Using Support Vector Machine For Classification And Feature Extraction Of Spam In Email

We provide an overview of recent and successful content-based e-mail spam filtering algorithms in this article. Our main focus is on spam filters based on machine learning and variants influenced by them. We report on significant ideas, methodologies, key endeavors, and the field's current state-of-the-art. The initial interpretation of previous work demonstrates the fundamentals of spam filtering and feature engineering in e-mail. We finish by looking at approaches, procedures, and evaluation standards, as well as exploring intriguing offshoots of recent breakthroughs and proposing directions of future research

Effect of chemicals treatment and fiber loading on mechanical properties of borassus (Toddy palm) fiber/epoxy composites

Abstract: The aim of the present study was to investigate and compare the mechanical properties of untreated and chemically modified Borassus fiber reinforced epoxy composites. Composites were prepared by hand lay-up process by reinforcing Borassus fibers with epoxy matrix. To improve the fiber-matrix adhesion properties, alkali (NaOH), and alkali combined with silane (3- aminopropyltriethoxysilane) treatments on the fibers surface were carried out. Examinations through Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) were conducted to investigate the structural and physical properties of the Borassus fibers. Tensile properties such as modulus and strength of the composites made by chemically modified and untreated Borassus fibers were studied using a Universal Testing Machine (UTM). Based on the experimental results, it was found that the tensile properties of the Borassus reinforced epoxy composites were significantly improved, as compared with the neat epoxy. It was also found that the fiber treated with combination of alkali and silane exhibited superior mechanical properties as compared with alkali and untreated fiber composites. The nature of fiber/matrix interface was examined through SEM of cryo-fractured samples. Chemical resistance of composites was also found to be improved with chemically modified fiber composites

Effect of land configurations and Pongamia mulch on soil moisture content and yield of yellow pericarp sorghum during kharif

The present work aims to determine the effect of land configurations and Pongamia pinnata mulch on soil moisture content and yield of yellow sorghum during kharif, 2018-19 on sandy clay loam soils of Hyderabad. The experiment was conducted at the College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad. The treatments included land configurations (Flatbed, Ridge and furrow, Broad bed and furrow, Flatbed + Mulch, Ridge and Furrow + Mulch, Broad bed and furrow + Mulch) and yellow sorghum genotypes (PYPS 101, PYPS 102, PYPS 103 and PYPS 104). Mulch used in this investigation was Pongamia leaf mulch applied @ 6 t ha-1 uniformly at 20 DAS. Soil moisture played a vital role in increasing crop yields in the rainfed regions of the semi-arid tropics. During most crop growth stages, the availability of soil water was increased by Broad bed and furrow + mulch, resulting in increased grain yield by 37 % (1701 kg ha-1) of yellow sorghum over flatbed. Ridge and furrow + mulch were found to be the next best treatment, with a grain yield of 1590 kg ha-1. Mulched treatments of flatbed, ridge and furrow and broad bed and furrow increased the grain yield by 20%, 28% and 37%, respectively, compared to flatbed without mulch. The present study will help in recognizing profitable moisture conservation practices and the role of Pongamia mulch in soil moisture conservation and yield maximization of yellow sorghum

Physiological approaches to improving harvest index and productivity in sunflower

Factors associated with variation in harvest index and approaches to improve harvest index (HI) and productivity in sunflower are discussed in this article. In recent years, higher productivity in sunflower has been achieved mainly through increased crop growth rates. Besides, an improvement in harvest index also has contributed for improved productivity to a certain extent. In our study we observed that medium duration types (100 to 110 days) had high HI compared with early or long-duration varieties and we also attempted to understand the ways and means to improve HI in sunflower types with varied duration. Genotypes which had low partitioning of dry matter to stem plus thalamus had high HI. Genotypes which accumulated high biomass during post flowering stages of development also showed high HI and seed yield. In a few genotypes remobilization of photosynthates from vegetative plant parts to the seed resulted in high HI and seed yield. Among the sink characters, the number of seed per head, test weight and seed density (weight/volume) also contributed to achieving high HI values. Identification and selection of genotypes based on these criteria will increase the production further. Since large amount of biomass is still locked up in the vegetative plant parts, any practice to manipulate the mobilization of photosynthates from vegetative parts to head also improves HI and thus seed yield. In our experiment, we observed that foliar application of boron nutrient and application of growth regulators to the head improved the translocation of photosynthates to the head and thus increased the HI and seed yield

Data Analytics in Abroad and Indian Education System-Using Data Mining Classification Techniques by R Language

Education System in recent years has been a progression, in Indian and Abroad Education system. In selecting the next education establishment by the scholars. The most key terms of selecting associate in nursing institute area unit pursue data, institute enfranchisement, institute ranking, freshman retention, graduation rates and strength of the college resources, location, feel of field life, placement records, analysis activities, course length, course outcome, educational offerings, activities and sports, price of the provision of economic aid and etc. This paper proposes to handle the coed quality in choosing an establishment to pursue educational activity in abroad/India supported the on top of mentioned key terms by having a deep analysis victimization data processing, classification and prediction model techniques victimization R language with Rattle Package

An Extensive Benchmark Experimental Evaluation of Methods for Multi Label Learning In R

A smart product is one that is able to immingle with masses. Sensible merchandise does not seem to be solely easy merchandise, however, with a touch of cleverness supplemental to permit the user some flexibility operative. Smart product adapts to the context of the user and does not force the user to adapt to that. Sensible merchandise have a group of properties that creates them distinctive area unit self informative, self organizing, extensible, self property, device capabilities, practicality, integrity, user services, property. The client’s ranking or priority whereas shopping for varied sensible merchandise area unit dynamical day by day as a result of advancements in technology and customer principally target the advanced options of the sensible merchandise they are shopping for. This paper principally shows, however, affectively sensible merchandise area unit utilized by the shoppers and area unit hierarchic based mostly upon their performance by exploitation R language and WEKA. By using R we can have a deep analysis over the various smart products and the user can be able to know the most widely purchased smart products according to their ranking. We can have deep analysis of smart products using data mining classification and prediction techniques such as J48, Random Forest machine learning algorithms in WEKA and R Language. R allows wide number of smart products data and analyzes with in limited resources. The WEKA and R language is opted to see the classification and prediction performances. Four measures (sensitivity, specificity, accuracy, F–measure) of performance here considered are based on confusion matrix/Error Matrix of R and WEKA, table of counts revealing the performance of each algorithm’s confusion regarding the true classifications and predictions. The observation of all the four performance measures used to analyze the smart products use

Assessment of crop loss in Arabica coffee due to white stem borer, Xylotrechus quadripes Chevrolat (Coleoptera: Cerambycidae) infestation

The coffee white stem borer (CWSB) is the most dreaded pest of Arabica coffee in India. Due to the concealed nature of this pest, the management measures are difficult and require the timely implementation of control measures. The recommended practices for the management of CWSB mainly targets on eggs and early instar larvae, apart from tracing and uprooting of infested plants before the commencement of flight periods (April-May and Oct-Dec). In general, youngArabica coffee plants infested by CWSB die within a year, whereas aged plants withstand the attack for few more years. However, such plants become less productive, susceptible to diseases and also serve as inoculum for further spreading of the infestation. A study was undertaken to assess the crop loss due to CWSB infestation on established Arabica plantation in Tamil Nadu. The result indicated a significant difference between healthy and infested plants and the crop loss was to the tune of 17.7 per cent. Further, quantitative data on out-turn percentages recorded at different stages of coffee processing (right from harvesting of fruits to marketable green coffee bean) are discussed in this paper

Aflatoxins B1 in different grades of chillies (Capsicum annum L.) in India as determined by indirect competitive-ELISA

Samples of the three grades of chilli pod (grades 1 to 3) were collected during surveys in 1998 and 1999 from the principal market yards and cold storage facilities of the major chilli-growing areas of Andhra Pradesh (AP), India. Chilli powders were collected from different supermarkets in Hyderabad, AP. They were analysed for aflatoxin B1 (AFB1) content by an indirect competitive ELISA. To avoid the influence of interfering substances present in chilli extracts, it was necessary to prepare the aflatoxin standards in methanol extracts of chillies free from aflatoxins. For nine representative samples there was good agreement between ELISA and HPLC estimations of AFB1 and the results suggested that the ELISA procedure adopted was dependable. Of the 182 chilli samples tested, 59% of the samples were contaminated with AFB1 and 18% contained the toxin at non-permissible levels. The highest AFB1 concentration of 969 µg/kg was found in one sample representing grade 3. Overall the maximum percentage of chilli pods showing AFB1 levels higher than 30 μg/kg (non-permissible levels) was in grade 3. Chilli pods stored in refrigerated rooms showed the lowest proportion of samples containing aflatoxin. Nearly 9% of the chilli powders sold in supermarkets contained non-permissible aflatoxin levels. This report highlights the importance of using grade 1 chilli pods to minimize aflatoxin contamination

Onset of human preterm and term birth is related to unique inflammatory transcriptome profiles at the maternal fetal interface.

BackgroundPreterm birth is a main determinant of neonatal mortality and morbidity and a major contributor to the overall mortality and burden of disease. However, research of the preterm birth is hindered by the imprecise definition of the clinical phenotype and complexity of the molecular phenotype due to multiple pregnancy tissue types and molecular processes that may contribute to the preterm birth. Here we comprehensively evaluate the mRNA transcriptome that characterizes preterm and term labor in tissues comprising the pregnancy using precisely phenotyped samples. The four complementary phenotypes together provide comprehensive insight into preterm and term parturition.MethodsSamples of maternal blood, chorion, amnion, placenta, decidua, fetal blood, and myometrium from the uterine fundus and lower segment (n = 183) were obtained during cesarean delivery from women with four complementary phenotypes: delivering preterm with (PL) and without labor (PNL), term with (TL) and without labor (TNL). Enrolled were 35 pregnant women with four precisely and prospectively defined phenotypes: PL (n = 8), PNL (n = 10), TL (n = 7) and TNL (n = 10). Gene expression data were analyzed using shrunken centroid analysis to identify a minimal set of genes that uniquely characterizes each of the four phenotypes. Expression profiles of 73 genes and non-coding RNA sequences uniquely identified each of the four phenotypes. The shrunken centroid analysis and 10 times 10-fold cross-validation was also used to minimize false positive finings and overfitting. Identified were the pathways and molecular processes associated with and the cis-regulatory elements in gene's 5' promoter or 3'-UTR regions of the set of genes which expression uniquely characterized the four phenotypes.ResultsThe largest differences in gene expression among the four groups occurred at maternal fetal interface in decidua, chorion and amnion. The gene expression profiles showed suppression of chemokines expression in TNL, withdrawal of this suppression in TL, activation of multiple pathways of inflammation in PL, and an immune rejection profile in PNL. The genes constituting expression signatures showed over-representation of three putative regulatory elements in their 5'and 3' UTR regions.ConclusionsThe results suggest that pregnancy is maintained by downregulation of chemokines at the maternal-fetal interface. Withdrawal of this downregulation results in the term birth and its overriding by the activation of multiple pathways of the immune system in the preterm birth. Complications of the pregnancy associated with impairment of placental function, which necessitated premature delivery of the fetus in the absence of labor, show gene expression patterns associated with immune rejection