The logger module determines when a write to the log has been completed and calls the appropriate callback with the specified context. Through the callback, the program that caused the metadata to be modified is notified when the write of the metadata to disk has been completed. The completion of a log write may also cause the next write to be initiated.

With write-back caching, the processor writes data to its local cache first before writing that cached data to memory or disk.

The write-intent log can use a bitmap to flag the portions of a storage system where a write is to occur.

data consistency may be maintained in networked storage environments using a write-intent log that first records the intent to write data before writing the data into multiple locations.

The bitmap can be referred to as an “event gate bitmap” or simply a “gate bitmap”.

a write-back cache system stores every write into the cache but may not immediately store the write into the drive. Instead, the write-back cache system tracks which cache memory locations have been modified by marking those cache entries as “dirty”. The data in the dirty cache locations are written back to the drive when triggered at a later time

When an array has a write-intent bitmap, a spindle (a device, often a hard drive) can be removed and re-added, then only blocks changes since the removal (as recorded in the bitmap) will be resynced.

Therefore a write-intent bitmap reduces rebuild/recovery (md sync) time if:

the machine crashes (unclean shutdown) one spindle is disconnected, then reconnected If one spindle fails and has to be replaced, a bitmap makes no difference

Intent logging minimizes system downtime after abnormal shutdowns by logging filesystem transactions. When the system is halted unexpectedly, this log can be replayed and outstanding transactions completed. The check and repair time for filesystems can be reduced to a few seconds, regardless of the filesystem size.

the primary and backup virtual bridges are adapted to transmit the packets over the network by tunneling through the network, and the primary and backup virtual bridges are arranged to transmit the packets using a virtual private LAN service (VPLS).

STP ensures that all data paths in a network of bridges are free of loops by disabling forwarding of packets through certain interfaces.

BPDU contains, among other parameters, the unique identifier of the bridge that the transmitting bridge believes to be the root, the cost of the path to the root from the transmitting port, the identifier of the transmitting bridge, and the identifier of the transmitting port

processing the BPDU comprises eliminating the loops only from the TLS identified by the control frames.

transmitting the control frames comprises inserting information in the control frames that identifies the TLS among the plurality of TLSs

Unlike IP routers, LSRs simply use the packet label as an index to a look-up table, which specifies the output interface for the packet and the label that the LSR should attach to the packet for the next hop.

A transparent LAN service (TLS) provides bridge-like functionality between multiple sites over a large network.

Loops in the network topology can cause these broadcast packets to flood the network.

As illustrated, detected conditions are displayed as overlay content (such as bounding regions 530, 532 and 534) over an original X-ray image, where each overlay indicates to the practitioner which regions contain which specific detected conditions.

A deterministic network supports deterministic traffic flows, which are also called ‘Guaranteed Rate’ (GR) traffic flows. A GR traffic flow can transmit packets at a guaranteed rate, along a fixed path from a source node to a destination node, through a network of deterministic packet-switches. A deterministic packet-switch will eliminate the use of the heuristic sub-optimal schedulers used in the Best-Effort Internet routers and switches. In a deterministic network, a logical controller can pre-compute deterministic transmission schedules for each switch in advance, and these schedules can be re-used as long as the traffic demands through a router or switch do not change.

. The switch has controllers which can be configured to store several deterministic periodic schedules, which can be configured by an SDN control-plane.

A controller can monitor the packet arrivals to detect unauthorized packets from a cyber-attacker, and inform the SDN control-plane.

The control plane is the part of a network that controls how data packets are forwarded — meaning how data is sent from one place to another. The process of creating a routing table, for example, is considered part of the control plane. Routers use various protocols to identify network paths, and they store these paths in routing tables. In contrast to the control plane, which determines how packets should be forwarded, the data plane actually forwards the packets. The data plane is also called the forwarding plane

A crosspoint buffer is a temporary storage space located at each individual crosspoint within the N×M switching matrix. The purpose of the crosspoint buffer is to hold the data packets coming from the enabled input queues before they are switched to their respective output ports.

Next, the seed generator 1719 generates the seed 1722, 1816. The seed 1722 may be, for example, a random number, pseudo random number, one-time pad. Next, the key pair generator 1721 generates an asymmetric encryption key pair including an encryption key (A=) 1724 and a decryption key (=B) 1726 from the seed 1722 1818.

Contexts can include, by example, colour, sensor data and geographic location; a context can be manually selected by the user or automatically preselected by the system including the keypad. Moreover, multiple contexts can be combined to produce progressively stronger passwords.

In the embodiments of the invention, the term Security Proxy 502 will be used for both a security proxy computer having a processor and memory, and for security proxy software instructions stored in a computer readable memory for execution by a processor.

The UID 310 may be stored in encrypted form. The UID 310 is used to uniquely identify the trusted security device 300, in order to ensure that a customer physically has the trusted security device 300 when accessing the institution web server.

In the method described above, the storing the unique identity of the portable security device comprises storing a unique identity of one or more of the following: a cellphone, a smart phone, and a personal portable computing device having a further computer readable storage medium having computer readable instructions stored thereon for executing by a further processor for communicating with the security proxy server.

When the neuron generates an output (fires a spike), the cross-correlogram may be determined based on (i) a time record of pre-synaptic input into the neuron with a time interval ΔT prior to the output; and (ii) a time record of post-synaptic output by the neuron with the same time interval.

Long-term potentiation (LTP) is a process involving persistent strengthening of synapses that leads to a long-lasting increase in signal transmission between neurons.

In one or more implementations, the adaptive plasticity mechanism may be based on a similarity measure (e.g., a cross-correlogram, cross-correlation, convolution, deconvolution, and/or mutual information) between neuron output and neuron input. When the neuron generates an output (fires a spike), the cross-correlogram may be determined based on (i) a time record of pre-synaptic input into the neuron with a time interval ΔT prior to the output; and (ii) a time record of post-synaptic output by the neuron with the same time interval.

the term "plasticity" refers to the ability of the network's synapses to change their strength or efficacy based on the patterns of neural activity and the information processing demands.

FIGS. 1 to 4 show a first exemplary embodiment of a steering device having a superposition gearing which is suitable for superposing a further steering angle on a steering angle input by a drive. Here, the superposition gearing together with a drive motor forms an actuator of a superposition steering system.

Due to this compensating movement, e.g. loads of the superposition drive (in particular of the drive worm or of the actuator for driving the drive worm) and of the locking means (in particular of the locking element and the rotatable element), which can lead to damages in particular at high speeds, are avoided or at least largely reduced

The steering wheel 1 furthermore includes a locking means 3 separate from the superposition drive 2, which serves to lock the superposition drive by mechanical action; for example to ensure a safe introduction of a steering angle into the steering shaft by a torque applied by the driver via the steering wheel rim 11 in the case of a failure of the superposition drive or in its non-active condition.

The steering wheel 1 according to the invention as shown in FIG. 1 includes a steering wheel rim 11, via which a driver of the motor vehicle can rotate the steering wheel and thus impose a steering angle on a steering shaft connected with the steering wheel. The steering wheel 1 furthermore includes a superposition drive 2 with which an additional steering angle can be imposed on the steering shaft, which is superimposed on the steering angle introduced into the steering shaft by rotating the steering wheel rim.

The superposition drive in particular includes a drive worm meshing with a worm gear and arranged in its housing, wherein the locking means is arranged on a portion (abutment portion) of the housing of the superposition drive and is elastically mounted on the abutment portion by means of the bearing means.

In one variant, the first rule is characterized by a first inhibitory efficacy configured to suppress the response of the neurons of the first portion to the first feature. In another variant, the instructions are further configured to, when executed: based on a second rule, adjust a second plurality of inhibitory connections, individual ones of the second plurality of inhibitory connections configured to provide inhibitory signals between neurons of the first portion and neurons of the second portion. The second rule is characterized by e.g., a second inhibitory efficacy, the second efficacy being lower than the first inhibitory efficacy; and the first rule and the second rule cooperate to enable the neurons of the second portion to respond to the second feature.

a first portion of neurons of a network is configured to respond to the salient feature, and a second portion of neurons of the network is configured to respond to at least one of the one or more other features.

salient (e.g., less frequent) features in order to, for example, instruct a saccading module of a visual processing system to transition (saccade) to the salient feature. Such salient feature selection may also be referred to as formation of a “pop-out”.

stimulus refers to a signal or input that is provided to the spiking neuron network

In one implementation, the encoder apparatus may comprise a spiking neuron network configured to encode spectral illuminance (i.e., brightness and/or color) of visual input into spike latency.

Each of the unit-to-unit connections may be assigned, inter alia, a connection efficacy, which in general may refer to a magnitude and/or probability of input spike influence on unit output response (i.e., output spike generation/firing). The efficacy may comprise, for example a parameter—e.g., synaptic weight—by which one or more state variables of post-synaptic unit are changed. In one or more implementations, the efficacy may comprise a latency parameter by characterizing propagation delay from a pre-synaptic unit to a post-synaptic unit.

In spiking neural networks (SNNs), action potentials are used to represent the activation of neurons. When a neuron fires an action potential, it sends an excitatory output to all of its connected neurons. This excitatory output increases the likelihood that the connected neurons will fire action potentials as well.

Connection efficacy is a measure of the strength of a connection between two neurons. It is a measure of how likely it is that a signal from one neuron will be able to influence the activity of the other neuron.

Connection efficacy can be affected by a number of factors, including the number of synapses between the two neurons, the strength of the synapses, and the neurotransmitters that are released at the synapses

As used herein, the terms “pulse latency”, “absolute latency”, and “latency” are meant generally to refer to, without limitation, a temporal delay and/or a spatial offset between an event (e.g., the onset of a stimulus, an initial pulse, and/or just a point in time) and a pulse.

The optical flow is then configured to characterize the velocity of at least a portion of the visual data frame.

The velocity of a pixel is calculated by dividing the distance it has moved by the time it took to move. The optical flow can then be used to track the movement of objects in a video, or to estimate the depth of objects in a scene

the next step is to encode optical flow into one or more pulse latencies. The pulse latencies represent the time it takes for a pixel to move from its position in one frame to its position in the next frame.

The method starts by encoding motion information into one or more motion pulses. This can be done by tracking the movement of pixels between two frames of video. The motion pulses can be represented as a sequence of binary values, where a 1 indicates that a pixel has moved and a 0 indicates that it has not moved.

Difference of Gaussians (DoG) is calculated as the difference between two smoothed versions of an image obtained by applying two Gaussian kernels of different standard deviations (sigma) on that image.

In some implementations, described in detail below with respect to FIGS. 10A-10B, the visual input may comprise ambient light stimulus 1052 captured through, inter alia, optics of an eye. In some implementations, such as, for example, encoding of light gathered by a lens 1064 in visual capturing device 1160 (e.g., telescope, motion or still camera, microscope, portable video recording device, smartphone), illustrated in FIG. 10B below, the visual input received at step 802 of method 800 may comprise ambient light stimulus 1062 captured by, inter alia, device lens 1064 or output of the imaging (CMOS/APS) array. In one or more implementations, such as, for example, retinal encoder 1076 configured for digitized visual input in a processing apparatus 1070 (e.g., portable video recording and communications device) described with respect to FIG. 10B, below, the visual input of FIG. 8 may comprise digitized pixel values (RGB, CMYK, grayscale) refreshed at suitable rate

scaling excitability of the spiking neuron means that the neuron can adjust its sensitivity to synaptic input based on the activity levels it senses.

The apparatus 100 may be configured to receive sensory input 102 and to encode the input 102 into spike output 132. In some implementations of visual encoding, the input 102 may comprise light input, e.g., provided by a camera lens or natural light entering retinal implant

The apparatus 100 may be configured to receive sensory input 102 and to encode the input 102 into spike output 132. In some implementations of visual encoding, the input 102 may comprise light input, e.g., provided by a camera lens or natural light entering retinal implant.

a platoon between a host vehicle (which may be the trailing vehicle in the platoon) and a platoon partner (which may be the leading vehicle in the platoon) is describe

One type of vehicle convoying system is sometimes referred to as vehicle platooning in which a second, and potentially additional, vehicle(s) is/are automatically or semi-automatically controlled to closely follow a lead vehicle in a safe manner.

The calculation independence may be based on a syntax format. The syntax format may confine data of the data entry to a row of the spreadsheet file, with each instance of a cell of the row comprising a null, an independent variable of the one or more independent variables, the dependent variable, a spreadsheet formula of the one or more spreadsheet formulas, the extra-spreadsheet instruction, and/or an analysis instruction. The syntax format may also confine to the row of the spreadsheet file the one or more spreadsheet formulas including the formula algorithm.

Functional programming languages are specially designed to handle symbolic computation and list processing applications. Functional programming is based on mathematical functions. Some of the popular functional programming languages include: Lisp, Python, Erlang, Haskell, Clojure, etc.

An interpreted language is a programming language whose implementations execute instructions directly and freely, without previously compiling a program into machine-language instructions.

The programming language may include a structured query language (SQL).

Target efficacy is the desired level of efficacy for the plurality of connections in a spiking neuron network.

target efficacy (e.g., configured at operation 602)

Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks.[1] In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model.

a sample mean, median, a percentile ranking, and/or other statistical parameter,

The efficacy of a connection in a spiking neuron network refers to the strength of the connection between two neurons.

https://analyticsindiamag.com/a-tutorial-on-spiking-neural-networks-for-beginners/

The plasticity rule in a spiking neuron network is a rule that governs the change in synaptic strength between neurons. Synaptic plasticity is the ability of synapses to strengthen or weaken over time, in response to increases or decreases in their activity. The plasticity rule is used to manage connections in a spiking neuron network by modifying the plasticity rule based on statistical parameters associated with an efficacy of the plurality of connections1.

In other words, the plasticity rule is a mechanism that allows the network to learn and adapt over time by changing the strength of its connections

Spiking neural networks aim to bridge the gap between neuroscience and machine learning, using biologically realistic models of neurons to carry out the computation. Due to their functional similarity to the biological neural network, spiking neural networks can embrace the sparsity found in biology and are highly compatible with temporal code.

Before continuing, a clear understanding may be needed of what is in an SLA and where an SLA resides in technical sense. Consider the structure of domains as given in FIG. 1. Three international domains A, B and C may be connected to domain JP. Traffic from each domain A, B and C arrives at domain JP at its own physical interface. Usually at this interface shaping, policing, SLA verification, access traffic handling, measurements (e.g. for billing) etc. are performed. These are important actions defined in an SLA. Then the traffic from the domains A, B and C is combined at a multiplexer and enters domain JP. Classification of traffic inbound domain JP, which is another important aspect of an SLA, may take place at the physical interfaces or at a multiplexer. Domain JP can now handle traffic according to its own classes as defined in its SLAs. At a higher level an SLA exists technically at an interface between two neighbouring domains.

XFRD-8324-ERWH-3231 GHSR-3413-KBKV-8173 Pattern: 4 letters-4 digits-4 letters-4 digits Regular expression: [a-zA-Z]{4}-[0-9]{4}-[a-z]{4}-[0-9]{4} ABC.001.001.0001_0001 xyz.123.123.1234_1234 Pattern: 3 letters.3 digits.3 digits.4 digits_4 digits Regular expression: [a-zA-Z]{3}.[0-9]{3}.[0-9]{3}.[0-9]{4}_[0-9]{4}

DRAM is a form of RAM, and it has several types within its category. DRAM is volatile, like all RAM, so it can’t hold data without power. DRAM is fast and comes in different speeds and latency options. Look for a higher speed (MHz) number and a lower latency (CL) number for the best results. Most DRAM is found in DDR4 products, like those featured in HP desktop PCs and laptops. Look for the most updated generation of DDR memory; it’s reliable and affordable.

In an embodiment, server system 140 may be configured to, in addition to the aforementioned uses involving vehicle identification, also use an identification camera as a “red light camera” for the detection of events in which a vehicle incorrectly proceeds through an intersection controlled by a traffic light

Dual tone multi-frequency (DTMF) is the sounds or tones generated by a telephone when the numbers are pressed. These tones are transmitted with the voice channel.

By way of example, category information may include categories and corresponding criteria to qualify for particular categories such as viewer difficulty in seeing content displayed which may be linked with detected viewer states such squinting, leaning forward, head tilting, looking over glasses, and/or the like. Other categories could include sleepiness, disinterestedness, distraction, and/or the like, with corresponding criteria directed to eye state, facial state, and/or the like. In some embodiments, the rules 358 may include criteria for matching a set of indicia of viewer state to a set of one or more categories.

In various embodiments, the second content may include one or more of electronic programming guide information, television programming content, and/or advertising content.

, the set of rules 358 may include arbitration rules for handling multi-viewer situations. In some embodiments, the arbitration rules may provide for determining whether multiple viewers present are actually looking at the screen. For example, though multiple viewers may be present, it may be determined that only one viewer is actually viewing the content displayed. Others could be determined to be in various viewer states such as asleep or looking off-screen for a time period that satisfies a particular time threshold corresponding to non-attentiveness. Some embodiments may further determine that only one viewer is actually viewing the content displayed based on that one viewer looking at the screen for a time period that satisfies a particular time threshold corresponding to attentiveness.

(especially of the cause of something)

A base station controller (BSC) is a critical mobile network component that controls one or more base transceiver stations (BTS), also known as base stations or cell sites. Key BSC functions include radio network management (such as radio frequency control), BTS handover management and call setup.

A Mobile Switching Center (MSC), sometimes referred to as a Mobile Switching Server (MSS), is a component of 2G and 3G cellular networks that approves or rejects voice communications from one device to another and helps manage roaming.

Upon firing, for a front contact, Ag/Si conductive islands are formed providing conductive bridges between bulk paste and silicon wafer.