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KINGSTON, R.I. Oct. 22, 2020 The University of Rhode Island has named Gaurav Khanna, Ph.D., its founding director of Research Computing. Khanna comes to URI from the University of Massachusetts Dartmouth where he served as a professor of physics and co-director of the universitys Center for Scientific Computing & Visualization Research.

A respected leader in research computing for more than a decade, Khanna has directed several scientific computing efforts at UMass Dartmouth, including supporting the research efforts of faculty members across the campus. He also served as the founding director for the interdisciplinary Engineering & Applied Sciences Ph.D. program, the largest Ph.D. program at UMass Dartmouth.

Im looking forward to building a research computing center at the University of Rhode Island that will help support and grow the research efforts of both junior and established researchers across its campuses, says Khanna. I intend to develop a wide array of computational resources (local, regional, cloud) with full support, to advance the diverse research work underway at Rhode Islands only public research university.

Khanna also served on multiple committees in the UMass system that play a role in the governance of the Massachusetts Green High-Performance Computing Center and noted the opportunity to make similar advances at URI, I look forward to the center innovating in the space of green and energy-efficient computing, and in the emerging area of quantum computing.

As an accomplished researcher in the area of black hole and gravitational physics, Khanna has been funded by the National Science Foundation for nearly two decades and has published nearly 100 papers in top peer-reviewed research journals. His research has been covered widely in outlets including Wired, Forbes, BBC, HPCWire, Discovery, Space.com and the New York Times.

Khanna earned a Bachelor of Technology degree from the Indian Institute of Technology Kanpur, India in 1995. He earned his Ph.D. from Penn State in 2000.

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University of Rhode Island names respected professor, researcher, computational scientist to lead research computing efforts - URI Today

Quantum Computing in Aerospace and Defense

COVID-19 Industry impact

The market research extensively explores the effect of the COVID-19 outbreak on the market for Quantum Computing in Aerospace and Defense Market. Limits resulting in low sales and sector operators dominating the hospitality industry are at risk due to the lockdowns imposed to contain the spread of the virus, as cafes and restaurants have closed temporarily. Demand from food service providers is expected to recover, as the COVID-19 pandemic restrictions are easy. However, some participants may be forced to leave the sector.

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The market research also analyses methods such as PORTER analysis, PEST analysis, and SWOT analysis to provide companies with quality evaluation. It helps arrange and inspire companies investment strategies for a particular business segment in the near future. The review of market attributes, market overview, industry chain, historical and future data by categories, applications, and regions, and competition landscape are included in this market research. Industry research involves analyzing the global environment in order to estimate the markets vulnerabilities, assets, opportunities, and risks.

Insights on the Market

The purpose of the market study is to include evidence, estimates, statistics, historical data, and market data verified by the industry, as well as the appropriate methodology and evaluation for a full market evaluation. The market research also helps understand the structure by evaluating the dynamics of the market segments. Market segmentation is split on the basis of content, form, end-user, and region.

Segmentation of the Market

This detailed market analysis of Quantum Computing in Aerospace and Defense Market also provides a thorough summary and description of every segment offered in the analysis. Based on their market size, growth rate, and general attractiveness in terms of investment information and incremental value growth, the main segments are benchmarked. Market segmentation is divided into sub-groups, based on certain significant common attributes, into a wide customer or business market.

Segmented By Component (Hardware, Software, Services), By Application (QKD, Quantum Cryptanalysis, Quantum Sensing, Naval)

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Regional Estimation:

In terms of different geographies, the Quantum Computing in Aerospace and Defense Market report provides a comprehensive perspective on industry growth over the projected period, including Asia Pacific ( APAC), Europe (EU), North America (NA), Latin America (LATAM), and Middle East & Africa (MEA) revenue estimates.

Business Competitive Background:

The competitive market for Quantum Computing in Aerospace and Defense is measured by the number of domestic and foreign players participating in the market. The main focus is on the companys growth, merger, acquisition, and alliance, along with new product creation as measured strategies implemented by influential corporations to improve their customer market presence. D-Wave Systems Inc, Qxbranch LLC, IBM Corporation, Cambridge Quantum Computing Ltd, 1qb Information Technologies Inc., QC Ware Corp., Magiq Technologies Inc., Station Q-Microsoft Corporation, and Rigetti Computing are the prominent market participants examined and profiled in this study.

Highlights of the Market

The market study presents information on key manufacturers of Quantum Computing in Aerospace and Defense Market and revenues, profits, recent growth, and market share of key players. In order to evaluate the global and key regionsQuantum Computing in Aerospace and Defense Market advantages, potentials, opportunity, constraints, threat, and risks, the report has divided the breakdown data by category, regions, businesses, and applications.

By covering all markets, offering quality analysis, and insights to help our customers make the right choices, the market study offers solutions. The latest trends, niche areas, and leading company profiles are included in the study. To provide reliable and useful information, the market research database consists of numerous reports updated on a regular basis.

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Quantum Computing in Aerospace and Defense Market Trends and Forecast to 2028 - TechnoWeekly

DUBLIN, Oct. 22, 2020 /PRNewswire/ -- The "Smart Cities Market by Strategy, Technology, and Outlook for Solutions, Applications and Services 2020 - 2025" report has been added to ResearchAndMarkets.com's offering.

This report evaluates the smart cities market including leading vendors and strategies (such as a single vs. multi-vendor centric approach), infrastructure, solutions, applications, and services. The report analyzes market factors driving solution adoption, technology readiness and fitness for use, and other considerations.

The report assesses the aforementioned factors to derive penetration and revenue to forecast market value for the period of 2020 - 2025. The report also analyses the role of technology accelerating digital transformation including AI, edge processing, 5G deployment and usage, and advanced data analytics.

Technological innovation is one of the driving factors for the development of cities. These innovations are also an important support for those searching for new ways to manage resources and deliver services. A lot of smart city technologies are being developed to manage specific issues in energy distribution, energy management, transportation management, and public safety. New generations of sensor networks, big data analytics, and IoT applications are being deployed in public and privately managed physical spaces to meet these requirements, though many challenges remain.

An important focus area for smart cities is technology infrastructure to enable smart utilities (smart grids, sanitation, water, and gas), smarter buildings, and workplaces. Systems and resources are intertwined as mobility, communications, energy, water, platforms, monitoring/control, performance management, predictability and forecasting all merge together. We see great synergy coming in public and corporate collaboration, but it will take up to twenty years to fully develop.

Major initiatives are beginning to make a substantial positive impact as critical milestones are achieved. This includes network and system interoperability, security and privacy controls, and technology integration. For the latter, one of the key areas that we see is the combination of AI and IoT forming "thinking" cities that rely upon the Artificial Intelligence of Things (AIoT). Industry verticals we see as early beneficiaries include utilities, public safety, and transportation. Specific AIoT-enhanced smart city solutions within these verticals are poised to improve the overall efficiency and operational effectiveness of delivery systems as well as human capital management.

Select Report Findings:

Select Report Benefits:

Key Topics Covered:

1.0 Executive Summary

2.0 Smart City Overview2.1 A Global Need for a Smarter Urban Environment2.2 All Cities are "Smart" but some are Smarter than Others

3.0 Smart City Strategy and Planning3.1 Smart City Considerations3.1.1 Existing vs. New City Approach3.1.2 Smart City Development Factors3.1.3 Smart City Services Life Cycle3.1.4 Smart Community Services3.2 Smart City Business Models3.2.1 Build Own Operate (BOO)3.2.2 Build Operate Transfer (BOT)3.2.3 Build Operate Manage (BOM)3.2.4 Open Business Model (OBM)

4.0 Smart City Market Analysis4.1 Smart City Market Drivers4.1.1 High Bandwidth, Low Latency, and Reliable Communications4.1.2 Reduced Energy Consumption with Smart Energy Solutions4.1.3 Active Citizen Engagement Leads to Greater Smart City Support4.1.4 Improving Governance Services and National Security4.1.5 Accelerating Digital Transformation4.1.6 Fostering Urban Development4.2 Smart City Solution Focus Areas4.2.1 Smart Utilities4.2.2 Smart Transportation: Roadways, Vehicles, and Parking4.2.3 Smart Residences, Commercial Buildings, and Workplaces4.2.4 Smart Industries4.3 Specific Smart City Solution Areas4.3.1 Asset Tracking and Control4.3.2 Field and Home Area Network Solutions4.3.3 AI and Big Data supported Smart City Hubs4.3.4 Smart City Applications in Citizen Service4.3.5 Mobility Solutions, Governance, and Security in Smart Cities

5.0 Smart City Technology Analysis5.1 Machine to Machine and Internet of Things5.1.1 Machine to Machine Technologies and Communications5.1.2 Internet of Things in Smart Cities5.2 Smart City Data Management Technologies and Solutions5.3 Artificial Intelligence in Smart Cities5.3.1 Artificial Intelligence of Things (AIoT) in Smart Cities5.3.2 Combined AIoT and Data Analytics in Smart Cities5.4 Metropolitan and Wide Area Communications5.4.1 WiMAX5.4.2 LTE5.4.3 5G5.5 Short Range Communication Technology5.5.1 WiFi5.5.2 RFID5.5.3 Li-Fi5.6 Next Generation Computing support of Smart Cities5.6.1 Edge Based Computing: Localized Processing5.6.2 High Performance and Quantum Computing

6.0 Smart City Development by Region and Country

7.0 Smart City Value Chain and Application Analysis7.1 Smart City Ecosystem Analysis7.2 Smart City Product and Service Provider Opportunity Analysis7.2.1 Smart City Network Service Providers7.2.2 Smart City Integrators7.2.3 Smart City Product Vendors7.2.4 Smart City Managed Service Providers7.3 Equipment vs. Software and Service based Approach

8.0 Smart City Vendor and Service Provider Analysis8.1 2020 Imaging8.2 ABB8.3 Accela8.4 Accenture8.5 Aclara8.6 Aclima8.7 Advantech8.8 Aeris Communications8.9 AGT International8.10 Airspan8.11 Airtel8.12 Alibaba8.13 Allegro8.14 Ally8.15 Alstom SA8.16 Altair Semiconductor8.17 Alvarion8.18 Amazon8.19 Ambience Data8.20 AMCS8.21 AMD8.22 America Movil8.23 Amplia Soluciones SL8.24 Analog Devices Inc.8.25 Apple8.26 Appyparking8.27 Altran8.28 Arista Networks Inc.8.29 ARM Holdings8.30 Ascom8.31 Asus8.32 AT&T8.33 Atos8.34 Autogrid8.35 Ayyeka8.36 Azavea8.37 Baidu Inc.8.38 Banyanwater8.39 Barbara IoT8.40 Bentley Systems8.41 Blackberry Ltd8.42 Bosch Software Innovations GmbH8.43 Breezometer8.44 Bridj8.45 Broadcom Corporation8.46 BT Group8.47 Blyncsy8.48 Calthorpe Analytics8.49 Capgemini8.50 Cavium Inc.8.51 China Mobile8.52 China Unicom8.53 Ciena Corporation8.54 CIMCON Lighting8.55 Cisco8.56 Citrix Systems8.57 Cityflo8.58 Citymapper8.59 Civicsmart8.60 Clarity Movement Co.8.61 Cobham Wireless8.62 Colt8.63 Compology8.64 Contus8.65 Cradlepoint8.66 Cubic Corporation8.67 CyanConnode8.68 Dassault Systems8.69 Delta Controls8.70 Dispatchr8.71 Double Map8.72 DOVU8.73 Elichens8.74 Emagin8.75 Emerson Electric Co8.76 Enel8.77 Energyworx8.78 Enevo8.79 ENGIE8.80 Ericsson8.81 Evopark8.82 EZparking8.83 Fathom8.84 Filament8.85 Flamencotech8.86 Flowlabs8.87 Fluentgrid8.88 GE8.89 Getmy Parking8.90 Google8.91 Gridcure8.92 HCL Technologies Ltd8.93 HFCL8.94 Hitachi8.95 Honeywell8.96 HPE8.97 Huawei8.98 IBM8.99 Infarm8.100 Inrix8.101 Inspira8.102 Intel8.103 Intelizon Energy8.104 Inventum Technologies8.105 Itron8.106 Johnson Controls8.107 Kapsch Group8.108 Koninklijke Philips NV8.109 KORE Wireless8.110 LG CNS8.111 Libelium8.112 Logic Ladder8.113 Mapillary8.114 Maven Systems8.115 Meter Feeder8.116 Metrotech8.117 Microsoft8.118 Mindteck8.119 Miovision8.120 Mobike8.121 Moovel8.122 Moovit8.123 NEC8.124 Neighborland8.125 Nokia8.126 Nordsense8.127 NTT DATA8.128 One Concern8.129 Oorja On Move8.130 Opendatasoft8.131 Opusone8.132 Oracle Corporation8.133 Panasonic8.134 Parkwhiz8.135 Passport8.136 Phoenix Robotix8.137 Plume Labs8.138 Proclivis Technology Solutions8.139 Purplewifi8.140 QInfra Solutions8.141 Qualcomm Incorporated8.142 Quality Theorem8.143 Rachio8.144 Remix8.145 Ridlr8.146 Rubicon8.147 SAP8.148 Schneider Electric SA8.149 Sentiance8.150 Siemens AG8.151 Sierra Wireless8.152 Sigfox8.153 Signify8.154 Soofa8.155 Spacetime Insight8.156 Spatial Labs, Inc.8.157 Spice Digital8.158 Spot Hero8.159 Stae8.160 Streetlight Data8.161 Swiftly8.162 Takadu8.163 Tantalum8.164 Telefonica8.165 Telensa8.166 Toshiba8.167 Tractebel8.168 Trafi8.169 Transit Labs8.170 Transit Screen8.171 Transloc8.172 Trilliant8.173 Understory8.174 UrbanFootprint8.175 Urbee8.176 Urbiotica (Spain)8.177 Utilidata8.178 Valor Water Analytics8.179 Varentec8.180 Veniam8.181 Veolia8.182 Verizon8.183 Videonetics Technologies8.184 Vodafone8.185 Volocopter8.186 Watersmart8.187 Where Is My Transport8.188 Wipro8.189 Worldsensing SL8.190 Zagster8.191 Zenysis8.192 Zerocycle8.193 ZiFF Technologies

9.0 Smart Cities Market Forecast 2020 - 20259.1 Global Smart Cities Market 2020 - 20259.1.1 Smart Cities Market in Aggregate9.1.2 Smart Cities Market by Technology9.1.3 Smart Cities Market by Application9.1.4 Artificial Intelligence Market in Smart Cities9.1.5 IoT Market in Smart Cities9.1.6 5G Market in Smart Cities9.1.7 Cloud Computing Market in Smart Cities9.1.8 Big Data Analytics Market in Smart Cities9.1.9 Quantum Computing Market in Smart Cities9.1.10 Edge Computing Market in Smart Cities9.1.11 High-Performance Computing Market in Smart Cities9.2 Regional Smart Cities Market Forecast 2020 - 2025

10.0 Smart City Market Summary, Conclusions, and Recommendations10.1 Advertisers and Media Companies10.2 Artificial Intelligence Providers10.3 Automotive Companies10.4 Broadband Infrastructure Providers10.5 Communication Service Providers10.6 Computing Companies10.7 Data Analytics Providers10.8 Immersive Technology (AR, VR, and MR) Providers10.9 Networking Equipment Providers10.10 Networking Security Providers10.11 Semiconductor Companies10.12 IoT Suppliers and Service Providers10.13 Software Providers10.14 Smart City System Integrators10.15 Automation System Providers10.16 Social Media Companies10.17 Workplace Solution Providers10.18 Enterprise and Government

For more information about this report visit https://www.researchandmarkets.com/r/19qwu7

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Global Smart Cities Market Analysis 2020-2025: AI, IoT, and 5G (AIoT5G) will be the Most Influential Technologies - 63%, 34%, and 52% Respectively -...

Market Study Report, LLC, has added a research study on Quantum Computing market which delivers a concise outline of the market share, market size, revenue estimation, geographical outlook and SWOT analysis of the business. The report further offers key insights based on growth opportunities and challenges as experienced by leaders of this industry, while evaluating their present standing in the market and growth strategies.

The new Quantum Computing market research report presents a granular analysis of the business outlook and also covers the world market overview. It throws lights on various market segmentations based on product type, application spectrum, well-established companies, and regions.

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Additionally, the document analyses the impact of COVID-19 on the market growth.

Key features of Quantum Computing market report:

Regional Analysis of Quantum Computing market:

Quantum Computing Market Segmentation: Americas, APAC, Europe, Middle East & Africa

Overview of the regional terrain of Quantum Computing market:

Product types and application scope of Quantum Computing market:

Product landscape:

Product types: Hardware, Software and Cloud Service

Key factors enclosed in the report:

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Application Landscape:

Application segmentation: Medical, Chemistry, Transportation, Manufacturing and Others

Details stated in the report:

Other details specified in the report:

Competitive spectrum of the Quantum Computing market:

Competitive landscape of Quantum Computing market: D-Wave Solutions, IBM, Microsoft, Rigetti Computing, Google, Anyon Systems Inc., Intel, Cambridge Quantum Computing Limited and Origin Quantum Computing Technology

Major features as per the report:

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Quantum Computing Market 2020 | Outlook, Growth By Top Companies, Regions, Types, Applications, Drivers, Trends & Forecasts by 2025 - PRnews...

The world of computing is full of buzzwords: AI, supercomputers, machine learning, the cloud, quantum computing and more. One word in particular is used throughout computing algorithm.

In the most general sense, an algorithm is a series of instructions telling a computer how to transform a set of facts about the world into useful information. The facts are data, and the useful information is knowledge for people, instructions for machines or input for yet another algorithm. There are many common examples of algorithms, from sorting sets of numbers to finding routes through maps to displaying information on a screen.

To get a feel for the concept of algorithms, think about getting dressed in the morning. Few people give it a second thought. But how would you write down your process or tell a 5-year-old your approach? Answering these questions in a detailed way yields an algorithm.

To a computer, input is the information needed to make decisions.

When you get dressed in the morning, what information do you need? First and foremost, you need to know what clothes are available to you in your closet. Then you might consider what the temperature is, what the weather forecast is for the day, what season it is and maybe some personal preferences.

All of this can be represented in data, which is essentially simple collections of numbers or words. For example, temperature is a number, and a weather forecast might be rainy or sunshine.

Next comes the heart of an algorithm computation. Computations involve arithmetic, decision-making and repetition.

So, how does this apply to getting dressed? You make decisions by doing some math on those input quantities. Whether you put on a jacket might depend on the temperature, and which jacket you choose might depend on the forecast. To a computer, part of our getting-dressed algorithm would look like if it is below 50 degrees and it is raining, then pick the rain jacket and a long-sleeved shirt to wear underneath it.

After picking your clothes, you then need to put them on. This is a key part of our algorithm. To a computer a repetition can be expressed like for each piece of clothing, put it on.

Finally, the last step of an algorithm is output expressing the answer. To a computer, output is usually more data, just like input. It allows computers to string algorithms together in complex fashions to produce more algorithms. However, output can also involve presenting information, for example putting words on a screen, producing auditory cues or some other form of communication.

So after getting dressed you step out into the world, ready for the elements and the gazes of the people around you. Maybe you even take a selfie and put it on Instagram to strut your stuff.

Sometimes its too complicated to spell out a decision-making process. A special category of algorithms, machine learning algorithms, try to learn based on a set of past decision-making examples. Machine learning is commonplace for things like recommendations, predictions and looking up information.

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For our getting-dressed example, a machine learning algorithm would be the equivalent of your remembering past decisions about what to wear, knowing how comfortable you feel wearing each item, and maybe which selfies got the most likes, and using that information to make better choices.

So, an algorithm is the process a computer uses to transform input data into output data. A simple concept, and yet every piece of technology that you touch involves many algorithms. Maybe the next time you grab your phone, see a Hollywood movie or check your email, you can ponder what sort of complex set of algorithms is behind the scenes.

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What is an algorithm? How computers know what to do with data - The Conversation US