Exploiting semantic locality to improve peer-to-peer search mechanisms

A Peer-to-Peer(P2P) network is the most popular technology in file sharing today. With the advent of various commercial and non-commercial applications like KaZaA, Gnutella, a P2P network has exercised its growth and popularity to the maximum. Every node (peer) in a P2P network acts as both a client and a server for other peers. A search in P2P network is performed as a query relayed between peers until the peer that contains the searched data is found. Huge data size, complex management requirements, dynamic network conditions and distributed systems are some of the difficult challenges a P2P system faces while performing a search. Moreover, a blind and uninformed search leads to performance degradation and wastage of resources. To address these weaknesses, techniques like Distributed Hash Table (DHT) has been proposed to place a tight constraint on the node placement. However, it does not considers semantic significance of the data. We propose a new peer to peer search protocol that identities locality in a P2P network to mitigate the complexity in data searching. Locality is a logical semantic categorization of a group of peers sharing common data. With the help of locality information, our search model offers more informed and intelligent search for different queries. To evaluate the effectiveness of our model we propose a new P2P search protocol - LocalChord. LocalChord relies on Chord and demonstrates potential of our proposed locality scheme by re-modelling Chord as a Chord of sub-chords

Skilful Precipitation Nowcasting Using NowcastNet

Designing early warning system for precipitation requires accurate short-term forecasting system. Climate change has led to an increase in frequency of extreme weather events, and hence such systems can prevent disasters and loss of life. Managing such events remain a challenge for both public and private institutions. Precipitation nowcasting can help relevant institutions to better prepare for such events as they impact agriculture, transport, public health and safety, etc. Physics-based numerical weather prediction (NWP) is unable to perform well for nowcasting because of large computational turn-around time. Deep-learning based models on the other hand are able to give predictions within seconds. We use recently proposed NowcastNet, a physics-conditioned deep generative network, to forecast precipitation for different regions of Europe using satellite images. Both spatial and temporal transfer learning is done by forecasting for the unseen regions and year. Model makes realistic predictions and is able to outperform baseline for such a prediction task.Comment: NeurIPS 202

Precipitation Nowcasting With Spatial And Temporal Transfer Learning Using Swin-UNETR

Climate change has led to an increase in frequency of extreme weather events. Early warning systems can prevent disasters and loss of life. Managing such events remain a challenge for both public and private institutions. Precipitation nowcasting can help relevant institutions to better prepare for such events. Numerical weather prediction (NWP) has traditionally been used to make physics based forecasting, and recently deep learning based approaches have been used to reduce turn-around time for nowcasting. In this work, recently proposed Swin-UNETR (Swin UNEt TRansformer) is used for precipitation nowcasting for ten different regions of Europe. Swin-UNETR utilizes a U-shaped network within which a swin transformer-based encoder extracts multi-scale features from multiple input channels of satellite image, while CNN-based decoder makes the prediction. Trained model is capable of nowcasting not only for the regions for which data is available, but can also be used for new regions for which data is not available.Comment: arXiv admin note: substantial text overlap with arXiv:2311.17961; NeurIPS 202

Cost Based Optimization of Job Allocation in Computational Grids

Computational grids are distributed systems composed of heterogeneous computing resources which are distributed geographically and administratively. These highly scalable systems are designed to meet the large computational demands of many users from scientific and business orientations. Grid computing is a powerful concept, its chief appeal being the ability to make sure all of a resource’s computing power is used. In a grid world, the idle time of hundreds or thousands of resources could be harnessed and rented out to anyone who needed a massive infusion of processing power. First, the architecture of a grid system is presented. The design gives a mathematical model of the grid system for efficiently allocating the grids resources. The challenges faced for optimal job allocation motivate the exploration in optimizing grid resource allocations. We have extensively surveyed the current state of art in this area. A grid server coordinates the job allocation for the grid users and helps to select the best resources for a job among different possible resource offers with the best prices offered. Interaction between grid users and the resources require a mediator that uses different paradigm to communicate the needs of the two parties in terms of performance requirements, timing constraints, price charged etc. A game theoretic bargaining approach is studied to agree upon standard prices. We have implemented various job allocation schemes in computational grids based on the mathematical modeling of the grid system and bargaining protocol with the objective function of optimizing the cost. The performance of the schemes have been analyzed and compared. A new model for job allocation in computational grids has been proposed, for job allocation based on the clustering of resources

In vitro production of capsaicin through plant tissue culture

Capsaicin, a secondary metabolite produced in capsicum, is in high demand in pharmaceutical industry because of its various medicinal properties. Currently, the supply of capsaicin depends upon its extraction from capsicum fruits. This limits the production of capsaicin as it depends upon agricultural produce. The current review has compiled information from various literature published on chemistry and importance of capsaicin along with its method of production. It also reviews the process of in vitro production of capsaicin through plant tissue culture, strategies of increasing capsaicin accumulation and its advantages over extraction from fruits and artificial synthesis

Time-lapse seismic modeling and production data assimilation for enhanced oil recovery and CO2 sequestration

Production from a hydrocarbon reservoir is typically supported by water or carbon dioxide (CO2) injection. CO2 injection into hydrocarbon reservoirs is also a promising solution for reducing environmental hazards from the release of green house gases into the earth’s atmosphere. Numerical simulators are used for designing and predicting the complex behavior of systems under such scenarios. Two key steps in such studies are forward modeling for performance prediction based on simulation studies using reservoir models and inverse modeling for updating reservoir models using the data collected from field. The viability of time-lapse seismic monitoring using an integrated modeling of fluid flow, including chemical reactions, and seismic response is examined. A comprehensive simulation of the gas injection process accounting for the phase behavior of CO2-reservoir fluids, the associated precipitation/dissolution reactions, and the accompanying changes in porosity and permeability is performed. The simulation results are then used to model the changes in seismic response with time. The general observation is that gas injection decreases bulk density and wave velocity of the host rock system. Another key topic covered in this work is the data assimilation study for hydrocarbon reservoirs using Ensemble Kalman Filter (EnKF). Some critical issues related to EnKF based history matching are explored, primarily for a large field with substantial production history. A novel and efficient approach based on spectral clustering to select ‘optimal’ initial ensemble members is proposed. Also, well-specific black-oil or compositional streamline trajectories are used for covariance localization. Approach is applied to the Weyburn field, a large carbonate reservoir in Canada. The approach for optimal member selection is found to be effective in reducing the ensemble size which was critical for this large-scale field application. Streamline-based covariance localization is shown to play a very important role by removing spurious covariances between any well and far-off cell permeabilities. Finally, time-lapse seismic study is done for the Weyburn field. Sensitivity of various bulk seismic parameters viz velocity and impedance is calculated with respect to different simulation parameters. Results show large correlation between porosity and seismic parameters. Bulk seismic parameters are sensitive to net overburden pressure at its low values. Time-lapse changes in pore-pressure lead to changes in bulk parameters like velocity and impedance

Occurrence of Toxigenic Microcystis spp in Major Water Bodies of North East India

Toxigenic cyanobacterial blooms in the water bodies represent a major ecological problem around the world. Some species produces a diverse range of toxins that have hepatotoxic, neurotoxic, cytotoxic and dermatoxic activity and hence have deleterious effect on humans, animals and fishes leading to death as well. Cultural eutrophication of water bodies leads to increased incidence of these harmful cyanobacterial blooms worldwide. North-East India being a biodiversity hotspot harbor many species of cyanobacteria. Few reports suggested presence of few toxigenic cyanobacteria in the water bodies of Assam, but no systematic studies have been undertaken to evaluate their toxicity. This work is being conducted to gather information on major toxigenic cyanobacteria, with special emphasis to microcystin (a cyclic heptapeptides with high acute and chronic toxicities to humans and animals) producing strains. Water samples have been collected from few water bodies of North-East and enriched in specific media. The toxin Microcystin was detected using specific ELISA kit and positive results have been obtained. Further, 16s rDNA sequencing was employed for molecular identification of the strains

Performance Evaluation of Cabbage Cultivars under Open Field Cultivation in High Altitude of Tawang Arunachal Pradesh

The study has been undertaken to evaluate the performance of locally available commercial cultivars of cabbage in open field during summer season of 2019 at Defence Research Laboratory Research and Development Centre Tawang (Arunachal Pradesh). The commercial cultivars of these vegetables were evaluated based on the growth parameters and their yield performance under open field with paired row system of planting. It was found that the cultivar Green Express performance was outstanding among test edcultivars and it superseded cv. Royal Ball BC-51 and cv. Blue Jayes in terms of growth parameters as well as marketable yield (2.62 kg/m2) and biological yield (3.47 kg/m2). The cv. Royal Ball BC-86 was also found next best performing cultivar after cv. Green Express as former was at par with growth and yield parameter and harvest maturity of later. The head of cv. Green express attended harvest maturity (149.25 days) approximately one week earlier as compared to cv. Blue Jayes (155.0 days). However, the productivity of cultivars Green Express and Royal Ball BC-86 was found within the range of national average, therefore, these two cultivars could be recommended for the commercial cultivation with paired row system of planting under open field cultivation during summer season in high altitude areas of Tawang (Arunachal Pradesh)

Japanese Corporate Strategies To Achieve International Competitiveness: A Case Of The Telecom Industry

Japan, a competitiveness leader, for most of the 1970s and 1980s is at the crossroads. Most of the 1990s, it remained in recession, and there are serious doubts about the competitiveness of Japan and its leading industries. Telecom is a vital infrastructure industry for emerging e-lance economy. An attempt was made to evaluate the competitive performance of the Japanese telecom industry in an Asian context. The strategies of Japanese firms to enhance their and their industry's competitiveness are also briefly examined. The findings of an attempt to evaluate relative competitiveness at the industry level in the context of the telecom industry in India, Japan and Korea are presented here. Competitive analysis of the industry in three countries is done using the Porter's Diamond model. Detailed evaluation is performed using an adaptation of Asset-Process-Performance model. Then, an attempt is made to understand the role of corporate strategy in the remarkable success of the Japanese industry. The strategies of Korean firms and Indian firms are also compared briefly . Finally, conclusions are drawn based on findings of the researc