Mobile Phone Companies Increasing Market Share through Innovations, R&D Spending and Patents

This study aims to analyze the market share of four leading mobile phone companies in the context of their spending on R&D and the number of filed patents. The study aims to identify whether the companies that invest the most in R&D and file more patents have a competitive edge and increased market share compared to others. The adoption and advancement of technologies throughout the documented history of humankind have revealed how employing specific devices has cultivated the power for people and society to communicate. Moreover, innovations in travelling have increased prospects for real-time communication, and innovations in virtual real-time communication like mobile phones and the internet have become a part of everyday life. Following innovations, many companies emerged from nowhere with unique mobile phone devices and continued the business. But, few of them were wiped out from the market because their mobile phone offering was inferior to other competitors. This paper explores the innovation journey of mobile phone companies. In addition, it focuses on four leading brand names and corresponding success failures as well as the role of R&D expense and patents regarding innovations. Usually, innovation is considered as the engine of economic growth that serves customers better products and services and stays relevant in the market. Measuring innovation is not easy, but focusing on R&D and the quantifiable patent indicates that individual companies consistently serve customers with newer and better products

Mobile Cloud Encrypted Searching and Traffic Reduction

Now days, cloud infrastructure have been popular for storing data in the world. User can store his public and private data on cloud. To secure the private data it must be encrypted. This encrypted data should be retrieved and stored efficiently. This era is digital era. Nearly about each person has mobile phone. So smart phone would be the best client for the cloud. But using smart phone use wireless network which face many difficulties like low bandwidth, low latency, low battery, low transmission etc. The traditional search is not developed on focusing on smart phone so using smart phone it require the extra network traffic and long time for search. The application use the light weight trapdoor which reduce trapdoor size and provide feasible method for the network traffic efficiency. Also it use and Ranked Serial Binary Search algorithm 0and Trapdoor Mapping Table (TMT) to minimize the search time. The proposed system reduce the search time and network traffic

Machine Learning Based Fluid-Transportation Monitoring and Controlling

The discipline of fluid mechanics is developing quickly, propelled by previously unheard-of data volumes from experiments, field measurements, and expansive simulations at various spatiotemporal scales. The field of machine learning (ML) provides a plethora of methods for gleaning insights from data that can be used to inform our understanding of the fluid dynamics at play. As an added bonus, ML algorithms can be used to automate duties associated with flow control and optimization, while also enhancing domain expertise. This article provides a review of the background, current state, and potential future applications of ML in fluid mechanics. We provide an introduction to the most fundamental ML approaches and describe their applications to the study, modelling, optimization, and management of fluid flows. From the standpoint of scientific inquiry, which treats data as an integral aspect of modelling, experiments, and simulations, the benefits and drawbacks of these approaches are discussed. Since ML provides a robust information-processing framework, it can supplement and potentially revolutionize conventional approaches to fluid mechanics study and industrial applications. &nbsp

A Review: Efficient Encrypted Searching and Traffic Reduction As Mobile Cloud Services

Documentation of information on the Cloud Computing run as fast as Cloud entirely in the world. Even so it carriage distress to partron. Unless the data are encrypted For hostage. Encrypted data should be energetically searchable and retrievable Without any concealment particularly for the cellphone user. Although modern Interdisciplinary studies has solved many distress , the architectonically can not be applied on cellphone directly under the cellphone cloud environment. This is due to the contradict charged by wireless networks, such as latency sensitivity ,Poor connectivity, and low transmission rates. due to this extend to a chronic search Time and extra network traffic value. When using the conventional search schemes. This paper solve these matter by providing an efficient encrypted data search Method as cellphone cloud service. This method include lightweight trapdoor (encrypted Keyword) differentiate method, which is optimization of data sending process by decreasing the trapdoors size for traffic efficiency. In this publication we also include two Optimization method for data search, known as the trapdoor mapping table module and Ranked serial binary search algorithm to quick the search time. So by using Efficient data search over mobile cloud it Decreases search time by 34% to 47% and also network traffic by 17% to 41%

Artificial intelligence and higher education: a systematic visualizations based review

Artificial intelligence (AI) is evolving quickly, and its applications are attracting attention on a global scale. They have the potential to revolutionize many dimensions of human life, including education. AI has reformed various teaching methodologies, assessment methods and by enhancing their competitiveness and adaptability. In the current era, after the pandemic most preferably the AI and Education have interwoven and is continued to grab the attention of Academicians, Tutors, Instructors, the government, and students so that the research keeps AI and education intermingled for the benefit of society at large. The goal of our work is to present a visualization in form of the research trends and bibliometric analysis of research on the implementation of AI in HE during the 20 years. The study involves various parameters to include and exclude the research articles, we assessed 314 publications written by scientists in 67 different countries over the course of the last 20 years and included in the Scopus database. The study used word analysis and a variety of bibliometric markers to look at emerging patterns. In order to visualize the prominent research trends by locating keywords utilized inside AI in HE, VOSviewer was used..

Hospital admission with non-alcoholic fatty liver disease is associated with increased all-cause mortality independent of cardiovascular risk factors

Non-alcoholic fatty liver disease (NAFLD) is common and strongly associated with the metabolic syndrome. Though NAFLD may progress to end-stage liver disease, the top cause of mortality in NAFLD is cardiovascular disease (CVD). Most of the data on liver-related mortality in NAFLD derives from specialist liver centres. It is not clear if the higher reported mortality rates in individuals with non-cirrhotic NAFLD are entirely accounted for by complications of atherosclerosis and diabetes. Therefore, we aimed to describe the CVD burden and mortality in NAFLD when adjusting for metabolic risk factors using a ‘real world’ cohort. We performed a retrospective study of patients followed-up after an admission to non-specialist hospitals with a NAFLD-spectrum diagnosis. Non-cirrhotic NAFLD and NAFLD-cirrhosis patients were defined by ICD-10 codes. Cases were age-/sex-matched with non-NAFLD hospitalised patients. All-cause mortality over 14-years follow-up after discharge was compared between groups using Cox proportional hazard models adjusted for demographics, CVD, and metabolic syndrome components. We identified 1,802 patients with NAFLD-diagnoses: 1,091 with non-cirrhotic NAFLD and 711 with NAFLD-cirrhosis, matched to 24,737 controls. There was an increasing burden of CVD with progression of NAFLD: for congestive heart failure 3.5% control, 4.2% non-cirrhotic NAFLD, 6.6% NAFLD-cirrhosis; and for atrial fibrillation 4.7% control, 5.9% non-cirrhotic NAFLD, 12.1% NAFLD-cirrhosis. Over 14-years follow-up, crude mortality rates were 14.7% control, 13.7% non-cirrhotic NAFLD, and 40.5% NAFLD-cirrhosis. However, after adjusting for demographics, non-cirrhotic NAFLD (HR 1.3 (95% CI 1.1–1.5)) as well as NAFLD-cirrhosis (HR 3.7 (95% CI 3.0–4.5)) patients had higher mortality compared to controls. These differences remained after adjusting for CVD and metabolic syndrome components: non-cirrhotic NAFLD (HR 1.2 (95% CI 1.0–1.4)) and NAFLD-cirrhosis (HR 3.4 (95% CI 2.8–4.2)). In conclusion, from a large non-specialist registry of hospitalised patients, those with non-cirrhotic NAFLD had increased overall mortality compared to controls even after adjusting for CVD

Science with the Daksha High Energy Transients Mission

We present the science case for the proposed Daksha high energy transients mission. Daksha will comprise of two satellites covering the entire sky from 1~keV to $>1$~MeV. The primary objectives of the mission are to discover and characterize electromagnetic counterparts to gravitational wave source; and to study Gamma Ray Bursts (GRBs). Daksha is a versatile all-sky monitor that can address a wide variety of science cases. With its broadband spectral response, high sensitivity, and continuous all-sky coverage, it will discover fainter and rarer sources than any other existing or proposed mission. Daksha can make key strides in GRB research with polarization studies, prompt soft spectroscopy, and fine time-resolved spectral studies. Daksha will provide continuous monitoring of X-ray pulsars. It will detect magnetar outbursts and high energy counterparts to Fast Radio Bursts. Using Earth occultation to measure source fluxes, the two satellites together will obtain daily flux measurements of bright hard X-ray sources including active galactic nuclei, X-ray binaries, and slow transients like Novae. Correlation studies between the two satellites can be used to probe primordial black holes through lensing. Daksha will have a set of detectors continuously pointing towards the Sun, providing excellent hard X-ray monitoring data. Closer to home, the high sensitivity and time resolution of Daksha can be leveraged for the characterization of Terrestrial Gamma-ray Flashes.Comment: 19 pages, 7 figures. Submitted to ApJ. More details about the mission at https://www.dakshasat.in

Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level.Comment: 24 pages, 5 figure

Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.Comment: 27 pages, 3 figure