Squential Step Towards Pattern Warehousing

With the massive increase in the data, the demand by the analysts hyped for the proper repositories where they could analyse the concerned specific data patterns in order to make smart and quick decisions for the welfare and benefit of the business, organization or some social work. Pattern warehouse proved to be the best solution. This paper focuses on the discussion of existing architecture and moreover on the algorithms that is needed for retrieving the optimal patterns from the pattern warehouse. It also includes the detailed study about the sequential emergence of association rule algorithms which initially derive out patterns and later on those patterns are being optimized according to the interest of the analyst

JIWHA PARIKSHA- A MIRROR OF HUMAN HEALTH

The tongue is the primary organ of taste and considered as the mirror that reflects the conditions of the body's internal organs, particularly the organs of digestion and metabolism. The tongue also reflects the overall digestive, nutritive and metabolic conditions of the organism. An ideally healthy tongue will look clean and have a pink colour with no white coating. In Ayurveda, Acharya Yogaratnakara has mentioned tongue examination as Jiwha Pariksha under Ashtasthana pariksha. Jiwha (Tongue) tells about the Dosha, Agni and Kostha. The tongue is the window to our digestive system. There is a large amount of information that can be learned from this observation, including the health of various bodily systems, toxins within the system, emotional states, and much more. So, the inspection of the tongue becomes an important starting point in the clinical examination and a careful observation of the state of tongue, its colour, and shape often gives a physician an insight into the current health condition of the patient

Design and Development of a Cost Effective Robot for Academics and Small Industries

The current trends in technology development are indicating that robotics, automation and internet of things are going to take central place in our society, workplace and households. Still, a large section of population is not conversant with the usage, design and development of robotic system for various activities. The high cost of such devices is the major hindrance in making the robots and robotics technology available to larger section of society, industry and academics. In order to address the above issue of availability of cheap robotic system for them, we had initiated the effort to design cost effective open source robotic system. The main focus of this work to design, development and fabrication of intelligent robotic arm can accomplish predefined task accurately. The robot is designed to work in Arduino platform and actuated by servo drives. The motivation behind designing of this robot is to provide school, colleges and small industries of Chhattisgarh to adopt robotics and automation for education and production. The robot was designed with 4-degree of freedom and well tested, further modification and improvements are being implemented to perform more complicated and precise task in all condition. Testing and validation of the robot was carried out and results shows that it work properly

Deep Learning Techniques in Extreme Weather Events: A Review

Extreme weather events pose significant challenges, thereby demanding techniques for accurate analysis and precise forecasting to mitigate its impact. In recent years, deep learning techniques have emerged as a promising approach for weather forecasting and understanding the dynamics of extreme weather events. This review aims to provide a comprehensive overview of the state-of-the-art deep learning in the field. We explore the utilization of deep learning architectures, across various aspects of weather prediction such as thunderstorm, lightning, precipitation, drought, heatwave, cold waves and tropical cyclones. We highlight the potential of deep learning, such as its ability to capture complex patterns and non-linear relationships. Additionally, we discuss the limitations of current approaches and highlight future directions for advancements in the field of meteorology. The insights gained from this systematic review are crucial for the scientific community to make informed decisions and mitigate the impacts of extreme weather events

Development and characterization of surface solid dispersion of curcumin for solubility enhancement

Surface solid dispersion (SSD) of curcumin was developed and characterized with purview to overcome solubility hurdle in its pharmacokinetic and pharmacodynamic performance. SSDs were prepared by co-evaporation method using polyplasdone XL, croscarmelose sodium, and silicone dioxide and polyethlene glycol 6000 as carrier. The optimized SSD (F9) was characterized using FE-SEM and XRD as an analytical tool. The formulation of modified Curcumin shows better drug release profile as compared to the natural Curcumin. Formulation F9 released more than 90% of the loaded Curcumin within 30 minutes where marketed formulations shows 90% drug only after 60 minutes. &nbsp

Studies of genetic variability, heritability and genetic advance in balsam (Impatiens balsamina L.)

A field experiment was carried out with 34 genotypes of Balsam (Impatiens balsamina L.) to assess the variability, heritability and genetic advance with an objective to identify superior genotypes for further crop improvement programme. The experiment was conducted during rainy season 2014 at the Horticulture Research Farm, Department of Horticulture, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi. These genotypes show significant variation at 5% level of significance for different characters under study. Highest range of variation was reported with the number of flowers/plant (109-221). The phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) was maximum for seed yield/plant, i.e. 29.02 and  26.34 while, minimum in case of length of leaf, i.e.  8.35 and 6.48, respectively. High heritability was observed for all the characters except plant height, width of leaves and duration of flowering. Maximum heritability was recorded for duration of flowering (90.68%) and minimum was observed in width of leaf (30.04). High heritability (h2 = 90.64) with high genetic advance (GA= 71.36) as percentage of mean was observed for number of flowers/plant, which indicated that additive gene effects were more important for that trait. High genetic advance as per cent of mean was observed for number of flowers/plant (71.36) however, lowest for floral bud diameter (0.11) which indicates the preponderance of additive genes and selection will be effective for improvement of these traits

Improved Density Based Spatial Clustering of Applications of Noise Clustering Algorithm for Knowledge Discovery in Spatial Data

There are many techniques available in the field of data mining and its subfield spatial data mining is to understand relationships between data objects. Data objects related with spatial features are called spatial databases. These relationships can be used for prediction and trend detection between spatial and nonspatial objects for social and scientific reasons. A huge data set may be collected from different sources as satellite images, X-rays, medical images, traffic cameras, and GIS system. To handle this large amount of data and set relationship between them in a certain manner with certain results is our primary purpose of this paper. This paper gives a complete process to understand how spatial data is different from other kinds of data sets and how it is refined to apply to get useful results and set trends to predict geographic information system and spatial data mining process. In this paper a new improved algorithm for clustering is designed because role of clustering is very indispensable in spatial data mining process. Clustering methods are useful in various fields of human life such as GIS (Geographic Information System), GPS (Global Positioning System), weather forecasting, air traffic controller, water treatment, area selection, cost estimation, planning of rural and urban areas, remote sensing, and VLSI designing. This paper presents study of various clustering methods and algorithms and an improved algorithm of DBSCAN as IDBSCAN (Improved Density Based Spatial Clustering of Application of Noise). The algorithm is designed by addition of some important attributes which are responsible for generation of better clusters from existing data sets in comparison of other methods