The approach we take to modelling timing constraints is to include a clock variable representing the current time and a operation which advances this variable. We ensure the timing constraints are satisfied by preventing the clock variable from progressing to a point at which the required properties would be violated. It would seem that we could always satisfy the properties by prevent- ing time from progressing. However, we assume that in the real system time cannot be prevented from progressing and thus it is an obligation on the final implementation to ensure that the timingproperties are always satisfied in time. This is a fairly standard approach to dealing with time in formalisms. For example, this is similar to the approach taken by Abadi and Lamport . Unlike Abadi and Lamport, we are using a discrete model of time rather than a continuous one. A discrete model is sufficient for our purposes since we are interested in ensuring that certain properties hold within fixed time bounds and since the control of the real system is based on fixed time cycles. When we say that something happens at a certain time t, what we mean is that it happened within time period t.
The geometrical size and optical thickness of the en- velope are determined by the NS magnetic field strength and the mass accretion rate at the magnetosphere of the ULX pulsar. The mass accretion rate at the magnetosphere can be reduced with respect to the mass accretion rate from the donor star by a strong outflow from the disc (Shakura & Sunyaev 1973). In this paper, we construct a simple model of ULXs powered by accretion onto strongly magnetized NSs. Accounting for the possibility of strong out- flows from super-Eddington advective accretion discs we re- estimate the geometrical size of the envelope and its optical thickness as a function of the mass accretion rate from the donor star and NS magnetic field strength. Considering a toy model with a spherical envelope of a given optical thick- ness and a given geometrical size, and solving numerically the equations of radiative transfer in the envelope, we ob- tain constraints on the timingproperties of X-ray radiation escaping from the system.
Recall that the pseudo-code for the queue implementation was shown in Figure 4. We will assume that the queue is only touched by the qget and qput functions that are defined here, and the underlying lock location is not directly accessed by other code. We first verify that the queue implementation validates the as- sumptions made in the proof of the spin-lock implementation. First, since the only code that affects lockcell are the calls to the lock and unlock functions, it is easy to see no other code touches lockcell. Furthermore, on every control flow path, the unlock function is only called after having acquired the lock, it is not called more than once, and it is definitely called before either qget or qput returns. Moreover, any access to the queue and its fields occurs in program-order between a lock and an unlock from the same thread. Now we argue that the queue properties are ensured by the operations. There are three key properties: 1. The qget operation returns with a value that was previously placed in the
Many studies have been dedicated to formalizing and verifying timingproperties of real-time systems. Delay, deadline and expiry can be seen in many of those works, sometimes with dif- ferent names. In real-time calculus TCCS of Wang [Yi90] there is a delay construct ε (d) · P, which enforce the model to wait for d time units and then behave as process P and time cannot proceed if d time-units passed and process P has not started yet. Same mechanism has been used in Timed Modal Specification of Cerans et al [CGL97] to model maximal progress assumption where there is a must modality which enforces the maximum delay to the model. Delay in TCCS and maximal progress in Timed Modal Specification present the same constraint as deadline in our work. Also, what is called a loose delay in Timed Modal Specification forces the same be- havior as a delay does in our work. Besides, Urgent Event in Evans and Schneider work [ES00] has been encoded by preventing the time proceeding, if an urgent event is eligible to occur. This behavior of urgent event is the same as deadline events when current time is equal to the deadline and none of the deadline events have occurred yet. In Timed CSP [Sch99] time-out presents the same constraint as expiry does in our work and a delay in Timed CSP causes a similar behavior to what can be enforced by combining introduced delay and deadline in our work.
In this paper we study position-dependent timing shifts and timing resolution in position sensitive avalanche photodiodes (PSAPDs) and their effect on the coincidence window used in positron emission tomography (PET) systems using these devices. There is a delay in PSAPD signals that increases as the excitation position moves from the corner to the center of the device and the timing resolution concurrently worsens. The difference in timing between the center and corner can be up to 30.7 ns for a 14×14 mm 2 area PSAPD. This means that a PSAPD-based PET system could require a very wide coincidence timing window (>60 ns) if this effect is not corrected, although the individual crystal pairs still have full-width half-maximum (FWHM) timing resolutions better than 7.4 ns. In addition to characterizing the timingproperties of PSAPDs, two correction methods were developed and applied to data from a pair of PSAPD detectors. These two timing offset corrections reduced the timing shift of a crystal pair from 52.4 ns to 9.7 ns or 1.3 ns, improved FWHM timing resolution of the detector pair from 24.6 ns to 9.5 ns or 6.0 ns and reduced the timing window (sufficient to cover at least twice the FWHM for all crystal pairs) from 65.1 ns to 22.0 ns or 15.2 ns respectively. A two- step timing alignment method is proposed for a PET system consisting of multiple PSAPDs. Lastly, the effect of PSAPD size on the timing performance was also evaluated.
The purpose of this algorithm is to find the timing phase optimized for a single tap equalizer, the opposite extreme of the infinite length equalizer. This approach is called dispersion minimization (DM) approach  and produces better MSE performance for most finite equalizers than OEM timing, but an adaptive algorithm version of this DM algorithm has not been studied yet. We developed a baseband blind adaptive timing recov- ery algorithm that is closely related to this DM approach as Gardner is closely related to the OEM approach. Simulation results show that the proposed timing recovery algorithm enhances the performance of MMSE DFEs in comparison with Gardner timing.
Follow the processes above and then we can get the current synchronization results. We finally achieve the timing synchronization of QPSK system whose symbol rate is 1.2Gsps and the sampling rate is 4.8Gsps. Figure 5 and Figure 6 give the constellation and output of timing error detector as well as its filtered result in the condition of the signal-to-noise ratio of 20dB, we can see that when the loop tends to be stable, the timing error has very little jitter and eventually convergent to zero.
In the proposed work, Control Registers are designed according to JEDEC DDR4 SDRAM specification. From the results obtained, it is concluded that APB master successfully writes the timing parameter data into the control registers and also successfully reads the response from the CSR. When CSR register is updated with new value corresponding status register bit is successfully set to logic one indicating the DDR core that CSR register is updated with the new value or else reset to zero. Status register is successfully updated with the status on each read/write success/failure.The results also show that the DDR4 core is successfully reading the timing parameter from CSR for the command generation and loading this value into the counter logic.
In addition to tool generated timing reports, we can generate custom reports by writing TCL scripts to get required details about timing. We have written a script to report timing violation paths in custom format. In which you can mention the start point, end point, launch clock, capture clock, and slack of a path in tabular form in a file for all timing paths in design. By referring Vivado user guides and TCL script manual, we had written script to get timing paths in custom format (by referring Vivado user guide of TCL commands). This script will write timing paths in custom format as follow:
Engine combustion performance can be affected by engine operating parameters, such as fuel to air ratio, ignition timing, and the valve opening and closing event , hence emission control can be achieved by system identification of an inverse engine combustion process and optimisation using closed-loop control algorithms. To achieve this, various sensors are fitted onto the engine in order to monitor the combustion process. They are able to collect exhaust gas information, including the amount of carbon dioxide (CO2), oxygen (O2), carbon monoxide (CO) and nitric oxide (NOx), as well as the condition of exhaust gas including exhaust gas temperature and pressure . The Engine Control Unit (E.C.U.) can use such information to calculate the optimal engine operating parameters to control the emissions while keeping the engine in the best possible performance. The exhaust substance contains CO and NO, which are considered as pollutants and the maximum amount allowed is regulated by law.
The physiochemical differences in the three virions could reg- ulate the timing of BMV RNA release and subsequent gene expres- sion during infection. The more facile release of RNA1 could en- sure a higher level of expression of the 1a protein, which is responsible for the formation of the viral RNA replication factory. The 1a protein can also recruit the other BMV RNAs and possibly the RNA-dependent RNA polymerase (RdRp) to the replication factory (28). A mechanism to promote preferential expression of the 1a protein and the establishment of the replication factory could be advantageous in shielding BMV RNA replication from the host innate immune responses. This is consistent with the FIG 5 BMV RNA1 has different encapsidation and replication requirements than other RNAs. (A) Mutations in the N-terminal tail of the BMV CP examined for BMV RNA encapsidation and RNA replication. (B) Transmission electron micrographs of the WT and the four mutant BMV virions. The black scale bar denotes 50 nm. (C) RNAs encapsidated by the WT and mutant BMV virions. All virions were prepared in N. benthamiana. The identities of the RNAs are shown to the left of the agarose gels containing glyoxal-treated RNAs. (D) The effects of the N-terminal tail mutations on BMV RNA accumulation in N. benthamiana plants at 2, 4, and 6 days after agroinfiltration. The RNAs were identified in Northern blots treated with a riboprobe that recognizes the conserved 3= UTR of the BMV RNAs. Bands identified by the asterisks likely correspond to prematurely terminated RNA2 and/or degradation products (37). The relative amounts of the four full-length BMV RNAs within each sample are quantified below the image of the Northern blots. LC, rRNA used as a loading control.
2) Automated ECO fixes and Suggested Sequence for Fixing: The Primetime has inbuilt commands to do automated fixes as per user needs. It gives user the option to fix Design Rule Violations (DRV like max transition and max capacitance), setup, leakage power and hold. The user has the option to utilise PBA (Path Based Analysis) to calculate path timing for fixes. The user can use the method for fixing - cell sizing (includes cell sizing as well as Vt swap) and cell addition (buffer or inverter pair). The user can define the cells to be used for insertion. For leakage fixing the user has the option to set the priority of the available Vt to be swapped to. While doing any fixes the Primetime avoids trying to setup any further on a path while fixing it. The user has the option to set the allowed setup slack on the net if needed be. The user can give option to use only open sites or any occupied sites (for congested designs) for cell addition.
ACES Cases 2014.3 Jacoby, p. 2 This paper adds an electoral dimension to Germany’s policy responses. Indeed, while almost nobody abroad is happy with German policy, almost nobody at home has been upset with it. Angela Merkel easily won her 2013 re-election bid over an opponent who offered little substantive alternative when it came to policy towards Europe and who is, in any event, now her coalition partner with an agreement that explicitly rules out debt mutualization. But the paper goes beyond considering merely ‘what voters want,’ for here, as so often, they want many things all at once. German voters overwhelmingly wish to stick with the euro (about 2:1 in summer 2013), but they also support other policies— particularly austerity—that leave the euro highly vulnerable. Rather than merely stressing the obvious point that German voters are conflicted and confused, this paper injects an element of ‘time’ into what are too often otherwise static considerations of German policy. A focus on time and timing builds on a robust research agenda but one that has tended to emphasize day-to-day policymaking—especially at the EU level—rather than the exceptional and even crisis-driven considerations affected by timing. 6
In studies involving either TOJs or SJs, it is common to fit noisy data from individual participants with a continuous function to derive key parameters, such as a measure of central tendency. This is often taken as an estimate of the relative timing at which two events seem synchronous – the point of subjective simultaneity (PSS). This terminology itself is misleading, as there is seldom, if ever, a precise timing relationship at which two events seem synchronous and none other. Instead, there is typically a relatively broad range of timings at which events are at least sometimes judged as synchronous (see Figure 1 parts A and B). However, this basic approach is almost ubiquitous in studies of timing perception, as is the tendency to assign meaning to the fitted parameters without fully discussing the assumptions underlying the continuous function fits, and the limitations that these place on interpretation. Indeed, we speculate that researchers might sometimes forget that by fitting a function and extracting one or more parameters, they are implicitly countenancing a model of the underlying
The hip motor connects with a gt2 timing belt system. The 16 teeth pulley at the motor side has a diameter of 14mm, and the backlash on this type of timing belt is 0.013mm giving a backlash angle of 0.053 0 , this backlash multiplied over the length of the arm results in an imprecision of 0.37mm. The purpose of this arm is writing, thus the end effector with a pen should only touch the piece of paper, not pres it, resulting in the motors constantly having to work against gravity in holding the arms up and backlash not occurring during operation. There is however backlash present when force is applied to the endeffector. According to the manufactured, this backlash of the gearbox is <1 0 , resulting in <3.49mm imprecision perpendicular to each arm.
A perfect SOM analysis creates such apparent outcomes that envisioned maps could be dependably deciphered simply by taking a look at them, even though extra apportioning that utilizes SOM as a halfway step is often prescribed to ob- tain more precise outcomes  . In this study, popular visualizations of SOMs, such as U-matrix, component plans, assignment of rain gauges to neu- rons and the distribution of index properties represented by bar charts, are used. Furthermore, the study uses hierarchical clustering, an unverified method, for clustering the SOM . The approach begins with single data points as indi- vidual clusters, and at each progression, each cluster consolidates with the near- est pair of clusters until one cluster remains. Hence, the approach is also known as the agglomerative approach and calls for the definition of cluster proximity. In this investigation, cluster proximity is characterized by the average pairwise proximity among all sets of points in various groups and is represented by the average group distance. The outcome is called a dendrogram which is a tree-like diagram. A dendrogram shows both the cluster and sub-cluster relationships and the order in which the clusters were consolidated. The closeness of the clus- ters can be depicted by lengths of the limbs, and the data items can be clustered by cutting the dendrogram.
Timing Is Everything Luis M Schanga aBaker Institute for Animal Health, Cornell University, Ithaca, New York, USA ABSTRACT N Drayman et al in their recent article (mBio 8 e01612 17, 2017, https // doi[.]