An overview of E-learning Tools and Analysis of its Awareness among Management Students

Management students are supposed to have not only the strong theoretical foundation but also the knowledge of current affairs, strong analytical skills, decision making skills etc. E-learning tools offer many of advantage to improve the quality of education through interactive teaching learning environment. This study is one of the steps towards analyzing the awareness & use of internet as well as e-learning tools by management students in NMU region and an overview of E-Learning Tools. It is based on primary data that is collected through structured questionnaire. Analysis reveals that students are available with sufficient time to spend on internet. Similarly internet tools are used to collect information & theory contents only and its use for interactive processes is very limited. Based on aforesaid analysis, it is concluded that adoption of digital teaching learning environment in North Maharashtra University is very limited. And students themselves are not well trained to use e-learning tools to the full extent. Hence there is need of digital approach in management education

Isolated primary Hydatid cyst of kidney: A case report of asymptomatic patient

We report an isolated primary hydatid cyst of kidney in a pregnant asymptomatic woman. We also present salient diagnostic feature of asymptomatic patients of hydatid cyst

A Bibliometric Survey on the Reliable Software Delivery Using Predictive Analysis

Delivering a reliable software product is a fairly complex process, which involves proper coordination from the various teams in planning, execution, and testing for delivering software. Most of the development time and the software budget\u27s cost is getting spent finding and fixing bugs. Rework and side effect costs are mostly not visible in the planned estimates, caused by inherent bugs in the modified code, which impact the software delivery timeline and increase the cost. Artificial intelligence advancements can predict the probable defects with classification based on the software code changes, helping the software development team make rational decisions. Optimizing the software cost and improving the software quality is the topmost priority of the industry to remain profitable in the competitive market. Hence, there is a great urge to improve software delivery quality by minimizing defects and having reasonable control over predicted defects. This paper presents the bibliometric study for Reliable Software Delivery using Predictive analysis by selecting 450 documents from the Scopus database, choosing keywords like software defect prediction, machine learning, and artificial intelligence. The study is conducted for a year starting from 2010 to 2021. As per the survey, it is observed that Software defect prediction achieved an excellent focus among the researchers. There are great possibilities to predict and improve overall software product quality using artificial intelligence techniques

A novel approach for Face Recognition using Local Binary Pattern

This paper presents Local Binary pattern (LBP) as an approach for face recognition with the use of some global features also. Face recognition has received quite a lot of attention from researchers in biometrics, pattern recognition, and computer vision communities. The idea behind using the LBP features is that the face images can be seen as composition of micro-patterns which are invariant with respect to monotonic grey scale transformations and robust to factors like ageing. Combining these micro-patterns, a global description of the face image is obtained. Efficiency and the simplicity of the proposed method allows for very fast feature extraction giving better accuracy than the other algorithms. The proposed method is tested and evaluated on ORL datasets combined with other university dataset to give a good recognition rate and 89% classification accuracy using LBP only and 98% when global features are combined with LBP. The method is also tested for real images to give good accuracy and recognition rate. The experimental results show that the method is valid and feasible

AHP validated literature review of forgery type dependent passive image forgery detection with explainable AI

Nowadays, a lot of significance is given to what we read today: newspapers, magazines, news channels, and internet media, such as leading social networking sites like Facebook, Instagram, and Twitter. These are the primary wellsprings of phony news and are frequently utilized in malignant manners, for example, for horde incitement. In the recent decade, a tremendous increase in image information generation is happening due to the massive use of social networking services. Various image editing software like Skylum Luminar, Corel PaintShop Pro, Adobe Photoshop, and many others are used to create, modify the images and videos, are significant concerns. A lot of earlier work of forgery detection was focused on traditional methods to solve the forgery detection. Recently, Deep learning algorithms have accomplished high-performance accuracies in the image processing domain, such as image classification and face recognition. Experts have applied deep learning techniques to detect a forgery in the image too. However, there is a real need to explain why the image is categorized under forged to understand the algorithm’s validity; this explanation helps in mission-critical applications like forensic. Explainable AI (XAI) algorithms have been used to interpret a black box’s decision in various cases. This paper contributes a survey on image forgery detection with deep learning approaches. It also focuses on the survey of explainable AI for images

Ethnomedicinal Knowledge of Plants used by Local People in Buldhana District of Maharashtra (India)

The present investigation was aimed at documentation, analysis and evaluation of ethnomedicinal knowledge in the study area as the forces of acculturation are rapid in recent times. The underprivileged tribal and rural people of Buldhana district (Maharashtra India) do not receive adequate primary healthcare.  They have perforce been  still utilizing traditionally the plants in their surrounding for various purposes including ethnomedicine. The objective of the study was to document ethnobotanical knowledge especially of notable herbs utilized by the different backward people, whether tribal or rural, in the area under study.  Season-wise regular visits formed the basis of the present investigation.  Ethnomedicinal data was obtained through structural interviews, and discussions, following Jain (1987), with the tribal/rural informants, healers, medicine-men/women, etc. (with age between 50-65) or actual personal observations during ethnobotanical forays.  Minimum five to eight informants were taken into consideration for each claim.  This investigation brought on record that people of the study area generally utilize 62 plants species belonging 38 families.  Different plant parts such as fruit, stem-bark and root are most commonly employed.  Medicinal recipes viz. extract, powder and decoction are used in this preferential order. A fair wide range of diseases, as many as 35, are treated by people of Buldhana district using local plants. Jaundice and rheumatism are more prevalent in the study areas as compared to other diseases.  These ethnomedicinal claims may aid in finding novel lead molecules for welfare of mankind. The data would be useful for further scientific investigations

Breast Cancer Detection

Breast Cancer is highly predominant in women in today’s world. It starts in the breast during the initial stages and spreads to other areas of the body after some period of time. Breast cancer is the second-largest disease leading to the death of women. The disease is curable if detected early enough. Breast Cancer Application monitors the abnormal growth of breast cells during the early stages. They are often diagnosed during the advanced stages of breast cancer. It is the second most diagnosed cancer in women, affecting one in every eight women. Our project comprises two modules, first consists of an application with user login and self-test examine section where and the second section consists of identifying benign and malignant cells. The second section will be used by doctors' side for the detection of abnormalities of breasts as early as possible by providing the user screening data set. It contains Machine Learning techniques for the classification of malignant and benign tumors. There are more treatment options and a better chance of survival. If breast cancer is detected during the early stages then there is a 93 percent of higher survival rate in the first five years

A nanocrystal technology: to enhance solubility of poorly water soluble drugs

Most of the recently developed new chemical entities are poorly water soluble and they create major problems during formulation and development of new dosage form and due to poor solubility and poor bioavailability. The drugs belong to BCS class II and class IV has problem of solubility, to overcome the solubility problem nanotechnology is most useful technique. In this review article the main focus on Nanocrystals and various techniques used for preparation of Nanocrystals. Drug nanocrystals consists pure poorly water soluble drugs without any matrix material which means that it is carrier free drug delivery. Nanocrystals technologies have been introduced as advantageous, universal formulation approaches for the BCS class II and IV drugs. Nanocrystals, with greater surface to volume ratio, can effectively increase both the dissolution rate and saturation solubility of active ingredients The Nanocrystals is suitable drug delivery system for all commonly used routes of administration such as oral, IV, SC, and IM and topical application. Nanocrystals can also be incorporated into the tablets, capsules, fast-melts and lyophilized for sterile product applications. There are no of techniques which are used for production including precipitation, milling, high pressure homogenization and combination methods such as Nano-Edge, SmartCrystal and Precipitation-lyophilization-homogenization (PLH) technology

STANDARD OPERATING PROCEDURE OF PANCHATIKTA GHRITA AND STUDY OF ITS ANTIMICROBIAL ACTIVITY

Sneha kalpana is the specialized pharmaceutical procedure to prepare oleaginous medicine from Kalka and Drava- dravya. While reviewing ancient texts variations are found regarding preparatory procedures, ingredients used, confirmatory tests advised, indication of Panchatikta Ghrita. All the information available is in scattered form in different texts. To overcome these ambiguities it is necessary to develop Standard Operating Procedure (SOP). In this SOP the Sequential, Scientific and Logical illustration and documentation of each and every step is given. In Pre-Operative phase Shodhana of Guggulu and Murchchana of Ghrita was carried out. In operative phase Kwath-4L, Kalka-90gm, Guggul-70gm, Murchchit ghrita-240ml were taken together and subjected Snehasadhan vidhi for 3 days giving 2 hours of heat daily keeping the temp. in between 500 to 900 C till Snehasiddhi lakshana obtained.175gm of Panchatikta ghrita was prepared according to this SOP. It took 9 days to complete entire procedure. Quality parameter assessment was done by carrying physicochemical analysis viz. Sp. Gravity, Ref. index, Congealing point Sap value, Iodine value etc. Further antimicrobial study of Panchatikta ghrita against E-coli, Streptococcus Pyogens, Staphylococcus Aurens, S.typhi, C. Albicans etc was carried out. But no zone of inhibition was seen for any of the selected micro-organisms. The in vitro negative results didnt entirely reveal its therapeutic efficacy. In Ayurvedic therapeutics the Pharmacokinetics and Pharmacodynamics of the drug entirely depends upon Rasa, Veerya, Veepaka, Prabhava and balance of Tridosha in the body. The ingredients of Panchatikta Ghrita with their Rasa, Veerya, Veepak are very much competent to exhibit antimicrobial property from Ayurvedic perspective