An Investigation on the Variety of English Used by Students in the ESL Classroom

This study reports and discusses some of the common features evident in an English written composition of a group of Form Five students' from the districts of Kuala Pilah and Seremban in Negeri Sembilan. The results of the analysis suggest that the salient features identified in the written compositions are features of Malaysian English, which has been recognised as a new nonnative variety of English

Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey

Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods

Dyeing of cotton yarn with marigold (Tagetes erecta) petals: An emphasis on pre-treatments and mordants

Natural dyes and eco-friendly finishing of textile fabrics is gaining popularity because of the consciousness of people in saving the ecology. Widely available resources in India have encouraged researchers in experimenting on extraction and application of dyes for textile colouration. The aim of the present experiment was to standardize a protocol for optimization of pre-treatment, mordanting and dyeing of cotton yarn with African marigold flower petals. Myrobolan, pomegranate rind and tamarind hull were utilized in different concentrations for pre-treatment. Effect of different mordants and pre-treatment concentrations on colour strength (K/S, L, a* and b*) parameters of the cotton yarn is was studied. Optimised pre-treatment concentrations, mordants and dyeing techniques on colour fastness parameters are also presented. Myrobolan followed by pomegranate rind pre-treatment produced darker and even shades on cotton yarns. Metallic salts viz., Stannous Chloride, Copper Sulphate and Ferrous Sulphate proved to produce shades with good to excellent colour fastness properties

AN ASSESSMENT ON BUCCAL MUCOADHESIVE DRUG DELIVERY SYSTEM

Buccal drug delivery system (BDDS) has won a variety of exposure and traction as it possesses plenty of advantages and benefits as evaluate to different mucosal drug delivery systems. Buccal path for systemic drug delivery, the use of mucoadhesive polymers twill significantly increase the efficacy of many tablets, has been of outstanding interest over the previous couple of decades. This article affords a precise of BDDS mechanisms, consisting of a composition of the oral mucosa, delivery mechanism, numerous forms of BDDS, formulation, assessment and application of BDDS. Additionally, this text affords a precis over the patents, advertised products and destiny factors of BDDS. In this evaluation article, we've got tried to assemble the maximum significant reports (1988 to 2021) of formulation, assessment, application, patents of BDDS. This review will help pharmaceutical researchers to clarify the potential of BDDS to overcome the various existing drug delivery dispute like the efficiency of absorption, permeability and bioavailability of drugs

Effective Clustering Algorithms for VLSI Circuit Partitioning Problems

Abstract In this article, the effective circuit partitioning techniques are employed by using the clustering algorithms. The technique uses the circuit netlist in order to cluster the circuit in partitioning steps and it also minimizes the interconnection distance with the required iteration level. The clustering algorithm like K-Mean, Y-Mean, K-Medoid are performed on the standard benchmark circuits. The results obtained shows that the proposed techniques improves the time and also minimize the area by reducing the interconnection distance

DEVELOPMENT AND VALIDATION OF STABILITY INDICATING RP-HPLC METHOD FOR THE SIMULTANEOUS ESTIMATION OF ACLIDINIUM BROMIDE AND FORMOTEROL FUMARATE IN BULK AND INHALER FORMULATION

Objective: To develop a simple, accurate, precise, rapid and sensitive method for the simultaneous estimation of Formoterol fumarate and Aclidinium bromide in pharmaceutical dosage form. Methods: The chromatogram was run through Ascentis C18 150 x 4.6 mm, 5µ. Mobile phase containing Water: Acetonitrile taken in the ratio 60:40 was pumped through the column at a flow rate of 1.0 ml/min. The temperature was maintained at 30 °C. The optimized wavelength selected was 220 nm. Results: The retention times of Formoterol fumarate and Aclidinium bromide were found to be 2.953 min and 2.364 min. %RSD of the Aclidinium bromide and Formoterol fumarate was found to be 0.6 and 0.9, respectively. %Recovery was obtained as 99.81 % and 100.20% for Aclidinium bromide and Formoterol fumarate, respectively. LOD, LOQ values obtained from the Signal-to-noise ratio of Aclidinium bromide and Formoterol fumarate were 0.84 µg/ml, 2.56 µg/ml and 0.01 µg/ml, 0.03µg/ml respectively. Regression equation of Formoterol fumarate is y =9023x+268.67, and y = 4661.2x+1941.9 of Aclidinium bromide. Retention times were decreased and that run time was decreased, so the method developed was simple, rapid, sensitive and economical that can be adopted in regular quality control tests in Industries. Conclusion: Developed and Validated Formoterol fumarate and Aclidinium bromide in pharmaceutical dosage form by using RP-HPLC method

SOIL EROSION ESTIMATION OF WATERSHED USING GIS (A CASE STUDY OF MANJRA BASIN AT AURAD TALUKA)

To have any development activity especially for soil and water conservation measures, watershed management plays a vital role in conserving natural resources. Soil loss is a very serious problem which effects environment as it threatens agriculture and also surroundings. As the productivity of the land is caused by the soil loss and in turn down areas are adversely effected, soil conservation is a primary step for having any development activities. In reality, it is not possible to conserve all areas under threat of erosion because of the financial constraints. In practice, prioritization of watersheds is derived and vulnerable areas are prioritized and then taken for conservative methods and taking up the entire watershed would be financially not feasible. Many aspects are to be considered while prioritizing the watershed to be conserved like threats to lives, political suitability, social constraints etc, for the scope of this project the prioritization is not taken up as the study area is the catchment to small water body and the area considered is also small. Soil loss is Estimated using GIS technique which is the present most powerful software to easily and quickly ascertain the required for large areas. Universal soil loss equation is the most common method of evaluating the loss although many modifications were made to this equation but all are based on the factors considered in USLE only like rainfall erosivity, soil erodibility, slope length, slope class, land cover and land management practices are taken as directly proportional to the rate of annual soil erosion. In the present study, the watershed in Bidar district of Karnataka has been taken. The average annual erosion for the study area is estimated by USLE using GIS technique. The average soil loss from the watershed is estimated to be 892 tones/Ha/Year

WIRELESS TRAFFIC ANALYSIS AND ANOMALY DETECTION USING DEEP LEARNING

Presented herein are innovative techniques for analyzing network traffic and identifying anomalous patterns using Artificial Intelligence (AI). In particular, the techniques presented herein map the network traffic into pictures and use advanced image recognition AI to detect anomalies in those pictures. The solution uses Transfer Learning from pre-trained models such as RESNET50. Since the models are pre-trained, the amount of new training data and time is reduced drastically