We consider the problem of efficiently simulating population protocols. In the population model, we are given a distributed system of $n$ agents modeled as identical finite-state machines. In each time step, a pair of agents is selected uniformly at random to interact. In an interaction, agents update their states according to a common transition function. We empirically and analytically analyze two classes of simulators for this model.

First, we consider sequential simulators executing one interaction after the other. Key to the performance of these simulators is the data structure storing the agents' states. For our analysis, we consider plain arrays, binary search trees, and a novel Dynamic Alias Table data structure.

Secondly, we consider batch processing to efficiently update the states of multiple independent agents in one step. For many protocols considered in literature, our simulator requires amortized sub-constant time per interaction and is fast in practice: given a fixed time budget, the implementation of our batched simulator is able to simulate population protocols several orders of magnitude larger compared to the sequential competitors, and can carry out $2^{50}$ interactions among the same number of agents in less than 400s.

Multimodal Sentiment Analysis is an active area of research that leverages multimodal signals for affective understanding of user-generated videos. The predominant approach, addressing this task, has been to develop sophisticated fusion techniques. However, the heterogeneous nature of the signals creates distributional modality gaps that pose significant challenges. In this paper, we aim to learn effective modality representations to aid the process of fusion. We propose a novel framework, MISA, which projects each modality to two distinct subspaces. The first subspace is modality invariant, where the representations across modalities learn their commonalities and reduce the modality gap. The second subspace is modality-specific, which is private to each modality and captures their characteristic features. These representations provide a holistic view of the multimodal data, which is used for fusion that leads to task predictions. Our experiments on popular sentiment analysis benchmarks, MOSI and MOSEI, demonstrate significant gains over state-of-the-art models. We also consider the task of Multimodal Humor Detection and experiment on the recently proposed UR_FUNNY dataset. Here too, our model fares better than strong baselines, establishing MISA as a useful multimodal framework.

Lexicographic Depth First Search (LexDFS) is a special variant of a Depth First Search (DFS), which was introduced by Corneil and Krueger in 2008. While this search has been used in various applications, in contrast to other graph searches, no general linear time implementation is known to date. In 2014, K"ohler and Mouatadid achieved linear running time to compute some special LexDFS orders for cocomparability graphs. In this paper, we present a linear time implementation of LexDFS for chordal graphs. Our algorithm is able to find any LexDFS order for this graph class. To the best of our knowledge this is the first unrestricted linear time implementation of LexDFS on a non-trivial graph class. In the algorithm we use a search tree computed by Lexicographic Breadth First Search (LexBFS).

For any finite Galois field extension $mathsf{K}/mathsf{F}$, with Galois group $G = mathrm{Gal}(mathsf{K}/mathsf{F})$, there exists an element $alpha in mathsf{K}$ whose orbit $Gcdotalpha$ forms an $mathsf{F}$-basis of $mathsf{K}$. Such an $alpha$ is called a normal element and $Gcdotalpha$ is a normal basis. We introduce a probabilistic algorithm for testing whether a given $alpha in mathsf{K}$ is normal, when $G$ is either a finite abelian or a metacyclic group. The algorithm is based on the fact that deciding whether $alpha$ is normal can be reduced to deciding whether $sum_{g in G} g(alpha)g in mathsf{K}[G]$ is invertible; it requires a slightly subquadratic number of operations. Once we know that $alpha$ is normal, we show how to perform conversions between the working basis of $mathsf{K}/mathsf{F}$ and the normal basis with the same asymptotic cost.

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.

Rescue vessels are the main actors in maritime safety and rescue operations. At the same time, aerial drones bring a significant advantage into this scenario. This paper presents the research directions of the AutoSOS project, where we work in the development of an autonomous multi-robot search and rescue assistance platform capable of sensor fusion and object detection in embedded devices using novel lightweight AI models. The platform is meant to perform reconnaissance missions for initial assessment of the environment using novel adaptive deep learning algorithms that efficiently use the available sensors and computational resources on drones and rescue vessel. When drones find potential objects, they will send their sensor data to the vessel to verity the findings with increased accuracy. The actual rescue and treatment operation are left as the responsibility of the rescue personnel. The drones will autonomously reconfigure their spatial distribution to enable multi-hop communication, when a direct connection between a drone transmitting information and the vessel is unavailable.

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.

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.

In this paper we study a single machine scheduling problem on a set of independent jobs whose execution time is not known, but guaranteed to be either short or long, for two given processing times. At every time step, the scheduler has the possibility either to test a job, by querying a processing time oracle, which reveals its processing time, and occupies one time unit on the schedule. Or the scheduler can execute a job, might it be previously tested or not. The objective value is the total completion time over all jobs, and is compared with the objective value of an optimal schedule, which does not need to test. The resulting competitive ratio measures the price of hidden processing time.

Two models are studied in this paper. In the non-adaptive model, the algorithm needs to decide before hand which jobs to test, and which jobs to execute untested. However in the adaptive model, the algorithm can make these decisions adaptively to the outcomes of the job tests. In both models we provide optimal polynomial time two-phase algorithms, which consist of a first phase where jobs are tested, and a second phase where jobs are executed untested. Experiments give strong evidence that optimal algorithms have this structure. Proving this property is left as an open problem.

Wireless sensor networks have attracted much attention because of many applications in the fields of industry, military, medicine, agriculture, and education. In addition, the vast majority of researches has been done to expand its applications and improve its efficiency. However, there are still many challenges for increasing the efficiency in different parts of this network. One of the most important parts is to improve the network lifetime in the wireless sensor network. Since the sensor nodes are generally powered by batteries, the most important issue to consider in these types of networks is to reduce the power consumption of the nodes in such a way as to increase the network lifetime to an acceptable level. The contribution of this paper is using topology control, the threshold for the remaining energy in nodes, and two of the meta-algorithms include SA (Simulated annealing) and VNS (Variable Neighbourhood Search) to increase the energy remaining in the sensors. Moreover, using a low-cost spanning tree, an appropriate connectivity control among nodes is created in the network in order to increase the network lifetime. The results of simulations show that the proposed method improves the sensor lifetime and reduces the energy consumed.

This paper considers a convex optimization problem with cost and constraints that evolve over time. The function to be minimized is strongly convex and possibly non-differentiable, and variables are coupled through linear constraints.In this setting, the paper proposes an online algorithm based on the alternating direction method of multipliers(ADMM), to track the optimal solution trajectory of the time-varying problem; in particular, the proposed algorithm consists of a primal proximal gradient descent step and an appropriately perturbed dual ascent step. The paper derives tracking results, asymptotic bounds, and linear convergence results. The proposed algorithm is then specialized to a multi-area power grid optimization problem, and our numerical results verify the desired properties.

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.

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:

The Cannabis Issue Search online for information on CBD (cannabidiol), one of the main active components in marijuana and hemp plants, and you're likely to come across claims that it can help with everything from curing cancer to helping you sleep a little better.…

Monty Spears didn't know it at the time, but the last time he'd see his father would be through the window at the Life Care Center of Lewiston.…

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Sewing is my new coping mechanism.…

Here are a few ways to keep yourself entertained, and maybe even educate yourself a bit, while you're stuck at home:…

Another First Friday is here, and you can correctly assume that it will be all online once again. The May 1 Virtual First Friday is from 10 am to midnight.…

You’re out of a job. You’ve been stuck inside for weeks.…

The chafing.…

Warm summer nights are on the way.…

As soon as state Rep. Marcus Riccelli returned home from Olympia, he jumpstarted a community-wide effort to feed Spokane constituents deeply affected by the COVID-19 crisis.…

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.

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.

Systems and methods are disclosed that may be implemented for network management system (NMS) configuration management support for network devices using a learning and natural language processing application to capture the usage and behavior of the Command Line Interface (CLI) of a network device with the aid of a CLI knowledge model, which in one example may be ontology-based.

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.

The disclosure is related systems and methods for using operation durations of a data storage medium to generate random numbers. In one embodiment, a device may comprise a random number generator circuit configured to store a value representing a duration of an operation on the data storage medium, and generate a random number based on the value. Another embodiment may be a method comprising recording durations of access operations to a data storage medium, and generating a random number based on the durations.

A single software project in an integrated development environment (IDE) may be built for multiple target environments in a single build episode. Multiple different output artifacts may be generated by the build process for each of the target environments. The output artifacts are then deployed to the target environments, which may be homogeneous or heterogeneous environments. The same source project may be used to generate multiple output artifacts for the same target environment.

Methods and systems for managing data loads on a cluster of processors that implement an iterative procedure through parallel processing of data for the procedure are disclosed. One method includes monitoring, for at least one iteration of the procedure, completion times of a plurality of different processing phases that are undergone by each of the processors in a given iteration. The method further includes determining whether a load imbalance factor threshold is exceeded in the given iteration based on the completion times for the given iteration. In addition, the data is repartitioned by reassigning the data to the processors based on predicted dependencies between assigned data units of the data and completion times of a plurality of the processers for at least two of the phases. Further, the parallel processing is implemented on the cluster of processors in accordance with the reassignment.

An apparatus for decoding data segments representing a time-domain data stream, a data segment being encoded in the time domain or in the frequency domain, a data segment being encoded in the frequency domain having successive blocks of data representing successive and overlapping blocks of time-domain data samples. The apparatus includes a time-domain decoder for decoding a data segment being encoded in the time domain and a processor for processing the data segment being encoded in the frequency domain and output data of the time-domain decoder to obtain overlapping time-domain data blocks. The apparatus further includes an overlap/add-combiner for combining the overlapping time-domain data blocks to obtain a decoded data segment of the time-domain data stream.

An audio signal decoder has a time warp contour calculator, a time warp contour data rescaler and a warp decoder. The time warp contour calculator is configured to generate time warp contour data repeatedly restarting from a predetermined time warp contour start value, based on time warp contour evolution information describing a temporal evolution of the time warp contour. The time warp contour data rescaler is configured to rescale at least a portion of the time warp contour data such that a discontinuity at a restart is avoided, reduced or eliminated in a rescaled version of the time warp contour. The warp decoder is configured to provide the decoded audio signal representation, based on an encoded audio signal representation and using the rescaled version of the time warp contour.

A time warp contour calculator for use in an audio signal decoder receives an encoded warp ratio information, derives a sequence of warp ratio values from the encoded warp ratio information, and obtains warp contour node values starting from a time warp contour start value. Ratios between the time warp contour node values and the time warp contour starting value are determined by the warp ratio values. The time warp contour calculator computes a time warp contour node value of a given time warp contour node, on the basis of a product-formation having a ratio between the time warp contour node values of the intermediate time warp contour node and the time warp contour starting value and a ratio between the time warp contour node values of the given time warp contour node and of the intermediate time warp contour node as factors.

A visualization can include a set of swim lanes, each swim lane representing information about an event type. An event type can be specified, e.g., as those events having certain keywords and/or having specified value(s) for specified field(s). The swim lane can plot when (within a time range) events of the associated event type occurred. Specifically, each such event can be assigned to a bucket having a bucket time matching the event time. A swim lane can extend along a timeline axis in the visualization, and the buckets can be positioned at a point along the axis that represents the bucket time. Thus, the visualization may indicate whether events were clustered at a point in time. Because the visualization can include a plurality of swim lanes, the visualization can further indicate how timing of events of a first type compare to timing of events of a second type.

Techniques and systems for centralized access to multimedia content stored on or available to a computing device are disclosed. The centralized access can be provided by a media control interface that receives user inputs and interacts with media programs resident on the computing device to produce graphical user interfaces that can be presented on a display device.

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.

A timepiece includes an analogue-type display for displaying the minute at a given moment, constituted by a hand rotated at the rate of one revolution per hour by the mechanism of the timepiece, and a digital-type display for displaying the hour at a given moment, comprising a rotating member for displaying the figure indicative of the hour at a given moment and a drive mechanism for driving the display member which is controlled by the timepiece mechanism and is adapted to rotate the rotating member in jerks at intervals of one hour.

A device and method provide for an accurate output from a unit, such as an oscillator and/or clock providing an output indicative of frequency and/or time. The device includes a processing section having a microprocessor that develops a model characterizing the performance of the device, including establishing predicted accuracy variations, and the model is then used to correct the unit output. An external reference is used to provide a reference input for updating the model, including updating of predicted variations of the unit, by comparison of the reference input with the unit output. The ability of the model to accurately predict the performance of the unit improves as additional updates are carried out, and this allows the interval between the updates to be lengthened and/or the overall accuracy of the device to be improved. The accuracy of the output is thus adaptively optimized in the presence of systematic and random variations.

A wind direction indicating and time display unit is provided for use at the tee areas of a golf course. The unit wind direction indicating device is mounted on an upper surface of a support structure and extends upwardly therefrom. The wind direction indicating device includes a support pole, a sleeve mounted for rotation on the pole at the top thereof, a wind direction indicating element, such as a flag, secured to the sleeve and movable in response to changes in wind direction, and a pole support fitting. Secured to the upper surface of the support structure. A time display device, such as a clock, is secured in a laterally facing wall surface of the support structure.

A method is described for detecting the time messages in the faulty signal of a time-signal transmitter comprising the steps below. Probabilities are assigned to the received information/bits as they are received and whose sign specifies the value of the bit and whose numerical value indicates the certainty of reception. Except for the bits designating the minute information, the probabilities of successive time messages are totaled with time correctness in a one-dimensional memory field. From the totaled probabilities, a reduced time message is reconstructed that initially contains no information on the minutes. If the reconstructed time message does not change over two successive time intervals, and if preset minimum values for the number of probabilities are exceeded for all bits, then the reduced time message is recognized as being correct. The minutes are determined separately and added to the time message recognized as being correct.

A time-locked cigarette case has time-controlled locking mechanism which is manually adjustable by the user and also has a first latch rod which normally retains the case in a closed condition and a second latch rod which moves to retain the case in a closed condition if the first latch rod is jolted to an open position so as to prevent the case from being opened by jolting before the manually set time delay has expired.

A radio paging selective receiver determines that a received message is unread based on the time difference between the message reception time and the current time being larger that some predetermined value of time, and the paging selective receiver provides an indication of the unread message by displaying the reception time of the unread message in a second fashion which is visibly different from a first fashion normally used to display the current time.

A yo-yo has a recess in one of its faces accommodating a timepiece. The yo-yo is be releasably accommodated in a base, and the base may be worn on a user's person by various means including a wristband in the manner of a wristwatch, a fob or a watch chain in the manner of a pocket watch, a necklace in the manner of a necklace watch, or a holster.

In an electromagnetic converter comprising a rotor arranged by including a permanent magnet, a yoke disposed in the vicinity of the rotor for flowing magnetic flux and a coil wound around the yoke, at least a portion of the yoke is composed of an amorphous metal magnetic material. The amorphous metal magnetic material is a Co amorphous metal or a Fe amorphous metal. The electromagnetic converter is a small generator, a motor and the like. In an electronic timepiece provided with a generator device, the Co amorphous metal magnetic material is used for a first yoke (stator) and the Fe amorphous metal magnetic material is used for a second yoke (coil core). In an electronically-controlled mechanical watch, the Co amorphous metal magnetic material is used for a yoke. Portable electronic equipment is a timepiece provided with the electromagnetic converter, and so forth

A network is described for providing estimates of the current time. The network includes multiple computer systems each configured to provide an estimate of the current time in response to a received request. The computer systems are logically arranged to form a hierarchical structure, wherein the hierarchical structure includes multiple levels ranked with respect to one another. Each of the computer systems is assigned one of multiple levels of trust, and occupies one of the levels of the hierarchical structure dependent upon the assigned level of trust. The level of trust assigned to a given computer system is dependent upon a timekeeping dependability of the given computer system. The assigned level of trust may also be dependent upon a timekeeping security of the given computer system, where the timekeeping security is dependent upon a tamper resistance of the time clock of the given computer system. Methods for delegating a level of trust to a new computer system (i.e., a computer system not part of the network) and for adding a new computer system to the network are also described.

The device consists in compensating for the distortion of the characters marked on the dial caused by a lens, by writing the characters with a reverse pin cushion or barrel distortion.

A prefetch optimizer tool for an information handling system (IHS) may improve effective memory access time by controlling both hardware prefetch operations and software prefetch operations. The prefetch optimizer tool selectively disables prefetch instructions in an instruction sequence of interest within an application. The tool measures execution times of the instruction sequence of interest when different prefetch instructions are disabled. The tool may hold hardware prefetch depth constant while cycling through disabling different prefetch instructions and taking corresponding execution time measurements. Alternatively, for each disabled prefetch instruction in the instruction sequence of interest, the tool may cycle through different hardware prefetch depths and take corresponding execution time measurements at each hardware prefetch depth. The tool selects a combination of hardware prefetch depth and prefetch instruction disablement that may improve the execution time in comparison with a baseline execution time.

The invention features methods and compositions for the synthesis of multimerizing agents. An exemplary method for producing AP20187 may comprise: (a) coupling 2-N,Ndimethylaminomethyl-1,3-diaminopropane with AP20792 to produce the dimeric alcohol, AP20793; and (b) coupling the AP20793 so produced with API7362 to yield AP20187. In particular embodiments, the method further includes the step of producing API7362 by coupling API7360 with methyl-L-pipecolic acid, or a salt thereof.

A network storage server implements a method to discard sensitive data from a Persistent Point-In-Time Image (PPI). The server first efficiently identifies a dataset containing the sensitive data from a plurality of datasets managed by the PPI. Each of the plurality of datasets is read-only and encrypted with a first encryption key. The server then decrypts each of the plurality of datasets, except the dataset containing the sensitive data, with the first encryption key. The decrypted datasets are re-encrypted with a second encryption key, and copied to a storage structure. Afterward, the first encryption key is shredded.

The disclosed embodiments relate to pulse oximetry. An exemplary pulse oximeter comprises a probe that is adapted to be attached to a body part of a patient to create a signal indicative of an oxygen saturation of blood of the patient, and a processor that is adapted to receive the signal produced by the probe, to calculate an SPO2 value based on the signal, to detect a plurality of pattern types of SPO2 indicative of pathophysiologic events, and to produce an output indicative of a detected one of the plurality of pattern types.