Reviewerly/exHarmony huggingface dataset:
Multi-actor activity detection by modeling object relationships in extended videos based on deep learning

We present a Multi-actor Activity Detection Framework (MADF) to model the interactive relationship among multiple actors for activity detection in extended videos. MADF can detect 3 groups of multi-actor activities with different kinds of actors, which involves three stages: detection, classification and post-processing. In the detection stage, both interaction proposals and actor proposals are generated in each video clip, in order to eliminate irrelevant background in the scene. In the classification stage, 3 different classification networks are proposed to classify the 3 groups of activities. And further, for person–object interaction, an attention mechanism is adopted to help the person–object classification network to pay more attention to the small-scale objects; for person–person interaction, a suppression module is used to improve the accuracy of the person–person activity detection; for person–vehicle interaction, a spatial–temporal graph convolution network (GCN) module is embedded to model the fine-grained relationship between the person and vehicle in the person–vehicle classification network, with a proposed Mutually Exclusive Category Loss (MECLoss) helping this network distinguish mutually exclusive activities. At last, we use the off-the-shelf post-processing methods to re-score the proposals for more stable results. The proposed system achieves a great progress on our baseline and achieves the state-of-the-art results in TRECVID 2021 ActEV challenge.
AMR Steganalysis based on Adversarial Bi-GRU and Data Distillation

Existing AMR (Adaptive Multi-Rate) steganalysis algorithms based on pitch delay have low detection accuracy on samples with short time or low embedding rate, and the model shows fragility under the attack of adversarial samples. To solve this problem, we design an advanced AMR steganalysis method based on adversarial Bi-GRU (Bi-directional Gated Recurrent Unit) and data distillation. First, Gaussian white noise is randomly added to part of the original speech to form adversarial data set, then artificially annotate a small amount of voice to train the model. Second, perform three transformations of 1.5 times speed, 0.5 times speed, and mirror flip on the remaining original voice data, then put them into Bi-GRU for classification, and the final predicted label obtained by the decision fusion corresponds to the original data. All data with the label is put back into the Bi-GRU model for final training at last. What needs to be pointed out is that each batch of final training data includes normal and adversarial samples. This method adopts a semi-supervised learning method, which greatly saves the resources consumed by manual labeling, and introduces adversarial Bi-GRU, which can realize the two-direction analysis of samples for a long time. Based on improving the detection accuracy, the safety and robustness of the model are greatly improved. The experimental results show that for normal and adversarial samples, the algorithm can achieve accuracy of 96.73% and 95.6% respectively.
Digital Forensics Analysis of Windows 11 Shellbag with Comparative Tools

Operating systems have various components that produce artifacts. These artifacts are the outcome of a user’s interaction with an application or program and the operating system’s logging capabilities. Thus, these artifacts have great importance in digital forensics investigations. For example, these artifacts can be utilized in a court of law to prove the existence of compromising computer system behaviors. One such component of the Microsoft Windows operating system is Shellbag, which is an enticing source of digital evidence of high forensics interest. The presence of a Shellbag entry means a specific user has visited a particular folder and done some customizations such as accessing, sorting, resizing the window, etc. In this work, we forensically analyze Shellbag as we talk about its purpose, types, and specificity with the latest version of the Windows 11 operating system and uncover the registry hives that contain Shellbag customization information. We also conduct in-depth forensics examinations on Shellbag entries using three tools of three different types, i.e., open-source, freeware, and proprietary tools. Lastly, we compared the capabilities of tools utilized in Shellbag forensics investigations.
Research on 3D reconstruction technology based on the fusion of polarization imaging and light field depth information

For objects with smooth surface and single texture, the traditional reconstruction algorithm cannot accurately recover the ideal results. The research shows that the shape features of the measured object can be recovered more accurately by using polarization information in the reconstruction process. However, due to the ambiguity of the azimuth of the surface normal, it is difficult to obtain the accurate depth information directly. Referring to the depth information image provided by the light field camera, this paper designs a depth imaging system mixed by the polarization camera and the light field camera. The depth information obtained by the light field camera is used to guide and eliminate the ambiguity of the normal vector of the polarization surface, so as to achieve higher accuracy in the three-dimensional surface reconstruction of the object. The experiment and analysis show that the relative error between the reconstructed target surface and the real target surface is less than 10%.
Inward FDI, IFRS Adoption and Institutional Quality: Insights from the MENA Countries

The adoption of International Financial Reporting Standards (IFRS) by 166 countries since 2004 has been a major achievement in the international standardization of accounting regulations. The present paper draws on the Eclectic Paradigm as the analytical framework to investigate the effects of IFRS adoption on foreign direct investment (FDI) inflows. The analysis is conducted based on panel data from 22 Middle Eastern and North African economies (MENA) between 1996 and 2019. The findings indicate that FDI inflows are positively associated with IFRS, and countries implementing the accounting standards receive a higher increase in FDI inflows. Furthermore, the results show that institutional quality plays an important role in attracting FDI. These results remain robust using lag and time-fixed effect estimation methods. The findings have several implications for policymakers.
Spherical quantum dots in Deng–Fan–Eckart potential confining potential: Study of nonlinear optical rectification

In this article, the nonlinear optical rectification (NOR) of GaAs/Ga1−xAlxAs quantum dots (QDs) in the presence of the external tuning elements, such as Al-concentration and temperature in the Deng–Fan–Eckart (DFE) potential has been studied. The bound-state solutions of the radial Schrödinger equation can be obtained using the Factorization method. The density matrix theory and iterative method are used to calculate the analytical expression of the NOR coefficient. The obtained results can indicate that these tuning elements and structural parameters, such as Al-concentration, the depth and the strengths of DFE potential can affect the location and peak of formant in this system. Thus, the external tuning elements and structural parameters strongly affect the NOR properties of the GaAs/Ga1−xAlxAs QDs.
Exploring the development of high-level contributions to body representation using the rubber hand illusion and the monkey hand illusion

During development our body undergoes significant changes, yet we are able to maintain a coherent experience of our body and sense of self. Bodily experience is thought to comprise integration of multisensory signals (vision, touch, and proprioception) constrained by top-down knowledge of body appearance. Evidence from developmental studies suggests that low-level multisensory integration develops throughout childhood, reaching adult levels by 10 years of age. However, how high-level cognitive knowledge changes during childhood to constrain our multisensory body experience is unknown. This study describes four experiments examining high-level contributions to the bodily experience in children compared with adults using the rubber hand illusion and a monkey hand illusion. We found that children (5-17 years of age) exhibited more flexible body representations, showing stronger illusions for small and fantastical (monkey) fake hands compared with adults. Conversely, using a task indirectly capturing changes in hand size, we found that children and adults demonstrated statistically equivalent increases and decreases in hand size following illusions over large and small hands, respectively. Interestingly, at baseline children showed a bias in reporting larger hand size judgments that decreased with age. Finally, we did not find a relationship between individual differences in fantasy proneness and illusion strength for a fantastical (monkey) hand for children or adults, suggesting that developmental changes of top-down constraints are not purely driven by more diffuse boundaries between imagination and reality. These data suggest that high-level constraints acting on our multisensory body experience change during development, allowing children a more flexible bodily experience compared with adults.
SoK: All or Nothing - A Postmortem of Solutions to the Third-Party Script Inclusion Permission Model and a Path Forward

The web execution model allows third-party JavaScript to be leveraged in a single execution context. Access control for these scripts is currently all or nothing. It has been this way for over a decade despite the knowledge that this model allows for privacy violations and even user data exfiltration. Consequently, users have little to no control over which third-parties operate on their Personally Identifying Information (PII) when interacting with a web application. In this work we aim to explain the lack of solutions to this problem, and to suggest more promising future directions. We first survey past proposed solutions and their trade-offs. We then create a monitoring system in the Firefox browser which captures third-party script access to user supplied PII in HTML Form Elements. We proceed to inspect 100,000 websites with our Monitor and custom web crawler to highlight the complexity of use cases of third-party scripts operating on user PII. Our findings inform the creation of a grading rubric and systematization for solutions in this space, which we then apply to many previous works. The complexity exposed through this effort allows us to start a discussion around why current technological and policy solutions fail adoption. Ultimately we propose a research direction that allows web applications to take advantage of the interoperability of the web execution model while also respecting an end user's privacy and security.
A Scrutiny of Honeyword Generation Methods: Remarks on Strengths and Weaknesses Points

Abstract Honeyword system is a successful password cracking detection system. Simply the honeywords are (False passwords) that are accompanied to the sugarword (Real password). Honeyword system aims to improve the security of hashed passwords by facilitating the detection of password cracking. The password database will have many honeywords for every user in the system. If the adversary uses a honeyword for login, a silent alert will indicate that the password database might be compromised. All previous studies present a few remarks on honeyword generation methods for max two preceding methods only. So, the need for one that lists all preceding researches with their weaknesses is shown. This work presents all generation methods then lists the strengths and weaknesses of 26 ones. In addition, it puts 32 remarks that highlight their strengths and weaknesses points. This research has proved that every honeyword generation method has many weaknesses points.
Optimization of Cross Diagonal Pixel Value Differencing and Modulus Function Steganography Using Edge Area Block Patterns

Abstract The existence of a trade-off between embedding capacity and imperceptibility is a challenge to improve the quality of steganographic images. This research proposes to cross diagonal embedding Pixel Value Differencing (PVD) and Modulus Function (MF) techniques using edge area patterns to improve embedding capacity and imperceptibility simultaneously. At the same time still, maintain a good quality of security. By implementing them into 14 public datasets, the proposed techniques are proven to increase both capacity and imperceptibility. The cross diagonal embedding PVD is responsible for increasing the embedding capacity reaching an average value of 3.18 bits per pixel (bpp), and at the same time, the implementation of edge area block patterns-based embedding is a solution of improving imperceptibility toward an average value of PSNR above 40 dB and that of SSIM above 0.98. Aside from its success in increasing the embedding capacity and the imperceptibility, the proposed techniques remain resistant to RS attacks.
Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval

This paper considers large-scale efficient vehicle re-identification (Vehicle ReID). Existing works adopting deep hashing techniques function by projecting vehicle images into compact binary codes in the Hamming space. Since Hamming distance is less distinct, a considerable amount of discriminative information will be lost, leading to degraded retrieval performances. Inspired by the recent advancements in contrastive learning, we put forward the very first product quantization based framework for large-scale efficient vehicle re-identification: Supervised Contrastive Vehicle Quantization (SCVQ). Specifically, we integrate the product quantization process into deep supervised learning by designing a differentiable quantization network. In addition, we propose a novel supervised cross-quantized contrastive quantization (SCQC) loss for similarity-preserving learning, which is tailored for the asymmetric retrieval in the product quantization process. Comprehensive experiments on two public benchmarks have evidenced the superiority of our framework against the state-of-the-arts. Our work is open-sourced at https://github.com/chrisbyd/ContrastiveVehicleQuant
Construction of Ternary Bent Functions From Ternary Linear Functions

As in the binary case, ternary bent functions are defined as most non-linear ternary functions meaning that they are at the largest possible Hamming distance from affine ternary functions. It is therefore interesting to observe that some ternary bent functions can be constructed as various combinations of linear ternary functions. By starting from the combination of linear functions corresponding to the basic ternary bent functions the construction of different other ternary bent functions can be performed by the application of different combinations of FFT-like permutation matrices for ternary functions.
Preferences in the Intention to Download a COVID Tracing App: A Discrete Choice Experiment Study in the Netherlands and Turkey

Introduction High levels of adoption and usage for the COVID Tracing Apps (CTA) among the population is a stipulated prerequisite for success of the implementation of these apps, aiming to mitigate the pandemic and track spreading of the virus more efficient and effectively. In the current study, the main objective was to investigate individuals' preferences in the intention to download a COVID-19 tracing app in a pilot-study in both the Netherlands and Turkey. Methods We conducted a discrete choice experimental study through an online survey in two countries (the Netherlands [ N = 62] and Turkey [ N = 83]), with four different attributes: (1) data protection (data protection vs. no information), (2) manufacturer (government vs. company), (3) reward (no reward vs. voucher as a reward) and (4) gaming (no gaming elements vs. gaming elements). Participants were recruited among a student population. Results The results showed that data protection is one of the most important factors that significantly increases the probability to adopt a CTA. In general, the manufacturer, reward or gaming affected the probability to download the CTA less. Discussions Health authorities worldwide have generally released high quality CTA, although scientific studies assessing the most important factors that describe and predict the intention to download is limited. Sensitive personal data is collected through these apps, and may potentially threaten privacy, equality and fairness, which are important attributes to take into account when developing or launching a CTA, following the results of this study.
Scalable and Cost-effective Serverless Architecture for Information Extraction Workflows

Information extraction from an image or scanned document is a complex and challenging process since it involves recognizing various visual structures such as tables, boxes, logos, text, charts, etc. Hence, the content extraction applications contain a pipeline of multiple computer vision algorithms, APIs, and models. Deploying such applications for document processing requires a resilient system to deliver high performance. Such applications can be deployed on cloud to leverage the flexible infrastructure and multiple supporting services available there.
Hybrid shield for microwave single-photon counter based on a flux qubit

A scenario of shielding and stabilization of magnetic and electromagnetic fields in the measuring volume occupied by a superconducting flux qubit is considered. The qubit is used as an artificial macroscopic atom with discrete energy levels in a counter of single photons of the microwave range. It is shown that a decrease in the amplitude of variations of the external magnetic field inside the 3-layer hybrid cylindrical shield, composed of superconducting and ferromagnetic cylinders with the diameter-to-length ratio of 1:5, provides high stability of the magnetic field. The absolute value of the magnetic field at the sample location is determined mainly by the magnetic flux captured by the superconductor shields during their superconducting transition. Although the magnetic field stability is more important than the field itself for the photon counter, the paper also discusses experimental methods for reducing the absolute field value in the hybrid shield.
Trajectory PHD Filter for Adaptive Measurement Noise Covariance Based on Variational Bayesian Approximation

In order to solve the problem that the measurement noise covariance may be unknown or change with time in actual multi-target tracking, this paper brings the variational Bayesian approximation method into the trajectory probability hypothesis density (TPHD) filter and proposes a variational Bayesian TPHD (VB-TPHD) filter to obtain measurement noise covariance adaptively. By modeling the unknown covariance as the random matrix that obeys the inverse gamma distribution, VB-TPHD filter minimizes the Kullback–Leibler divergence (KLD) and estimates the sequence of multi-trajectory states with noise covariance matrices simultaneously. We propose the Gaussian mixture VB-TPHD (AGM-VB-TPHD) filter under adaptive newborn intensity for linear Gaussian models and also give the extended Kalman (AEK-VB-TPHD) filter and unscented Kalman (AUK-VB-TPHD) filter in nonlinear Gaussian models. The simulation results prove the effectiveness of the idea that the VB-TPHD filter can form robust and stable trajectory filtering while learning adaptive measurement noise statistics. Compared with the tag-VB-PHD filter, the estimated error of the VB-TPHD filter is greatly reduced, and the estimation of the trajectory number is more accurate.
Nearest Neighbor Mapping of Quantum Circuits to Two-Dimensional Hexagonal Qubit Architecture

Motivated by physical realization of hexagonal architectures, in this paper we have introduced the hexagonal neighborhood structure for a set of qubits in a two-dimensional (2-D) plane along with a simple measure for estimating neighborhood distance. As compared to the traditional layout of qubits on a 2-D Cartesian plane, the hexagonal arrangement offers greater flexibility in mapping the logical qubits from a quantum circuit into an array of physical qubits. In most of the prior works, the neighborhood cost is estimated as number of Swap operations required to ensure that all 2-qubit quantum gates operate on physically adjacent qubits. However, in recent times, CNOT Templates have been used to execute 2-qubit gates where the interacting qubits are not adjacent to each other. In this paper we exploit the benefits of CNOT Templates in mapping quantum circuits to hexagonal 2-D arrays. We propose an evolutionary algorithm to obtain a good placement of qubits in the hexagonal structure. We also show the benefits of this approach over a simple greedy qubit placement method. We have carried out experiments on a set of benchmark suites to evaluate the efficiency of the proposed approach. The results show an average improvement of 42.9% over a very recent state-of-the-art method.
On Material Indeterminacy

‘Material indeterminacy’ is the term I use to discuss how my work since 2010 has explored the consequences of placing materiality, indeterminacy, and responsiveness at the centre of a compositional practice, and what means for the relationships between instrument, player, and score. I propose that the structural consequence of contingency in instrumental performance is an underexplored aspect of experimental composition, which has historically tended to focus on models that either control contingency or obviate its consequences. ‘Material indeterminacy’ is proposed as a third way that folds the emergent consequences of contingency back into meaningful relation with the unfolding structure. This research is framed by theoretical perspectives on materiality: Andrew Pickering’s performative ontology of human and material agencies, specifically his ‘dance of agency’ between human and material; anthropologist Tim Ingold’s phenomenological approach to materiality that valorises the relational ‘working-with’ of human and material. The liveliness of materiality is considered in relation to Lucy Suchman’s work on situatedness and the entwined nature of plans and actions, and then returned to a musical context via listening and the discourse of improvisation as response-to-contingency. Finally, I discuss these ideas via examples of my own work from the Garden of Forking Paths compositional project (2019–2021).
On the boomerang uniformity of a class of permutation quadrinomials over finite fields

Let F2n be a finite field with 2n elements and fc_(x)=c0x2m(2k+1)+c1x2m+k+1+c2x2m+2k+c3x2k+1∈F2n[x], where n, m and k are positive integers with n=2m and gcd⁡(m,k)=e. In this paper, motivated by a recent work of Li, Xiong and Zeng (Li et al. (2021) [12]), we further study the boomerang uniformity of fc_(x) by using similar ideas and carrying out particular techniques in solving equations over finite fields. As a consequence, we generalize Li, Xiong and Zeng's result from the case of m being odd and e=1 to that of both m/e and k/e being odd.