Whether you’ve just purchased the Nikon D750 or you’re still in the research phase, you likely already know this is a DSLR with an amazing price point. It’s still one of the top rated cameras, even after more than 5 years on the market. Lightweight and extremely reliable, with excellent dynamic range, the Nikon D750 is a full frame DSLR Continue Reading

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Have you dreamed of a simple yet feature-rich portable camera? Something that’s a step up from compact cameras but still small enough to carry around in your day bag? A camera that will deliver the image quality of an entry-level DSLR without the bulk? Oh, and still be affordable? The Canon m50 mirrorless camera just might be your dream come Continue Reading

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How Much Does It Really Cost To Produce Your Favorite TV Show? infographic compares the cost to make the show to their ratings on IMDb. Cashnetusa.com comes to the conclusion that, while Game of Thrones paid out the big bucks and received the huge ratings, it isn’t always necessary. Peaky blinders received great reviews and spent 10 million less per episode!

Our new guide to the cost of producing the best and worst rated shows on TV in 2019 reiterates this sense that it’s not always the size of your production budget that counts, but what you do with it. The costly robots of Westworld are rivalled in ratings by the non-union zombies of The Walking Dead for a third of the price; Lost In Space was just as mediocre as the decidedly more earthbound NCIS: New Orleans.

And in the short-term, with the complete series rating hovering around 9.5 on IMDb, Game of Thrones still manages to top our new table as both the highest rated and highest costing show. But when you consider the bitter taste on the tongues of millions of disappointed HBO subscribers, would a more thought-through finale have been a better investment than all that extra cash? Or are GoT fans just sour because (as experts suggest) they’re going through an end-of-show ‘break-up’?

This infographic design does a lot of things right:

• Good scatterplot data visualization to illustrate their data

• Data points are clearly identified with data titles using proximity, not connecting lines necessary. This can often be a design challenge!

• Sources clearly identified with links so anyone can look into the data

• Use of Creative Commons to protect the infographic and encourage sharing

• The text on the infographic landing page includes the clickable data source links and a methodology description.

Found on Geekologie.com

In this article, we prove that the completeness of the Hamilton flow and essential self-dajointness are equivalent for real principal type operators on the circle. Moreover, we study spectral properties of these operators.

In cite{S 2017}, Suh gave a non-existence theorem for Hopf real hypersurfaces in the complex quadric with parallel normal Jacobi operator. Motivated by this result, in this paper, we introduce some generalized conditions named $mathcal C$-parallel or Reeb parallel normal Jacobi operators. By using such weaker parallelisms of normal Jacobi operator, first we can assert a non-existence theorem of Hopf real hypersurfaces with $mathcal C$-parallel normal Jacobi operator in the complex quadric $Q^{m}$, $m geq 3$. Next, we prove that a Hopf real hypersurface has Reeb parallel normal Jacobi operator if and only if it has an $mathfrak A$-isotropic singular normal vector field.

Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios with sufficient accuracy. To address this problem, we propose a new method which combines two GAN models, i.e., a learning-to-Blur GAN (BGAN) and learning-to-DeBlur GAN (DBGAN), in order to learn a better model for image deblurring by primarily learning how to blur images. The first model, BGAN, learns how to blur sharp images with unpaired sharp and blurry image sets, and then guides the second model, DBGAN, to learn how to correctly deblur such images. In order to reduce the discrepancy between real blur and synthesized blur, a relativistic blur loss is leveraged. As an additional contribution, this paper also introduces a Real-World Blurred Image (RWBI) dataset including diverse blurry images. Our experiments show that the proposed method achieves consistently superior quantitative performance as well as higher perceptual quality on both the newly proposed dataset and the public GOPRO dataset.

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an obstacle's space: a polyhedron, such as a cuboid, or a nonlinear differentiable surface, such as an ellipsoid. The former approach relies on disjunctive programming, which has a relatively high computational cost that grows exponentially with the number of obstacles. The latter approach needs to be linearized locally to find a tractable evaluation of the chance constraints, which dramatically reduces the remaining free space and leads to over-conservative trajectories or even unfeasibility. In this work, we present a hybrid approach that eludes the pitfalls of both strategies while maintaining the original safety guarantees. The key idea consists in obtaining a safe differentiable approximation for the disjunctive chance constraints bounding the obstacles. The resulting nonlinear optimization problem is free of chance constraint linearization and disjunctive programming, and therefore, it can be efficiently solved to meet fast real-time requirements with multiple obstacles. We validate our approach through mathematical proof, simulation and real experiments with an aerial robot using nonlinear model predictive control to avoid pedestrians.

We develop a supervised machine learning algorithm that is able to learn topological phases for finite condensed matter systems from bulk data in real lattice space. The algorithm employs diagonalization in real space together with any supervised learning algorithm to learn topological phases through an eigenvector ensembling procedure. We combine our algorithm with decision trees and random forests to successfully recover topological phase diagrams of Su-Schrieffer-Heeger (SSH) models from bulk lattice data in real space and show how the Shannon information entropy of ensembles of lattice eigenvectors can be used to retrieve a signal detailing how topological information is distributed in the bulk. The discovery of Shannon information entropy signals associated with topological phase transitions from the analysis of data from several thousand SSH systems illustrates how model explainability in machine learning can advance the research of exotic quantum materials with properties that may power future technological applications such as qubit engineering for quantum computing.

Cyber-physical systems for robotic surgery have enabled minimally invasive procedures with increased precision and shorter hospitalization. However, with increasing complexity and connectivity of software and major involvement of human operators in the supervision of surgical robots, there remain significant challenges in ensuring patient safety. This paper presents a safety monitoring system that, given the knowledge of the surgical task being performed by the surgeon, can detect safety-critical events in real-time. Our approach integrates a surgical gesture classifier that infers the operational context from the time-series kinematics data of the robot with a library of erroneous gesture classifiers that given a surgical gesture can detect unsafe events. Our experiments using data from two surgical platforms show that the proposed system can detect unsafe events caused by accidental or malicious faults within an average reaction time window of 1,693 milliseconds and F1 score of 0.88 and human errors within an average reaction time window of 57 milliseconds and F1 score of 0.76.

Recent studies have confirmed a growing trend, especially among youngsters, of using Online Social Media as favourite information platform at the expense of traditional mass media. Indeed, they can easily reach a wide audience at a high speed; but exactly because of this they are the preferred medium for influencing public opinion via so-called fake news. Moreover, there is a general agreement that the main vehicle of fakes news are malicious software robots (bots) that automatically interact with human users. In previous work we have considered the problem of tagging human users in Online Social Networks as credulous users. Specifically, we have considered credulous those users with relatively high number of bot friends when compared to total number of their social friends. We consider this group of users worth of attention because they might have a higher exposure to malicious activities and they may contribute to the spreading of fake information by sharing dubious content. In this work, starting from a dataset of fake news, we investigate the behaviour and the degree of involvement of credulous users in fake news diffusion. The study aims to: (i) fight fake news by considering the content diffused by credulous users; (ii) highlight the relationship between credulous users and fake news spreading; (iii) target fake news detection by focusing on the analysis of specific accounts more exposed to malicious activities of bots. Our first results demonstrate a strong involvement of credulous users in fake news diffusion. This findings are calling for tools that, by performing data streaming on credulous' users actions, enables us to perform targeted fact-checking.

Neural style transfer is a well-known branch of deep learning research, with many interesting works and two major drawbacks. Most of the works in the field are hard to use by non-expert users and substantial hardware resources are required. In this work, we present a solution to both of these problems. We have applied neural style transfer to real-time video (over 25 frames per second), which is capable of running on mobile devices. We also investigate the works on achieving temporal coherence and present the idea of fine-tuning, already trained models, to achieve stable video. What is more, we also analyze the impact of the common deep neural network architecture on the performance of mobile devices with regard to number of layers and filters present. In the experiment section we present the results of our work with respect to the iOS devices and discuss the problems present in current Android devices as well as future possibilities. At the end we present the qualitative results of stylization and quantitative results of performance tested on the iPhone 11 Pro and iPhone 6s. The presented work is incorporated in Kunster - AR Art Video Maker application available in the Apple's App Store.

We present a LiDAR-based and real-time capable 3D perception system for automated driving in urban domains. The hierarchical system design is able to model stationary and movable parts of the environment simultaneously and under real-time conditions. Our approach extends the state of the art by innovative in-detail enhancements for perceiving road users and drivable corridors even in case of non-flat ground surfaces and overhanging or protruding elements. We describe a runtime-efficient pointcloud processing pipeline, consisting of adaptive ground surface estimation, 3D clustering and motion classification stages. Based on the pipeline's output, the stationary environment is represented in a multi-feature mapping and fusion approach. Movable elements are represented in an object tracking system capable of using multiple reference points to account for viewpoint changes. We further enhance the tracking system by explicit consideration of occlusion and ambiguity cases. Our system is evaluated using a subset of the TUBS Road User Dataset. We enhance common performance metrics by considering application-driven aspects of real-world traffic scenarios. The perception system shows impressive results and is able to cope with the addressed scenarios while still preserving real-time capability.

Artificial intelligence technology has made its way absolutely necessary in a variety of industries including the fitness industry. Human pose estimation is one of the important researches in the field of Computer Vision for the last few years. In this project, pose estimation and deep machine learning techniques are combined to analyze the performance and report feedback on the repetitions of performed exercises in real-time. Involving machine learning technology in the fitness industry could help the judges to count repetitions of any exercise during Weightlifting or CrossFit competitions.

Retired Soccer Star Briana Scurry describes how the computerized baseline test works and how it is used for athletes who have sustained a concussion.

What Is Real-Time Conversation Analytics?

In contrast to post-call conversation analytics, which provides insights after the fact, real-time call conversation analytics can point them out at present times.

In this blog, I will walk through the essential steps to build a web app that can analyze call conversations in real-time to assist an agent. Once we’re finished, we’ll have an app which will:

Since late last year, a new coronavirus, now dubbed COVID-19, has been sweeping the globe, sickening more than 114,000 with flu- and cold-like symptoms and killing more than 4,000 so far.…

The apps and devices you use are conducting surveillance with your every move Sure, you lock your home, and you probably don't share your deepest secrets with random strangers.…

A system and method assesses and manages risk of an operation of a user. A rules engine of computer executable instructions stored in the storage device determines at least one of a safety risk measurement based on key performance indicators, an operational safety risk measurement for the operation as a function of the operational safety risk measurement information stored in a storage device and/or a conditional safety risk measurement for the operation as a function of the conditional safety risk measurement information stored in the storage device. A processor connected to the storage device executes the rules engine. An output interface connected to the processor indicates the determined safety risk for the operation.

Embodiments of the disclosure include a method for partitioning a deterministic finite automaton (DFA) into a plurality of groups. The method includes selecting, with a processing device, a subset of the plurality of states and mapping each state of the subset onto a group of the plurality of groups by assigning one or more transition rules associated with each state to a rule line of the group, wherein each rule line is assigned at most two transition rules and an extended address associated with one of the at most two transition rules. The method also includes iteratively processing each state of the subset mapped onto the group by removing the extended address from each rule line in the group with transition rules referring to a current state if the transition rules in the rule line branch within the group.

A system and method for implementing a dynamic menu characterized by a real-time menu architecture. An example method includes determining a menu structure, with reference to a data set, for use with user interface software. A menu is then displayed, wherein the menu includes menu items arranged according to the menu structure. An initial drop-down menu list of the menu includes one or more of the menu items. Each menu item is associated with a data object of the data set. A signal is generated when a change is made to a data set corresponding to a menu item. The menu is then updated based on the signal. In an illustrative embodiment, the example method further includes employing a browser to trigger implementation of the method. The browser communicates with a web server, which communicates with an application that is adapted to analyze the data set and associated data structure and provide an update in response thereto via, the signal, to the web server. The web server includes software for enabling the browser to render an updated menu or graphical representation thereof.

Herbicidal injury caused by 6-trisubstituted phenyl)-4-amino-2-pyridinecarboxylates in wheat and barley is reduced with the use of low rates of cloquintocet.

A system for intelligent monitoring and management of an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a real-time energy pricing engine, virtual system modeling engine, an analytics engine, a machine learning engine and a schematic user interface creator engine. The real-time energy pricing engine generates real-time utility power pricing data. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The machine learning engine stores acid processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system.

Methods, systems, and computer readable media for simulating realistic movement of user equipment in an LTE network are disclosed. According to one method, a logical topology of a long term evolution (LTE) access network is defined that includes defining connections between one or more eNodeBs (eNBs). A physical topology of the LTE access network is defined that includes defining locations of the eNBs and sectors, where the physical network topology is mapped to the logical network topology. One or more problem areas are defined within the physical network topology, where the one or more problem areas include locations where signal quality is degraded. One or more paths are defined through the physical network topology. A traffic profile for a user equipment (UE) device is defined. A plurality of messages is generated for simulating the movement of a UE device along a path through the physical network topology.

A device for generating limit torque with a function of yielding a torque change in real time includes a spring, a rotating portion having a cam surface formed therein, a transmitting portion transmitting an elastic force of the spring to the cam surface, a fixed portion with respect to which the relative rotation of the rotating portion is generated, and a limit-torque control portion provided to the fixed portion so as to control limit torque of the rotating portion by adjusting the elastic force of the spring. In the device, the limit-torque control portion controls the limit torque of the spring by changing the elastic force of the spring in real time.

A magnetic recording tape according to one embodiment includes at least about eight data bands, wherein each data band is defined between a pair of adjacent servo tracks, each pair of adjacent servo tracks defining only a single data band therebetween. One of the servo tracks has data encoded therein, the data including data for encryption. A magnetic recording tape according to another embodiment includes a plurality of servo tracks, each servo track comprising a series of magnetically defined bars. An average height of the bars is less than about 50 microns. About eight to about twenty six data bands are present on the tape. A tape supply cartridge according to various embodiments has a magnetic recording tape as described herein.

The techniques described herein implement an operating system that can reliably process time sensitive information in non real-time manner. Thus, the operating system described herein is capable of processing an instance of time sensitive input during a time period after the instance of time sensitive input is received (e.g., at a future point in time). To accomplish this, the techniques timestamp each instance of time sensitive input when it is received at a device. The techniques then store the timestamped instance of time sensitive input in a temporary queue, and make the timestamped instance available to the operating system at a time period after the time period when it is received, as indicated by the timestamp. Additional techniques described herein prioritize the activation of a driver configured to receive the time sensitive information during a boot sequence or a reboot sequence.

Methods of preparation and improved oat based puffed R-T-E or breakfast cereal products resulting there from with reduced sodium levels that provide good cooked grain flavor relative to other low or no sodium cooked cereal products and that approach the quality of higher sodium level products are provided. The methods include formulating cooked cereal doughs with minimal levels of sodium chloride and including a blend of potassium chloride and choline chloride. The cooked cereal dough is formed into pellets and gun puffed to form puff products having a total pyrazine content of at least 200 ppm. The puffed products are topically coated with saline solution and dried to provide the present improved low sodium high flavor finished breakfast cereal products.

Methods, systems and devices are provided for displaying monitored activity data in substantial real-time on a screen of a computing device. One example method includes capturing motion data associated with activity of a user via an activity tracking device. The motion data is quantified into a plurality of metrics associated with the activity of the user. The method includes connecting the activity tracking device with a computing device over a wireless data connection, and sending motion data from the activity tracking device to the computing device for display of one or more of the plurality of metrics on a graphical user interface of the computing device. At least one of the plurality of metrics displayed on the graphical user interface is shown to change in substantial real-time based on the motion data.

A method of treating an object with radiation that includes generating volumetric image data of an area of interest of an object and emitting a therapeutic radiation beam towards the area of interest of the object in accordance with a reference plan. The method further includes evaluating the volumetric image data and at least one parameter of the therapeutic radiation beam to provide a real-time, on-line or off-line evaluation and on-line or off-line modification of the reference plan.

Information technology tools can be provided to manage access by a plurality of attendees through a network to a presentation. Each of the attendees is registered with an associated content access status, and presentation data for the presentation is provided to a registered attendee based on the particular content access status of the registered attendee.

An agricultural system includes an agricultural row unit movable on a field between a first soil condition and a second soil condition, the first soil condition having a different soil hardness than the second soil condition. A down-pressure actuator applies an initial first pressure associated with the first soil condition. A soil-hardness sensing device is positioned at a distance D forward of the row unit and outputs a soil-hardness change signal when detecting a change from the first soil condition to the second soil condition. At least one memory device stores instructions that, when executed by at least one processor, cause the down-pressure actuator to change, in response to receiving the soil-hardness change signal, the initial first pressure to a different second pressure when the row unit encounters the second soil condition.

Methods and systems are described for improved drilling operations through the use of real-time drilling data to predict bit wear, lithology, pore pressure, a rotating friction coefficient, permeability, and cost in real-time and to adjust drilling parameters in real-time based on the predictions. The real-time lithology prediction is made by processing the real-time drilling data through a multilayer neural network. The real-time bit wear prediction is made by using the real-time drilling data to predict a bit efficiency factor and to detect changes in the bit efficiency factor over time. These predictions may be used to adjust drilling parameters in the drilling operation in real-time, subject to override by the operator. The methods and systems may also include determining various downhole hydraulics parameters and a rotary friction factor. Historical data may be used in combination with real-time data to provide expert system assistance and to identify safety concerns.

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.

A radio-frequency (RF) amplifier having a direct response to an arbitrary signal source to output one or more electrosurgical waveforms within an energy activation request, is disclosed. The RF amplifier includes a phase compensator coupled to an RF arbitrary source, the phase compensator configured to generate a reference signal as a function of an arbitrary RF signal from the RF arbitrary source and a phase control signal; at least one error correction amplifier coupled to the phase compensator, the at least one error correction amplifier configured to output a control signal at least as a function of the reference signal; and at least one power component coupled to the at least one error correction amplifier and to a high voltage power source configured to supply high voltage direct current thereto, the at least one power component configured to operate in response to the control signal to generate at least one component of the at least one electrosurgical waveform.

Polymerization reactor systems providing real-time control of the average particle size of catalyst system components are disclosed. Methods for operating such polymerization reactor systems also are described.

A patient wearable, continuously operating extracorporeal pump apparatus which accesses the patient's arterial venous pressure differential by applying external pressure to a subcutaneous graft that has been cannualized to modulate blood flow through an extracorporeal circuit and to drive the pump for delivering a medicament, such as an anticoagulant, to the site of an intravenous cannula to prevent clogging thereof and also to move a dialysate through a circuit, including a dialyzer and a dialysate rejuvenating cartridge, whereby kidney failure can be treated without recourse to prior art hemodialysis machines found in most treatment facilities. With slight modification, the present invention can be used to remove excess fluids from CHF patients, to remove toxins from the blood in those suffering from liver failure and to facilitate administration of insulin to diabetics and/or glucose to those having hypoglycemia.

A system and method for interactively producing a 3D representation of a vector graphic is disclosed. A vector graphic representing a 2D graphic having a number of endpoints joined by vector segments is automatically or interactively converted into a triangulated mesh in a form readable by a 3D printer. The conversion from vector graphic to a triangulated mesh is accomplished by generating an n-sided polygon in the vicinity of each endpoint of the vector graphic. Each of the vertices of the polygon are then be joined by a line to a corresponding vertex on the next adjacent polygon. Each vertex is also joined to an adjacent vertex on the next adjacent polygon. The process is continued until all polygons are joined, resulting in a triangulated mesh, which is then converted into a format readable by a 3D printer and sent to a 3D printer to produce the 3D representation.

Aspects of the present disclosure relate to systems and methods for receiving, managing, and displaying annotations on documents in real-time. A user (e.g., an author of a document) uploads a document into a real-time annotation system, which may then generate a composite presentation based on the uploaded document. The composite presentation includes all the content of the document presented in a specially configured graphical user interface to receive and manage annotations from a plurality of user devices.

Computer implemented systems and methods are provided for generating a predictive graphical user interface. In some embodiments, a system for generating a predictive graphical user interface may comprise at least one processor configured to receive real-time and historical data associated with utilization of a facility. The at least one processor may be configured to generate, based on the real-time and historical data, instructions to display a user interface depicting a first representation of utilization of the facility at a first time. The at least one processor may be configured to receive a request to display a second representation of utilization of the facility, the request including a selection of a second time, and generate, based on the real-time and historical data, instructions to display, within the interface, a second representation of utilization of the facility, the second representation reflecting utilization at the second time, wherein the second time is a future time relative to the first time.

A method of pulsed-air compacting of mold-sand in combination with compacting by compression supplements the pulsed-air compacting of the mold-sand by an operation of re-compacting the mold-sand by pressing which is performed with the pattern plate containing the patterns by the plate moving inside the cavity of the filling frame in the direction of the latticed pressing element which is subjected to a counter-pressure force corresponding in its value to the prescribed level of the half mold compaction. The method is realized with a device in which the pattern plate containing the patterns is mounted with the possibility of a reciprocal motion inside the cavity of the filling frame, and the pressing cylinder is mounted with the possibility to apply a force against the movable pattern plate.

Inhibition of expansion of a cereal product, such as a ready-to-eat cereal, by a particulate insoluble component such as fiber and/or calcium is avoided by pelletizing the particulate insoluble component. A binder component, such as gelatinized starch, is used to bind particles of the particulate insoluble component into a coherent mass which is formed into non-expanded pellets for fortification of the cereal product. The expanded cereal products, such as extruded puffed RTE cereals which contain the pellets, exhibit a crisp, uniform texture and cell structure, improved, prolonged bowl life, a non-gritty mouthfeel, and a smooth, uniform surface appearance even though they are fortified with high amounts of the solid or particulate insoluble nutritional components.

A method of calculating a 3-D geologic model in real time using, as input, 2-D geologic data. The 3-D is used for conducting further drilling operations. The model may be updated in real time using additional measurements obtained during drilling operations.

Plus, I have no interest in my husband now that he is smoking again. I'm a cis bi woman, and I mainly have sex with people with penises. I have a really gross problem, sorry.…

DAVE Malone is standing down as Winchester City’s director of football at the end of 2018.

South Coast surveying practice, Realest have been instructed alongside joint agents Lambert Smith Hampton to market The Director General’s House in Southampton. The iconic building which was given its name as the former residence of the Director General of the Ordnance Survey, is located at the head of London Road fronting The Avenue and Rockstone Place.

Realest, the newest commercial practice on the central South Coast, has completed the off market sale of Meridians House, Meridians Cross, Ocean Village, Southampton on behalf of Astoria Holdings to Charter Court Investments represented by Maughan Mitchell.

Author Hugh Sebag-Montefiore has written for the Daily Echo about the involvement of the Rifle Brigade, a Winchester-based regiment, on the first day of the battle of the Somme.