Archive for the ‘Machine Learning’ Category

Unisys to Research Use of Artificial Intelligence and Machine Learning to Detect Deceitful and Persuasive Writing for Australia’s Defence and National…

Bloomberg

(Bloomberg) -- New Yorks apartment investors are suddenly waist-deep in distress.By December, they were behind on $395 million of debt backed by mortgage bonds, almost 150 times the level a year earlier, according to Trepp data on commercial mortgage-backed securities. Tenants in rent-stabilized units owe at least $1 billion in rent and wealthier ones are fleeing the city, leaving behind vacancies and pushing newly-built luxury towers into foreclosure.For years, as crime dwindled and rent climbed in New York, investors gobbled up apartment buildings. But with the citys economy and culture crushed by Covid-19, mounting job losses have derailed the gentrification boom and put financial pressure on landlords.The people who specialize in mortgage workouts are the busiest people in New York real estate, said Barry Hersh, a clinical associate professor of real estate at New York University.The developers who are in the most trouble pushed hard into Harlem and the Brooklyn hipster hubs of Crown Heights, Flatbush and Bushwick, squeezing out working-class residents by building new expensive units. Now, theyre grappling with eviction bans and new tenant protections as rent falls across New York.Colony 1209, a steel-gray apartment building, opened six years ago in the heart of Bushwick, an industrial vision of urban chic, with a billiards room and 24-hour doorman. The website pitched one bedrooms for $2,500 to like-minded settlers in the mostly Black and Hispanic neighborhood, which it called Brooklyns new frontier.Now Colony, renamed Dekalb 1209, faces foreclosure after owner Spruce Capital Partners defaulted on a $46 million mortgage. The five-year interest-only loan matured in October and was not extended, triggering the default, according to monthly filings by the loans servicer, Wells Fargo & Co.The lender is filing to repossess the building -- as soon as New Yorks foreclosure moratorium expires -- while simultaneously discussing workout alternatives with the borrower. Spruce could not be reached for comment.Right before Covid hit, investors were willing to pay top-dollar for luxury buildings like Colony. They wanted alternatives to rent-regulated buildings, which saw values crimped by a 2019 law that banned tactics landlords depended on to convert rent-stabilized units to market-rate.That was the bright spot until the pandemic happened, said Victor Sozio, executive vice president at Ariel Property Advisors, a commercial brokerage firm in New York City.Plans StymiedEmerald Equities, a fast-growing condo conversion specialist, filed for bankruptcy in December on buildings in Harlem. In its filing, the company said its well-laid plans were stymied by the tenant-friendly law. Residents organized a rent strike, then collections plunged even more after the pandemic, driving Emerald to hand ownership to LoanCore Capital, which loaned $203 million for the project.Doug Kellner, an attorney for Emerald tenants, blames the current market troubles on New Yorks eviction ban because it came without any accompanying financial support.Everybody realizes that rent is the green blood that keeps a building operational, Kellner said.Across the boroughs, rents are on a downward spiral, as landlords try to fill empty apartments with ever-sweeter tenant concessions -- only to see the number of vacant listings surge further.In Manhattan, available units nearly tripled in December from a year earlier, and the median rent plunged 17% to $2,800, according to data from Miller Samuel Inc. and Douglas Elliman Real Estate. Rents are down 11% in Brooklyn and 18% in Northwest Queens, where starry-eyed developers built glassy apartment fortresses along the waterfront for young midtown professionals.In some ways, investors may be better insulated than after the 2008 financial crisis. Lenders generally required bigger down payments and underwrote loans based on current rents rather than expectations for the future, said Shimon Shkury, Ariels president. If the vaccine works and college students and office workers start to return, so will the market, Shkury said.I dont think there will be as much distress as you think, he said.Deregulating RentsLenders have already put $1.4 billion of commercial-backed multifamily debt on watchlists because of issues such as rising vacancies or impending maturities. Thats 19% of all outstanding debt, compared with 22% at the nadir of the financial crisis.The trouble will filter from highly-leveraged investors who expanded quickly to lenders with the most aggressive underwriting, says NYUs Hersh.There will be banks that go under, he said.At the same time, the market for multifamily buildings has gone soft. The total dollar volume of New York City multifamily sales was $4.5 billion in 2020, a 61% plunge from 2018, before the pandemic or the new rent laws, according to a report by Ariel.Still, firms such Limekiln Real Estate Investment Management, see opportunities. The company made $224 million in New York multifamily loans in the second half of 2020, up from $9.3 million before the pandemic. Its easier to extract better terms in a lenders market, said Scott Waynebern, Limekilns president.Its tricky to find where the bottom is, he said.For more articles like this, please visit us at bloomberg.comSubscribe now to stay ahead with the most trusted business news source.2021 Bloomberg L.P.

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Unisys to Research Use of Artificial Intelligence and Machine Learning to Detect Deceitful and Persuasive Writing for Australia's Defence and National...

Development of a Novel, Potentially Universal Machine Learning Algorithm for Prediction of Complications After Total Hip Arthroplasty – DocWire News

This article was originally published here

J Arthroplasty. 2020 Dec 30:S0883-5403(20)31300-0. doi: 10.1016/j.arth.2020.12.040. Online ahead of print.

ABSTRACT

BACKGROUND: As the prevalence of hip osteoarthritis increases, the number of total hip arthroplasty (THA) procedures performed is also projected to increase. Accurately risk-stratifying patients who undergo THA would be of great utility, given the significant cost and morbidity associated with developing perioperative complications. We aim to develop a novel machine learning (ML)-based ensemble algorithm for the prediction of major complications after THA, as well as compare its performance against standard benchmark ML methods.

METHODS: This is a retrospective cohort study of 89,986 adults who underwent primary THA at any California-licensed hospital between 2015 and 2017. The primary outcome was major complications (eg infection, venous thromboembolism, cardiac complication, pulmonary complication). We developed a model predicting complication risk using AutoPrognosis, an automated ML framework that configures the optimally performing ensemble of ML-based prognostic models. We compared our model with logistic regression and standard benchmark ML models, assessing discrimination and calibration.

RESULTS: There were 545 patients who had major complications (0.61%). Our novel algorithm was well-calibrated and improved risk prediction compared to logistic regression, as well as outperformed the other four standard benchmark ML algorithms. The variables most important for AutoPrognosis (eg malnutrition, dementia, cancer) differ from those that are most important for logistic regression (eg chronic atherosclerosis, renal failure, chronic obstructive pulmonary disease).

CONCLUSION: We report a novel ensemble ML algorithm for the prediction of major complications after THA. It demonstrates superior risk prediction compared to logistic regression and other standard ML benchmark algorithms. By providing accurate prognostic information, this algorithm may facilitate more informed preoperative shared decision-making.

PMID:33478891 | DOI:10.1016/j.arth.2020.12.040

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Development of a Novel, Potentially Universal Machine Learning Algorithm for Prediction of Complications After Total Hip Arthroplasty - DocWire News

Global Trade Finance Market Technologies such as blockchain, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT)…

Covina CA, Jan. 25, 2021 (GLOBE NEWSWIRE) -- Trade finance is the financing of international trade rows, acting as an intermediary between importers and exporters to mitigate the risks involved in transactions and enhance working capital efficiency in businesses. It deals with activities related to financing of domestic and international trade. The trade finance includes issuing letters of credit (LCs), receivables and invoice finance, credit agency, export finance, bank guarantees, insurance, and others.

The global trade finance market accounted for US$ 41,075.4 million in 2019 and is estimated to be US$ 53,015.6 million by 2025 and is anticipated to register a CAGR of 4.2%.

The report "Global Trade Finance Market, By Product Type (Guarantees, Letter of Credit, Documentary Collection, Supply Chain Finance, and Others), By Services Providers (Banks, and Trade Finance Houses), By Application (Energy, Finance, Transport, Power Generation, Healthcare, Metals and Non Metallic Minerals, Renewables, and Others), and By Region (North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa) - Trends, Analysis and Forecast till 2025.

Request a Free Sample Copy of this Business Intelligence Report @ https://www.prophecymarketinsights.com/market_insight/Insight/request-sample/4575

Key Highlights:

In July 2018, IBM has launched in collaboration with CLS a blockchain platform, LedgerConnect aimed at the financial services industry and till now, nine budgetary administrations organizations, including banks Barclays and Citi, have associated them with this platform.

In May 2019, Deloitte Tests Data Management on Ethereum Blockchain with Three Irish Banks, named Institute of Banking (IoB), Bank of Ireland, AIB and Ulster Bank, for verification of staff credential.

Analyst View:

Increasing investment in trade finance

The development of technologies such as optical character recognition (OCR) to read container numbers, radio frequency identification (RFID) and quick response (QR) codes to identify and trace shipments, blockchain, and enhancing digitization of trade documents drive the trade finance market growth. Advancements in technology, switching from traditional banking methods for documentation to ease the paperwork, and efficient enhancement in trade finance industry provide opportunities for the market. In addition, strategic formulation along with adoption of structuring and pricing tools offer some other growth opportunities to the market. Support from banks to firms ability to mitigate payment risk by purchasing trade credit insurance boosts the market growth.

Story continues

Browse 60 market data tables* and 35 figures* through 140 slides and in-depth TOC on Global Trade Finance Market, By Product Type (Guarantees, Letter of Credit, Documentary Collection, Supply Chain Finance, and Others), By Services Providers (Banks, and Trade Finance Houses), By Application (Energy, Finance, Transport, Power Generation, Healthcare, Metals and Non Metallic Minerals, Renewables, and Others), and By Region (North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa) - Trends, Analysis and Forecast till 2025

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Key Market Insights from the report:

The global trade finance market accounted for US$ 41,075.4 million in 2019 and is estimated to be US$ 53,015.6 million by 2025 and is anticipated to register a CAGR of 4.2%. The market report has been segmented on the basis of product type, services providers, application, and region.

Depending upon product type, the guarantees segment is projected to grow at highest CAGR over the forecast period. Owing to the fact that agency financing acts as a mediator between buyers and sellers who are involved in international trading. It provides highly structured financing solutions, which, in turn, enhances exporters risk capacity, allowing domestic companies to export goods and services to buyers around the world with a certain level of security. Moreover, international agency financing offer guarantees to cover commercial bank credits, direct funding, and mitigates political risks.

In terms of services providers, the banks segment generated the highest revenue in 2018 and is anticipated to continue the same during the forecast period, owing to the fact that banks act as intermediaries in trade finance ecosystem to provide inter-firm trade credits to buyers, sellers, and other parties involved in the trade. Furthermore, banks are accelerating trade finance processes by transforming their paper-based methods to more efficient and transparent digitized models, thus becoming the highest service providers in the trade finance market.

Depending upon application, the target market is segmented into energy, finance, transport, power generation, healthcare, metals and non-metallic minerals, renewables, and others. Energy segment show the highest growth in the region due to low interest rates and fees provided by international banks.

By region, Asia Pacific dominated the trade finance software market in 2019, followed by Europe and North America. This is primarily due to the increasing adoption of trade finance software to manage and automate the trade finance process. Europe is expected to grow at the fastest growth rate during the forecast period owing to the involvement of export credit agencies (ECA) conducting international trade, enhancing public policy from government agencies, and promoting trade across the globe.

To know the upcoming trends and insights prevalent in this market, click the link below:

https://www.prophecymarketinsights.com/market_insight/Global-Trade-Finance-Market-4575

Competitive Landscape:

The prominent player operating in the global trade finance market includes Banco Santander SA, Bank of America Corp., BNP Paribas SA, Citigroup Inc., Agricole Group, Goldman Sachs Group Inc., HSBC Holdings Plc, JPMorgan Chase & Co., Morgan Stanley and Wells Fargo & Co.

The market provides detailed information regarding the industrial base, productivity, strengths, manufacturers, and recent trends which will help companies enlarge the businesses and promote financial growth. Furthermore, the report exhibits dynamic factors including segments, sub-segments, regional marketplaces, competition, dominant key players, and market forecasts. In addition, the market includes recent collaborations, mergers, acquisitions, and partnerships along with regulatory frameworks across different regions impacting the market trajectory. Recent technological advances and innovations influencing the global market are included in the report.

About Prophecy Market Insights

Prophecy Market Insights is specialized market research, analytics, marketing/business strategy, and solutions that offers strategic and tactical support to clients for making well-informed business decisions and to identify and achieve high-value opportunities in the target business area. We also help our clients to address business challenges and provide the best possible solutions to overcome them and transform their business.

Some Important Points Answered in this Market Report Are Given Below:

Explains an overview of the product portfolio, including product development, planning, and positioning

Explains details about key operational strategies with a focus on R&D strategies, corporate structure, localization strategies, production capabilities, and financial performance of various companies.

Detailed analysis of the market revenue over the forecasted period.

Examining various outlooks of the market with the help of Porters five forces analysis, PEST & SWOT Analysis.

Study on the segments that are anticipated to dominate the market.

Study on the regional analysis that is expected to register the highest growth over the forecast period

Key Topics Covered

Introduction

Study Deliverables

Study Assumptions

Scope of the Study

Research Methodology

Executive Summary

Opportunity Map Analysis

Market at Glance

Market Share (%) and BPS Analysis, by Region

Competitive Landscape

Heat Map Analysis

Market Presence and Specificity Analysis

Investment Analysis

Competitive Analysis

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Global Trade Finance Market Technologies such as blockchain, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT)...

AFTAs 2020: Most Innovative Third-Party Technology Vendor (AI, Machine Learning and Analytics)Behavox – www.waterstechnology.com

Enterprise risk and compliance solutions provider Behavox experienced explosive demand for its product in 2020, as the worlds sudden pivot to remote working tested business continuity protocols and created new opportunities for employee misconduct.

This is why the companywhich offers a machine learning-powered platform that helps firms aggregate and analyze enterprise communications data, including email, messaging and voice, for risk assessment, regulatory compliance and fraud monitoringwins this AFTA for the second year in a row. The coronavirus accelerated the understanding that the workplace is no longer a place, says Erkin Adylov, Behavox founder and CEO. It has become a digital realm, and the laws of people dont apply in that realmit is a complete Wild West. And work is not going to become less digitalfirms are thinking that we need to bring the same laws that govern our day-to-day lives to that digital realm, but they need someone to organize all the data they generate.

Early in 2020, Behavox received a $100 million investment from SoftBank, itself a client. The company then signed up a number of the worlds largest banks and asset managers, and doubled its headcount, as it moved into new territories (Japan and the Nordics) and expanded its existing office in Montreal to accommodate additional data scientists and engineers.

The company also managed to complete implementations in months that normally would have taken far more time, with many customers taking advantage of the cloud-based version of the platform. One implementation, at Danske Bank, took just five months.

This year, as the company grows, it is planning to enhance its platform with Behavox Boost, a tool for modeling employee performance, and Motivate, which analyzes soft concepts like team morale and the quality of team collaboration.

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AFTAs 2020: Most Innovative Third-Party Technology Vendor (AI, Machine Learning and Analytics)Behavox - http://www.waterstechnology.com

A Nepalese Machine Learning (ML) Researcher Introduces Papers-With-Video Browser Extension Which Allows Users To Access Videos Related To Research…

Amit Chaudhary, a machine learning (ML) researcher from Nepal, has recently introduced a browser extension that allows users to directly access videos related to research papers published on the platform arXiv.

ArXiv has become an essential resource for new machine learning (ML) papers. Initially, in 1991, it was launched as a storage site for physics preprints. In 2001 it was named ArXiv and had since been hosted by Cornell University. ArXiv has received close to 2 million submissions across various scientific research fields.

Amit obtained publicly released videos from 2020 ML conferences. He then indexed the videos and reverse-mapped them to the relevant arXiv links through pyarxiv, a dedicated wrapper for the arXiv API. The Google Chrome extension creates a video icon next to the paper title on the arXiv abstract page, enabling users to identify and access available videos related to the paper directly.

Many research teams are creating videos to accompany their papers. These videos can act as a guide by providing demo and other valuable information on the research document. In several situations, the videos are created as an alternative to traditional in-person presentations at AI conferences. This is useful in current circumstances as almost all panels have moved to virtual forms due to the Covid-19 pandemic.

The Papers-With-Video extension enables direct video links for around 3.7k arXiv ML papers. Amit aims to figure out how to pair documents and videos related effectively but has different titles, and with this, he hopes to expand coverage to 8k videos. He has proposed community feedback and has now tweaked the extensions functionality based on user remarks and suggestions.

The browser extension is not available on the Google Chrome Web Store yet. However, one can find the extension, installation guide, and further information on GitHub.

GitHub: https://github.com/amitness/papers-with-video

Paper List: https://gist.github.com/amitness/9e5ad24ab963785daca41e2c4cfa9a82

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A Nepalese Machine Learning (ML) Researcher Introduces Papers-With-Video Browser Extension Which Allows Users To Access Videos Related To Research...