Voice Search Technology: An Overview

Donepudi, Praveen Kumar

doi:10.18034/ei.v2i2.502

Cited by 26 publications

(24 citation statements)

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“…Though there have been substantial efforts to develop validated biomarkers for the expedition of clinical trials, the reduction of development costs, the development of precision drug, personalized therapeutics and the classification of individuals with disease conditions, the use of psychometric and imaging approaches have not been widely successful. Biomarkers' contribution in terms of clinical diagnosis have also been unimpressive because, in part, there is a shortage of free-moving workflow linking clinical last-mile biomarker founding efforts with grounded validation techniques (Donepudi, 2014b).…”

Section: The Validation Of Biomarkersmentioning

confidence: 99%

Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach

Rahman

2021

Malays. j. med. biol. res.

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Biomarkers that are validated and robust are required for the enhancement of diagnosis, the observation of drug-related activity, therapeutic reactions, and as the blueprint for developing safer and more direct therapeutic efforts for a variety of chronic ailments. Various kinds of biomarkers have proven impactful when it comes to the discovery and development of drugs, but the procedure that involves identifying and verifying ailment-specific biomarkers has proven to be hassling. In recent times, there have been some advancements in multiple omics (also known as multi-omics) methods like transcriptomic, cytometry, genomics, proteomics, metabolomics and imaging. These advancements have made it possible for the discovery and development of distinct biomarkers for complicated chronic ailments to be accelerated expeditiously. In spite of the fact that numerous drawbacks still need to be looked into, ongoing efforts for the discovery and improvement of illness-associated biomarkers will go a long way in optimizing decision-making across the entire process of drug development and expand our comprehension of the infection processes. In addition, when the preclinical biomarkers are effectively translated into the clinic, the way will pave well to an equally effective implementation of personalized therapies throughout complicated illness environments to become beneficial to patients, healthcare service providers and the industry of bio-pharma.

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Section: The Validation Of Biomarkersmentioning

confidence: 99%

Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach

Rahman

2021

Malays. j. med. biol. res.

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“…Hence, to meet farm challenges and increase food demand, computer, satellite, internet, mobile, and social media technology are used. It is expected that the combination of IT and agricultural techniques will result in increased output, perhaps up to 60% (Donepudi, 2014b). However, with the introduction of technology, companies have undergone dramatic changes across many industries globally (Kakkad, Patel, Shah, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

How Artificial Intelligence Improves Agricultural Productivity and Sustainability: A Global Thematic Analysis

Vadlamudi¹

2019

Asia Pac. j. energy environ.

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In the face of the agricultural sector's challenges, food security with an increasing human population and high demand for food is a significant problem. Traditional methods used by farmers have not been sufficient to meet the food requirements of the growing population. As a result, the agricultural sector has begun to deploy artificial intelligence to meet the demand for food and sustainability. This study was conducted to examine how AI improves farmers' productivity and sustainability. Data were analyzed using centering resonance analysis, t-test, ANOVA, and text mining news articles from 2014-2019 in Africa, Asia, Europe, and North America. Results show that AI is used primarily to increase productivity and efficiency and secondarily to address labor shortages and environmental sustainability concerns. The results at the regional level reflect the active adoption of AI in North America and Europe, with increasing efforts in Asia and Africa.

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“…Alleged intellectual driver models treat the driver's behavior because of some mind-boggling data handling techniques, which can be separated into a few phases of perceiving, assessing, objective setting, and choosing (Möbus et al, 2009;Salvucci et al, 2001;Donepudi, 2014b). A formalization of such models by hybrid automata began, yet ended up being very unpredictable.…”

Section: Hybrid Automation Simulation Of Human Driversmentioning

confidence: 99%

Hybrid Automata: An Algorithmic Approach Behavioral Hybrid Systems

Ballamudi¹

2019

Asia Pac. j. energy environ.

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Hybrid automata strategies have advanced as a vital tool to design, check and direct the execution of hybrid systems. Any way they can – and we assume should – be utilized to communicate quantitative models about hybrid systems in different areas, for example, experimental sciences. Since the conventional design of hybrid automata compares well to consecutively integrate behavioral chains in living creatures, we look for a use of hybrid modeling procedures in the social sciences and, particularly, brain research. We attempt to address the question related to how human drivers move onto an expressway and simultaneously utilize this study as our test-bed for utilizing hybrid automata inside behavioral sciences. Hybrid automata give a language to displaying and exploring advanced and simple calculations in real-time systems. Hybrid automata are studied here from a dynamical systems point of view. Essential and adequate conditions for the presence and uniqueness of arrangements are inferred and a class of hybrid automata whose arrangements rely consistently upon the underlying state is described. The outcomes on presence, uniqueness, and progression fill in as a beginning stage for solid study. In this paper, we present the structure of hybrid automata as a model and detailed language for hybrid systems. Hybrid automata can be seen as a theory of timed automata, in which the behavior of factors is represented in each state by a bunch of differential conditions. We show that a large number of the models considered in the workshop can be characterized by hybrid automata. While the reachability issue is undecidable in any event, for extremely confined classes of hybrid automata, we present two semi-decision techniques for checking security properties of piecewise-straight hybrid automata, in which all factors change at steady rates. The two techniques are based, individually, on limiting and figuring fix points on for the most part endless state spaces. We show that if the end of the method, at that point they offer the right responses. We then show that for a significant number of the run of the mill workshop models, the strategies do end and hence give an algorithmic approach to confirming their properties.

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Voice Search Technology: An Overview

Cited by 26 publications

References 0 publications

Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach

Biomarkers and Bioactivity in Drug Discovery using a Joint Modelling Approach

How Artificial Intelligence Improves Agricultural Productivity and Sustainability: A Global Thematic Analysis

Hybrid Automata: An Algorithmic Approach Behavioral Hybrid Systems

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