Quantitative and Approximate Monitoring

In runtime verification, a monitor watches a trace of a system and, if possible, decides after observing each finite prefix whether or not the unknown infinite trace satisfies a given specification. We generalize the theory of runtime verification to monitors that attempt to estimate numerical values of quantitative trace properties (instead of attempting to conclude boolean values of trace specifications), such as maximal or average response time along a trace. Quantitative monitors are approximate: with every finite prefix, they can improve their estimate of the infinite trace's unknown property value. Consequently, quantitative monitors can be compared with regard to a precision-cost trade-off: better approximations of the property value require more monitor resources, such as states (in the case of finite-state monitors) or registers, and additional resources yield better approximations. We introduce a formal framework for quantitative and approximate monitoring, show how it conservatively generalizes the classical boolean setting for monitoring, and give several precision-cost trade-offs for monitors. For example, we prove that there are quantitative properties for which every additional register improves monitoring precision.Comment: To appear in LICS 2021; corrected a referenc

UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning

Training deep neural networks often forces users to work in a distributed or outsourced setting, accompanied with privacy concerns. Split learning aims to address this concern by distributing the model among a client and a server. The scheme supposedly provides privacy, since the server cannot see the clients' models and inputs. We show that this is not true via two novel attacks. (1) We show that an honest-but-curious split learning server, equipped only with the knowledge of the client neural network architecture, can recover the input samples and obtain a functionally similar model to the client model, without being detected. (2) We show that if the client keeps hidden only the output layer of the model to "protect" the private labels, the honest-but-curious server can infer the labels with perfect accuracy. We test our attacks using various benchmark datasets and against proposed privacy-enhancing extensions to split learning. Our results show that plaintext split learning can pose serious risks, ranging from data (input) privacy to intellectual property (model parameters), and provide no more than a false sense of security.Comment: Proceedings of the 21st Workshop on Privacy in the Electronic Society (WPES '22), November 7, 2022, Los Angeles, CA, US

Organoleptic Differences of Biscuits Made From Yellow Pumpkin Flour as a Substitution of Wheat Flour

Introduction: Wheat flour is made from wheat which is a sub-tropical plant that can be grown easily in tropical environment like Indonesia. In response to this, efforts need to be made to find substitutes for wheat flour through increasing local food acceptability to reduce import dependence of wheat. This study aimed to analyze and determine the organoleptic differences of biscuits made from yellow pumpkin flour. Methods: This type of research is experimental with a completely random design consisting of 6 treatments, namely P1 (0% yellow pumpkin flour : 100% wheat flour), P2 (10% yellow pumpkin flour : 90% wheat flour), P3 (20% yellow pumpkin flour : 80% wheat flour), P4 (30% yellow pumpkin flour : 70% wheat flour), P5 (40% yellow pumpkin flour : 60% wheat flour) and P6 (50% yellow pumpkin flour : 50% wheat flour). Data were analyzed using the Kruskal Wallis test with a significance level of 1% and Mann Whitney test. Results: The results showed that the organoleptic value of biscuits with the highest acceptability from the color aspect was at P2 (3,72), aromatic smell at P2 (3,68), taste at P1 (3,76), and texture at P1 (3,52). Conclusion: This study may conclude the potential use of yellow pumpkin flour mixture when preparing wheat-base biscuits. Therefore, import dependency of wheat can be reduced

Grover Search for Portfolio Selection

We present explicit oracles designed to be used in Grover's algorithm to match investor preferences. Specifically, the oracles select portfolios with returns and standard deviations exceeding and falling below certain thresholds, respectively. One potential use case for the oracles is selecting portfolios with the best Sharpe ratios. We have implemented these algorithms using quantum simulators

On surface wave fields arising in soil-structure interaction problems

Abstract The paper aims at generalization of the specialized formulation, originally developed for the surface wave fields induced by prescribed surface stresses. We extend this formulation to soil-structure interaction problems with unknown contact stresses and internal sources. The problem for an internal source embedded in an elastic half-plane is reduced to that for prescribed surface stresses by considering the point source solution for an unbounded medium. In this case the sub-problems corresponding to normal and tangential stresses assume a separate treatment. Then, we analyze interaction of an elastic half-plane with a one degree of freedom mass-spring system. The focus is on a near-resonant regime investigated by a perturbation technique

Safety and Liveness of Quantitative Automata

The safety-liveness dichotomy is a fundamental concept in formal languages which plays a key role in verification. Recently, this dichotomy has been lifted to quantitative properties, which are arbitrary functions from infinite words to partially-ordered domains. We look into harnessing the dichotomy for the specific classes of quantitative properties expressed by quantitative automata. These automata contain finitely many states and rational-valued transition weights, and their common value functions Inf, Sup, LimInf, LimSup, LimInfAvg, LimSupAvg, and DSum map infinite words into the totally-ordered domain of real numbers. In this automata-theoretic setting, we establish a connection between quantitative safety and topological continuity and provide an alternative characterization of quantitative safety and liveness in terms of their boolean counterparts. For all common value functions, we show how the safety closure of a quantitative automaton can be constructed in PTime, and we provide PSpace-complete checks of whether a given quantitative automaton is safe or live, with the exception of LimInfAvg and LimSupAvg automata, for which the safety check is in ExpSpace. Moreover, for deterministic Sup, LimInf, and LimSup automata, we give PTime decompositions into safe and live automata. These decompositions enable the separation of techniques for safety and liveness verification for quantitative specifications.Comment: Full version of the paper to appear in CONCUR 202

Multi-wavelength temporal and spectral analysis of Blazar S5 1803+78

Blazars are a class of AGN, one of their jets is pointed towards the earth. Here, we report about the multi-wavelength study for blazar S5 1803+78 between MJD 58727 to MJD 59419. We analysed $\gamma$-ray data collected by Fermi-LAT, X-ray data collected by Swift-XRT \& NuSTAR, optical photons detected by Swift-UVOT \& TUBITAK observatory in Turkey. Three flaring states are identified by analysing the $\gamma$-ray light curve. A day scale variability is observed throughout the flares with the similar rise and decay times suggesting a compact emission region located close to the central engine. Cross-correlation studies are carried out between $\gamma$-ray, radio, and X-ray bands, and no significant correlation is detected. The $\gamma$-ray and optical emission are significantly correlated with zero time lag suggesting a co-spatial origin of them. A significant positive correlation between the R-I index and the V magnitude is observed. The broadband spectral energy distributions (SEDs) modeling was performed for all the flaring episodes as well as for one quiescent state for comparison. SEDs are best fitted with the synchrotron-self Compton (SSC) model under a one-zone leptonic scenario. The SED modeling shows that to explain the high flaring state strong Doppler boosting is required.Comment: 13 pages, 14 figures, 4 tables, Accepted in MNRA

Skin cancer risk and shade: comparing the risk of foresters with other outdoor workers

Background: Keratinocyte carcinoma (KC) is an increasingly important public health problem with an especially high prevalence in outdoor workers. In contrast to other occupations, foresters spend most of their outdoor time under the shade of trees. Objectives: We aimed to compare the unique sun exposure patterns and sun protection behaviour of foresters with those of other outdoor workers and their relation to the KC risk. Methods: In July 2018, a cross‐sectional study was conducted at an international forestry fair using a questionnaire about health awareness and skin cancer screening by dermatologists to assess the prevalence of KC. Results: A total of 591 participants (78.7% male; mean age 46.8 ± 16.2 years) including 193 foresters were enrolled. Of all foresters, 72% experienced sunburns (solar erythema) within the past year and 50% of them experienced the worst sunburn during work. Foresters were most likely to often/always wear protective clothes (29.0%) but were least likely to often/always avoid midday sun (23.8%) and stay in the shade (31.1%). Having an outdoor profession or spending hours outside for leisure was negatively associated with sun protection. Skin examination revealed an overall KC prevalence of 16.7%, with 16.5% of foresters being affected. Conclusion: Despite being protected by trees, the risk of KC for foresters is comparable to that of other professional groups. Shade alone may not provide sufficient protection. Additional sun protection measures are necessary