Optimizing fitness-for-use of differentially private linear queries

In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each application. In this paper, we consider the problem of answering linear queries under differential privacy subject to per-query accuracy constraints. Existing practical frameworks like the matrix mechanism do not provide such fine-grained control (they optimize total error, which allows some query answers to be more accurate than necessary, at the expense of other queries that become no longer useful). Thus, we design a fitness-for-use strategy that adds privacy-preserving Gaussian noise to query answers. The covariance structure of the noise is optimized to meet the fine-grained accuracy requirements while minimizing the cost to privacy.

Rapid design of aircraft fuel quantity indication systems via multi-objective evolutionary algorithms

The design of electrical, mechanical and fluid systems on aircraft is becoming increasingly integrated with the aircraft structure definition process. An example is the aircraft fuel quantity indication (FQI) system, of which the design is strongly dependent on the tank geometry definition. Flexible FQI design methods are therefore desirable to swiftly assess system-level impact due to aircraft level changes. For this purpose, a genetic algorithm with a two-stage fitness assignment and FQI specific crossover procedure is proposed (FQI-GA). It can handle multiple measurement accuracy constraints, is coupled to a parametric definition of the wing tank geometry and is tested with two performance objectives. A range of crossover procedures of comparable node placement problems were tested for FQI-GA. Results show that the combinatorial nature of the probe architecture and accuracy constraints require a probe set selection mechanism before any crossover process. A case study, using approximated Airbus A320 requirements and tank geometry, is conducted and shows good agreement with the probe position results obtained with the FQI-GA. For the objectives of accessibility and probe mass, the Pareto front is linear, with little variation in mass. The case study confirms that the FQI-GA method can incorporate complex requirements and that designers can employ it to swiftly investigate FQI probe layouts and trade-offs.

Robust Data Programming with Precision-guided Labeling Functions

Scarcity of labeled data is a bottleneck for supervised learning models. A paradigm that has evolved for dealing with this problem is data programming. An existing data programming paradigm allows human supervision to be provided as a set of discrete labeling functions (LF) that output possibly noisy labels to input instances and a generative model for consolidating the weak labels. We enhance and generalize this paradigm by supporting functions that output a continuous score (instead of a hard label) that noisily correlates with labels. We show across five applications that continuous LFs are more natural to program and lead to improved recall. We also show that accuracy of existing generative models is unstable with respect to initialization, training epochs, and learning rates. We give control to the data programmer to guide the training process by providing intuitive quality guides with each LF. We propose an elegant method of incorporating these guides into the generative model. Our overall method, called CAGE, makes the data programming paradigm more reliable than other tricks based on initialization, sign-penalties, or soft-accuracy constraints.

Trajectory Planning Algorithm of UAV Based on System Positioning Accuracy Constraints

This paper describes a novel trajectory planning algorithm for an unmanned aerial vehicle (UAV) under the constraints of system positioning accuracy. Due to the limitation of the system structure, a UAV cannot accurately locate itself. Once the positioning error accumulates to a certain degree, the mission may fail. This method focuses on correcting the error during the flight process of a UAV. The improved genetic algorithm (GA) and A* algorithm are used in trajectory planning to ensure the UAV has the shortest trajectory length from the starting point to the ending point under multiple constraints and the least number of error corrections.

Special aspects of modulation RCS measurement in Ka-band

Radar reflectors are used as standards for radioelectronic devices calibration, as navigation beacons for air and naval traffic control and for radar visibility increase. Controlled (parametric) reflectors change reflected signal characteristics. This leads to appearance of easily detectable additional frequency components on modulation frequency. Ka-band parametric reflector design, consisting of horn reflector and phase switch 0°/180° board, is suggested. Technique of parametric reflector modulation RCS measurement, using complex envelope of reflected signal in every phase switch state, is suggested. Measuring bench description is given. Comparative analysis of theoretical calculations and experimental results is carried out. Accuracy of modulation RCS measurement according to the said technique is obtained experimentally. Measurements accuracy constraints are detected.

Accounting for programmed ribosomal frameshifting in the computation of codon

Experimental evidence shows that synonymous mutations can have important consequences on genetic fitness. Many organisms display codon usage bias (CUB), where synonymous codons that are translated into the same amino acid appear with distinct frequency. CUB is thought to arise from selection for translational efficiency and accuracy, termed the translational efficiency hypothesis (TEH). Indeed, CUB indices correlate with protein expression levels, which is widely interpreted as evidence for translational selection. However, these tests neglect −1 programmed ribosomal frameshifting (−1 PRF), an important translational disruption effect found across all organisms of the tree of life. Genes that contain −1 PRF signals should cost more to express than genes without. Thus, CUB indices that do not consider −1 PRF may overestimate genes’ true adaptation to translational efficiency and accuracy constraints. Here, we first investigate whether −1 PRF signals do indeed carry such translational cost. We then propose two corrections for CUB indices for genes containing −1 PRF signals. We retest the TEH under these corrections. We find that the correlation between corrected CUB index and protein expression remains intact for most levels of uniform −1 PRF efficiencies, and tends to increase when these efficiencies decline with protein expression. We conclude that the TEH is strengthened and that −1 PRF events constitute a promising and useful tool to examine the relationships between CUB and selection for translation efficiency and accuracy.