EFFICACY OF PATRAPINDA SWEDA AND MATRA BASTI (COMBINED THERAPY) IN THE MANAGEMENT OF SANDHIVATA (OSTEO ARTHRITIS)

According to WHO Sandhivata is the second commonest musculoskeletal problem in the world after backache. The present clinical trial was conducted to evaluate the efficacy of Ptrapinda Sweda and Matra Basti (combined Chikitsa) in the management of Sandhivata. Total 30 patients were selected for clinical trial. All the 30 patients were treated with Patrpinda Sweda for first 8 days and Vatanashak tail Matra basti for next 8 days. Results were assessed according to a standard grading system for Shool, Graha, Sparshasahatva and Shotha. Functional impairment was assessed by observing walking time. There was complete relief of Shool in 36.6%, Sparshasahatva in 43.3% and Graha in 43%. Significant improvement was observed in Shotha and in walking time. Marked improvement was observed in Shool in 40%, Sparshasahatva in 33.3% and Graha in 40%. Hence it is concluded from the study that the combination of Patrpinda sweda and Matra Basti is a reliable management of Sandhivata, which should be repeated at least 6 monthly to maintain the symptomless state

MANAGEMENT OF VITILIGO (SHVITRA) ACCORDING TO AYURVEDA: A CASE STUDY

The color of the skin is important biologically, cosmetically and socially. Vitiligo is an acquired condition where melanocytes are absent in affected area. The worldwide prevalence of Vitiligo is lesser than 1%. Though the condition is rare and non communicable, patients who are suffering from Vitiligo may experience cosmetically disfiguring and psychological problems like depression. It is not clear why the melanocytes disappear from the skin. Theories regarding the Vitiligo include an autoimmune cause because of association with other autoimmune disorders, presence of antimelanin antibodies and lymphocytic infiltrate in early lesions. In Ayurveda, all the skin diseases are described under the heading of ‘Kushta’, which are further divided in to two namely ‘Mahakushta’ and ‘Kshudra Kushta’. Shvitra has been mentioned separately. Based upon clinical features of Shvitra, it can be correlated with Vitiligo. Aacharya Charak has mentioned Shvitra under the ‘Rakta Pradoshaj Vikara’. Considering the limitations of modern medical system and side effects associated with long term use of medicines, Ayurveda has much more convincing treatment modalities for Vitiligo. In present study emphasis has been made to study efficacy of Shvitrahara Vati and Shitrahara Lepa in Shvitra (Vitiligo)

Pulmonary Function Tests by Spirometry in Patients with Metabolic Syndrome: A Comprehensive Analysis

A cohort of 113 participants satisfying the criteria for metabolic syndrome was used in this study to examine the link between metabolic syndrome and pulmonary function as measured by spirometry. The US National Cholesterol Education Programme Adult Treatment Panel III criteria for metabolic syndrome were used to select participants for a cross-sectional study. We gathered and analyzed information on each subject's demographics, metabolic parameters and lung function tests (FEV1, FVC, and FEV1/FVC ratio). The correlations between the elements of the metabolic syndrome, gender, and pulmonary function indicators were evaluated using statistical analysis. There was a wide age range in the study sample, with the 40 to 59 year old age bracket being the most common. Males had a higher prevalence of metabolic syndrome, according to the gender distribution. Males had greater systolic, diastolic, triglyceride, and fasting blood glucose levels than females, as well as lower levels of high-density lipoprotein cholesterol, among other symptoms of the metabolic syndrome. A sizable number of the individuals had abnormal pulmonary function, with a mixed obstructive and restrictive pattern being the most common. The number of metabolic syndrome components and pulmonary impairment were found to be significantly correlated. The strong link between metabolic syndrome and pulmonary dysfunction is shown in this study, underscoring the significance of early detection and therapy of metabolic syndrome, especially in people with impaired pulmonary function. To enhance the metabolic and pulmonary health of this population, comprehensive lifestyle treatments should be taken into consideration

Analysis of Image Enhancement Techniques

Resolution is one of the most important characteristic of an image and it defines the quality of an image. Resolution in its most basic form can be defined as the number of pixels of an image. For proper processing, the image needs to have spatial, temporal and spectral resolution. Images from remote sensing devices especially satellite images undergo resolution degradation due to environmental changes, limitations in sensor characteristics, etc. It is thus necessary to improve these images for better visual interpretation and to make them suitable for further processing. Image enhancement is a crucial preprocessing step which is problem oriented and application specific. In this paper, satellite image resolution enhancement techniques based on the Wavelet domain like DWT, WZP and DWTSWT are compared. Wavelet Transform is an important field for the research in Image Processing. Image enhancement being a subjective process is compared using quantitative parameters like PSNR, MSE, MAE and SSIM

Survey on: Software Puzzle for Offsetting DoS Attack

A Denial of Service (DoS) attack is a malevolent attempt to make a server or a network resource inaccessible to users, usually by temporarily breaking or suspending the services of a host connected to the Internet. DoS attacks and Distributed DoS (DDoS) attacks attempt to deplete an online service's resource such as network bandwidth, memory and computational power by overwhelming the service with bogus requests. Thus, DoS and DDoS attacks have become a major problem for users of computer systems connected to the Internet. Many state-art of the techniques used for defending the internet from these attacks have been discussed in this paper. After conducting an exhaustive survey on these techniques it has been found that the proposed software puzzle scheme that randomly generates only after a client request is received at the server side gives better performance as compared with previous techniques

Classification and Grading of Wheat Granules using SVM and Naive Bayes Classifier

India is the second leading producer of wheat in the world. Specifying the quality of wheat manually is very time consuming and requires an expert judgment. With the help of image processing techniques, a system can be made to avoid the human inspection. Classification of wheat grains is carried out according to their grades to determine the quality. Images are acquired for wheat grains using digital camera. Conversions to gray scale, Smoothing, Thresholding, Canny edge detection are the checks that are performed on the acquired image using image processing technique. Classification and Grading of wheat grain is carried out by extracting morphological, color and texture features. These features are given to SVM and Naive Bayes Classifier for classification. To evaluate the classification accuracy, from the total of 1300 data sets 50% were used for training and the remaining 50% was used for testing. The classification system was supervised corresponding to the predefined classes of grades. Results showed that overall accuracy of SVM and Naive Bayes classifier is 94.45%, 92.60% respectively. So, the classification performance of SVM is better than Naive Bayes Classifier. DOI: 10.17762/ijritcc2321-8169.15085

Review Paper on Healthcare Monitoring System

The proposed model enables users to improve health related risks and reduce healthcare costs by collecting, recording, analyzing and sharing large data streams in real time and efficiently. The idea of this project came so to reduce the headache of patient to visit to doctor every time he need to check his blood pressure, heart beat rate, temperature etc. With the help of this proposal the time of both patients and doctors are saved and doctors can also help in emergency scenario as much as possible. The proposed outcome of the project is to give proper and efficient medical services to patients by connecting and collecting data information through health status monitors which would include patient?s heart rate, blood pressure and sends an emergency alert to patient?s doctor with his current status and full medical information. In simple terms, i.e. ?Smart? objects which use various sensors and actuators that are able to perceive their context, and via built in networking capabilities they could communicate to each other, access the open source Internet services and interact with the human world. This not only makes the world connected but also robust and comfortable. It consists of a system that communicates between network connected systems, apps and devices that can help patients and doctors to monitor, track and record patients? vital data and medical information. Some of the devices include smart meters, wearable health bands, fitness shoes, RFID based smart watches and smart video cameras. Also, apps for smart phones also help in keeping a medical record with real time alert and emergency services

Feature Classification and Extreme Learning Machine Based Detection of Phishing Websites

Phishing is a cyber-attack that uses a phishing website impersonating a real website to deceive internet users into disclosing sensitive information. Attackers using stolen credentials not only utilize them for the targeted website, but they may also be used to access other famous genuine websites. This paper proposes a novel approach for detecting phishing websites using a feature classification technique and an Extreme Learning Machine (ELM) algorithm. The proposed system extracts various features from the website URL and content, including text-based, image-based, and behavior-based features. These features are then classified using a feature selection technique, which selects the most relevant features to improve the detection accuracy. The selected features are then fed into the ELM algorithm, which is a powerful machine learning method for classifying and predicting data. The ELM algorithm It trains upon a huge set of data legitimate & phishing websites, and final outcome model is applied to classify unknown websites as either legitimate or phishing. The proposed approach is evaluated on several benchmark datasets and compared with other state-of-the-art phishing detection methods. The experimental results demonstrate that the proposed approach achieves high detection accuracy and outperforms other methods in terms of precision, recall, and F1-score. The proposed approach can be used as an effective tool for detecting and preventing phishing attacks, which are a major threat to the security of online users