827 research outputs found
Data mining with Predictive analysis for healthcare sector: An Improved weighted associative classification approach
Association mining has seen its growth right through data mining during the last few years as it has the ability to search for that entire database that could be of least constraints associated with it.Thus finding such small database sets could be done with the help of predictive analysis method. The paper enlightens the combinational classification of association and classification data mining. For this to happen a new set of constraints need to be introduced namely classification association rule( CAR).some systems like classification systems with domain experts are the ones that can be associated with. For fields like medicine where a lot many patients consult each doctor, but every patient has got different personal details not necessarily may suffer with same disease. So the doctor may look for a classifier, which could provide all details about every patient and henceforth necessary medications can be provided. However there have been many other classification methods like CMAR, CPAR MCAR and MMA and CBA.Some advance associative classifiers have also seen growth very recently with small amendments in terms of support and confidence, thereby accuracy. In this paper we proposed a HIT algorithm based automated weight calculation approach for weighted associative classifier
Extended Apriori for association rule mining: Diminution based utility weightage measuring approach
The field of Association rule mining is a dynamic area for innovation of knowledge through which uncountable procedures have been expounded. Recently, by including significant components viz. value (utility), volume of items (weight) etc, the researchers have enhanced the quality of association rule mining for industry by bringing out the association designs. In this note, a proficient methodology has been put forward based on weight factor and utility for effective digging out of important association rules. At the very beginning, a traditional Apriori algorithm has been utilized that make use of the anti-monotone property which states that if n items are recurring continuously then n-1 items should also recur by which the scores of weightage(W-Gain), utility(U-Gain) and diminution(D-sum), are derived at. Eventually, we derive a subset of important association rules through which EUW-Score is generated. The tentative outcome demonstrates the effectiveness of the methodology in generating high utility association rules that is profitably used for the business improvement
Value of Animal Symbols in Ashwin Sanghi’s The Krishna Key
Mythology is broad filed which is immortal. Within the realm of Hindu Dharma Mythology, the great Avatar alludes in ten different ways to the everlasting manifestation of God Vishnu. The researcher purges animal avatars with various faces, such as Kurma, Matsya, Varaha, and Narsimha. Narsimha also assumes human shape to safeguard the world from evil and rescues devout devotees. Animal avatars' metamorphosis demonstrates the value and significance of animals on Earth as well as how they have contributed to society's prosperity in the past, present, and future. While wild animals are not valued as much in society, in mythology animals always come first to destroy evil things with the aid of God and Goddess in war and other situations as well. Goddess Durga, for instance, is represented by a lion, which is a symbol of willpower and victory. Animal vehicles are symbolic of the god they carry in Hindu iconography, which deals with positive things. The bull-incarnation of Lord Shivan, Nandhi Bhagavan, is a symbol of virility and strength. Dinka, Lord Ganapathy's mouse car, is a symbol of quickness and intelligence. Karthikeya's peacock carriage, Parvani, stands for grandeur and majesty. Saraswathi's Hamsa chariot is a symbol of grace, beauty, and wisdom
Edge detection on DICOM image using triangular norms in Type-2 fuzzy
In image processing, edge detection is an important venture. Fuzzy logic plays a vital role in image processing to deal with lacking in quality of an image or imprecise in nature. This present study contributes an authentic method of fuzzy edge detection through image segmentation. Gradient of the image is done by triangular norms to extract the information. Triangular norms (T norms) and triangular conorms (T conorms) are specialized in dealing uncertainty. Therefore triangular norms are chosen with minimum and maximum operators for the purpose of morphological operations. Also, mathematical properties of aggregation operator to represent the role of morphological operations using Triangular Interval Type-2 Fuzzy Yager Weighted Geometric (TIT2FYWG) and Triangular Interval Type-2 Fuzzy Yager Weighted Arithmetic (TIT2FYWA) operators are derived. These properties represent the components of image processing. Here Edge detection is done for DICOM image by converting into 2D gray scale image, using Type-2 fuzzy MATLAB and which is the novelty of this work
Standardization of container type, substrate and nutrition for potted plant production of China aster [Callistephus chinensis (L.) Ness.] var. Arka Archana
A study was conducted at the ICAR-Indian Institute of Horticultural Research, Hesaraghatta, Bengaluru for three consecutive seasons during 2019-20, to standardize the container type, substrate combination and nutrition for potted plant production of China aster var. Arka Archana. The treatments comprised of two type of containers (plastic and coir), three substrates {Red soil + FYM + Sand (1:1:1 v/v), Arka Fermented cocopeat (AFC), AFC + Vermicompost (1:1 v/v)} and four nutrition concentration (160:30:180 ppm N:P: K, 128:24:144 ppm N:P: K, 96:18:108 ppm N:P: K and Jeevamrutha @ 3%) laid out in factorial completely randomized design with three replications. Plant height at flowering (33.12 cm), number of primary branches (12.4), plant spread (536.64 cm2), number of flowers/plant (26.47), flower size (5.26 cm) and uptake of major, secondary and minor nutrients were maximum in the plants grown in 6" plastic pots using the substrate combination of soil +sand +FYM (1:1:1 v/v/v) along with the weekly application of nutrient solution of 96:18:108 ppm NPK/plant. This production protocol resulted in a dense canopy and highly floriferous potted plants. The benefit cost ratio of potted China aster production was 1.70. This technology can be adopted by the nurserymen for large-scale commercial potted plant production
HANDLING OF RECURRENCE CONCEPT DRIFT IN DATA STREAM USING TIMESTAMP OF AUXILIARY LEARNING MODEL
Data stream is a collection or sequence of data instances of infinite length. Stream classification or online classification is more challenging task due to speed, diversity of concept or nature, type of distribution (linear or skewed), heterogeneous of data sources, lack of re-reading of instances and possibility of recurrence. This paper focuses on the concept drift under recurrence. The major challenge in data stream is handling of high volume of data of infinite length. Classification of instances under concept drift and recurrence is more difficult due to maintenance of past classifier results. To handle this situation in more efficient manner through swapping technique followed operating system’s demand paging concept with little modification
HANDLING OF RECURRENCE CONCEPT DRIFT IN DATA STREAM USING TIMESTAMP OF AUXILIARY LEARNING MODEL
Data stream is a collection or sequence of data instances of infinite length. Stream classification or online classification is more challenging task due to speed, diversity of concept or nature, type of distribution (linear or skewed), heterogeneous of data sources, lack of re-reading of instances and possibility of recurrence. This paper focuses on the concept drift under recurrence. The major challenge in data stream is handling of high volume of data of infinite length. Classification of instances under concept drift and recurrence is more difficult due to maintenance of past classifier results. To handle this situation in more efficient manner through swapping technique followed operating system’s demand paging concept with little modification
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An NGO-Implemented Community-Clinic Health Worker Approach to Providing Long-Term Care for Hypertension in a Remote Region of Southern India.
Poor blood pressure control results in tremendous morbidity and mortality in India where the leading cause of death among adults is from coronary heart disease. Despite having little formal education, community health workers (CHWs) are integral to successful public health interventions in India and other low- and middle-income countries that have a shortage of trained health professionals. Training CHWs to screen for and manage chronic hypertension, with support from trained clinicians, offers an excellent opportunity for effecting systemwide change in hypertension-related burden of disease. In this article, we describe the development of a program that trained CHWs between 2014 and 2015 in the tribal region of the Sittilingi Valley in southern India, to identify hypertensive patients in the community, refer them for diagnosis and initial management in a physician-staffed clinic, and provide them with sustained lifestyle interventions and medications over multiple visits. We found that after 2 years, the CHWs had screened 7,176 people over age 18 for hypertension, 1,184 (16.5%) of whom were screened as hypertensive. Of the 1,184 patients screened as hypertensive, 898 (75.8%) had achieved blood pressure control, defined as a systolic blood pressure less than 140 and a diastolic blood pressure less than 90 sustained over 3 consecutive visits. While all of the 24 trained CHWs reported confidence in checking blood pressure with a manual blood pressure cuff, 4 of the 24 CHWs reported occasional difficulty documenting blood pressure values because they were unable to write numbers properly. They compensated by asking other CHWs or members of their community to help with documentation. Our experience and findings suggest that a CHW blood pressure screening system linked to a central clinic can be a promising avenue for improving hypertension control rates in low- and middle-income countries
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