Miracle-dz/UniFAR-FTUs huggingface dataset:
Exposures Exposed: A Measurement and User Study to Assess Mobile Data Privacy in Context

Mobile devices have access to personal, potentially sensitive data, and there is a large number of mobile applications and third-party libraries that transmit this information over the network to remote servers (including app developer servers and third party servers). In this paper, we are interested in better understanding of not just the extent of personally identifiable information (PII) exposure, but also its context i.e., functionality of the app, destination server, encryption used, etc.) and the risk perceived by mobile users today. To that end we take two steps. First, we perform a measurement study: we collect a new dataset via manual and automatic testing and capture the exposure of 16 PII types from 400 most popular Android apps. We analyze these exposures and provide insights into the extent and patterns of mobile apps sharing PII, which can be later used for prediction and prevention. Second, we perform a user study with 220 participants on Amazon Mechanical Turk: we summarize the results of the measurement study in categories, present them in a realistic context, and assess users' understanding, concern, and willingness to take action. To the best of our knowledge, our user study is the first to collect and analyze user input in such fine granularity and on actual (not just potential or permitted) privacy exposures on mobile devices. Although many users did not initially understand the full implications of their PII being exposed, after being better informed through the study, they became appreciative and interested in better privacy practices.
Minimum discrepancy principle strategy for choosing k in k-NN regression

This paper presents a novel data-driven strategy to choose the hyperparameter $k$ in the $k$-NN regression estimator. We treat the problem of choosing the hyperparameter as an iterative procedure (over $k$) and propose using an easily implemented in practice strategy based on the idea of early stopping and the minimum discrepancy principle. This estimation strategy is proven to be minimax optimal, under the fixed-design assumption on covariates, over different smoothness function classes, for instance, the Lipschitz functions class on a bounded domain. After that, the novel strategy shows consistent simulations results on artificial and real-world data sets in comparison to other model selection strategies such as the Hold-out method.
Grasping Detection Network with Uncertainty Estimation for Confidence-Driven Semi-Supervised Domain Adaptation

Data-efficient domain adaptation with only a few labelled data is desired for many robotic applications, e.g., in grasping detection, the inference skill learned from a grasping dataset is not universal enough to directly apply on various other daily/industrial applications. This paper presents an approach enabling the easy domain adaptation through a novel grasping detection network with confidence-driven semi-supervised learning, where these two components deeply interact with each other. The proposed grasping detection network specially provides a prediction uncertainty estimation mechanism by leveraging on Feature Pyramid Network (FPN), and the mean-teacher semi-supervised learning utilizes such uncertainty information to emphasizing the consistency loss only for those unlabelled data with high confidence, which we referred it as the confidence-driven mean teacher. This approach largely prevents the student model to learn the incorrect/harmful information from the consistency loss, which speeds up the learning progress and improves the model accuracy. Our results show that the proposed network can achieve high success rate on the Cornell grasping dataset, and for domain adaptation with very limited data, the confidence- driven mean teacher outperforms the original mean teacher and direct training by more than 10% in evaluation loss especially for avoiding the overfitting and model diverging.
The WaZP galaxy cluster sample of the dark energy survey year 1

We present a new (2+1)D galaxy cluster finder based on photometric redshifts called Wavelet Z Photometric (WaZP) applied to DES first year (Y1A1) data. The results are compared to clusters detected by the South Pole Telescope (SPT) survey and the redMaPPer cluster finder, the latter based on the same photometric data. WaZP searches for clusters in wavelet-based density maps of galaxies selected in photometric redshift space without any assumption on the cluster galaxy populations. The comparison to other cluster samples was performed with a matching algorithm based on angular proximity and redshift difference of the clusters. It led to the development of a new approach to match two optical cluster samples, following an iterative approach to minimize incorrect associations. The WaZP cluster finder applied to DES Y1A1 galaxy survey (1511.13 deg2 up to mi = 23 mag) led to the detection of 60 547 galaxy clusters with redshifts 0.05 < z < 0.9 and richness Ngals ≥ 5. Considering the overlapping regions and redshift ranges between the DES Y1A1 and SPT cluster surveys, all sz based SPT clusters are recovered by the WaZP sample. The comparison between WaZP and redMaPPer cluster samples showed an excellent overall agreement for clusters with richness Ngals (λ for redMaPPer) greater than 25 (20), with 95 per cent recovery on both directions. Based on the cluster cross-match, we explore the relative fragmentation of the two cluster samples and investigate the possible signatures of unmatched clusters.
Inference for Moment Inequalities: A Constrained Moment Selection Procedure

Inference in models where the parameter is defined by moment inequalities is of interest in many areas of economics. This paper develops a new method for improving the performance of generalized moment selection (GMS) testing procedures in finite-samples. The method modifies GMS tests by tilting the empirical distribution in its moment selection step by an amount that maximizes the empirical likelihood subject to the restrictions of the null hypothesis. We characterize sets of population distributions on which a modified GMS test is (i) asymptotically equivalent to its non-modified version to first-order, and (ii) superior to its non-modified version according to local power when the sample size is large enough. An important feature of the proposed modification is that it remains computationally feasible even when the number of moment inequalities is large. We report simulation results that show the modified tests control size well, and have markedly improved local power over their non-modified counterparts.
The Koopman Expectation: An Operator Theoretic Method for Efficient Analysis and Optimization of Uncertain Hybrid Dynamical Systems

For dynamical systems involving decision making, the success of the system greatly depends on its ability to make good decisions with incomplete and uncertain information. By leveraging the Koopman operator and its adjoint property, we introduce the Koopman Expectation, an efficient method for computing expectations as propagated through a dynamical system. Unlike other Koopman operator-based approaches in the literature, this is possible without an explicit representation of the Koopman operator. Furthermore, the efficiencies enabled by the Koopman Expectation are leveraged for optimization under uncertainty when expected losses and constraints are considered. We show how the Koopman Expectation is applicable to discrete, continuous, and hybrid non-linear systems driven by process noise with non-Gaussian initial condition and parametric uncertainties. We finish by demonstrating a 1700x acceleration for calculating probabilistic quantities of a hybrid dynamical system over the naive Monte Carlo approach with many orders of magnitudes improvement in accuracy.
Spectrally Selective Solar Absorbers with High-temperature Insensitivity

It is of significance to incorporate spectral selectivity technology into solar thermal engineering, especially at high operational temperatures. This work demonstrates spectrally selective solar absorbers made of multilayer tungsten, silica, and alumina thin films that are angular insensitive and polarization-independent. An overall absorptance of 88.1% at solar irradiance wavelength, a low emittance of 7.0% at infrared thermal wavelength, and a high solar to heat efficiency of 79.9% are identified. Additionally, it shows the annealed samples maintain an extremely high absorption in solar radiation regime over at least 600 C and the solar absorbers after thermal annealing at 800 C still work well in a CSP system with an even high concentration factor of over 100.
Encounters involving planetary systems in birth environments: the significant role of binaries

Most stars form in a clustered environment. Both single and binary stars will sometimes encounter planetary systems in such crowded environments. Encounter rates for binaries may be larger than for single stars, even for binary fractions as low as 10-20 per cent. In this work, we investigate scatterings between a Sun-Jupiter pair and both binary and single stars as in young clusters. We first perform a set of simulations of encounters involving wide ranges of binaries and single stars, finding that wider binaries have larger cross sections for the planet's ejection. Secondly, we consider such scatterings in a realistic population, drawing parameters for the binaries and single stars from the observed population. The scattering outcomes are diverse, including ejection, capture/exchange and collision. The binaries are more effective than single stars by a factor of several or more in causing the planet's ejection and collision. Hence, in a cluster, as long as the binary fraction is larger than about 10 per cent, the binaries will dominate the scatterings in terms of these two outcomes. For an open cluster of a stellar density 50 pc$^{-3}$, a lifetime 100 Myr and a binary fraction 0.5, we estimate that of the order of 1 per cent of the Jupiters are ejected, 0.1 per cent collide with a star, 0.1 per cent change ownership and 10 per cent of the Sun-Jupiter pairs acquire a stellar companion during scatterings. These companions are typically 1000s of au distant and in half of the cases (so 5 per cent of all Sun-Jupiter pairs), they can excite the planet's orbit through Kozai--Lidov mechanism before stripped by later encounters. Our result suggests that the Solar System may have once had a companion in its birth cluster.
LOCUS: A regularized blind source separation method with low-rank structure for investigating brain connectivity

Network-oriented research has been increasingly popular in many scientific areas. In neuroscience research, imaging-based network connectivity measures have become the key for understanding brain organizations, potentially serving as individual neural fingerprints. There are major challenges in analyzing connectivity matrices including the high dimensionality of brain networks, unknown latent sources underlying the observed connectivity, and the large number of brain connections leading to spurious findings. In this paper, we propose a novel blind source separation method with low-rank structure and uniform sparsity (LOCUS) as a fully data-driven decomposition method for network measures. Compared with the existing method that vectorizes connectivity matrices ignoring brain network topology, LOCUS achieves more efficient and accurate source separation for connectivity matrices using low-rank structure. We propose a novel angle-based uniform sparsity regularization that demonstrates better performance than the existing sparsity controls for low-rank tensor methods. We propose a highly efficient iterative Node-Rotation algorithm that exploits the block multi-convexity of the objective function to solve the non-convex optimization problem for learning LOCUS. We illustrate the advantage of LOCUS through extensive simulation studies. Application of LOCUS to Philadelphia Neurodevelopmental Cohort neuroimaging study reveals biologically insightful connectivity traits which are not found using the existing method.
Symbol and Frame Timing Estimation for Multicarrier HF Packet Radio

— High frequency (HF) channel is a difficult medium for data transmission. Multi-carrier transmission over HF channel is used to avoid effects of frequency-selective fading. In this paper, we present algorithms for estimation of symbol and frame timing of particular HF packet-radio signals. In particular, we analyze the proposed data-aided frame timing estimation method.
Extension of the SCEC Broadband Platform to Simulation of Strong Ground Motions from Subduction Earthquakes

This project was motivated by a request from Professor Brendon Bradley, co-leader of the New Zealand QuakeCoRE: Centre for Earthquake Resilience, for the PI’s to participate in a project entitled “Validation of Strong Ground Motion Simulations of two Historical New Zealand Subduction Zone Earthquakes on the SCEC Broadband Strong Ground Motion Simulation Platform. ” To date, the SCEC BBP has only been developed for use in simulating the strong ground motions of shallow crustal earthquakes. Professor Bradley has expressed the desire that the validations be performed within the framework of the SCEC BBP, and suggested that we seek funds from SCEC to perform preparatory work for extending the SCEC BBP capability to subduction earthquakes in readiness for the New Zealand project. That project, which included collaboration with Professor Bradley, has been completed and the report is attached at the end of this report. This project represents a strategic partnership between QuakeCoRE and SCEC that will develop long-lasting mutual benefits for both organizations.
Moldable scenario builder Master Thesis

Current behavior-driven development (BDD) practices promise to engage more stakeholders in an agile software development process through the use of behavior speciﬁcations of the software product. However, current capabilities for behavior speciﬁcation restrict possible feedback as they fail to reliably connect the speciﬁcation with the corresponding implementation. We analyzed 14 BDD tools to observe their limitations for facilitating feedback between multiple stake-holders. We observed that the existing BDD tools differ in characteristics regarding their support for a ubiquitous language and speciﬁcation format. Despite the recent attempts to write more natural language speciﬁcations, the existing tools are largely developer-oriented and limit the engagement of other participants. The analyzed tools focus mostly on asserting input values against desired business output for a BDD scenario and much less on manipulating the output itself. To tackle the aforementioned limitations, we present our prototype solution ‘Moldable scenario editor’ implemented in the Pharo environment. To achieve this, we allow BDD scenarios to return objects and adapt their representation to the perspective of non-technical stakeholders. We strive to engage more participants in the agile software development process by giving them different ways to experiment with behavior speciﬁcations within an IDE. For instance, we use an embedded rich text editor to illustrate how plain textual speciﬁcations can leverage the corresponding implementation. Similarly, with a combination of graphical elements, we allow users to experiment with domain objects i.e. , compose new BDD tests without having to code. We speculate that such an approach can bind behavior speciﬁcations more closely to the implementation, and facilitate effective collaboration among team members.
Starting of Loaded Induction Motors Using Variable-Frequency Drives

Most of the papers dealing with variable frequency drive (VFD) are concerned with speed control rather than the starting period. This paper is mainly concerned with the starting period. The paper presents a proposed control strategy for VFD to enhance the performance of induction motors during the starting period. The main objective of the proposed control scheme is to provide high starting torque while the starting current is maintained within acceptable limits. This is implemented up to the rated speed. Beyond the rated speed, the objective is to target the steady-state operating point following the nominal torque-speed characteristic of the motor. The capabilities of the proposed control scheme in the two regions are examined, and a good performance is confirmed. This scheme is suitable for motors which need high starting torque and have several starting times per day. Index Terms – Induction motor, starting current, starting torque, variable-frequency drive.
Mobile Augmented Reality as a Control Mode for Real-time Music Systems

Mobile augmented reality has only been made possible in the last few years, owing to the increasing processing power, more responsive hardware sensors and improved cameras of modern mobile computers. As a result of this, the mobile app markets have started filling up with augmented reality applications, ranging from games to navigation assistants. Similarly, the increasing power of mobile devices combined with their multitude of interaction inputs has made them extremely suitable for music purposes – real-time synthesis, control and editing – and we are beginning to see more and more music creation apps on the market. However, as of yet there have been no attempts to mix these two ideas – augmented reality and music creation – in neither commercial products nor research. As such, an augmented reality real-time music system has been implemented inspired by the tangible table-top real-time music system, the Reactable with the aim of investigating the effects of an augmented-reality control mode on the enjoyment, intuitiveness of interaction, immersion and ease-of-use of a real-time music system. A series of subjective user tests were conducted and the results show that using an augmented reality control mode over a more traditional top-down screen-centric control mode improves the perceived enjoyment and engagement of the music experience, both of which are essential properties for such systems.
Micro Hole for Trapping Flowing Cell

Micro holes have been designed to trap a biological cell, which flows through a micro channel in vitro. Several micro traps of a half cylindrical hole of 0.002 mm depth (0.02 mm diameter) have been fabricated on the surface of the polydimethylsiloxane (PDMS) disk with the photolithography technique. A rectangular flow channel (0.1 mm depth × 1 mm width × 20 mm length) has been constructed with a silicone film of 0.1 mm thick, which has been sandwiched by two transparent PDMS disks. Two types of biological cells were used in the test alternatively: C2C12 (mouse myoblast cell line originated with cross-striated muscle of C3H mouse), or MC3T3-E1 (mouse osteogenic cell line). A constant flow (2.8 ×10 m/s or 8.3 ×10 m/s) of a suspension of cells was introduced with a syringe pump. The behavior of cells moving over the micro holes was observed with an inverted phase contrast microscope. The results show that the cell is trapped with the micro hole under the wall shear rate less than 100 s for several seconds.
Anticipatory Vehicle Routing for Same-Day Pick-up and Delivery using Historical Data Clustering

In this paper we address the problem of same-day pick-up and delivery where a set of tasks are known a priori and a set of tasks are revealed during operation. The vehicle routes are precomputed based on the known and predicted requests and adjusted online as new requests are revealed. We propose a novel anticipatory insertion method which incorporates a set of predicted requests to beneficially adjust the routes of a fleet of vehicles in real-time. Requests are predicted based on historical data, which is clustered in advance. We exploit inherent patterns of the demand, which are captured by historical data and include them in a dynamic vehicle routing solver based on heuristics and adaptive large neighborhood search. The proposed method is evaluated using numerical simulations on a variety of real-world problems with up to 1655 requests per day. Their degree of dynamism ranges from 0.70 to 0.93. These instances represent dynamic multi-depot pickup and delivery problems with time windows. The method has shown to require less driven kilometers than comparable methods.
The derivatives of oseltamivir design passing through the important cleft of neuraminidase against influenza virus by de novo design

Owing to its unique function to release the progeny virus particles from the surface of an infected cell, neuraminidase has drawn special attention for developing new drugs to treat influenza viruses. The 150-cavity that is adjacent to the active pocket of the group-1 neuraminidase (N1) renders the conformational change from ‘open’ form to ‘closed’ form when enzyme is binding with a ligand. Consequently, it would be a better strategy to design multi-binding-site inhibitors including X and R groups with proper shapes, sizes and electronic charges fitting into the active site. The NCI and ZINC fragment databases were screened for finding the optimal fragments with de novo design technique. By doing so, 24 derivatives of oseltamivir were obtained by linking the fragments at two different sites of the scaffold of oseltamivir. Molecular docking and dynamics showed that these compounds not only adopt more favourable conformation but also have stronger binding interaction with receptor. Most importantly, all compounds skilfully pass through the cleft (formed by Glu119 and Arg156) and fit into 150-cavity. Therefore, the selected 24 derivatives may become promising candidates for treating influenza virus; in addition, the findings reported here may at least provide useful insights and stimulate new strategy in this area.
Days-of- Week Effect on Tehran Stock Exchange Returns: An Empirical Analysis

The purpose of this study is to concentrate on the investigation of days-of-week effect on Tehran Stock Exchange and its comparison with other emerging markets. Using Classical Linear Regression (CLR) as well as Autoregressive Conditional Heteroskedasticity (ARCH) models it in indicated has indicated that there is significantly positive total return on Saturdays and significantly negative total return on Sundays. There is no significant return on the other days of the week. So, one may suggest that it would be reasonable to sell on Saturday and buy it on Sunday. Comparing this result with that of other emerging stock markets, it can be concluded that days- of- week effect on returns of Tehran Stock Exchange is different from other emerging markets.
Effects of coppicing on the growth of oak timber trees in the Bradfield Woods, Suffolk

(1) The growth in diameter of standard oak trees is increased by a measurable, though small, degree, by the temporary removal of their surrounding underwood by coppicing. This effect is demonstrable for at least 9 yr following coppicing. (2) The tree-ring chronology for the Bradfield Woods can be cross-matched with those of several other oak chronologies in the British Isles. The level of agreement is independent of the distance between the sites.