Reviewerly/exHarmony huggingface dataset:
Digital watermarking algorithm based on 4-level discrete wavelet transform and discrete fractional angular transform

Nowadays, there are many watermarking algorithms based on wavelet transform. The simple one is to insert directly the watermark into the wavelet transform coefficients. However, most of the existing watermarking schemes can only resist traditional signal processing attacks, such as image compression, noise and filtering. When the watermarked image is subject to geometric transformations, especially rotation attack, it is hard to detect the watermark successfully. In this paper, a digital watermarking algorithm is proposed based on 4-level discrete wavelet transform and discrete fractional angular transform. To enhance the security of the algorithm, the watermark is scrambled with the simplicity of Arnold transform and chaos-based mix optical bistability model, since the chaos is pseudorandom and sensitive to the initial values. And the watermark is embedded into the medium frequency sub-band of the 1-level wavelet decomposition according to the Harris feature point detection. Simulation results show that the proposed digital watermarking algorithm by combining 4-level discrete wavelet transform with discrete fractional angular transform could resist rotation attack and other common attacks.
Some remarks of random graphs

At the beginning of the paper, the known models are briefly presented (The Barabási–Albert model, Watts–Strogatz model, Erdős-Rényi model). In the later part of the paper, some results are presented, which are valid in the Erdős-Rényi model and are also related to the dominant sets of graphs. These results will be considered further in a later paper (Bacsó et al., 2021).
Gradient Compression with a Variational Coding Scheme for Federated Learning

Federated Learning (FL), a distributed machine learning architecture, emerged to solve the intelligent data analysis on massive data generated at network edge-devices. With this paradigm, a model is jointly learned in parallel at edge-devices without needing to send voluminous data to a central FL server. This not only allows a model to learn in a feasible duration by reducing network latency but also preserves data privacy. Nonetheless, when thousands of edge-devices are attached to an FL framework, limited network resources inevitably impose intolerable training latency. In this work, we propose model-update compression to solve this issue in a very novel way. The proposed method learns multiple Gaussian distributions that best describe the high dimensional gradient parameters. In the FL server, high dimensional gradients are repopulated from Gaussian distributions utilizing likelihood function parameters which are communicated to the server. Since the distribution information parameters constitute a very small percentage of values compared to the high dimensional gradients themselves, our proposed method is able to save significant uplink band-width while preserving the model accuracy. Experimental results validated our claim.
The Analysis of Code-Switching and Code-Mixing in a Fanfiction Entitled “Crazy Rich Chenle”

This article is entitled “The Analysis of code-switching and code-mixing in a fan-fiction entitled “Crazy Rich Chenle””. This study aims to analyze the types of code-switching, types of code-mixing as well as the reasons of code-switching and code-mixing. The data is taken from the fan-fiction entitled “Crazy Rich Chenle”, written by Hadids and uploaded on the online reading platform known as “wattpad”. The documentation method and note-taking technique being used to collect the data. The data were analyzed using descriptive qualitative methods. This study uses the theory of Hoffman (1991) about types of code-switching and the theory proposed by Musyken (2000) about types of code-mixing. The result of this study showed that there are three types of code-switching and three types of code-mixing found and used by the characters in the fan-fiction “Crazy Rich Chenle”. The characters in the fan-fiction “Crazy Rich Chenle” mostly used inter-sentential switching and insertion types of code-mixing
3D Human Pose Estimation using Multi-scale and Multi-level Features

In this paper, we propose a novel graph-convolution-based network architecture for 2D-to-3D human pose estimation using multi-scale and multi-level features. For multi-scale features, we propose a novel pooling/unpooling approach considering the human skeletal structure to obtain both global and local feature information of human pose, and then use it to compose an encoder-decoder structure applicable to the graph-structured data. For multi-level features, we utilize the feature information in each depth-level in the neural network architecture, thus enhancing the performance of the model. Extensive experiments show that our proposed model architecture using multi-scale multi-level features outperforms the state-of-the-art approaches.
3D Gait Measurement of Mouse Using RGB-D Video from Below

Mouse is a useful animal model to address the neural mechanism of higher brain function and test pharmacodynamics of new drugs. Development of new behavioral analysis to detect subtleties of emotion is valuable for the evolution of neuroscience research and drug discovery. 3D gait measurement is expected to contribute greatly to them. Several methods for 3D gait measurement of mouse were proposed. For example, there is a method using optical motion capture with markers and multiple cameras, but this method has problems of preparing the markers sets, and the effect of markers on mouse behavior. Another method is to use a single RGB-D camera and calculate the position of the limbs using the distance from the center of gravity based on the depth image, but it has a problem that the error is large for the size of mouse foot. In this study, we propose a simple, highly accurate and markerless gait measurement method using a single RGB-D camera. As a result, the proposed method can reduce the error to about half compared to the error in the previous study and measure the gait of mouse with sufficient accuracy.
Analysis of Firmware Security Mechanisms

Ravindrababu, Sandeep Gogineni Venugopal, Varsha Alves-Foss, JimAttacks, such as Mirai Botnet and Stuxnet, which both target low-level devices, have shown how vulnerable firmware on today’s devices is. As a result of these attacks, security mechanisms such as address space layout randomization (ASLR), stack canaries, non-executable stack, data execution prevention, and others have been implemented in firmware in an attempt to mitigate the exploits. Some of these techniques, however, have limits and are vulnerable to particular attacks. In this paper, the standard security mechanisms currently in use are initially described. Following that, we analyze their shortcomings. Finally, we present the findings of the experiments to see if these security techniques are reliable.
Sentiment Analysis of Roman-Urdu Tweets about Covid-19 Using Machine Learning Approach: A Systematic Literature Review

From the past decade, growth of social media encourages researchers to perform several academic studies on the user generated data. Sentiment Analysis is tool used to generate summary of public opinion about a topic, which helps in effective decision making. Most of the work in sentiment analysis has been performed on English Language Dataset. Many Languages such as Urdu, Hindi, and Italian faced lack of attention due to their complex morphological structure and unavailability of resources. COVID-19 has affected human life around the world. Many researchers have performed their studies using twitter data for knowing the sentiments of people throughout the time of pandemic. In this Paper we are giving a general overview about the process of Sentiment Analysis of Roman-Urdu Tweets. For the dataset query we have used the data generated by user about COVID19.
PSYCHOLOGICAL AND PEDAGOGICAL PROBLEMS OF A STUDENT’S PROFESSIONAL SELF-DEVELOPMENT

The article substantiates the psychological and pedagogical concept of a student’s professional self-development, reveals the identified patterns and principles of developing strategies for a student’s professional self-development, establishes an integrative-project mechanism, presents a procedural model. The authors present the experience of implementing the concept of professional self-development of a student, characterize the pedagogical project of an open network experimental Foresight platform “Strategies for the professional self-development of a student.” Professional self-development is ensured by the integration of the components of the strategic potentials of the student’s personality, interaction and higher education on the basis of their accumulation, integration and transformation. Strategies are manifested in the direction of the design and self-design of a promising developing specialist, which creates an impetus for the development of professional and personal competencies. The scientific and pedagogical prerequisites and tendencies for solving the problem of the student’s professional self-development, conditioned by the study of the structure and content of the student’s professional self-development, the specifics of the conditions of education, principles and patterns, organization, forms, means and methods of activating the processes of self-development, have been established.
Explainable Quality Estimation: CUNI Eval4NLP Submission

This paper describes our participating system in the shared task Explainable quality estimation of 2nd Workshop on Evaluation & Comparison of NLP Systems.The task of quality estimation (QE, a.k.a.reference-free evaluation) is to predict the quality of MT output at inference time without access to reference translations.In this proposed work, we first build a word-level quality estimation model, then we finetune this model for sentence-level QE.Our proposed models achieve near stateof-the-art results.In the word-level QE, we place 2nd and 3rd on the supervised Ro-En and Et-En test sets.In the sentence-level QE, we achieve a relative improvement of 8.86% (Ro-En) and 10.6% (Et-En) in terms of the Pearson correlation coefficient over the baseline model.
Two Levels of Security for Protection of Images Copyright

Due to illegal manipulation and image processing attacks, digital image copyright protection is receiving a significant research attention. This paper has introduced a blind invisible watermarking method to protect the copyright of digital color images. This method is based on the combination of digital transforms (DWT, DCT) in the frequency domain. The embedding process involved in this method is based on partitioning the host image into 16 × 16 non-overlap blocks, and the chaotic maps are used to generate random numbers in order to choose the appropriate blocks for the inclusion process involved in the purpose of increasing the security of proposed system. As for the extraction process, it is carried out in a way that does not require the presence of original image but rather follows the same embedding protocol to extract the embedded and encrypted watermark. To raise the security level, a hybrid encryption method has been proposed by using the chaotic map and DNA coding for encrypting the watermark before embedding it. Experimental results evident the good imperceptibility. In addition, the proposed method effectively resists common “image processing attacks.”
RASTI marks a new dawn for research publishing

Abstract Sue Bowler talks to the people in charge of the first new RAS journal in almost a century, RAS Techniques and Instruments, and hears that it is the place to discuss advances in the complex methods and tools that are changing the way scientists work.
Optimal quantum feedback algorithm for spin ensemble purification

We present a coherent quantum feedback algorithm to purify a mesoscopic spin ensemble at the ultimate level of a single spin. Moreover our feedback can engineer classically correlated states extending over multiple modes.
Deployment Modes of Your ARM Template

In Chapter 5, we reviewed how to define the various scopes in which you can target an Azure Resource Manager (ARM) deployment. Sometimes we might have to deploy an ARM template and target the same environment.
Soft Computing based Artificial Neural Network and Multiple Feature set Intelligence system for Image Retrieval

Abstract This paper proposes an Image Retrieval model using Multiple Feature Sets and Artificial Neural Network (IR-MFS-ANN), where the multiple features Histogram of oriented Gradient (HoG), Overlapping Local Binary Pattern (OLBP), Color and Statistical features are considered. Visual information is one of the most important data in the field of social networking, medicine, military, and these areas contain an enormous volume of semi-organized and organized heterogeneous information related to explicit subjects. However, retrieval and usage of suitable information from the comprehensive information archives are important to meet the content extraction and retrieval challenges. To improve retrieval performance, the image representation, modeling, scalable algorithm that permit accessing large archives are integrated into the retrieval framework. The proposed model utilizes ANN to find the distance between feature vectors. The proposed algorithm is tested and analyzed with various retrieval techniques and it is found that ANN-based image retrieval outperforms the state-of-the-art techniques [1–5]. The proposed method results in accuracy of 94%, 92%, 95%, and 94% for Wang, Cifar-10, Oxford Flower, and ImageNet standard databases respectively.
PENGGUNAAN KATA KERJA SIMPLE PAST TENSE DAN ADJECTIVE DALAM PENULISAN TEKS RECOUNT

The aim of the research is to know the use of simple past tense and adjective verbs of SMPN in Central Jakarta in writing recount text and to find out what errors the most dominant students made. The research approach used in this study is a qualitative approach. After analyzing the students' writing, the writer gets the conclusion that 1) the most common types of mistakes in simple past tense are misformation at 67.99%. This error reached 189 errors out of a total of 278 errors. Meanwhile, the least type of misuse of is misordering by 3.96%. This error reached 11 errors out of a total of 278 errors. While the other types of errors were error of omission of 12.23% which reached 34 errors out of a total of 278 errors and error of addition of 9.71% which totaled 27 errors out of a total of 278 errors. 2) Errors in adjective writing were 17 errors or 6.11%. Keywords: simple past tense, recount text, EFL, junior high school
Generalization of Spin Operators

The study shall look to the group of generators SU(4).From these generators, a new group spin operator will be constructed.We will classify these groups into right handed groups and left handed groups.These two groups will satisfy all the properties of Pauli spin operators S x , S y and S z with respect to the frame xyz.The analysis shows that the number of groups spin operators depends on the order of the group.This leads us to construct the theorem which defines the number of the groups spin operators.The analysis also leads to two kinds of frames: left handed frame (LHF) and right handed frame (RHF).The right handed operators will act on the RHF, and left hand operators act on the LHF.The study shall discuss the notion of spin squeezing for pure spin 3/2 system by using our new frames and new spin operators.It will show that our calculation is equivalent to the calculation by using Pauli spin operators.
Perbandingan Cloud Computing Microsoft Onedrive, Dropbox, dan Google Drive

Cloud Computing is one of the latest web-based information technology that provides services that are able to provide sources of information and services.Now with the development of mobile technology that supports and with the industrial revolution has supported mobile computing everywhere with cloud computing technology.The development of the cloud is very fast and there are many cloud facilities scattered today.This study analyzes Cloud Computing in a comparison of Microsoft OneDrive, Dropbox, and Google Drive so that users can distinguish and compare cloud computing and their respective uses.The results provide or describe the differences so that the use of the three cloud computing can be maximized.As a consideration towards the industrial revolution 4.0 all cloud-based activities and supporting the internet of things.Nowadays, many popular and popular cloud computing is used, spread almost in every handset used by the community, knowing the detailed functions are expected to provide convenience in the support of the industrial revolution in the new phase at this time.
ERROR ANALYSIS IN STUDENTS’ CLASSROOM DISCUSSION AT MTS LKMD WAEMOLI (Analisis Kesalahan Berbahasa Dalam Diskusi Siswa Kelas VIII MTS LKMD Waemoli)

AbstractThis study the analysis of language errors in Indonesian subjects at MTs LKMD Waemoli, Buru Regency inclass discussion activities. The research design used in this research is descriptive qualitative, namelycollecting, processing, analyzing, and presenting data objectively about the object of research, namely languageerrors in class discussion activities of class VIII students of MTs LKMD Waemoli, Buru Regency, especiallywords, phrases, clauses, and the sentence. Data collection techniques are carried out to obtain the informationneeded in order to achieve the research objectives, the techniques used are observation techniques andrecording techniques. The results showed that the form of language error analysis for grade VII students at MTsLKMD Waemoli, Buru Regency in class discussion activities was the use of words, use of phrases, use ofclauses, and use of sentences. Based on the data obtained regarding the analysis of students' language errors inclass discussions, it can be said that in the use of words there are 168 non-standard word uses, in the use ofphrases there are 7 errors, the use of clause errors there are 13 errors and 10 errors in the use of sentences. Theoverall dialogue on the data in the analysis is 146 which is more wrong with the use of errors in words.Keywords: language, error analysis, class discussion.
Augmented / virtual / mixed reality systems optical terminology

Abstract In this part of our tutorial, we attempt to explain and cover several most important non‐imaging parameters that form the complementary part of the base requirements list for an XR system specification. The non‐imaging part of the system specification is often treated with less attention, and in many cases is the reason for dissatisfactory system performances. In our extensive experience, we found that this part is critical when designing an XR system, since the non‐imaging parameters have very high impact on the visual image perception and ultimately the user experience. Taking them into consideration from early design stages on can make the difference between the mediocre performances product and the product that produces the ‘wow effect’.
Person Named Entity Recognition in Balinese

Named Entity Recognition (NER) is part of information extraction whose task is to classify text which is categorized into several classes such as names of people (figures), organizations, and locations. In this study, the authors propose making a NER identify the names of characters in Balinese language documents. This study will use a rule-based method (rule-based). Rules are build based on the morphological structure and linguistic meaning of Balinese names. The research conducted, that the system has an accuracy of 67.41%, precision of 83.42%, recall of 77.83%, and F-Score of 80.53%.
Diagnostics of digital competencies of the pedagogue

This article examines the development of digital competencies of the pedagogue and presents the toolset for their assessment and self-assessment. The subject of this research is the process of detecting digital competencies of the pedagogue. An attempt is made to structure the key indicators of the formation of digital competencies of the pedagogue and conduct their level differentiation. The author provides the matrix of the development of digital competencies, which may become a benchmark for the competent control over student&amp;rsquo;s learning activity in digital educational space. Such matrix serves as the theoretical model for detecting the level of formation of IT-competencies of the pedagogue in the conditions of rural and ungraded schools. The three levels of the development of digital competencies are presented therein. In their professional development, the pedagogue undergoes the three stages, which can designated as &amp;ldquo;Application &amp;ndash; Adaptation &amp;ndash; Elaboration&amp;rdquo;. This indicates the three levels of development IT- competencies of the pedagogue implemented in the following types of professional activity: work with information resources; control over the learning, upbringing and developmental processes; elaboration of electronic educational materials, creation of educational environment, and countering destructive trends on the Internet; self-management of professional development of the pedagogue. The criteria are formulated in accordance with the highlighted types of professional activity of the pedagogue. The level of development IT-competencies is detected through the analysis of pedagogical situations, when the pedagogue must choose one of three behavioral strategies that are associated related with the general use, general pedagogical, and subject-methodical competency respectively. The article is prepared within the framework of the state task of the Ministry of Education No. 073-03-2021-015 / 2 of July 21, 2021 for the implementation of research works (on the topic &amp;ldquo;Research and development of methodical recommendations on the use of modern digital and Internet technologies on the example of rural and ungraded schools in the context of ensuring quality educational process (the online format of implementation is offered)&amp;rdquo;.
A Method to Deduce and Synthesize the Dafny Programs

We propose a systematic method to deduce and synthesize the Dafny programs. First, the specification of problem is described in strict mathematical language. Then, the derivation process uses program specification transformation technology to perform equivalent transformation. Furthermore, Dafny program is synthesized through the obtained recursive relationship and loop invariants. Finally, the functional correctness of Dafny program is automatically verified by Dafny verifier or online tool. Through this method, we deduce and synthesize Dafny programs for many typical problems such as the cube sum problem, the minimum (or maximum) contiguous subarray problems, several searching problems, several sorting problems, and so on. Due to space limitation, we only illustrate the development process of Dafny programs for two typical problems: the minimum contiguous subarray problem and the new local bubble sorting problem. It proves that our method can effectively improve the correctness and reliability of Dafny program developed. What’s more, we demonstrate the potential of the deductive synthesis method by developing a new local bubble Sorting program.