasing accuracy by matching using points in geometric shape instead of using block matching methods.
BIOEFFICACY OF HYPTIS SUAVEOLENS AND MELOCHIA CHORCORIFOLIA AGAINST THE ARMYWORM, SPODOPTERA LITURA (FAB.) (LEPIDOPTERA: NOCTUIDAE)

The objective of the present study was to evaluate antifeedant, insecticidal, oviposition deterrent and ovicidal activity of different fractions obtained from the crude extracts of H. suaveolens (Lamiaceae) and M. corchorifolia (Sterculiaceae) against Spodoptera litura (Fab.) (Lepidoptera : Noctuidae), four fractions obtained from H. suaveolens, fraction III was found to inhibit the feeding ratio of the S. litura and it is apparent from the table. While in M. corchorifolia only three fractions have been obtained, among them fraction II was found to induced more feeding deterrent activity at 2000 ppm concentration. Ethylacetate extract of H. suaveolens yielded four fractions and diethylether extract of M. corchorifolia yielded five fractions. As per the data fraction III showed statistically significant ovicidal activity. It is also interesting to note that the same fraction was exerted strong ovipositional deterrent activity. Whereas, ethylacetate extract of M. corchorifolia yielded five fractions of which, fraction III showed increased ovicidal activity over the other fractions at higher concentration. Larvicidal activity obtained from the fraction II was significant than the other two fractions of the same extract. The larvicidal activity exhibited by the five fractions of diethyl ether extract of M. corchorifolia is shown in table 5. It is clear that fraction III at 1000 and 2000-ppm concentration was found to have increased activity than the other fractions.
noise removal from Speech Signals using Rank Order Mean Method

— This paper presents a noise cancellation technique to remove impulsive noises that commonly corrupt speech signals using Rank Order Mean is proposed. The rank order differentiation is applied to input signal to estimate the time occurrence of impulsive noise. Then rank order mean is used for replacing the noisy samples to get the noise free signal. The above described technique shows improvement in terms of Signal to Noise Ratio (SNR) and Perceptual Evaluation of Speech Quality (PESQ) with respect to the existing techniques.
Isolation and identification of newly effective bacterial strains exhibiting great ability of lignin and Rice straw biodegradation

Great amounts of lignin and lignin-related compounds such as rice straw are produced as wastes of agriculture activity or effluent from the pulping, and paper industries (de La Santoes et al., 2009). Lignin is the second abundant biomass that is associated with cellulose and hemicellulose in plant cells. It is a poly polymer and high molecular weight that gave it rigidity and resistant against decomposition by different kinds of microorganisms, (Wang et al., 2011).
Gait Recogniton System for Human Identification using BPNN Classifier

 Abstract — Recognition of any individual is a task to identify people. Human recognition methods such as face, fingerprints, and iris generally require user’s cooperation, physical contact or close proximity. These methods are not able to recognize an individual at a distance therefore recognition using gait is relatively new biometric technique without these disadvantages. Human identification using Gait is method to identify an individual by the way he walk or manner of moving on foot. Gait offers ability of distance recognition or at low resolution. In this paper, firstly binary silhouette of a walking person is detected from each frame. Secondly, feature from each frame is extracted using image processing operation. Here center of mass, step size length, and cycle length are talking as key feature. At last BPNN technique is used for training and testing purpose. Here all experiments are done on gait database and input video.
SOCIRANK: IDENTIFYING AND RANKING PREVALENT NEWSTOPICS USING SOCIAL MEDIA FACTORS

To predict interactions between social media and traditional news streams is becoming increasingly relevant for a variety of applications, including: understanding the underlying factors that drive the evolution of data sources, tracking the triggers behind events, and discovering emerging trends. Researchers have developed such interactions by examining volume changes or information diffusions, however, most of them ignore the semantical and topical relationships between news and social media data. Our work is the first attempt to study how news influences social media, or inversely, based on topical knowledge. We introduce a hierarchical Bayesian model that jointly models the news and social media topics and their interactions. We show that our proposed model can capture distinct topics for individual datasets as well as discover the topic influences among multiple datasets. By applying our model to large sets of news and tweets, we demonstrate its significant improvement over baseline methods and explore its power in the discovery of interesting patterns for real world cases.
Cardiovascular Disease Classification using Photoplethysmography Signals- Survey

In recent years, heart disease has been one of the main causes of death worldwide. Statistics report that around 17 million people die every year due to this disease. Usually the heart disease diagnosis is done using Electrocardiogram (ECG) which is very expensive for the people to afford especially in remote areas. But using Photoplethysmography (PPG) signals it is easier, non-invasive and less expensive in detecting the heart diseases and other abnormalities of human body. So in this paper, various PPG signals usage and their merits are discussed. Also this work focuses on several methods and algorithms of cardiovascular disease (CVD) classification. Several classifier techniques in the field of biomedical signal processing methods are also examined.
“Efficacy of Therapeutic Swedish Massage in the Treatment of Non-specific Pain of the Lumbar Region”

Research objective are (1) assess the effectiveness of Swedish massage in the treatment of non-specific pain in the lumbar region, to (2) measure the effects of Swedish massage on pain intensity, disability indexes and anxiety levels and to (3) measure pain intensity, disability indexes and anxiety levels before and after a single session. An experimental pilot study was implemented in a private physiotherapeutic center in Athens, Greece. Forty-five (45) women with non-specific pain in the lumbar region were selected. In this study; Ten sessions performed day after day of classical Swedish massage techniques (effleurage, petrissage, kneading, rolling, friction). The following Outcome Measures were used: Baecke Questionnaire, Pain intensity (Visual Analog Scale), Oswestry Disability Index, Rolland-Morris Disability and HAMilton Anxiety Scale (HAMA). The results showed significant pain reduction after the 5 th session which was maintained until the end of the research programme and 1 month after (p=0,006). Only at the end of the 10 sessions there was a statistically significant reduction in anxiety levels between the two groups (p=0,025). Regarding the functional levels, there was a statistically significant difference between the two groups at the end of 10 sessions [Rolland-Morris (p=0.000) and Oswestry Disability Index (p=0,001)]. Before and after a single session of Swedish massage, pain intensity and anxiety levels were reduced and functional ability was improved. The Results of this pilot study support the effectiveness of Swedish massage for the treatment of non-specific pain in the lumbar region and its efficacy in reducing pain. If results are confirmed in a larger randomized trial, Swedish massage could be an important component of therapeutic sessions.