Fast, non-monte-carlo estimation of transient performance variation due to device mismatch

This paper describes an efficient way of simulating the effects of device random mismatch on circuit transient characteristics, such as variations in delay or in frequency. The proposed method models DC random offsets as equivalent AC pseudo-noises and leverages the fast, linear periodically time-varying (LPTV) noise analysis available from RF circuit simulators. Therefore, the method can be considered as an extension to DC match analysis and offers a large speed-up compared to the traditional Monte-Carlo analysis. Although the assumed linear perturbation model is valid only for small variations, it enables easy ways to estimate correlations among variations and identify the most sensitive design parameters to mismatch, all at no additional simulation cost. Three benchmarks measuring the variations in the input offset voltage of a clocked comparator, the delay of a logic path, and the frequency of an oscillator demonstrate the speed improvement of about 100-1000x compared to a 1000-point Monte-Carlo method

Online optimal flux-weakening control of permanent-magnet brushless AC drives

An enhanced online optimal control strategy, which maximizes the flux-weakening performance of a brushless AC motor, is described, and applied to motors having different rotor topologies: interior (radial or circumferential), inset, and surface-mounted magnet. It enables the maximum inherent power capability of a brushless AC motor to be achieved independent of any variation in its parameters, and facilitates maximum efficiency over the entire speed range. It also results in good transient dynamic performance, since it is coupled with feedforward vector control based on optimal current profiles

Evolutionary design of a full-envelope full-authority flight control system for an unstable high-performance aircraft

The use of an evolutionary algorithm in the framework of H1 control theory is being considered as a means for synthesizing controller gains that minimize a weighted combination of the infinite norm of the sensitivity function (for disturbance attenuation requirements) and complementary sensitivity function (for robust stability requirements) at the same time. The case study deals with a complete full-authority longitudinal control system for an unstable high-performance jet aircraft featuring (i) a stability and control augmentation system and (ii) autopilot functions (speed and altitude hold). Constraints on closed-loop response are enforced, that representing typical requirements on airplane handling qualities, that makes the control law synthesis process more demanding. Gain scheduling is required, in order to obtain satisfactory performance over the whole flight envelope, so that the synthesis is performed at different reference trim conditions, for several values of the dynamic pressure, used as the scheduling parameter. Nonetheless, the dynamic behaviour of the aircraft may exhibit significant variations when flying at different altitudes, even for the same value of the dynamic pressure, so that a trade-off is required between different feasible controllers synthesized at different altitudes for a given equivalent airspeed. A multiobjective search is thus considered for the determination of the best suited solution to be introduced in the scheduling of the control law. The obtained results are then tested on a longitudinal non-linear model of the aircraft

TimeTrader: Exploiting Latency Tail to Save Datacenter Energy for On-line Data-Intensive Applications

Datacenters running on-line, data-intensive applications (OLDIs) consume significant amounts of energy. However, reducing their energy is challenging due to their tight response time requirements. A key aspect of OLDIs is that each user query goes to all or many of the nodes in the cluster, so that the overall time budget is dictated by the tail of the replies' latency distribution; replies see latency variations both in the network and compute. Previous work proposes to achieve load-proportional energy by slowing down the computation at lower datacenter loads based directly on response times (i.e., at lower loads, the proposal exploits the average slack in the time budget provisioned for the peak load). In contrast, we propose TimeTrader to reduce energy by exploiting the latency slack in the sub- critical replies which arrive before the deadline (e.g., 80% of replies are 3-4x faster than the tail). This slack is present at all loads and subsumes the previous work's load-related slack. While the previous work shifts the leaves' response time distribution to consume the slack at lower loads, TimeTrader reshapes the distribution at all loads by slowing down individual sub-critical nodes without increasing missed deadlines. TimeTrader exploits slack in both the network and compute budgets. Further, TimeTrader leverages Earliest Deadline First scheduling to largely decouple critical requests from the queuing delays of sub- critical requests which can then be slowed down without hurting critical requests. A combination of real-system measurements and at-scale simulations shows that without adding to missed deadlines, TimeTrader saves 15-19% and 41-49% energy at 90% and 30% loading, respectively, in a datacenter with 512 nodes, whereas previous work saves 0% and 31-37%.Comment: 13 page

Enhanced information retrieval using domain-specific recommender models

The objective of an information retrieval (IR) system is to retrieve relevant items which meet a user information need. There is currently significant interest in personalized IR which seeks to improve IR effectiveness by incorporating a model of the user’s interests. However, in some situations there may be no opportunity to learn about the interests of a specific user on a certain topic. In our work, we propose an IR approach which combines a recommender algorithm with IR methods to improve retrieval for domains where the system has no opportunity to learn prior information about the user’s knowledge of a domain for which they have not previously entered a query. We use search data from other previous users interested in the same topic to build a recommender model for this topic. When a user enters a query on a topic, new to this user, an appropriate recommender model is selected and used to predict a ranking which the user may find interesting based on the behaviour of previous users with similar queries. The recommender output is integrated with a standard IR method in a weighted linear combination to provide a final result for the user. Experiments using the INEX 2009 data collection with a simulated recommender training set show that our approach can improve on a baseline IR system

Investigation of Air Transportation Technology at Princeton University, 1989-1990

The Air Transportation Technology Program at Princeton University proceeded along six avenues during the past year: microburst hazards to aircraft; machine-intelligent, fault tolerant flight control; computer aided heuristics for piloted flight; stochastic robustness for flight control systems; neural networks for flight control; and computer aided control system design. These topics are briefly discussed, and an annotated bibliography of publications that appeared between January 1989 and June 1990 is given

Questionnaire surveys to discover academic staff and library staff perceptions of a National Union catalogue

During the feasibility study into a National Union catalogue for the UK (UKNUC), a questionnaire survey was undertaken of the needs of both academic staff in higher education and library staff. A response rate of 40-50 per cent was achieved, 846 questionnaires being returned for academics and 724 for librarians. The analysis suggests that a UKNUC would be highly valued and heavily used by all categories. Academics felt it would have a positive effect on their information searching, and wished to include the holdings of the British Library, and libraries of both the major research universities and the ``traditional’’ universities. They wanted it to be comprehensive and easy to use, to include locations of both books and journals, and to facilitate subject collection searching. Library staff have similar priorities to academics, although there are more variations by sector and a recognition of a UKNUC’s value as a potential source of bibliographic records

Z39.50 broadcast searching and Z-server response times: perspectives from CC-interop

This paper begins by briefly outlining the evolution of Z39.50 and the current trends, including the work of the JISC CC-interop project. The research crux of the paper focuses on an investigation conducted with respect to testing Z39.50 server (Z-server) response times in a broadcast (parallel) searching environment. Customised software was configured to broadcast a search to all test Z-servers once an hour, for eleven weeks. The results were logged for analysis. Most Z-servers responded rapidly. 'Network congestion' and local OPAC usage were not found to significantly influence Z-server performance. Response time issues encountered by implementers may be the result of non-response by the Z-server and how Z-client software deals with this. The influence of 'quick and dirty' Z39.50 implementations is also identified as a potential cause of slow broadcast searching. The paper indicates various areas for further research, including setting shorter time-outs and greater end-user behavioural research to ascertain user requirements in this area. The influence more complex searches, such as Boolean, have on response times and suboptimal Z39.50 implementations are also emphasised for further study. This paper informs the LIS research community and has practical implications for those establishing Z39.50 based distributed systems, as well as those in the Web Services community. The paper challenges popular LIS opinion that Z39.50 is inherently sluggish and thus unsuitable for the demands of the modern user