Reviewerly/exHarmony huggingface dataset:
Readout of quantum information spreading using a disordered quantum walk

We design a quantum probing protocol using Quantum Walks to investigate the Quantum Information spreading pattern. We employ Quantum Fisher Information, as a figure of merit, to quantify extractable information about an unknown parameter encoded within the Quantum Walk evolution. Although the approach is universal, we focus on the coherent static and dynamic disorder to investigate anomalous and classical transport as well as Anderson localization. Our results show that a Quantum Walk can be considered as a readout device of information about defects and perturbations occurring in complex networks, both classical and quantum.
Automatic Generation and Validation of Instruction Encoders and Decoders

Abstract Verification of instruction encoders and decoders is essential for formalizing manipulation of machine code. The existing approaches cannot guarantee the critical consistency property, i.e., that an encoder and its corresponding decoder are mutual inverses of each other. We observe that consistent encoder-decoder pairs can be automatically derived from bijections inherently embedded in instruction formats. Based on this observation, we develop a framework for writing specifications that capture these bijections, for automatically generating encoders and decoders from these specifications, and for formally validating the consistency and soundness of the generated encoders and decoders by synthesizing proofs in Coq and discharging verification conditions using SMT solvers. We apply this framework to a subset of X86-32 instructions to illustrate its effectiveness in these regards. We also demonstrate that the generated encoders and decoders have reasonable performance.
Meta-inferences and Supervaluationism

Abstract Many classically valid meta-inferences fail in a standard supervaluationist framework. This allegedly prevents supervaluationism from offering an account of good deductive reasoning. We provide a proof system for supervaluationist logic which includes supervaluationistically acceptable versions of the classical meta-inferences. The proof system emerges naturally by thinking of truth as licensing assertion, falsity as licensing negative assertion and lack of truth-value as licensing rejection and weak assertion. Moreover, the proof system respects well-known criteria for the admissibility of inference rules. Thus, supervaluationists can provide an account of good deductive reasoning. Our proof system moreover brings to light how one can revise the standard supervaluationist framework to make room for higher-order vagueness. We prove that the resulting logic is sound and complete with respect to the consequence relation that preserves truth in a model of the non-normal modal logic NT . Finally, we extend our approach to a first-order setting and show that supervaluationism can treat vagueness in the same way at every order. The failure of conditional proof and other meta-inferences is a crucial ingredient in this treatment and hence should be embraced, not lamented.
Robust Adversarial Imitation Learning via Adaptively-Selected Demonstrations

The agent in imitation learning (IL) is expected to mimic the behavior of the expert. Its performance relies highly on the quality of given expert demonstrations. However, the assumption that collected demonstrations are optimal cannot always hold in real-world tasks, which would seriously influence the performance of the learned agent. In this paper, we propose a robust method within the framework of Generative Adversarial Imitation Learning (GAIL) to address imperfect demonstration issue, in which good demonstrations can be adaptively selected for training while bad demonstrations are abandoned. Specifically, a binary weight is assigned to each expert demonstration to indicate whether to select it for training. The reward function in GAIL is employed to determine this weight (i.e. higher reward results in higher weight). Compared to some existing solutions that require some auxiliary information about this weight, we set up the connection between weight and model so that we can jointly optimize GAIL and learn the latent weight. Besides hard binary weighting, we also propose a soft weighting scheme. Experiments in the Mujoco demonstrate the proposed method outperforms other GAIL-based methods when dealing with imperfect demonstrations.
Mask Detection and Tracing System

Covid19 has given a new identity for wearing a mask. It is meaningful when these masked faces are detected accurately and efficiently. As a unique face detection task, face mask detection is much more difficult because of extreme occlusions which leads to the loss of face details. Besides, there is almost no existing large-scale accurately labelled masked face dataset, which increase the difficulty of face mask detection. The system encourages to use CNN-based deep learning algorithms which has done vast progress towards researches in face detection In this paper, we propose novel CNN-based method which is formed of three convolutional neural networks to detect face mask. Besides, because of the shortage of face masked training samples, we propose a new dataset called” face mask dataset” to finetune our CNN models. We evaluate our proposed face mask detection algorithm on the face mask testing set, and it achieves satisfactory performance
#PowerInNumbers: How Digital Libraries Use Collaborative Social Media Campaigns to Promote Collections

Social media provides ample opportunity for digital libraries to work together to promote their online collections to users. Despite this, institutions rarely connect on social networking platforms, and there is little research of the outcomes when they do. This article examines the benefits of the monthly collaborative social media campaign #ArchivesHashtagParty, launched by the National Archives and Records Administration in August 2017, during the month of April 2021. Using Twitter analytics and personal observations, the author explores how users engage with the campaign and interact with material, how digital libraries work together as a community to promote their collections, and whether this campaign benefits participating libraries. Using return on investment to measure user engagement and increase in followers, this study finds that participating in this one-day collaborative campaign can benefit digital libraries of all sizes and is a valuable addition to social media strategies.
HUBUNGAN ANTARA KECERDASAN EMOSIONAL DAN MOTIVASI BELAJAR DENGAN HASIL BELAJAR IPA SISWA SMP NEGERI 1 SUNGGUMINASA

This research aims at: (1) discovering the students’ emotional intelligence (2) discovering the students’ learning motivation, (3) discovering the science learning outcomes , (4) examining the relationship between emotional intelligence and the science learning outcomes, (5) examining the relationship between learning motivation and the science learning outcomes, and (6) examining the relationship of both emotional intelligence and learning motivation collaboratively to the science learning outcomes at SMP Negeri 1 Sungguminasa. This research is an ex-post-facto research. The Population in this research was the students of SMP Negeri 1 Sungguminas. The sampling technique used was random sampling with the total of sample 244 students. The data collection techniques were questionnaires and documentation. The data was analyzed by employing regression test and correlation test. The results of the research reveal that: (1) the students’ emotional intelligence in general is in high category, (2) the students’ learning motivation in general is in high category, (3) the science learning outcomes in general is in high category, (4) there are positive relation signicantly between emotional intelligence and the science learning outcomes. The learning outcomes follow the improvement of emotional intelligence with coefficient level of correlation (r) is 0.492 and effective contribution R2 is 24.2%, (5) there are positive relation significantly between learning motivation and the science learning outcomes. The learning outcomes follow the improvement of learning motivation with coefficient level of correlation (r) is 0.490 and effective contribution R2 is 24%, (6) there are positive relation significantly of both emotional intelligence and learning motivation collaboratively to the science learning outcomes at SMP Negeri 1 Sungguminasa, The learning outcomes is the linear function of emotional intelligence and learning motivation, means that the science learning outcomes follow the improment of emotional intelligence and learning motivation with coefficient level of correlation (r) is 0.548 and effective contribution R2 is 30%.
Pengujian Validitas dan Reliabilitas Model UTAUT 2 dan EUCS Pada Sistem Informasi Akademik

The research instrument is used to collect data or measure the object of a study. The purpose of this study was to determine which instruments were declared valid and reliable and to find out the variables with the highest validity and reliability values. Validity testing is carried out to determine the effectiveness of an instrument, while reliability testing is carried out to show the level of reliability of the indicators used. Testing the validity and reliability using software SmartPLS version 3.3.2 with a measurement scale that is Likert scale. Validity testing is done by looking at the average variance extracted (AVE) value and the comparison of the latent variable correlations values, while reliability testing is done by looking at the composite reliability value. The population in this study were active students at the State Islamic University (UIN) Raden Fatah Palembang, totaling 19,260 students with the determination of the sample using the Slovin formula with a level of significance = 5%. Data collection in this study was carried out by distributing online questionnaires. The questionnaire was made based on indicators on the model used, where the models used were UTAUT 2 and EUCS. The UTAUT 2 model can be used to measure the level of user acceptance of the system consisting of the variables of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, perceived value, habit, and behavioral intention. Furthermore, the EUCS model is used to measure the level of user satisfaction which consists of content, accuracy, format, ease of use, timeliness, and user satisfaction variables. The results of the validity and reliability testing state that all indicators are valid and reliable with an AVE value &gt; 0.50 in the validity test and the composite reliability value &gt; 0.70 in the reliability test. The validity test with the highest value is found in the ease of use variable with an AVE value of 0.826 and reliability testing with the highest value is found in the performance expectancy variable with a composite reliability value of 0.924. With this research, it is expected to obtain variables in the model to evaluate user acceptance and satisfaction with academic information systems
Unification in Pretabular Extensions of S4

L.L. Maksimova and L. Esakia, V. Meskhi showed that the modal logic S4 has exactly 5 pretabular extensions: PM1-PM5. In this paper, we study and systematize the problem of unification for all given pretabular logics. We showed that PM2,PM3 have finitary, and PM1,PM4,PM5 have unitary types of unification. Complete sets of unifiers in logics are described.
Eight Direction Improved Sobel Algorithm Based on Morphological Processing in 5G Smart Grid

Aiming at the 5G application scenario of smart grid, it is difficult to quickly process massive videos and pictures and extract effective edge information. In this paper, based on the analysis of traditional Sobel edge detection operator, aiming at its shortcomings of noise sensitivity and limited direction template, we improve it. Firstly, morphological processing is added to smooth the image to improve the sensitivity of traditional Sobel operator to noise. Secondly, this paper proposes an algorithm of Gaussian filtering combined with improved difference formula. At the same time, Sobel operator template is improved to eight direction Sobel template based on Manhattan distance. Simulation results show that the proposed algorithm can significantly improve the noise sensitivity and edge ambiguity of existing algorithms in the aspects of boundary point suppression, anti noise, and image edge optimization.
Zero knowledge based data deduplication using in-line Block Matching protocol for secure cloud storage

In the area of cloud computing, data deduplication enables the cloud server to store a single copy of data by eliminating redundant files to improve storage and network efficiency.Proof-of-ownership (PoW) is a cryptographic function that verifies the user who really owns the data.Most of the existing schemes have tried to solve the deduplication problem by providing the same encryption key for identical data.However, these schemes suffer from dynamic changes in ownership management.In this paper, we propose an in-line block matching (IBM) protocol based on zero-knowledge proof for deduplication with dynamic ownership management, which eliminates the unauthorized access of sensitive data.In this proposed work, for a new file, the uploader randomly chooses a file encryption key and encrypts the file.The user also computes a unique proof for the uploaded file by dividing the file into number of blocks and stores this proof to the cloud server.The cloud server computes the group key for the ciphertext and re-encrypts it using this group key.The cloud server also does the proof verification against the subsequent uploader for an existing file.The cloud server is honest-but-curious, so the proposed scheme confirms that the cloud server does not know any information about file encryption key even though it plays a proxy role.The result shows that our proposed scheme protects the data from both cloud server and adversaries.Also, the computational cost is comparatively less than other existing schemes.
BlindTLS

Governments across the globe limit which sites their citizens can visit by employing multiple kinds of censorship techniques for different types of traffic. ISPs have been able to effectively censor HTTPS traffic by inspecting the TLS handshake which leaks the domain being visited. TLS1.3 attempts to solve this with a proposed ESNI extension which encrypts the SNI (server name indication) value. Since ESNI is optional, ISPs have been known to simply drop handshakes that attempt to use it; SNI based censorship is therefore still a problem even in TLS1.3. We present BlindTLS, a technique that hides the true SNI value in TLS1.2. BlindTLS requires no server modifications and expects only minimal (existing) external infrastructure to circumvent TLS-based censorship. We evaluate and show that BlindTLS is able to successfully provide access to a majority of websites blocked by a real-world ISP with minimal performance overhead.
SUBJECTIVE UNDERSTANDING OF THE STUDENT WHEN USING OPEN EDUCATIONAL RESOURCES

The relevance of the study is determined by the fact that open educational resources carry the ability to overcome the basic methodological construct complicating the learning process among students and namely the use of international experience while learning and obtaining knowledge. This study shows the aspects of functioning open educational resources and their technological basis. The novelty of the work was the formation of a model for the use of open educational resources in training of specialized courses of the Department of applied chemistry. The authors showed that the effectiveness of open educational resources use depends directly on the share of online learning and technological isolation of subjects. In particular, not only learning processes in the implementation of the program in applied chemistry, but also other disciplines that require the exchange of experience between countries and the use of a wide range of technological equipment and online structure are considered. In particular, training on the example of databases, information networks, and other spatially distributed structures are considered too. The practical significance of the study is defined by the fact that the use of open educational resources will not only intensify the learning process at the university, but also to determine the possibility of integration into the world educational space.
Research on the Cultivation Path of Innovative and Entrepreneurial Talents in Colleges and Universities in the New Era

The Government Work Report once again called for further promoting mass entrepreneurship and innovation. Innovation and entrepreneurship is the engine of China's sustainable economic development, and the cultivation of innovative talents is the key to innovation activities. At present, innovation education is widely carried out in Chinese universities, but there are still some problems. The paper comes up with a new path: 1) Make clear the thinking concept, and creates an ecological environment for the cultivation of talents; 2) Innovate educational mode and build a scientific system; 3) Promote industry, teaching, university and research integration so as to expand practice system; 4) Strengthen the teaching staff, innovate the collaborative education subject; 5) Define clearly rights and responsibilities, establish and improve an evaluation mechanism. In order to assume the responsibility and historical mission entrusted by the country and the times, the universities should comprehensively upgrade the cultivation of innovative and entrepreneurial talents and promote the implementation of the national strategy for development.
Reasoning about the garden of forking paths

Lazy evaluation is a powerful tool for functional programmers. It enables the concise expression of on-demand computation and a form of compositionality not available under other evaluation strategies. However, the stateful nature of lazy evaluation makes it hard to analyze a program's computational cost, either informally or formally. In this work, we present a novel and simple framework for formally reasoning about lazy computation costs based on a recent model of lazy evaluation: clairvoyant call-by-value. The key feature of our framework is its simplicity, as expressed by our definition of the clairvoyance monad. This monad is both simple to define (around 20 lines of Coq) and simple to reason about. We show that this monad can be effectively used to mechanically reason about the computational cost of lazy functional programs written in Coq.
User Engagement for Sustaining Services

Abstract In the first phase of SERVIR-HKH, there was disconnect between the cutting-edge technology products that were developed and the specific needs of the users. Thus, the service planning approach shifted the focus from products to comprehensive services that put the users’ need first. User engagement improved the quality of the services by addressing user feedback and also building sustainability into the services from the very beginning. This chapter aims to introduce the concept of user engagement in the context of SERVIR-HKH and its execution within the service planning framework; it also dwells on the lessons that have been learnt. The chapter also gives prominence to examples of user engagement case studies as well as to the tools and techniques that have been adopted for successful user engagement. It also describes the insights, achievements, and experiences during the implementation process of the user engagement module in the HKH region.
VLSI Architectures of a Wiener Filter for Video Coding

In the modern age, the use of video has become fundamental in communication and this has led to its use through an increasing number of devices. The higher resolution required for images and videos leads to more memory space and more efficient data compression, obtained by improving video coding techniques. For this reason, the Alliance for Open Media (AOMedia) developed a new open-source and royalty-free codec, named AOMedia Video 1 (AV1). This work focuses on the Wiener filter, a specific loop restoration tool of the AV1 video coding format, which features a significant amount of computational complexity. A new hardware architecture implementing the separable symmetric normalized Wiener filter is presented. Furthermore, the paper details possible optimizations starting from the basic architecture. These optimizations allow the Wiener filter to achieve a 100× reduction in processing time, compared to existing works, and 5× improvement in megasamples per second.
Security of search and verification protocol in multidimensional blockchain

The issue of secure data exchange and performing external transactions between robust distributed ledgers has recently been among the most significant in the sphere of designing and implementing decentralized technologies. Several approaches have been proposed to speed up the process of verifying transactions on adjacent blockchains. The problem of search has not been under research yet. The paper contains security evaluation of data exchange between independent robust distributed ledgers inside multidimensional blockchain. Main principles, basic steps of the protocol and major requirements for it are observed: centralized approach, subset principle and robust SVP. An equivalence of centralized approach and ideal search and verification functionality is proven. The probability of successful verification in case of using fully connected network graph or equivalent approach with fully connected graph between parent and child blockchain is shown. The insecurity of approach with one-to-one links between child and parent ledgers or with a subset principle is proven. A robust search and verification protocol for blocks and transactions based on the features of robust distributed ledgers is presented. The probability of attack on this protocol is mostly defined by the probability of attack on verification and not on search. An approach to protection against an attacker with 50% of nodes in the network is given. It is based on combination of various search and verification techniques.
Research on Efficient Deep Learning Algorithm Based on ShuffleGhost in the Field of Virtual Reality

Deep learning algorithms are facing the limitation in virtual reality application due to the cost of memory, computation, and real-time computation problem. Models with rigorous performance might suffer from enormous parameters and large-scale structure, and it would be hard to replant them onto embedded devices. In this paper, with the inspiration of GhostNet, we proposed an efficient structure ShuffleGhost to make use of the redundancy in feature maps to alleviate the cost of computations, as well as tackling some drawbacks of GhostNet. Since GhostNet suffers from high computation of convolution in Ghost module and shortcut, the restriction of downsampling would make it more difficult to apply Ghost module and Ghost bottleneck to other backbone. This paper proposes three new kinds of ShuffleGhost structure to tackle the drawbacks of GhostNet. The ShuffleGhost module and ShuffleGhost bottlenecks are utilized by the shuffle layer and group convolution from ShuffleNet, and they are designed to redistribute the feature maps concatenated from Ghost Feature Map and Primary Feature Map. Besides, they eliminate the gap of them and extract the features. Then, SENet layer is adopted to reduce the computation cost of group convolution, as well as evaluating the importance of the feature maps which concatenated from Ghost Feature Maps and Primary Feature Maps and giving proper weights for the feature maps. This paper conducted some experiments and proved that the ShuffleGhostV3 has smaller trainable parameters and FLOPs with the ensurance of accuracy. And with proper design, it could be more efficient in both GPU and CPU side.