An overview of corona virus disease 19 - COVID 19

A remerging infectious disease that has caught the entire world unaware. Coronavirus is an enveloped virus having non- segmented positive-sense RNA genome and belongs to the family Coronaviridae. Important modes of transmission are direct contact and respiratory droplets. Though the virus survives on environmental surfaces for varied period of time, it gets easily inactivated by chemical disinfectants .The major clinical features in uncomplicated cases include fever (88%), dry cough (67%), myalgia (14.9%) or fatigue (38%). In the absence of an effective treatment and vaccine, preventive measures like physical distancing, hand hygiene, following respiratory etiquettes & wearing mask assume great importance. Vigourous surveillance, contact tracing and containment can go a long way in controlling the spread of Covid 19

Node analysis of digital drapemeter

A digital drapemeter has been designed and developed for the node analysis of the varying commercial fabrics. The image analysis technique is used for the acquisition of the images and processed through the software. The separate graphical user interface is developed to display the values of DC% of the fabrics. The result confirms that there is a good and positive correlation between the newly designed drapemeter and the commercially available traditional drapemeter. Negative correlation has been found between the numbers of nodes and the drape coefficient of fabrics

Chaturvinshati Upkrama and its role in management of poisoning

Agadtantra is the branch of Astanga Ayurved having system of knowledge for conquering poisons. Acharya Charaka has explained twenty-four modalities of treatment which are to be employed while treating poison. Chaturvinshati Upkramas are unique in the management of poisons. It can be seen that most of them are based on same principle of modern medicine. Chaturvinshati Upkramas is common for all types of Visha i.e., Sthaavara, Jangama, Gara, Dooshi Visha etc. In most of the cases Upakramas should be selected by the physician on the basis of the type of Visha Prakruti (constitution), Saatmya (compatibility), Ritu (season), Desha (place), Vega (impulse) and Balaabala (strength and weakness of both the patient and poison)

Efficient kNN Join over Dynamic High-dimensional Data

The k nearest neighbor (kNN) join searches for the k nearest neighbors for each query point in the query dataset U from the answer points in the answer dataset I. It is a fundamental operation in many applications, including databases, data mining, computer vision, machine learning, recommendation systems, and more. In today's digital era, data is generated at an astonishing rate. These real-world high-dimensional datasets are dynamic, necessitating frequent updates to keep up with the constant influx of new information. With the surge in data volume and dimensionality, many approaches have been proposed to enhance the efficiency of kNN join operations on static and dynamic high-dimensional data. However, we observed that existing research fails to offer an efficient solution for dynamic high-dimensional datasets. To address the limitations of existing work, this thesis proposes a comprehensive set of novel methods and optimisations designed to enhance the efficiency and scalability of kNN join operations over high-dimensional data. Our contributions can be divided into four parts: First, we introduce an HDR+ Tree that features lazy updates, batch operations, and optimised deletions, significantly improving the performance of existing algorithms. Second, we propose the HDR-Forest, an innovative approach for handling non-globally correlated datasets efficiently. By clustering the dataset and constructing multiple HDR-Trees, the HDR-Forest captures local correlations among data. Enhanced by the precomputation of principal component analysis (PCA) states and pruning-based kNN recomputation during item deletions, our method sets a new benchmark in the field. Third, we pioneer an efficient parallel solution for dynamic kNN join, leveraging Simultaneous Multi-Threading (SMT) technologies and Single Instruction Multiple Data (SIMD) instructions for parallelisation, marking the first instance of exact kNN join computation over high-dimensional data in a parallelised manner. Lastly, we propose an efficient cluster-based batch update technique that groups similar updates into clusters in a reduced dimensional space for batch processing. Instead of handling updates individually, this method enables shared computation for updating similar items, leading to significantly improved efficiency with minimal overhead. Additionally, we introduce a cluster-based pruned search method for the reversed kNN (RkNN) search process during updates, utilising the HDR-Tree. This technique efficiently prunes data clusters that do not affect the updates, avoiding unnecessary computations. By processing updates in clusters rather than individually, our method significantly enhances the efficiency and overall performance of batch updates. This approach reduces the computation cost associated with non-leaf nodes while maintaining comparable costs for leaf nodes, making it highly effective for large-scale high-dimensional data. The collective outcome of our research advances the state-of-the-art in dynamic kNN join operations, offering methodologies that improve computational efficiency and scalability, and extend applicability to more diverse and dynamically updating datasets. The experimental results across different datasets confirm the effectiveness and efficiency of our proposed solutions, showcasing their potential to significantly benefit various real-world applications in need of high-performance data analysis capabilities

Weakly SSM : On the Viability of Weakly Supervised Segmentations for Statistical Shape Modeling

Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical applications, including morphology-based diagnostics and surgical planning. However, the effectiveness of SSM is often constrained by the necessity for expert-driven manual segmentation, a process that is both time-intensive and expensive, thereby restricting their broader application and utility. Recent deep learning approaches enable the direct estimation of Statistical Shape Models (SSMs) from unsegmented images. While these models can predict SSMs without segmentation during deployment, they do not address the challenge of acquiring the manual annotations needed for training, particularly in resource-limited settings. Semi-supervised and foundation models for anatomy segmentation can mitigate the annotation burden. Yet, despite the abundance of available approaches, there are no established guidelines to inform end-users on their effectiveness for the downstream task of constructing SSMs. In this study, we systematically evaluate the potential of weakly supervised methods as viable alternatives to manual segmentation's for building SSMs. We establish a new performance benchmark by employing various semi-supervised and foundational model methods for anatomy segmentation under low annotation settings, utilizing the predicted segmentation's for the task of SSM. We compare the modes of shape variation and use quantitative metrics to compare against a shape model derived from a manually annotated dataset. Our results indicate that some methods produce noisy segmentation, which is very unfavorable for SSM tasks, while others can capture the correct modes of variations in the population cohort with 60-80\% reduction in required manual annotation

Paper on Design Improvement and Analysis of Rotary Air Compressor Blades

Starter trial of a solitary vane pivoting sleeve rotational blower for refrigeration framework application is introduced in this paper. For the most part, single vane pivoting sleeve rotating blower is a kind of rotational blower family that has been created ongoing years. The qualities of the blower plan and pressure idea in suchthat of this blower should be superior to anything others rotational blower in term of spillage and grating. The task of the blower instrument is straightforwardly from the pole to the system pressure segments. This imply when the pole begin to turn, the instrument pressure segments will be pivot together a similar way and this system can pack the refrigerant at all speed of revolution.. This is on account of the plan of the vane tip is installed in the swing opening at the pivoting

Designing Security Model for Un-Reliable Cloud IAAS Storage

With the internet getting so popular data sharing and security of personal data has gain much more importance than before. Cloud provides and efficient way to outsource the data either online or offline but data security becomes one of the major issues in unreliable cloud environment. The proposed system addresses the security issues in cloud environment and also provides a way to provide better security and load balancing in cloud environment. The proposed system uses cryptographic symmetric algorithm AES with key size of 256 for data encryption and Ultra Zip compression which provides a compression ratio up to 50% depending on the file type. After encryption and compression the data is splitted into multiple parts and each part is stored in separate data server. The proposed work can be used in many different application like social networking sites and file hosting websites

Classical and contemporary aspect of Dushi Visha

In Today’s Era people follows western lifestyle and food habits. Peoples are constantly exposed to environmental chemicals through polluted water, soil, air and food. Toxins gets accumulated in body tissues that leads to serious health. New generation is likely to consume junk food, cold drinks, working late nights. As Dushi Visha is mild in potency it is not fatal and causes various diseases as the toxins remain in the body for longer period. Unfavorable environment (Desha), time (Kaala), food, over exertion, mental dilemma, anger etc. Reduces the immunity of a person, and these are the aggravating factors of Dushi Visha. To remove these toxins from body Panchakarma therapy should be done yearly as it is the detoxification procedure it detoxifies the body and neutralizes the toxins. Every year it should be done periodically so that it will maintain physiology of body and prevent from diseases

A Review on Issues in Cloud Computing Services

With the internet getting so popular data sharing and security of personal data has gain much more importance than before. Cloud provides and efficient way to outsource the data either online or offline but data security becomes one of the major issues in unreliable multi-cloud environment. This paper addresses the issues in multi-cloud environment and also provides a way to provide better security in multi-cloud environment. Further it discusses the different encryption algorithms that can be used to maintain a design framework for cloud environment

Critical review on pathogenesis of Vataj and Vatakaphaj Gridhrasi (Sciatica)

In Ayurveda, nomenclature of diseases has been done in different ways e.g. according to DoshaDushya involved, according to symptoms etc. Here, the word Gridhrasi is suggestive of the typical character of pain and also the gait of the patient. Gridhra means vulture. Vulture is fond of meat and has a particular fashion of eating meat. It pierces its beak deeply in the flesh and then draws it forcefully, causing severe pain. The pain in Gridhrasi is also of the same kind, hence the name of this illness. Secondly, Gridhra also means the man who is greedily striving after meat like that of vulture. Such a person is more prone to this disease ‘Gridhrasi’. Also, because of the persisting severe pain, the patient has a typical gait (slightly tilted towards the affected side, affected leg in flexed position and the other leg is extended). This gait resembles that of the vulture. The particular causative factors of Gridhrasi are not mentioned in the classics. The general causes of Vatavyadhi are considered as the causes of Gridhrasi since it is considered under eighty Nanatmaja Vata Vyadhies. These Vata disorders are caused by almost the same Vata Prakopaka Nidanas, but the different diseases are due to the Samprapti Vishesha of the vitiated Vayu. The Vataprakopaka Hetus found in different Samhita