Miracle-dz/UniFAR-FTUs huggingface dataset:
Categorical Inference Poisoning: Verifiable Defense Against Black-Box DNN Model Stealing Without Constraining Surrogate Data and Query Times

Deep Neural Network (DNN) models have offered powerful solutions for a wide range of tasks, but the cost to develop such models is nontrivial, which calls for effective model protection. Although black-box distribution can mitigate some threats, model functionality can still be stolen via black-box surrogate attacks. Recent studies have shown that surrogate attacks can be launched in several ways, while the existing defense methods commonly assume attackers with insufficient in-distribution (ID) data and restricted attacking strategies. In this paper, we relax these constraints and assume a practical threat model in which the adversary not only has sufficient ID data and query times but also can adjust the surrogate training data labeled by the victim model. Then, we propose a two-step categorical inference poisoning (CIP) framework, featuring both poisoning for performance degradation (PPD) and poisoning for backdooring (PBD). In the first poisoning step, incoming queries are classified into ID and (out-of-distribution) OOD ones using an energy score (ES) based OOD detector, and the latter are further classified into high ES and low ES ones, which are subsequently passed to a strong and a weak PPD process, respectively. In the second poisoning step, difficult ID queries are detected by a proposed reliability score (RS) measurement and are passed to PBD. In doing so, the first step OOD poisoning leads to substantial performance degradation in surrogate models, the second step ID poisoning further embeds backdoors in them, while both can preserve model fidelity. Extensive experiments confirm that CIP can not only achieve promising performance against state-of-the-art black-box surrogate attacks like KnockoffNets and data-free model extraction (DFME) but also work well against stronger attacks with sufficient ID and deceptive data, better than the existing dynamic adversarial watermarking (DAWN) and deceptive perturbation defense methods. PyTorch code is available at https://github.com/Hatins/CIP_master. git.
Cavitation in a Two-Dimensional Nozzle and Liquid Jet Atomization : LDV Measurement of Liquid Velocity in a Nozzle

Cavitation in nozzles of liquid injectors is known to affect the atomization of a discharged liquid jet. To understand how cavitating flow in a nozzle enhances the liquid jet atomization, liquid velocity distribution of cavitating flow in a two-dimensional transparent nozzle was measured using a Laser Doppler Velocimetry (LDV) system. As a result, the following conclusions were obtained: (1) The inception of cavitation occurs near the outer edge of separated boundary layer (SBL), where the time-averaged local velocity takes the highest value and the time-averaged pressure is almost equal to the vapor saturation pressure. (2) When the cavitation number σ is greater than 0.78 (in no cavitation and developing cavitation regimes), the reattachment of SBL occurs in the middle of the nozzle. A large velocity fluctuation, which appears just downstream of SBL, decreases near the nozzle exit. Hence the wavy jet is formed in these regimes. (3) For σ < 0.65 (in super cavitation regime), the lateral flow directing from the core region toward the side walls just upstream of the nozzle exit is a major cause of the increase in the spray angle and drastic enhancement of liquid jet atomization. The strong turbulence just upstream of the exit must play an important role in the formation of ligaments on liquid jet interface.
Testing for interaction in an I×J×K contingency table

S-UMMARY Zelen (1971) proposed an asymptotic test for zero three-way interaction in the 2 x 2 x K table. This paper presents two examples for the 2 x 2 x 2 case where Zelen's test directly contradicts the data. We further show that the correct asymptotic representation of Zelen's exact sampling distribution does, in fact, differ from his result. His test statistic will reject the null hypothesis with probability one asymptotically even under the null hypothesis, except i special instances. The test statistic arising naturally from the asymptotic distribution is the classical goodness-of-fit test obtained by Bartlett (1935) and Norton (1945) and given by Plackett (1974). This result extends to the generalizations of Zelen's result to I x J x K tables
N-tuple texture recognition and the zero crossing sketch

The authors present a novel approach to real-time texture classification, derived from the n-tuple method of Bledsoe and Browning. Methods for texture classification based on approximations to the nth order co-occurrence spectrum are discussed. Limitations of these methods are highlighted, and a new method based around Marr's zero crossing sketch is presented. Preliminary results are presented comparing the new method and other n-tuple based schemes.
Low pressure organic vapor phase deposition of small molecular weight organic light emitting device structures

A new technique for the deposition of amorphous organic thin films, low pressure organic vapor phase deposition (LP-OVPD), was used to fabricate organic light emitting devices (OLEDs) consisting of a film of aluminum tris-(8 hydroxyquinoline) (Alq3) grown on the surface of a film of N′-diphenyl-N,N′-bis(3-methylphenyl)1-1′biphenyl-4-4′diamine. The resulting heterojunction OLED was found to have a performance similar to conventional, small molecular weight OLEDs grown using thermal evaporation in vacuum. The LP-OVPD grown device has an external quantum efficiency of 0.40±0.05% and a turn-on voltage of approximately 6 V. The rapid throughput demonstrated with LP-OVPD has the potential to facilitate low cost mass production of conventional small molecule based OLEDs, and its use of low vacuum in a horizontal reactor lends itself to roll-to-roll deposition of organic films for many photonic device applications.
Midplane Faraday rotation: A densitometer for large tokamaks

The density in a large tokamak such as International Thermonuclear Experimental Reactor (ITER), or any of the proposed future US machines, can be determined by measuring the Faraday rotation of a 10.6 μm laser directed tangent to the toroidal field. If there is a horizontal array of such beams, then ne(R) can be readily obtained with a simple Abel inversion about the center line of the tokamak. For a large machine, operated at a full field of 30 T m and a density of 2×1020/m3, the rotation angle would be quite large−about 60° for two passes. A layout in which a single laser beam is fanned out in the horizontal midplane of the tokamak, with a set of retroreflectors on the far side of the vacuum vessel, would provide good spatial resolution, depending only upon the number of reflectors. With this proposed layout, only one window would be needed. Because the rotation angle is never more than 1 ‘‘fringe,’’ the data is always good, and it is also a continuous measurement in time. Faraday rotation is dependent .
Tire‐Road Interaction Noise

The relative importance of tire noise to overall vehicle noise is established. A general discussion is given of the considerations of the tire engineering process and design procedure followed in the manufacture of a tire. The important parameters influencing tire noise are discussed based on the physical data base as it exists today and unknown and contradictory areas are identified. The basic mechanisms of tire‐noise generation, although not well defined, are investigated from a theoretical viewpoint. Areas for future research and development are identified based on gaps in the existing physical data base.
Transposon mutagenesis and genome sequencing identify two novel, tandem genes involved in the colony spreading of Flavobacterium collinsii, isolated from an ayu fish, Plecoglossus altivelis

Bacteria of the family Flavobacteriaceae (flavobacteria) primarily comprise nonpathogenic bacteria that inhabit soil and water (both marine and freshwater). However, some bacterial species in the family, including Flavobacterium psychrophilum and Flavobacterium columnare, are known to be pathogenic to fish. Flavobacteria, including the abovementioned pathogenic bacteria, belong to the phylum Bacteroidota and possess two phylum-specific features, gliding motility and a protein secretion system, which are energized by a common motor complex. Herein, we focused on Flavobacterium collinsii (GiFuPREF103) isolated from a diseased fish (Plecoglossus altivelis). Genomic analysis of F. collinsii GiFuPREF103 revealed the presence of a type IX secretion system and additional genes associated with gliding motility and spreading. Using transposon mutagenesis, we isolated two mutants with altered colony morphology and colony spreading ability; these mutants had transposon insertions in pep25 and lbp26. The glycosylation material profiles revealed that these mutants lacked the high-molecular-weight glycosylated materials present in the wild-type strain. In addition, the wild-type strains exhibited fast cell population movement at the edge of the spreading colony, whereas reduced cell population behavior was observed in the pep25- and lbp26-mutant strains. In the aqueous environment, the surface layers of these mutant strains were more hydrophobic, and they formed biofilms with enhanced microcolony growth compared to those with the wild-type. In Flavobacterium johnsoniae, the Fjoh_0352 and Fjoh_0353 mutant strains were generated, which were based on the ortholog genes of pep25 and lbp26. In these F. johnsoniae mutants, as in F. collinsii GiFuPREF103, colonies with diminished spreading capacity were formed. Furthermore, cell population migration was observed at the edge of the colony in wild-type F. johnsoniae, whereas individual cells, and not cell populations, migrated in these mutant strains. The findings of the present study indicate that pep25 and lbp26 contribute to the colony spreading of F. collinsii.
Gamma-Ray Burst Class Properties

Guided by the supervised pattern recognition algorithm C4.5 developed by Quinlan in 1986, we examine the three gamma-ray burst classes identified by Mukherjee et al. in 1998. C4.5 provides strong statistical support for this classification. However, with C4.5 and our knowledge of the BATSE instrument, we demonstrate that class 3 (intermediate fluence, intermediate duration, soft) does not have to be a distinct source population: statistical/systematic errors in measuring burst attributes combined with the well-known hardness/intensity correlation can cause low peak flux class 1 (high fluence, long, intermediate hardness) bursts to take on class 3 characteristics naturally. Based on our hypothesis that the third class is not a distinct one, we provide rules so that future events can be placed in either class 1 or class 2 (low fluence, short, hard). We find that the two classes are relatively distinct on the basis of Band's work in 1993 on spectral parameters α, β, and Epeak alone. Although this does not indicate a better basis for classification, it does suggest that different physical conditions exist for class 1 and class 2 bursts. In the process of studying burst class characteristics, we identify a new bias affecting burst fluence and duration measurements. Using a simple model of how burst duration can be underestimated, we show how this fluence duration bias can affect BATSE measurements and demonstrate the type of effect it can have on the BATSE fluence versus peak flux diagram.
Research Challenges, Recent Advances, and Popular Datasets in Deep Learning-Based Underwater Marine Object Detection: A Review

Underwater marine object detection, as one of the most fundamental techniques in the community of marine science and engineering, has been shown to exhibit tremendous potential for exploring the oceans in recent years. It has been widely applied in practical applications, such as monitoring of underwater ecosystems, exploration of natural resources, management of commercial fisheries, etc. However, due to complexity of the underwater environment, characteristics of marine objects, and limitations imposed by exploration equipment, detection performance in terms of speed, accuracy, and robustness can be dramatically degraded when conventional approaches are used. Deep learning has been found to have significant impact on a variety of applications, including marine engineering. In this context, we offer a review of deep learning-based underwater marine object detection techniques. Underwater object detection can be performed by different sensors, such as acoustic sonar or optical cameras. In this paper, we focus on vision-based object detection due to several significant advantages. To facilitate a thorough understanding of this subject, we organize research challenges of vision-based underwater object detection into four categories: image quality degradation, small object detection, poor generalization, and real-time detection. We review recent advances in underwater marine object detection and highlight advantages and disadvantages of existing solutions for each challenge. In addition, we provide a detailed critical examination of the most extensively used datasets. In addition, we present comparative studies with previous reviews, notably those approaches that leverage artificial intelligence, as well as future trends related to this hot topic.
Nonlinear processing of a shift-invariant discrete wavelet transform (DWT) for noise reduction

A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal one. Another difference is the shift invariance as opposed to the traditional orthogonal wavelet transform. We show that this new approach can be interpreted as a repeated application of Donoho's original method. The main feature is, however, a dramatically improved noise reduction compared to Donoho's approach, both in terms of the l2 error and visually, for a large class of signals. This is shown by theoretical and experimental results, including synthetic aperture radar (SAR) images.
A Basic-sine and cosine with symbolical solutions of certain differential equations

The object of this paper is to introduce certain functions analogous to the circular functions. The functions will be denoted by Formulae analogous to will be obtained, and the use of the functions in symbolical solutions of certain differential equations exemplified. The connection of the functions with generalised Bessel-functions of order half an odd integer will be shown.
Three-dimensional Computations of Water–Air Flow in a Bottom Spillway During Gate Opening

Abstract Undesired entrainment of air in a bottom spillway often leads to problems in both safety and operational functions. A numerical analysis of a transient process of air entrainment into bottom spillway flows when a spillway gate is opened was conducted in this study. The Volume of Fluid (VOF) model was used. The 3D computational domain consisted of a spillway conduit, a moving bulkhead gate, a gate shaft, an upstream reservoir and a downstream outlet. The large number of cells, together with the dynamic mesh modelling of the moving gate, required substantial computational resources, which necessitated parallel computing on a mainframe computer. The simulations captured the changes in the flow patterns and predicted the amount of air entrainment in the gate shaft and the detrainment downstream, which help in the understanding of the system behaviour during opening of the spillway gate. The initial conduit water level and the gate opening procedure affect the degree of air entrainment in the gate shaft. To release the undesired air, a de-aeration chamber with a tube leading to the atmosphere was added to the conduit. Despite the incomplete air release, the de-aeration chamber was found to be effective in reducing water surface fluctuations in the downstream outlet.
Between interdependence and autonomy: Toward a typology of work design modes in the new world of work

Despite the rapid pace with which the world of work has been transforming, our concept of work design—the content and organization of work tasks, activities, relationships, and responsibilities—has remained remarkably resistant to change. This shortcoming not only limits our theoretical understanding of work design but also constrains organizations' ability to sufficiently adapt to human resource management (HRM) needs in the new world of work. I review the principal categories of work design to theorize about a typology of work design modes and their inherent HRM configurations. The typology proposes four ideal-typical modes—organization-defined work design, self-directed internal work design, formalized external work design
Supporting skill integration in an intelligent tutoring system for code tracing

Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives: The current work presents the development and empirical evaluation of instructional design targeting students' difficulties in code tracing particularly in integrating component skills in the Trace Table Tutor (T3), an intelligent tutoring system. Methods: Beyond the instructional features of active learning, step-level support, and individualized problem selection of intelligent tutoring systems (ITS), the instructional design of T3 (e.g., hints, problem types, problem selection) was optimized to target skill integration based on a domain model where integrative skills were represented as combinations of component skills. We conducted an experimental study in a university-level introductory Python programming course and obtained three findings. Results and Conclusions: First, the instructional features of the ITS technology support effective learning of code tracing, as evidenced by significant learning gains (medium-to-large effect sizes). Second, performance data supports the existence of integrative skills beyond component skills. Third, an instructional design focused on integrative skills yields learning benefits beyond a design without such focus, such as improving performance efficiency (medium-to-large effect sizes). Major Takeaways: Our work demonstrates the value of designing for skill
Bipolar Switching Properties of the Transparent Indium Tin Oxide Thin Film Resistance Random Access Memories

In this study, the bipolar switching properties and electrical conduction behaviors of the ITO thin films RRAM devices were investigated. For the transparent RRAM devices structure, indium tin oxide thin films were deposited by using the RF magnetron sputtering method on the ITO/glass substrate. For the ITO/ITOX/ITO/glass (MIM) structure, an indium tin oxide thin film top electrode was prepared to form the transparent RRAM devices. From the experimental results, the 102 On/Off memory ratio and bipolar switching cycling properties for set/reset stable states were found and discussed. All transparent RRAM devices exhibited the obvious memory window and low set voltage for the switching times of 120 cycles. The electrical transport mechanisms were dominated by the ohmic contact and space charge limit conduction (SCLC) models for set and reset states. Finally, the transmittances properties of the transparent ITO/ITOX/ITO RRAM devices for the different oxygen growth procedures were about 90% according to the UV–Vis spectrophotometer for the visible wavelength range.
A new approach for rapid evaluation of the potential field in three dimensions

Efficient evaluation of the potential field is an essential requirement for simulation of large ensembles of particles in many applications, including astrophysics, plasma physics, molecular dynamics, very large–scale integration systems and micro–electro–mechanical systems. Current methods use multipole expansion of spherical harmonics for the potential field, which is computationally expensive in terms of running time and memory requirements when a high degree of accuracy is desired. In this paper, a new approach is presented for efficient and rapid evaluation of the potential field in three dimensions. The mathematical background for the proposed approach stems from an exponential integral representation of Green's function, 1/r, and an approximation to the integral by using Gauss quadratures, which distinctively differs from the theory of spherical harmonics. The translations are simple in structure, error–free and independent of the approximation, which enables the overall accuracy and computational performance to be controlled externally via the approximation. In addition, the gradient of the potential can be readily retrieved as a by–product of the computational process. More importantly, the memory requirement is independent of the desired degree of accuracy. The technique presented here opens new possibilities for efficient distributed computing and parallel processing of large–scale simulation of particle systems.
Synchronised PWM strategies based on space vector approach. Part 1 : Principles of waveform generation

The authors deal with space-vector-based generation of synchronised three-phase PWM waveforms with three-phase, half-wave and quarter-wave symmetries. The necessary and sufficient conditions for synchronisation and the waveform symmetries are brought out in terms of the inverter states. These conditions are applied to the conventional and modified forms of space vector modulation to generate synchronised PWM waveforms with all the symmetries. Further, the necessary conditions governing the numbers of switchings of the different phases in any given sector to maintain the symmetries are identified. These rules are used to develop two new clamping strategies, namely the asymmetric zero-changing strategy and the boundary sampling strategy, which exploit the flexible features of space vector methods like double-switching of a phase and clamping of two phases in a sampling period. Typical waveforms corresponding to the different strategies are presented along with their theoretical and experimental spectra. The performance assessment of these strategies and their application to drives are dealt with in Part 2.