Reviewerly/exHarmony huggingface dataset:
The Origin of Nonlinear Dynamics Involving Complexity in Modern Sciences

This paper reveals the origin of nonlinear dynamics and presents a solution for nonlinear systematic problems based on other science.Generally, physical phenomena are divided into linear static logical problems and nonlinear dynamic systematic problems, but all scientists have solved both problems using the same algebraic logical solution in statistical physics based on determinism such as chaos theory.Surprisingly, this is a contradiction and a serious mistake because there is a perfect solution such as the system analysis theory existing in other science.Unfortunately, it has developed in the 20 th century by engineers.Thus, classical physicists could not solve it.Meanwhile, the author achieved the systematic solution for many unsolved nonlinear systematical, further, proved the research result through simulation using specially designed simulation device.Thus, this is a revolutionary achievement because it can easily solve the unsolved nonlinear dynamics that exists in all fields of science.Ironically most determinists do not welcome and reject it.However, it has no matter, it will be separated from current physics and other scientists studied it in the second physics.Therefore, it would be contributed to solve the unsolved nonlinear dynamics in complex science.
An exactly solvable quantum-metamaterial type model

The key difficulty in the modelling of large quantum coherent structures lies in keeping track of nonlocal, multipoint quantum correlations between their constituent parts. Here we consider a special case of such a system, a fractal quantum metamaterial interacting with electromagnetic field, and show that it can be exactly solved by using a combination of the Haar transform and the Wigner-Weyl transform. Theoretical and experimental investigation of finite-size precursors to exactly solvable fractal quantum structures as this will help illuminate the behaviour of generic quantum coherent structures on a similar spatio-temporal scale.
Probabilities in Session Types

This paper deals with the probabilistic behaviours of distributed systems described by a process calculus considering both probabilistic internal choices and nondeterministic external choices. For this calculus we define and study a typing system which extends the multiparty session types in order to deal also with probabilistic behaviours. The calculus and its typing system are motivated and illustrated by a running example.
Towards Generation of Cat States in Trapped Ions Set-Ups via FAQUAD Protocols and Dynamical Decoupling

The high fidelity generation of strongly entangled states of many particles, such as cat states, is a particularly demanding challenge. One approach is to drive the system, within a certain final time, as adiabatically as possible, in order to avoid the generation of unwanted excitations. However, excitations can also be generated by the presence of dissipative effects such as dephasing. Here we compare the effectiveness of Local Adiabatic and the FAst QUasi ADiabatic protocols in achieving a high fidelity for a target superposition state both with and without dephasing. In particular, we consider trapped ions set-ups in which each spin interacts with all the others with the uniform coupling strength or with a power-law coupling. In order to mitigate the effects of dephasing, we complement the adiabatic protocols with dynamical decoupling and we test its effectiveness. The protocols we study could be readily implemented with state-of-the-art techniques.
Temporal Consistency Based Deep Face Forgery Detection Network

With the rapid development of deep learning techniques as well as increasingly more visual information being made publicly available on the Internet, image translation methods have achieved great progress and encouraging performance. The manipulation and fabrication of visual information has become accessible and difficult to distinguish by the naked eye, which will have adverse effects on cloud and communication security. Thus, face forgery detection techniques have recently attracted increasing attention. Most recent works regard the face forgery detection problem as the typical image classification task, ignoring the exploration of inherent properties of forgery visual information itself. In this paper, we first explore the inherent limitation of fake videos, and find that the temporal consistency could help distinguish fake faces from real faces. A temporal consistency based deep face forgery detection network is proposed to directly detect fake videos when given multiple consistent video frames. The proposed method effectively considers the frame consistency property and achieves promising detection performance. Experimental results on the face forgery detection dataset demonstrate the superior performance of the proposed method.
Enhanced Digital Gradient Sensing Using Backlight Digital Speckle Target

Digital gradient sensing (DGS) is a non-contact and full-field optical measurement technique, which assesses mechanical behaviors of transparent materials or specular structures by measuring angular deflections of light rays. However, owing to the poor light-gathering capability of its imaging system, the dynamic performance of DGS is heavily restricted. Here, a method of enhancing the dynamic performance of DGS by improving its speckle target is proposed. The method employs the technique of backlight illumination, which significantly increases the utilization efficiency of light, shortens the exposure time, and enhances the dynamic performance of DGS. Additionally, it also uses the optimized digital speckle pattern to improve the measurement precision and accuracy. For validation, a comparison experiment was conducted, proving that the proposed method can improve the utilization efficiency of light by about 80 times and improve the quality of the speckle images by about 40%. Real tests, including a uniaxial tension test using transmission-mode DGS (t-DGS) and a three-point bending test using reflection-mode DGS (r-DGS), were also carried out, showing the efficacy and high compatibility of the proposed backlight digital speckle target. In summary, this simple method greatly improves the performance of DGS, which can be used as a standard method in both t-DGS and r-DGS.
The SLT 2021 children speech recognition challenge: Open datasets, rules and baselines

Automatic speech recognition (ASR) has been significantly advanced with the use of deep learning and big data. However improving robustness, including achieving equally good performance on diverse speakers and accents, is still a challenging problem. In particular, the performance of children speech recognition (CSR) still lags behind due to 1) the speech and language characteristics of children's voice are substantially different from those of adults and 2) sizable open dataset for children speech is still not available in the research community. To address these problems, we launch the Children Speech Recognition Challenge (CSRC), as a flagship satellite event of IEEE SLT 2021 workshop. The challenge will release about 400 hours of Mandarin speech data for registered teams and set up two challenge tracks and provide a common testbed to benchmark the CSR performance. In this paper, we introduce the datasets, rules, evaluation method as well as baselines.
Simple proof of confidentiality for private quantum channels in noisy environments

Complete security proofs for quantum communication protocols can be notoriously involved, which convolutes their verification, and obfuscates the key physical insights the security finally relies on. In such cases, for the majority of the community, the utility of such proofs may be restricted. Here we provide a simple proof of confidentiality for parallel quantum channels established via entanglement distillation based on hashing, in the presence of noise, and a malicious eavesdropper who is restricted only by the laws of quantum mechanics. The direct contribution lies in improving the linear confidentiality levels of recurrence-type entanglement distillation protocols to exponential levels for hashing protocols. The proof directly exploits the security relevant physical properties: measurement-based quantum computation with resource states and the separation of Bell-pairs from an eavesdropper. The proof also holds for situations where Eve has full control over the input states, and obtains all information about the operations and noise applied by the parties. The resulting state after hashing is private, i.e., disentangled from the eavesdropper. Moreover, the noise regimes for entanglement distillation and confidentiality do not coincide: Confidentiality can be guaranteed even in situation where entanglement distillation fails. We extend our results to multiparty situations which are of special interest for secure quantum networks.
Dialogics of idea form-creation as a means of thinking

Theoretical problems mostly arise in a situation of collision of mutually unacceptable provisions of a separate theory, which are in a state of active confrontation. Possible ways or methods of solving these problems are usually indicated by ideas – a kind of psychological tools of thinking, the structure and functional purpose of which allow reflecting the object of comprehension in many ways and holistically, thus preventing the prospect of its extreme manifestations as mutually contradictory concepts of one-sided theoretical ideas-approaches. The peculiarity of the idea form-creation process is determined by the fact that thinking, stimulating the functional purpose of the idea, uses while its development improved rules of concepts derivation and changed principles of proving their truth, which are different from those that caused the theoretical problem occurrence. The improvement of these rules and the change of principles is carried out by taking into account the function of the operational component of thinking as a such, which leaves behind its categorical component only the function of the source of links to be reorganized. Mental operations that carry out this reorganization are triadic inferences, the use of which through thinking as psychological tools is possible by providing the content of the conceivable form of dialogics, i.e. a kind of dialogue logic of two logics, which meets the requirements of dialogical essence of thinking and principles of dialectics. Dialogics considers formally mutually contradictory understanding positions of one and the same object of comprehension, organizing them as a positively significant form of a theoretical problem statement. To solve it successfully, dialogics uses the idea as a mental tool, which is given the form of a dialectical-logical concept that can reflect the essence of a particular theoretical problem, manifested in the form of dialectical unity of formally opposite theoretical positions. Most importantly, the idea as a mental tool of reflecting the essence of the problem raises the theoretical comprehension of the investigated object over the functional degree of finding its place in a particular concept or paradigmatic model and opens the prospect of its objectification at the metaparadigmatic level in an exhaustive category-methodological completeness.
Nonquantum information gain from higher-order correlation functions

Nonlinear correlation functions are at the heart of quantum theory. The second-order correlation function $g^{(2)}(\tau)$ has been a cornerstone of quantum optics since over half a century and a myriad of quantum and classical applications has been discovered. In contrast, higher-order correlation functions have so far only been used to reveal the nonclassical character of the emitted fields. In this paper, we study the relation between the $k$th-order correlation function $g^{(k)}(0)$ and the projection of the underlying quantum state of light onto the subspace of Fock states with photon number less than $k$. We show, that when $g^{(k)}(0)$ falls below a critical value, lower bounds for the projection on this subspace can be concluded as well as on the ratio of the subspace with one upto $k-1$ photons and $k$ to infinity. These bounds are at face value only valid for nonclassical quantum states. However, when the quantum state includes a nonzero projection on the vacuum state, the value of $g^{(k)}(0)$ is artificially enhanced, potentially covering these projections. We derive an effective $k$th-order correlation function, which accounts for the effect of vacuum. We show that the information gained from the effective correlation function is not limited to nonclassical quantum states and thus constitute a quantum- and classical application of higher-order correlation functions.
Cloud-Edge Fusion Based Abnormal Object Detection of Power Transmission Lines Using Incremental Learning

The accurate and timely abnormal object detection is of crucial importance for the safe operation of power grid. It is rather difficult, however, to completely manually recognize such objects based on the uploaded pictures in the cloud server. To meet the demand of accuracy and timeliness, this paper proposes to combine the cloud/edge fusion framework and deep learning techniques for abnormal object detection. Specifically, we first train the model of abnormal object detection by using YOLOv4 in the cloud server, and then apply the trained model to detect whether there is an abnormal object for each captured picture in edge servers. As the data sample is not very large at the early stage of the system, we use some enhancement techniques to enlarge the number of pictures, and afterwards new real-time data streams are also used for incremental learning. Our experiments show that the proposed framework can accurately and timely detect the abnormal objects near power transmission lines.
Lectura crítica en el desarrollo de habilidades de investigación en profesores de postgrado

In the last decade, education in Ecuador has improved due to the effectiveness of public policies.University legislation has implemented profound changes in the search for quality at all levels, which represents a challenge for the training of teachers.In this sense, the objectives of this study were to identify the research skills that are most difficult to acquire for students in master's education programs in Ecuador, and to explain the role of critical reading in their development.An exploratory study was carried out, using comparative analysis to examine the qualitative data derived from the monographs written by these students; evaluating your performance in presenting such results; likewise, two discussion groups were formed with the same students.The results of this first phase revealed weaknesses in research capacity, which are attributed to deficiencies in a sufficient critical reading to achieve the expected objectives.It is concluded that the use of critical reading is an indispensable precedent for the achievement of complex competences such as research, therefore, it requires an interdisciplinary, methodological, systematic and unified work in the teaching of all the modules that the program covers..
Separated Schmidt modes in the angular spectrum of biphotons

We prepare qudits based on angular multimode biphoton states by modulating the pump angular spectrum. The modes are prepared in the Schmidt basis and their intensity distributions do not overlap in space. This allows one to get rid of filtering losses while addressing single modes and to realize a single-shot qudit readout.
Nowhere to Hide: Cross-modal Identity Leakage between Biometrics and Devices

Along with the benefits of Internet of Things (IoT) come potential privacy risks, since billions of the connected devices are granted permission to track information about their users and communicate it to other parties over the Internet. Of particular interest to the adversary is the user identity which constantly plays an important role in launching attacks. While the exposure of a certain type of physical biometrics or device identity is extensively studied, the compound effect of leakage from both sides remains unknown in multi-modal sensing environments. In this work, we explore the feasibility of the compound identity leakage across cyber-physical spaces and unveil that co-located smart device IDs (e.g., smartphone MAC addresses) and physical biometrics (e.g., facial/vocal samples) are side channels to each other. It is demonstrated that our method is robust to various observation noise in the wild and an attacker can comprehensively profile victims in multi-dimension with nearly zero analysis effort. Two real-world experiments on different biometrics and device IDs show that the presented approach can compromise more than 70\% of device IDs and harvests multiple biometric clusters with ~94% purity at the same time.
Detecting Non‐Markovianity via Linear Entropy of Choi State

Non-Markovian dynamics detection is one of the most popular subjects in the quantum information science. In this paper, a linear-entropy-based non-Markovianity witness scheme is constructed. The positive definiteness of the Choi state will be broken in the non-Markovian evolution, which can be witnessed by its linear entropy. Thus, the linear entropy of the Choi state can be used to witness the non-Markovian dynamics. The effectiveness of the proposed method is verified by an example of the pure dephasing channel. Also, it is shown that this method can be extended to the one based on R\'enyi entropy.
Comprehensive assessment of gas turbine health condition based on combination weighting of subjective and objective

The multi-parameter comprehensive evaluation method of gas turbine can accurately grasp the state of engine health. Eight evaluation indicators were chosen from the condition of engine gas path degradation, the combustion system and the whole machine vibration. Aimed at the uncertainty of data information, the objective attribute weights were gotten based on the method of the combination of fuzzy clustering and information entropy by calculating the mutual information. In view of the equilibrium of data, another objective weights were gotten using the entropy weight method. Then the linear weighted sum method of the two was used to get the final objective weights of indicators. Subjective weights were obtained by analytic hierarchy process. Integrating the subjective and objective weights, multiplication combination method was used to determine the final weights. The multi-attribute comprehensive evaluation of gas turbine health status was carried out combined with a 2,000 hours test. Results show that the method can integrate the advantages of objective and subjective weighting methods, evaluation results are in line with the practical experience, which means it is a feasible way to the gas turbine condition assessment and maintenance decision.
Modified Password Guessing Methods Based on TarGuess-I

<math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mtext>TarGuess</mtext> <mo>−</mo> <mtext>I</mtext> </math> is a leading online targeted password guessing model using users’ personally identifiable information (PII) proposed at ACM CCS 2016 by Wang et al. It has attracted widespread attention in password security owing to its superior guessing performance. Yet, after analyzing the users’ vulnerable behaviors of using popular passwords and constructing passwords with users’ PII, we find that this model does not take into account popular passwords, keyboard patterns, and the special strings. The special strings are the strings related to users but do not appear in the users’ demographic information. Thus, we propose <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <mtext>TarGuess</mtext> <mo>−</mo> <msup> <mrow> <mtext>I</mtext> </mrow> <mrow> <mo>+</mo> <mi>K</mi> <mi>P</mi> <mi>X</mi> </mrow> </msup> </math> , a modified password guessing model with three semantic methods, including (1) identifying popular passwords by generating top-300 lists from similar websites, (2) recognizing keyboard patterns by relative position, and (3) catching the special strings by extracting continuous characters from user-generated PII. We conduct a series of evaluations on six large-scale real-world leaked password datasets. The experimental results show that our modified model outperforms <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mtext>TarGuess</mtext> <mo>−</mo> <mtext>I</mtext> </math> by 2.62% within <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mn>100</mn> </math> guesses.
On Internal Re-keying

In this paper we introduce a classification of existing re-keying-based approaches to increase the security of block cipher operation modes. We introduce the concepts of external and internal re-keying putting the focus on the second one. Whereas the external re-keying approach is widely used and provides the mechanism of key usage control on a message stream processing level, the internal re-keying approach is the first known mechanism providing such a control on a single message processing level. These approaches can be applied completely independently. The internal re-keying approach was already applied to the $$\mathrm {\text {CTR}}$$ encryption mode and yielded the $$\text {CTR-ACPKM}$$ mode. The mode is a part of RFC 8645 “Re-keying Mechanisms for Symmetric Keys”, which represents the consensus of the Crypto Forum Research Group (CFRG) of the Internet Research Task Force (IRTF). In the current paper we apply the internal re-keying approach to the well-known $$\mathrm {\text {GCM}}$$ authenticated encryption mode. The main results of this paper are a new internally re-keyed $$\text {GCM-ACPKM}$$ mode and its security bounds. We estimate the security of the $$\text {GCM-ACPKM}$$ mode respecting standard security notions. We compare both security and performance of the $$\text {GCM-ACPKM}$$ and $$\mathrm {\text {GCM}}$$ modes. The results show that changing $$\mathrm {\text {GCM}}$$ mode by integrating the $$\mathrm {\text {ACPKM}}$$ internal re-keying procedure increases security, significantly extending the lifetime of a key with a negligible loss in performance. Also we show how the re-keying approaches could increase the security of TLS 1.3 and CMS cipher suites.
FPGA Implementation and Evaluation of a Real-Time Image-Based Vibration Detection System with Adaptive Filtering

This paper shows design and implementation of an image-based vibration detection system on a field-programmable gate array (FPGA), aiming at application to tremor suppression for microsurgery assistance systems. The system can extract a vibration component within a user-specified frequency band from moving images in real-time. For fast and robust detection, we employ a statistical approach using dense optical flow to derive vibration component, and design a custom hardware based on the Lucas-Kanade (LK) method to compute optical flow. And for band-pass filtering without phase delay, we implement the band-limited multiple Fourier linear combiner (BMFLC), a sort of adaptive band-pass filter which can recompose an input signal as a mixture of sinusoidal signals with multiple frequencies within the specified band, with no phase delay. The whole system is implemented as a deep pipeline on a Xilinx Kintex-7 XC7K325T FPGA without using any external memory. We employ fixed-point arithmetic to reduce resource utilization while maintaining accuracy close to double-precision floating-point arithmetic. Empirical experiments reveal that the proposed system extracts a high-frequency tremor component from hand motions, with intentional low-frequency motions successfully filtered out. The system can process VGA moving images at 60fps, with a delay of less than 1 µs for the BMFLC, suggesting effectiveness of the deep pipelined architecture. In addition, we are planning to integrate a CNN-based segmentation system for improving detection accuracy, and show preliminary software evaluation results.