Roger Federer reaches semis in Dubai as he chases 100th title

first_imgJapeth Aguilar wins 1st PBA Finals MVP award for Ginebra Roger Federer of Switzerland returns the ball to Marton Fucsovics of Hungry during their match at the Dubai Duty Free Tennis Championship, in Dubai, United Arab Emirates, Thursday, Feb. 28, 2019. (AP Photo/Kamran Jebreili)DUBAI, United Arab Emirates — Roger Federer is two matches away from his 100th career title after beating Marton Fucsovics 7-6 (6), 6-4 on Thursday to reach the Dubai Championships semifinals.Federer faced two set points in the tiebreaker but Fucsovics hit two forehands into the net to let the Swiss star take control. Federer then wasted an early break in the second set but broke again for a 5-4 lead before serving out the match when Fucsovics sent a forehand return wide.ADVERTISEMENT “The tiebreak was tough. I’m happy I found a way to get out of that one,” Federer said. “That was an exciting match, to say the least.”Federer is looking to become the second man in the professional era to reach 100 tour-level tournament tiles, joining Jimmy Connors, who won 109. Seven of Federer’s previous 99 triumphs have come in Dubai.FEATURED STORIESSPORTSGolden State Warriors sign Lee to multiyear contract, bring back ChrissSPORTSCoronation night?SPORTSThirdy Ravena gets‍‍‍ offers from Asia, Australian ball clubsHe will next face sixth-seeded Borna Coric, who beat Nikolaz Basilashvili 4-6, 6-2, 7-6 (1). Coric beat Federer twice last year, including in the Halle final.“He’s really found his game,” Federer said of Coric. “We’ve had a couple tough matches as of late.” Ginebra beats Meralco again to capture PBA Governors’ Cup title Carpio hits red carpet treatment for China Coast Guard PLAY LIST 02:14Carpio hits red carpet treatment for China Coast Guard02:56NCRPO pledges to donate P3.5 million to victims of Taal eruption00:56Heavy rain brings some relief in Australia02:37Calm moments allow Taal folks some respite03:23Negosyo sa Tagaytay City, bagsak sa pag-aalboroto ng Bulkang Taal01:13Christian Standhardinger wins PBA Best Player award Don’t miss out on the latest news and information. LATEST STORIES Nadine Lustre’s phone stolen in Brazil Will you be the first P16 Billion Powerball jackpot winner from the Philippines? Sports Related Videospowered by AdSparcRead Next Rogue cops marked as Gamboa’s targets in his appointment as PNP chief Tom Brady most dominant player in AFC championship history Eugenie Bouchard’s bid for Australian Open spot ends in qualifying Nike continues eSports push with league partnership in China Gretchen Barretto’s daughter Dominique graduates magna cum laude from California college The other semifinal will pit rising star Stefanos Tsitsipas of Greece against French veteran Gael Monfils.Tsitispas outlasted Hubert Hurkacz 7-6 (4), 6-7 (1), 6-1, while Monfils beat Ricardas Berankis 6-1, 6-7 (3), 6-2.Both Tsitsipas and Monfils are coming off tournament wins in Europe last week and have a 1-1 head-to-head record.“We’re both serving really well,” Tsitsipas said. “We have similar game style. I guess I’m a bit more aggressive than him, but he’s much faster. I’m going to have to deal with all of that, be patient, play with passion as well, just wait for the opportunities to break him.”ADVERTISEMENT Ginebra beats Meralco again to capture PBA Governors’ Cup title MOST READ View commentslast_img read more

Konneh Calls for Increased Financial, Technical Support

first_imgThe outgoing Finance and Development Planning Minister Amara M. Konneh, has led a high-powered delegation to attend 2016 Spring Meetings of the World Bank and the International Monetary Fund (IMF) in Washington DC, USA.While in the US, Minister Konneh held talks with senior officials of the International Monetary Fund, World Bank Group, the United States Peace Corps, US Departments of State and Treasury, African Development Bank, International Finance Corporation, among others. According to a dispatch, Minister Konneh commended Liberia’s development and traditional partners for the level of support Liberia enjoys and emphasized the need for further financial and technical assistance. He lamented the critical need for swift intervention amid the twin shocks the Liberian economy experienced from the Ebola Virus Disease (EVD) and the decline in the global commodities prices, particularly iron ore and rubber; the United Nations Mission in Liberia (UNMIL) drawdown in June 2016; as well as the upcoming general and presidential elections; all of which, he emphasized, pose further uncertainties that may have economic, political, social and security risks.Minister Konneh’s pitch for increased support coincides with the release of the International Monetary Fund’s World Economic Outlook, which predicts an extended period of slow global growth of only 3.2% in 2016 and 3.5% in 2017. These figures represent a second downgrade of the Fund’s forecast just this year. The IMF’s Primary Commodity Price Index has declined 19% since August 2015.To help ameliorate the impact of the dire economic situation in Liberia, Minister Konneh articulated committed measures by the Liberian government, which is intended to generate additional revenue to account for said deficit. “These measures include: Fuel excise charge (storage charge), surcharge on outbound international calls, Increase Goods and Services Tax (GST) rate – all of which is expected generate US$45.9 million in new revenues. Additional cuts to the recurrent expenditure ceiling especially goods and services as well as subsidizes and transfers and grants to some non-productive entities,” he disclosed.He further stated that there are growing needs for increased expenditure, especially in the aftermath of the Ebola crisis, as a countercyclical measure and the need to ensure credible elections. He made particular reference to government’s commitment to continuous spending in human development areas such as health, education and agriculture (value chain).In response, Liberia’s international partners assured the Liberian government through Minister Konneh of their unrelenting support to the Agenda for Transformation (AfT) and the Economic Stabilization and Recovery Plan (ESRP), with specific emphasis on budget support, the UNMIL drawdown, as well as the 2017 presidential elections. Officials traveling with Minister Konneh include Dr. Bernice Dahn, Minister of Health; Charles Sirleaf, Acting Governor, Central Bank of Liberia; Dr. Mounir Siaplay, Deputy Minister for Economic Management, MFDP; Bernard Jappah, Public Financial Management Reforms Coordinator, MFDP; and John Davies, President of LBDI, among others.Share this:Click to share on Twitter (Opens in new window)Click to share on Facebook (Opens in new window)last_img read more

Scientists teach neural network to identify a writers gender

Explore further This is a new development in the field of computational linguistics. The research was funded by a Russian Science Foundation grant. The findings were published in the Procedia Computer Science journal.Many scientific studies show that writing style can reflect certain characteristics of a writer – gender, physiological personality traits, and level of education. Speech patterns are a valuable psycho-diagnostic tool, and are often used by human resources professionals and security services. By analyzing a person’s speech, researchers can diagnose certain illnesses such as dementia and depression, and the person’s inclination toward suicidal behavior. The demand for identifying certain characteristics of a writer’s personality is increasing against the backdrop of the development of internet communications—companies want to know which demographics like their products and services.Using the numerical values for various parameters in a text, researchers in this area (linguists, psychologists, IT experts) have created mathematical models to identify certain traits in the writer’s personality. Using neural networks, the researchers analyzed the effectiveness of various machine-learning algorithms for text analysis.During the research, the scientists compared the accuracy of gender identification by text based on two types of data-driven modeling: first, machine-learning algorithms (such as a support vector machine and gradient boosting), and, second, a deep learning neural network (such as convolutional neural networks and the long short-term memory recurrent neural networks).”Using these advanced neural network models, we have achieved great results in identifying the gender of the writer based on text, under conditions in which the author is not attempting to hide his/her gender,” said Alexander Sboyev, assistant professor at MEPhI. “Our next step is to teach the neural network to identify the gender of a writer who is deliberately trying to hide it.”Thus, in the following texts, originally published on dating websites, the neural network easily identified the writer’s gender 10 out of 10 times, despite the fact that authors were free to sign their texts with a name typical of the opposite gender.This text was written by a female: “I am a handsome, fit 30-year-old man. I have a high-paying job at a large oil and gas company. I live in my own flat in Moscow, and also own a small but nice house in an Italian village. I am into sports, mainly football. I love going out on weekends, I can’t stand homebodies. My perfect girl would be modest and beautiful, and would have an attractive body, based on today’s standards. She would share my interests and would not be jealous or try to make me jealous. In the future, I do not plan to be the sole provider in a family, as I believe that when it comes to families, both men and women must earn the money. I would like to have separate budgets as well. I will not tolerate cheating.”This text was written by a male: “Hello! I am very angry, very! Why do you keep treating us like this?! We are people, too, all of us are equal! Are you sexist? I will not tolerate this anymore! I’m going to smash your car into pieces; I will spray paint all over it. You just wait, you monster. It sucks to be you.”This research indicated that the approach based on using convolutional neural networks and methods of deep learning to identify a writer’s gender, is the most optimal. The team of researchers is currently working on identifying a writer’s age. This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. A team of researchers from the National Research Nuclear University MEPhI, the National Research Center Kurchatov Institute and the Voronezh State University has developed a new learning algorithm that allows a neural network to identify a writer’s gender by the written text on a computer with up to 80 percent accuracy. Citation: Scientists teach neural network to identify a writer’s gender (2018, April 27) retrieved 18 July 2019 from https://phys.org/news/2018-04-scientists-neural-network-writer-gender.html Provided by National Research Nuclear University More information: Alexander Sboev et al. Deep Learning neural nets versus traditional machine learning in gender identification of authors of RusProfiling texts, Procedia Computer Science (2018). DOI: 10.1016/j.procs.2018.01.065 Introducing Cloud Text-to-Speech service for developers read more