Data mining is an unsupervised learning technique to extract the insights and hidden relationships among data. Data mining has more importance in data science and machine learning because through data mining all hidden information is shown to determine various aspects of the data set. Clustering is a data mining technique to group the data, on the basis of similarity measures. The objects or data points in a cluster are similar. Similarly, objects or data points in another cluster will also be similar. But when these clusters are compared, they are dissimilar to each other. Clustering is considered the most important unsupervised learning technique because it deals with finding a structure in a collection of unlabeled data. Clustering can be done by the different approaches like partitioning clustering, hierarchical clustering, density-based clustering, and grid-based clustering. These clustering approaches can be done by the numbers of algorithms, such as K-means clustering, Fuzzy C-means clustering, Hierarchical clustering, DBSCAN, OPTICS, STING, ROCK and CACTUS. This proposed paper contained reviews of the above techniques by using a more powerful programming language (Python) as a tool. Evidence attainable from this study is helpful for researchers to select an appropriate clustering approach based on their domain.
Cysts, polyps and inflammatory process are the major benign tumors of the oral cavity. The SCC, lymphomas, sarcomas of bones and soft tissues and rarely melanomas are malignancies of oral cavity. Distal metastases from of breast carcinoma, lungs, abdominal organs and prostate can occur in oral cavity. The age of these lesions is among less than one year kids up to 85 years old, almost 90% of the patient’s average age of 40 years. These tumors distributed in all over the world especially in the socio-demographic area. Objectives: To evaluate the histopathological outlines of OMF specimens received in pathological Department of SMC/SGTH KPK. Methods: A cross sectional retrospective study. Results: Of a total of 321 samples 164 (51%) were male while 157 (49%) were women with a proportion of M: F=1.05: 1. Mesenchymal tumors, other than osseous tumor, have the maximum quantity of 33.9% cases trailed by epithelioid lesions, 20%, odontogenic masses 5.3%, lesions of salivary gland were 14.6%, lesions of benign cyst were 12.5%, inflammatory lesions 11% and the minimum numbers of oral and maxillofacial specimens was bone tumor with 2.9% cases. From the benign tumors fibro epithelial tumor 23% is the commonest. The SCC was 57%, the largest contributor among all malignancies. Conclusion: Our study demonstrates the variations of age, sex and location in the oral and maxillofacial masses. The malignant masses are common an elderly aged patient, while the benign are more common an early and middle age people.
Laminar natural convection in two-dimensional Prismatic enclosure is studied and analysis numerically. For the enclosure top inclined walls are considered at low temperature, two vertical walls are adiabatic and strip heater at constant high temperature mounted on the bottom enclosure, while the reminder bottom wall kept at low known temperature. The partial differential equations for two dimensional conservation of mass, momentum and energy are solved using finite element software package (FLEXPDE.5). For Rayleigh number varying from 103 to 105 and for constant Prandtal number Pr=0.7 the change in temperature and flow fields (stream functions) were investigated for different heater locations and for different number of heaters. The effect of the number and locations of the strip heaters on local and mean Nusslet number were examined. Results were presented by streamlines, isotherms and Nusselt number and it indicates that the Nusselt number is significantly affected by increasing both Ra and number of heaters. A comparison of the streamlines, isotherms curves and average Nusselt at the same boundary conditions was made with that obtained by Tanmay et al.(7), and showed a good agreement.
This research studies a three-dimensional fluid flow, and heat transfer in the heat sink numerically using air as a coolant. The numerical effects of the number of fins and their thickness on the performance of the heat sink are investigated using Ansys Icepak. Various fin numbers and fin thicknesses are used to check the heat sink’s optimal thermal performance. The results demonstrated that the maximum temperature, pressure drop, and thermal resistance decrease with the increase in the fin number and thickness. According to the results, the optimal thickness and number of fins for the current study are 15 and 0.25 mm, respectively. Also, it is observed that increasing the number of fins has a greater effect than increasing the thickness of the fins on the maximum temperature, pressure drop, and thermal resistance.
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