Squared Extrapolation Methods (SQUAREM): A New Class of Simple and Efficient Numerical Schemes for Accelerating the Convergence of the EM Algorithm

We derive a new class of iterative schemes for accelerating the convergence of the EM algorithm, by exploiting the connection between fixed point iterations and extrapolation methods. First, we present a general formulation of one-step iterative schemes, which are obtained by cycling with the extrapolation methods. We, then square the one-step schemes to obtain the new class of methods, which we call SQUAREM. Squaring a one-step iterative scheme is simply applying it twice within each cycle of the extrapolation method. Here we focus on the first order or rank-one extrapolation methods for two reasons, (1) simplicity, and (2) computational efficiency. In particular, we study two first order extrapolation methods, the reduced rank extrapolation (RRE1) and minimal polynomial extrapolation (MPE1). The convergence of the new schemes, both one-step and squared, is non-monotonic with respect to the residual norm. The first order one-step and SQUAREM schemes are linearly convergent, like the EM algorithm but they have a faster rate of convergence. We demonstrate, through five different examples, the effectiveness of the first order SQUAREM schemes, SqRRE1 and SqMPE1, in accelerating the EM algorithm. The SQUAREM schemes are also shown to be vastly superior to their one-step counterparts, RRE1 and MPE1, in terms of computational efficiency. The proposed extrapolation schemes can fail due to the numerical problems of stagnation and near breakdown. We have developed a new hybrid iterative scheme that combines the RRE1 and MPE1 schemes in such a manner that it overcomes both stagnation and near breakdown. The squared first order hybrid scheme, SqHyb1, emerges as the iterative scheme of choice based on our numerical experiments. It combines the fast convergence of the SqMPE1, while avoiding near breakdowns, with the stability of SqRRE1, while avoiding stagnations. The SQUAREM methods can be incorporated very easily into an existing EM algorithm. They only require the basic EM step for their implementation and do not require any other auxiliary quantities such as the complete data log likelihood, and its gradient or hessian. They are an attractive option in problems with a very large number of parameters, and in problems where the statistical model is complex, the EM algorithm is slow and each EM step is computationally demanding

CRITICAL REVIEW OF HERBS ACTING ON PRANAVAHA SROTOVIKAR

The human body contains several channels through which the Doshas, Dhatus and Malas travel which are called as Srotamsi. There are thirteen Abhyantra srotamsi, each of which relates to specific organs, and are increased and vitiated by specific factors. Among thirteen Abhyantra srotas Pranavaha is one. Its main function is to provide the medium, through which Prana flows, which is governed by Vata. General causes of vitiation of Pranavaha Srotas include suppression of natural urges; seasonal, environmental, lifestyle and dietary patterns that are Ruksha, Sita in nature; exertion and exercise while hungry etc. they produce different symptoms like Kasa, Svasa, Hikka etc. Though Brihatrayeekaras have mentioned wide range of herbs for treatment of Pranavaha Sroto Vikaras, Charaka has mentioned around 30 drugs in 3 categories related to Pranavaha srotas i.e. Kasahara, Svasahara and Hikkahara Dasaimanis while Susrutha and Vagbhata has mentioned Svasa and Kasahara dravyas in Ganas like Surasadi and Vidarigandhadi ganas. Apart from these a lot of drugs are mentioned in their respective treatments. Among these the drugs like Sati, Puskaramoola, Abhaya, Trikatu, Brihati, Kantakari, Tamalaki, Tulasi are very frequently mentioned for the treatment of different Pranavaha Sroto vikaras. In the present paper research activities carried out around the world on different herbs used in the Pranavaha sroto vikaras are reviewed which will provide a scientific rationale of using them in Ayurveda

MULTI-GIGABIT PATTERN FOR DATA IN NETWORK SECURITY

In the current scenario network security is emerging the world. Matching large sets of patterns against an incoming stream of data is a fundamental task in several fields such as network security or computational biology. High-speed network intrusion detection systems (IDS) rely on efficient pattern matching techniques to analyze the packet payload and make decisions on the significance of the packet body. However, matching the streaming payload bytes against thousands of patterns at multi-gigabit rates is computationally intensive. Various techniques have been proposed in past but the performance of the system is reducing because of multi-gigabit rates.Pattern matching is a significant issue in intrusion detection systems, but by no means the only one. Handling multi-content rules, reordering, and reassembling incoming packets are also significant for system performance. We present two pattern matching techniques to compare incoming packets against intrusion detection search patterns. The first approach, decoded partial CAM (DpCAM), pre-decodes incoming characters, aligns the decoded data, and performs logical AND on them to produce the match signal for each pattern. The second approach, perfect hashing memory (PHmem), uses perfect hashing to determine a unique memory location that contains the search pattern and a comparison between incoming data and memory output to determine the match. The suggested methods have implemented in vhdl coding and we use Xilinx for synthesis

A Novel 2DOF Fractional Controller for Wind-Solar Integrated Power System

Power system is an integration of many power generating units with continuous load variation due to which the frequency of the power system changes. Using traditional proportional integral (PI) controllers, frequency transients are reduced, and with sufficient time delay zero steadystate error is obtained. In this proposed research article, a three-area thermal plant system with wind and solar photovoltaic power generating systems is considered. This integration of renewable system will lead to the frequency transients which has to be addressed seriously. To improve the frequency profile of this diverse-source interconnected power system, a novel two degree of freedom proportional fractional integral double derivative (2-DOF-PFIDD) controller is proposed. The integral square error (ISE) cost function is utilized to discover the best parameter gains of the proposed controller using the intelligent water drops algorithm (IWDs). The benefits of the proposed controller are evaluated using an IEEE-39 bus system with wind and solar photovoltaic (SPV) generation. Uncertainties in the wind and solar power system characteristics such as wind speed and irradiance are considered. Comparisons with typical proportional integral derivative (PID), two degree of freedom proportional integral derivative (2-DOF PID), and 2-DOF-PIDD controllers are presented to demonstrate the efficacy of proposed controller for improving the frequency and tie-line power profiles

CSWin Transformer-CNN Encoder and Multi-Head Self-Attention Based CNN Decoder for Robust Medical Segmentation

Convolutional Neural Networks have demonstrated exceptional effectiveness in the field of medical image segmentation by effectively capturing intricate local details such as edges and textures. But still, their limited domain of view often impedes comprehensive representation of global information. Transformers, on the other hand, have shown promise in modeling long-range dependencies, yet, Convolutional Neural Networks occasionally face challenges in effectively capturing high-level spatial features. An ideal segmentation model ought to effectively harness both local and global features to achieve precision and semantic accuracy. This article introduces a novel Cross Shaped Window Transformer framework, employing U-shaped network architecture. This network combines a Convolutional Neural Network encoder with a Multi-Head Self-Attention based CNN decoder. Within the CNN encoder, a transformer path is integrated with a shifted window mechanism, enhancing the representation of both local and global information, thus ensuring robust medical image segmentation. The encoder\u27s skip connections are reinstated using a Multi-Head Self-Attention decoder. To decode a wide range of features and manage distortions in local details, a dilated-Uper decoder is introduced. The Synapse dataset is utilized to assess the effectiveness of the proposed method, revealing that it surpasses existing approaches with an impressive accuracy of approximately 93%

Smart cities development in India

102-107The Smart Cities Mission launched in 2015 is to provide Indian cities with core infrastructure and enable a decent quality of life to its citizens. Building clean, green and sustainable environment along with the application of Smart Solutions to the cities is a major objective of this ongoing mission. One of the underlying principles of developing Smart cities is to make these cities inclusive for all- especially abled, elderly, the poor and the disadvantaged. This paper discusses the major components of Smart cities and the various technology led practises that are envisioned to be adopted. Application of ‘Smart solutions’ will enable cities to use technology, information and data to improve infrastructure and services. Comprehensive development in this way will improve quality of life, create employment and enhance incomes for all, especially the poor and the disadvantaged, leading to inclusive cities

A CRITICAL REVIEW ON THE CONCEPT OF DRUG AS A WHOLE

Drug is an independent variable and one among Pada Chatustaya. Successful treatment depends on the choice of appropriate dose and dosage form. Nowadays the advancement in science has led to the extensive use of extracts and isolated compounds. Principles of extraction are seen in the classical dosage forms where a suitable homogenous medium was used based on the type of the drug. Drugs having water-soluble fraction are used as Kwatha, those having fat-soluble fractions are used as Ghrita/ Taila and so on. Present day extracts are obtained by extracting herbal drug of certain particle size with suitable extraction medium. Ayurveda propounds the principles of Rasa Panchaka and attributes the actions of a drug to any one of the Rasa-Vipaka-Guna-Veerya-Prabhava where each component plays a specific role or a combined role. Hence a chemically isolated derivative may not serve the purpose and will produce adverse effects. Even-though drugs have got some active principles with which they work, they have some other fractions too, which counteract their bad effects, if any. Therefore Ayurveda advocates that drug should be used as a whole so that the desired effects may have without any side effects. Therefore, research works should be directed towards providing the use of whole drugs and find ways to potentiate the drugs as per principles of Ayurveda. This article highlights the importance of administration of drug as a whole rather than extracts or isolated phytochemicals.

Smart cities development in India

The Smart Cities Mission launched in 2015 is to provide Indian cities with core infrastructure and enable a decent quality of life to its citizens. Building clean, green and sustainable environment along with the application of Smart Solutions to the cities is a major objective of this ongoing mission. One of the underlying principles of developing Smart cities is to make these cities inclusive for all- especially abled, elderly, the poor and the disadvantaged. This paper discusses the major components of Smart cities and the various technology led practises that are envisioned to be adopted. Application of ‘Smart solutions’ will enable cities to use technology, information and data to improve infrastructure and services. Comprehensive development in this way will improve quality of life, create employment and enhance incomes for all, especially the poor and the disadvantaged, leading to inclusive cities

INFLUENCE OF STABILIZATION EXERCISES ON ARTICULAR CARTILAGE CHANGES IN DEGENERATIVE TIBIO- FEMORAL JOINT DISEASE- A PILOT STUDY

Objectives: To determine the effectiveness of knee joint stabilization exercises in minimizing articular cartilage degeneration and to examine theeffectiveness of knee joint stabilization exercises on decreasing pain, improving range of motion (ROM) and muscle strength.Methods: About 20 volunteer subjects (age 35-65 years) with primary osteoarthritis fulfilled the inclusion criteria given the knee stabilizationexercises for 8 weeks. Pain, muscle strength, functional outcome score, and serum cartilage oligomeric matrix protein (COMP) values were measuredpre- and post-intervention using visual analog scale, dynamometer, and ELISA test. Data were analyzed using a paired t-test with Statistical Packagefor the Social Sciences version 20 to find out the difference between the pre- and post-test.Results: The results of the study have shown that significant difference between pre- and post-test values of pain, ROM, muscle strength and functionaloutcome score with p<0.05, and there is statistical in significance in serum COMP value (p<0.05).Conclusion: Stabilization exercises of knee joint were shown to be beneficial for decreasing pain, improving ROM and muscle strength, and there wasno effect on articular cartilage changes in degenerative tibiofemoral joint disease.Keywords: Serum cartilage oligomeric matrix protein, Knee stabilization exercises, Proprioception exercises, Muscle strength. Â