Interventi volti a promuovere la ricerca e per listruzione universitaria21.10.2020
Nell'ambito dell'RA Con riferimento alle azioni della Linea Inoltre si conferma la scelta di investire nelle esperienze di apprendimento e scambio all'estero, attraverso il finanziamento di percorsi di studio durevoli in paesi stranieri. Saranno promosse, inoltre, iniziative post lauream dottorati, borse di ricerca, etc. Possibili corsi potranno riguardare la figura dell'Energy manager, del Progettista di energie rinnovabili, del Paesaggista, dell'Amministratore del territorio, ecc. Studenti degli istituti di istruzione universitaria o equivalente; docenti e ricercatori; studenti con diploma di scuola secondaria superiore, apprendisti ex art.
Formazione professionale. Questo sito utilizza cookie per comprendere le preferenze degli utenti e migliorarne la navigazione. Per avere maggiori dettagli leggi la nota informativa sulla privacy oppure accetta l'utilizzo dei cookie. Interventi volti a promuovere la ricerca e per l'istruzione universitaria - POR Puglia Azione Linea Principali gruppi target Studenti degli istituti di istruzione universitaria o equivalente; docenti e ricercatori; studenti con diploma di scuola secondaria superiore, apprendisti ex art.
Bandi e avvisi. Piani Formativi aziendali. Pass Laureati Pass Laureati. Progetti e affidamenti. Borse di studio Adisu.Listening to others, absorbing their expressions and viewing things differently shall do you and your loved ones a world of good. With time, you shall also see your social image and rapport with others improving.
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Check out what is for you in this planetary. More TOP STORIES More Subscribe POPULAR QUIZ What kind of Aries are you.Also when cloning a dataset, you can modify the names, labels, descriptions and preferred flags of its fields using a fields argument with entries for those fields you want to change. See a description for all the arguments below. Dataset Cloning Arguments Argument TypeDescription category optional Integer The category that best describes the dataset.
See the category codes for the complete list of categories. Example: "category": 1 description optional String A description of the dataset up to 8192 characters long. Example: "description": "This is a description of my new dataset" fields optional Object Updates the names, labels, and descriptions of the fields in the new dataset.
An entry keyed with the field id of the original dataset for each field that will be updated. Specifying a range of rows. As illustrated in the following example, it's possible to provide a list of input fields, selecting the fields from the filtered input dataset that will be created. Filtering happens before field picking and, therefore, the row filter can use fields that won't end up in the cloned dataset. See the Section on filtering sources for more details.
Each new field is created using a Flatline expression and optionally a name, label, and description. A Flatline expression is a lisp-like expresion that allows you to make references and process columns and rows of the origin dataset.
See the full Flatline reference here. Let's see a first example that clones a dataset and adds a new field named "Celsius" to it using an expression that converts the values from the "Fahrenheit" field to Celsius. A new field can actually generate multiple fields. In that case their names can be specified using the names arguments.
In addition to horizontally selecting different fields in the same row, you can keep the field fixed and select vertical windows of its value, via the window and related operators. For example, the following request will generate a new field using a sliding window of 7 values for the field named "Fahrenheit" and will also generate two additional fields named "Yesterday" and "Tomorrow" with the previous and next value of the current row for the field 0.
The list of values generated from each input row that way constitutes an output row of the generated dataset. See the table below for more details. See the Section on filtering rows for more details.
Example: "description": "This field is a transformation" descriptions optional Array A description for every of the new fields generated. Example: "fields": "(window Price -2 0)" label optional Array Label of the new field. Example: "label": "New price" labels Array Labels for each of the new fields generated. Example: "name": "Price" names optional Array Names for each of the new fields generated. Basically, a Flatline expresion can easily be translated to its json-like variant and vice versa by just changing parentheses to brackets, symbols to quoted strings, and adding commas to separate each sub-expression.
For example, the following two expressions are the same for BigML. If you specify both sampling and filtering arguments, the former are applied first. As with filters applied to datasources, dataset filters can use the full Flatline language to specify the boolean expression to use when sifting the input.
Flatline performs type inference, and will in general figure out the proper optype for the generated fields, which are subsequently summarized by the dataset creation process, reaching then their final datatype (just as with a regular dataset created from a datasource).
In case you need to fine-tune Flatline's inferences, you can provide an optype (or optypes) key and value in the corresponding output field entry (together with generator and names), but in general this shouldn't be needed. Samples Last Updated: Monday, 2017-10-30 10:31 A sample provides fast-access to the raw data of a dataset on an on-demand basis.
When a new sample is requested, a copy of the dataset is stored in a special format in an in-memory cache. Multiple and different samples of the data can then be extracted using HTTPS parameterized requests by sampling sizes and simple query string filters. That is to say, a sample will be available as long as GETs are requested within periods smaller than a pre-established TTL (Time to Live).
The expiration timer of a sample is reset every time a new GET is received. If requested, a sample can also perform linear regression and compute Pearson's and Spearman's correlations for either one numeric field against all other numeric fields or between two specific numeric fields.
You can also list all of your samples.ThePremium offers ad free access to all TheSportster content and so much more. For best Experience with our website. Kindly use Google Chrome instead of opera mini browser. Here we are using Poasson distribution to calculate percents for all tree possible outcomes. The method test all possible permutation of results up to 5 goals. By calculating all results below 2. More information about algorithms we used will be add in our betting theory handbook.
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Joe OsborneSat, Dec 9, 12:10pmThe baseball world is buzzing after the two biggest offseason commodities finally found their landing spots. First, Japanese sensation Shohei Ohtani. Rob TritesFri, Dec 8, 5:40pmThings are getting packed at the top of the NFC and with two matchups this Sunday that pit four of the six teams currently in the conference's.
Stephen CampbellFri, Dec 8, 1:52pmAs we enter Week 14 of the 2017 NFL season, the playoff picture in both the AFC and NFC is starting to become clear. With the postseason on the. Joe OsborneFri, Dec 8, 1:50pmThe sports betting world is filled with lots of different types of people nice guys, complete losers, people who are lactose-intolerant, the. Joe OsborneFri, Dec 8, 1:40pmGoing into Week 14 of the NFL season, lots of in-game betting trends have developed that can give bettors of the live game a serious advantage with.
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Allsvenskan 17:00 Trelleborgs - Jonkopings 1. Friendly Games 20:45 Poland - Mexico 1. Football League Trophy 19:45 Lincoln City - Notts County 1. Ligue 2 18:45 Le Havre - Reims 1. Ligue 2 19:00 Tours - Bourg Peronnas 1. Ligue 2 19:00 Niort - Clermont 1. La Coruna - Las Palmas 1. Liga 1 17:05FCSB - Poli Timisoara 1. Ligue 1 18:05 Nice - Strasbourg 1. Serie A 18:05 Vasco - Coritiba 1. Seria A 16:30 Verona - Benevento 1.
Etienne - Metz 1. Pauli - Kaiserslautern 11 October Russia. KHL 16:30 Dynamo Moscow - Bars Kazan 1. Serie B 10:30 Pescara - Cittadella 2.That's the first time that's happened. Bored with lending here, and want to go into the home financing. MBS CommentaryMBS RECAP: Best 2-Day Winning Streak in Quite a WhileFor the purposes of this recap, "winning streak" would be defined as a day where Fannie 3. Mortgage Rate WatchMortgage Rates Very Close to 1-Month LowsMortgage rates moved noticeably lower today as bond market improved for the 2nd day in a row--the first time that's happened since early November (when.
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MND NewsWireGig Workers Less Enthusiastic About Homeownership "Gig," a term that used to refer mostly to a musician's booking, is now being used to describe a whole sector of the U. Fannie Mae defines it. MBS CommentaryMBS Day Ahead: This Week's Rally Further Stretches. Consolidating, biding time, coiling, storing energy, etc. Over the years on MBS Live and elsewhere, you may have come into several iterations of this.
Pipeline PressTech Products and a Flattening Yield CurveHow long will venture capital firms enjoy being in a declining margin business like residential lending, historically dominated by individual, family.
MND NewsWireRefi Demand Highest in Months Despite Fairly Flat RatesThere was the usual post-holiday resurgence in the volume of mortgage applications last week, following a subdued level of activity the previous week which. MBS CommentaryMBS RECAP: Bonds Rally After Weaker StartMuch like yesterday's session, today saw bond markets begin the day in slightly weaker territory only to rally into slightly stronger territory by.
Mortgage Rate WatchMortgage rates were more intuitive today with most lenders keeping things unchanged at first. This matched the movement in underlying bond markets, where. MND NewsWireEntry-Level Homes Driving Price AppreciationCoreLogic said on Tuesday that home prices rose in October by 0. MBS CommentaryMBS Day Ahead: For Bonds, Year-End is Looking Like. A sideways range with higher lows and lower highs. The risk of p eriodic volatility regardless of economic data's suggestion.
Pipeline PressFreddie and Fannie Changes from Agencies, Investors. Today, 2 billion adults around the world remain without a bank account. MBS CommentaryMBS RECAP: Bonds Push Back After Weaker Start on Tax.
Friday evening brought the passage of the Senate's version of the tax bill. It now moves to a joint session for "reconciliation" (Senate. MND NewsWire60-Day Delinquency Rate Doubles in Hurricane-Impacted. In its Mortgage Monitor for September, Black Knight outlined the first wave of mortgage delinquencies that appeared to be arising out of Hurricanes Harvey. Mortgage Rate WatchMortgage Rates Steady to Higher, Depending on LenderMortgage rates were distinctly mixed today, with some lenders clearly moving higher while others were effectively unchanged.
The deciding factor is both. Reproduction in whole or in part in any form without the express written permission of MortgageNewsDaily. ALL FREE NO PAYMENTS. DDoSThe number of IP-enabled IoT devices has increased dramatically in the last several years and according to IHS, it is predicted to reach the staggering number of 30.
This assumption was however proven wrong in February 2017. In February 2017, a new Windows Trojan containing IoT attack code was detected in the wild by ASERT and other malware researchers.
What was different about this Windows Trojan is that in addition to infecting Windows computers, it also scanned for vulnerable IoT devices and then proceeded to infect them with the Mirai IoT botnet code. This means that if a Windows computer infected by this Trojan, is connected to the networks inside the corporate firewalls, the Windows computer will start to scan for and infect all those vulnerable IoT device behind the barriers which were previously believed to be safe from attackers.
These resources are in almost all cases, NOT protected against DDoS attacks originating from the inside and are therefore very vulnerable against this kind of attack. Botnet DDoS malware and traditional Ransomware malware also started to cross-pollinate in 2017 as the attackers realized that DDoS attacks against network infrastructures can be far more devastating than infecting end-user computers.