If the Main Door of your flat/office/building faces West, then read on to find out how you will fare in 2006 in your Career/Business, Health, Wealth, Relationships, Harmony and Love. Be aware of your strengths and be warned of the negative energy that you may have to face, to plan your strategies well ahead. Also advice regarding directions to be avoided for renovation, reconstruction, redecoration, etc. in 2006. Get to know the Fengshui Enhancers and Cures that can help you, too.

If the Main Door of your flat/office/building faces North East, then read on to find out how you will fare in 2006 in your Career/Business, Health, Wealth, Relationships, Harmony and Love. Be aware of your strengths and be warned of the negative energy that you may have to face, to plan your strategies well ahead. Also advice regarding directions to be avoided for renovation, reconstruction, redecoration, etc. in 2006. Get to know the Fengshui Enhancers and Cures that can help you, too.

If the Main Door of your flat/office/building faces North West, then read on to find out how you will fare in 2006 in your Career/Business, Health, Wealth, Relationships, Harmony and Love. Be aware of your strengths and be warned of the negative energy that you may have to face, to plan your strategies well ahead. Also advice regarding directions to be avoided for renovation, reconstruction, redecoration, etc. in 2006. Get to know the Fengshui Enhancers and Cures that can help you, too.

If the Main Door of your flat/office/building faces South East, then read on to find out how you will fare in 2006 in your Career/Business, Health, Wealth, Relationships, Harmony and Love. Be aware of your strengths and be warned of the negative energy that you may have to face, to plan your strategies well ahead. Also advice regarding directions to be avoided for renovation, reconstruction, redecoration, etc. in 2006. Get to know the Fengshui Enhancers and Cures that can help you, too.

Discover legal marketing trends & predictions in SEO, PPC, Web Design, Content, and Social Media that will impact lawyers in 2020, and get actionable tips from Consultwebs to apply in your law firm.

Ashton Whiteley: Despite persistent political uncertainty, the German economy looks set to continue its upward trend in 2018.

At the beginning of a new homecoming season, Occasion Brands, LLC, releases this 2019 issue of Pulse of Homecoming with pre-season predictions of consumer purchasing trends for homecoming 2019 dresses.

Learn how to develop a LSTM neural network with PyTorch on trading data to predict future prices by mimicking actual values of the time series data.

Check out this curated collection of coronavirus-related projections, dashboards, visualizations, and data that we have encountered on the internet.

Avi Goldfarb, a professor at the University of Toronto’s Rotman School of Management, explains the economics of machine learning, a branch of artificial intelligence that makes predictions. He says as prediction gets cheaper and better, machines are going to be doing more of it. That means businesses — and individual workers — need to figure out how to take advantage of the technology to stay competitive. Goldfarb is the coauthor of the book “Prediction Machines: The Simple Economics of Artificial Intelligence.”

Digital transformation has just begun.

Not a single industry is safe from the unstoppable wave of digitization that is sweeping through finance, retail, healthcare, and more.

In 2020, we expect to see even more transformative developments that will change our businesses, careers, and lives.

See the rest of the story at Business Insider

See Also:

• GoBear has acquired AsiaKredit to drive growth through digital consumer lending
• US personal savings rate increases due to lowered spending amid social distancing
• RBS is shuttering its standalone digital bank Bó due to coronavirus fallout

As we approach a new year?and a new decade?executives from multiple industry sectors offer predictions on the intertwined areas of CX, information governance and compliance, and automation and AI

This work presents a novel data-driven framework for constructing eigenfunctions of the Koopman operator geared toward prediction and control. The method leverages the richness of the spectrum of the Koopman operator away from attractors to construct a rich set of eigenfunctions such that the state (or any other observable quantity of interest) is in the span of these eigenfunctions and hence predictable in a linear fashion. The eigenfunction construction is optimization-based with no dictionary selection required. Once a predictor for the uncontrolled part of the system is obtained in this way, the incorporation of control is done through a multi-step prediction error minimization, carried out by a simple linear least-squares regression. The predictor so obtained is in the form of a linear controlled dynamical system and can be readily applied within the Koopman model predictive control framework of [12] to control nonlinear dynamical systems using linear model predictive control tools. The method is entirely data-driven and based purely on convex optimization, with no reliance on neural networks or other non-convex machine learning tools. The novel eigenfunction construction method is also analyzed theoretically, proving rigorously that the family of eigenfunctions obtained is rich enough to span the space of all continuous functions. In addition, the method is extended to construct generalized eigenfunctions that also give rise Koopman invariant subspaces and hence can be used for linear prediction. Detailed numerical examples with code available online demonstrate the approach, both for prediction and feedback control.

Temporal event segmentation of a long video into coherent events requires a high level understanding of activities' temporal features. The event segmentation problem has been tackled by researchers in an offline training scheme, either by providing full, or weak, supervision through manually annotated labels or by self-supervised epoch based training. In this work, we present a continual learning perceptual prediction framework (influenced by cognitive psychology) capable of temporal event segmentation through understanding of the underlying representation of objects within individual frames. Our framework also outputs attention maps which effectively localize and track events-causing objects in each frame. The model is tested on a wildlife monitoring dataset in a continual training manner resulting in $80\%$ recall rate at $20\%$ false positive rate for frame level segmentation. Activity level testing has yielded $80\%$ activity recall rate for one false activity detection every 50 minutes.

Event-related potential (ERP) speller can be utilized in device control and communication for locked-in or severely injured patients. However, problems such as inter-subject performance instability and ERP-illiteracy are still unresolved. Therefore, it is necessary to predict classification performance before performing an ERP speller in order to use it efficiently. In this study, we investigated the correlations with ERP speller performance using a resting-state before an ERP speller. In specific, we used spectral power and functional connectivity according to four brain regions and five frequency bands. As a result, the delta power in the frontal region and functional connectivity in the delta, alpha, gamma bands are significantly correlated with the ERP speller performance. Also, we predicted the ERP speller performance using EEG features in the resting-state. These findings may contribute to investigating the ERP-illiteracy and considering the appropriate alternatives for each user.

We perform an effectivization of classical results concerning universal coding and prediction for stationary ergodic processes over an arbitrary finite alphabet. That is, we lift the well-known almost sure statements to statements about Martin-L"of random sequences. Most of this work is quite mechanical but, by the way, we complete a result of Ryabko from 2008 by showing that each universal probability measure in the sense of universal coding induces a universal predictor in the prequential sense. Surprisingly, the effectivization of this implication holds true provided the universal measure does not ascribe too low conditional probabilities to individual symbols. As an example, we show that the Prediction by Partial Matching (PPM) measure satisfies this requirement. In the almost sure setting, the requirement is superfluous.

Consider the following prediction problem. Assume that there is a block box that produces bits according to some unknown computable distribution on the binary tree. We know first $n$ bits $x_1 x_2 ldots x_n$. We want to know the probability of the event that that the next bit is equal to $1$. Solomonoff suggested to use universal semimeasure $m$ for solving this task. He proved that for every computable distribution $P$ and for every $b in {0,1}$ the following holds: $$sum_{n=1}^{infty}sum_{x: l(x)=n} P(x) (P(b | x) - m(b | x))^2 < infty .$$ However, Solomonoff's method has a negative aspect: Hutter and Muchnik proved that there are an universal semimeasure $m$, computable distribution $P$ and a random (in Martin-L{"o}f sense) sequence $x_1 x_2ldots$ such that $lim_{n o infty} P(x_{n+1} | x_1ldots x_n) - m(x_{n+1} | x_1ldots x_n) rightarrow 0$. We suggest a new way for prediction. For every finite string $x$ we predict the new bit according to the best (in some sence) distribution for $x$. We prove the similar result as Solomonoff theorem for our way of prediction. Also we show that our method of prediction has no that negative aspect as Solomonoff's method.

We show that combining a prediction model (based on neural networks), with a new method of test pooling (better than the original Dorfman method, and better than double-pooling) called 'Grid', we can reduce the number of Covid-19 tests by 73%.

With the rapidly worldwide spread of Coronavirus disease (COVID-19), it is of great importance to conduct early diagnosis of COVID-19 and predict the time that patients might convert to the severe stage, for designing effective treatment plan and reducing the clinicians' workloads. In this study, we propose a joint classification and regression method to determine whether the patient would develop severe symptoms in the later time, and if yes, predict the possible conversion time that the patient would spend to convert to the severe stage. To do this, the proposed method takes into account 1) the weight for each sample to reduce the outliers' influence and explore the problem of imbalance classification, and 2) the weight for each feature via a sparsity regularization term to remove the redundant features of high-dimensional data and learn the shared information across the classification task and the regression task. To our knowledge, this study is the first work to predict the disease progression and the conversion time, which could help clinicians to deal with the potential severe cases in time or even save the patients' lives. Experimental analysis was conducted on a real data set from two hospitals with 422 chest computed tomography (CT) scans, where 52 cases were converted to severe on average 5.64 days and 34 cases were severe at admission. Results show that our method achieves the best classification (e.g., 85.91% of accuracy) and regression (e.g., 0.462 of the correlation coefficient) performance, compared to all comparison methods. Moreover, our proposed method yields 76.97% of accuracy for predicting the severe cases, 0.524 of the correlation coefficient, and 0.55 days difference for the converted time.

In this technical report we give an elementary introduction to Quantum Computing for non-physicists. In this introduction we describe in detail some of the foundational Quantum Algorithms including: the Deutsch-Jozsa Algorithm, Shor's Algorithm, Grocer Search, and Quantum Counting Algorithm and briefly the Harrow-Lloyd Algorithm. Additionally we give an introduction to Solomonoff Induction, a theoretically optimal method for prediction. We then attempt to use Quantum computing to find better algorithms for the approximation of Solomonoff Induction. This is done by using techniques from other Quantum computing algorithms to achieve a speedup in computing the speed prior, which is an approximation of Solomonoff's prior, a key part of Solomonoff Induction. The major limiting factors are that the probabilities being computed are often so small that without a sufficient (often large) amount of trials, the error may be larger than the result. If a substantial speedup in the computation of an approximation of Solomonoff Induction can be achieved through quantum computing, then this can be applied to the field of intelligent agents as a key part of an approximation of the agent AIXI.

A modeling framework for evaluating the impact of weather conditions on farming and harvest operations applies real-time, field-level weather data and forecasts of meteorological and climatological conditions together with user-provided and/or observed feedback of a present state of a harvest-related condition to agronomic models and to generate a plurality of harvest advisory outputs for precision agriculture. A harvest advisory model simulates and predicts the impacts of this weather information and user-provided and/or observed feedback in one or more physical, empirical, or artificial intelligence models of precision agriculture to analyze crops, plants, soils, and resulting agricultural commodities, and provides harvest advisory outputs to a diagnostic support tool for users to enhance farming and harvest decision-making, whether by providing pre-, post-, or in situ-harvest operations and crop analyzes.

Embodiments provide methods, apparatus, systems, and computer readable media associated with predicting predicates and branch targets during execution of programs using combined branch target and predicate predictions. The predictions may be made using one or more prediction control flow graphs which represent predicates in instruction blocks and branches between blocks in a program. The prediction control flow graphs may be structured as trees such that each node in the graphs is associated with a predicate instruction, and each leaf associated with a branch target which jumps to another block. During execution of a block, a prediction generator may take a control point history and generate a prediction. Following the path suggested by the prediction through the tree, both predicate values and branch targets may be predicted. Other embodiments may be described and claimed.

A hypervisor and one or more guest operating systems resident in a data processing system and hosted by the hypervisor are configured to selectively enable or disable branch prediction logic through separate hypervisor-mode and guest-mode instructions. By doing so, different branch prediction strategies may be employed for different operating systems and user applications hosted thereby to provide finer grained optimization of the branch prediction logic for different operating scenarios.

A method for accurately determining the shape of currents in a current spectrum for a circuit design is provided. The method includes determining timing and power consumption characteristics. In one embodiment, timing characteristics are provided through a electronic design automation tool. The timing characteristics yield a current pulse time width. In another embodiment, power consumption characteristics are provided by an EDA tool. The power consumption characteristics yield a current pulse amplitude. The shape of the current pulse is obtained by incrementally processing a power analyzer tool over relatively small time increments over one or more clock cycles while capturing the switching nodes of a simulation of the circuit design for each time increment. In one embodiment, the time increments are one nanosecond or less.

An electronic device for text prediction in a virtual keyboard. The device includes a memory including an input determination module for execution by the microprocessor, the input determination module being configured to: receive signals representing input at the virtual keyboard, the virtual keyboard being divided into a plurality of subregions, the plurality of subregions including at least one subregion being associated with two or more characters and/or symbols of the virtual keyboard; identify a subregion on the virtual keyboard corresponding to the input; determine any character or symbol associated with the identified subregion; and if there is at least one determined character or symbol, provide the at least one determined character or symbol to a text prediction algorithm.

Method and Apparatus for predicting the volume of a component separated from a composite fluid by predicting the volume of the composite fluid from sensed pressure and predicting the volume of other separated components from sensed movement of the other components to collection bags.

An axial power distribution control device includes an axial offset calculation unit 52, a parameter calculation unit 53, and an axial offset determining unit 55. The axial offset determining unit 55 predicts whether a core axial offset of the power distribution is increased or decreased after a current time, based on a major axis of an ellipse drawn by the xenon parameter and the iodine parameter calculated by the parameter calculation unit 53 and the xenon parameter and the iodine parameter at the current time. This makes it possible to predict a change of the axial offset of the power distribution of a reactor for suppressing a xenon oscillation in the reactor.

A method for estimating an inclination and azimuth at a bottom of a borehole includes forming a last survey point including a last inclination and a last azimuth; receiving at a computing device bending moment and at least one of a bending toolface measurement and a near bit inclination measurement from one or more sensors in the borehole; and forming the estimate by comparing possible dogleg severity (DLS) values with the bending moment value.

Provided is an inter-layer video decoding method including determining a size of a subblock of a current block by comparing at least one of a height and a width of a predetermined minimum size of the subblock with at least one of a height and a width of the current block of a first layer image; determining at least one subblock from the current block according to the size of the subblock of the current block; determining a candidate block that corresponds to the current block and is included in an encoded second layer image; determining a candidate subblock from the candidate block of the second layer image by using the subblock of the current block; determining motion information of the subblock included in the current block by using motion information of the candidate subblock included in the candidate block; and generating a prediction block of the current block by using the motion information of the subblock included in the current block.

A picture prediction method and a related apparatus are disclosed. The picture prediction method includes: determining motion vector predictors of K pixel samples in a current picture block, where K is an integer greater than 1, the K pixel samples include a first vertex angle pixel sample in the current picture block, a motion vector predictor of the first vertex angle pixel sample is obtained based on a motion vector of a preset first spatially adjacent picture block of the current picture block, and the first spatially adjacent picture block is spatially adjacent to the first vertex angle pixel sample; and performing, based on a non-translational motion model and the motion vector predictors of the K pixel samples, pixel value prediction on the current picture block. Solutions in the embodiments of the present application are helpful in reducing calculation complexity of picture prediction based on a non-translational motion model.

The invention provides diagnostic and therapeutic targets for pulmonary disease, in particular, fibrotic lung disease. The inventors have found that a genetic variant MUC5B gene is associated with increased expression of the gene, increased risk of developing a pulmonary disease, and an improved prognosis and survival among those developing the pulmonary disease.

One or more processors determine wear for a robotic device. The one or more processors divide a direction of travel of a robotic device into zones. Each zone has an associated counter that counts how many times the robotic device has entered a given zone. The one or more processors update a count for a zone in response to the robotic device entering that zone. The one or more processors determine a level of wear for a component associated with the robotic device. The level of wear is based, at least in part, on a total of counts for the zones.

A renal failure blood therapy system includes a renal failure blood therapy machine, concentration levels for each of a plurality of solutes removed from a patient's blood at each of the multiple times, a display device configured to display for selection at least one removed blood solute from the plurality of removed blood solutes, and a device programmed to (i) estimate at least one renal failure blood therapy patient parameter using the determined concentration levels for the at least one selected removed blood solute, (ii) determine a plurality of acceptable renal failure blood therapy treatments that meet a predetermined removed blood solute clearance for the at least one selected removed blood solute using the at least one renal failure blood therapy patient parameter, and (iii) enable selection of at least one of the plurality of acceptable renal failure blood therapy treatments for operation at the renal failure blood therapy machine.

EVEN from a young age he wanted to conquer the world of sailing.

Copyright 2020 NPR. To see more, visit https://www.npr.org.

Copyright 2020 NPR. To see more, visit https://www.npr.org.

There's only a few days left until this year's Oscars are handed out, so now's a good time to catch up on your film viewing. In this week's "Cinema Chat," WEMU's David Fair talks to Michigan and State Theater executive director Russ Collins about the latest movie news and all of the new flicks landing on the big screen this weekend.

Once the staple of regional travel, motels are facing an increasingly uncertain future as online alternatives bite away at revenue.

Rob Minshull produces Weekends with Warren and is an avid reader. You can hear Dan Gardner being interviewed by Warren Boland on Sunday 13th Weekends with Warren.

The dystopian best-seller 1984 was published exactly seventy years ago. Its influence has been profound. But does it really speak to today’s politico-cultural environment?

The dystopian best-seller 1984 was published exactly seventy years ago. Its influence has been profound. But does it really speak to today’s politico-cultural environment?

A model predicts COVID-19 deaths in the U.S. will drop to zero by June. Another suggests without a vaccine, the coronavirus will be with us for years.

As U.S. faces its most trying coronavirus pandemic days, industry leaders imagine the future of travel.

With Tom Brady out of the picture, how will the Jets fare this season?

With Tom Brady out of the picture, how will the Jets fare this season?

Predicting the four acting races for the 2020 Oscars is easy this year, but there's still drama in the best picture race and others

NOSTRADAMUS is hailed as the world's greatest prophetic mind, with three predictions people think he got right. Did he predict the coronavirus outbreak?

Steven Gerrard believes Ryan Kent will get even better for Rangers as he’s not even fully fit yet.

Digital transformation has just begun.

Not a single industry is safe from the unstoppable wave of digitization that is sweeping through finance, retail, healthcare, and more.

In 2020, we expect to see even more transformative developments that will change our businesses, careers, and lives.

To help you stay ahead of the curve, Business Insider Intelligence has put together a list of 30 Big Tech Predictions for 2020 across Banking, Connectivity & Tech, Digital Media, Payments & Commerce, Fintech, and Digital Health.

This exclusive report can be yours for FREE today.

Join the conversation about this story »

This past year, I predicted the fall of both Zuck and Trump, not to mention the triumph of cannabis and rationale markets. But in 2019, the sociopaths won – bigly. Damn, was I wrong. One year ago this week, I sat down to write my annual list of ten or so predictions for the coming … Continue reading "Predictions Review: Trump, Zuck Crush My Optimism In 2019"