Reviewerly/exHarmony huggingface dataset:
Digital Watermarking Image Using Discrete Wavelet Transform and Discrete Cosine Transform with Noise Identification

In today's world, the security of digital multimedia content has become a significant concern. At the same time, the crime rate is increasing day by day, and cybercrime is one of them. At present, criminals are involved in various crimes at different times with images. As a result, innocent people are acknowledging it. This study makes an important contribution to the field of image processing. This paper will discuss how to protect an image from copyright. Also, what kind of noise is in a picture, and are their histograms. So criminals can't easily harass people, and a commoner can become a criminal without committing any crime. For this reason, this paper will use watermarking to protect the copyright. Watermarking an original image is accomplished using two methods: DWT and DCT. The proposed method decomposes the original image into low and high-frequency components using a one-level discrete wavelet transform (DWT). The average of each sub-band is calculated. Using the discrete wavelet transform, a watermark is embedded into the original image's one-level low-low (LL), high-low (HL), low-high (LH), and high-high (HH) subbands. Another image watermark that makes use of the discrete cosine transforms. This paper discusses the challenges and requirements for modeling a figure in the MATLAB watermark decoding system using discrete cosine transforms, discrete wavelet transforms, noise identification, and histograms. Watermarking is also covered in this study, with copyright protection being listed as the main copyright protection method for both the original and watermarked image.
Emonotate: Development a Tool for Collecting Appraisal Trajectories for Time-Series Media Contents

In the field of storytelling and filmmaking, we are often aware of the viewer&#x0027;s subjective state, such as emotional state and so on. A similar concept is direction, which is often accumulated by the heuristic findings of creators. The issue is that the emotional state of the viewer is subjective, making it hard for computational approach. Our approach is utilizing appraisal trajectory. The appraisal trajectory is a line chart drawn the viewer&#x0027;s own emotional state from the beginning to the end of the content. We think that the appraisal trajectory enables us to handle the viewer&#x0027;s emotional state with a computer. We think to need accumulate basic findings about subjective trajectories; therefore, we develop a tool to collect subjective trajectories: emonotate. This tool provides some features: input and store the various emotional states of viewers and viewers intuitively agreeable input by visual feedback of arbitrary appraisal trajectories. In order to evaluate the validity, we conduct the experiment of 104 participants drawing subjective trajectories based on protagonist emotional state about 2 animation contents and the subjective quantity is the protagonist emotional state. Both works yielded intuitively correct results, demonstrating the realism of our tool. We think our experimental facts indicate the possibility of our tool collecting subjective trajectories and the issues.
Muscle tone control system based on LIF model neural network

The article describes the solution to the control problem using machine learning. The article presents a model to simulate muscle tone. Based on spiking neural network control system was designed. The task of the neural network was to find a control function to maintain the muscle length. A LIF model of a spiking neural network was used. Excitatory signal was produced by muscle activity. Inhibitor signal was produced by motor neuron activity. Numerical simulations were performed and analyzed. A critical value of synapse weight was found. This value can be understood as a bifurcation parameter of the dynamic system.
Sensor Fusion and Optimal Platform Trajectory Planning for Ground Target Localization with Terrain Uncertainty and Measurement Biases

A ground target can be localized using an airborne angle-only sensor. However, possible measurement bias causes a delay in error convergence. Adding measurements from a range-only sensor can improve localization by attaining faster convergence. Estimation accuracy can be improved further by optimizing the trajectories of the platforms containing the angle-only and range-only sensors. To ensure observability in 3-D localization, in most of the recent works, the height of the ground target from the sea level is assumed to be known perfectly. However, in most practical applications, target height is obtained from a Digital Terrain Elevation Database (DTED), having multiple levels of resolution. As a result, in addition to the bias uncertainty, the terrain uncertainty is required to be handled. In this work, Cramer Rao Lower Bound (CRLB) is derived for the localization problem considering the terrain and measurement bias uncertainties. A CRLB based optimization algorithm is proposed for optimal platform trajectory planning. We propose two localization approaches to handle the biases. The first approach involves bias compensation using a prior whereas the target and bias states are estimated jointly in the second approach. In both approaches, range sensor fusion is proposed to improve localization accuracy. The effectiveness of our algorithms is verified using Monte Carlo simulations.
Automatic Tutorial Generation from Input Text File using Natural Language Processing

In the present scenario, it has become a major necessity to create easy-to-access, easily-understandable and less time-consuming resources/tutorials. Our application proposes to create a full-fledged tutorial, provided an input in the form of a text file (txt/pdf). We have adopted a generator-subscriber model with role specific duties. The generator is provided with the option to generate tutorials and the subscriber can view/access the tutorials. The input provided by the generator is analysed to identify headings, subheadings and paragraphs as a hierarchy. Additionally, the uploaded material is summarised and a concise presentation with audio voiceover, to enhance comprehension of the user, is presented for quick learning. Furthermore, to ensure user interaction, assessments in the form of multiple-choice questions are dynamically created from the uploaded material. The scores of assessments are instantly provided and the subscriber's performance is recorded to show progress. The application is further extended to handle multimedia input in the form of images. In order to increase the usability of the application and make it accessible to a wider population, language agnosticism has been attempted. The features of language agnosticism are currently concentrated on Indian languages (Kannada and Hindi). A complete user-friendly web interface with a catalogue of automatically generated tutorials is provided for easy use of all the features and hassle-free learning.
Leveraging Technology to Enhance Effective Electronic Policing in Developing Countries

In Namibia, the introduction of electronic policing (e-policing) has brought changes in the organisation of Police work, mainly recording, storing, and sharing of Police information electronically for the betterment of Police service delivery. The introduction of e-policing in Namibia also came with challenges such as backlog of cases not updated on time. The purpose of this study is to assess the challenges brought by implementing e-policing and propose better strategies to curb the challenges. A quantitative approach was used to analyze data obtained through structured questionnaires. The research aims to focus on the following sub-objectives: to assess the current organisation policy on e-policing system; to investigate the challenges of implementing e-policing, and recommend strategies that can be used for a successful implementation of e-policing through studying relevant literatures. The research identified that Police officers understand e-policing differently and the major challenge faced by the organisation is budgetary fund allocation.
A Multilevel Clustering Model for Coherent Topic Discovery in Short Texts

Deducing meaning from collections of documents has become an increasingly important task for decision makers, both in industry and academia. To address this challenge, topic modelling techniques have been developed to identify and isolate words that most closely summarise the contents of document collections. However, the topics extracted from collections of short texts by these techniques, achieve low coherence scores, thereby defeating the purpose for which these techniques were created. In this paper, we propose the n-gram_cluster model, a model that exploits the semantic closeness between n-grams and word clusters formed from collections of the n-grams at different levels to discover topics. The model is able to discover semantically coherent topics from collections of short texts. We evaluated the performance of our model against those of three other conventional models showing that it is able to form topics that achieve comparatively higher coherence scores.
Aircraft Route Planning and Local Dynamic Obstacle Avoidance

This paper proposes a track planning method based on optimized A* algorithm and a dynamic window method path planning method under sudden threats. Using a real geographic elevation data model, the global path of the aircraft is obtained by using the A* algorithm planning after the improvement of the Dubins curve. This paper analyzes the sudden dynamic threats and external obstacles that may be encountered by the aircraft during flight, and uses the DWA algorithm to achieve the dynamic local obstacle avoidance goal, and simulates the simulation to verify the feasibility of the proposed method.
Professional education in Russia: from standards to educational programs

The problem of modernization of federal state educational standards, which no longer meet the requirements of the sphere of labor, is considered. It is proposed to use a common approach to the training of an engineer and a bachelor of engineering and technology, whose competencies are reduced in a broad sense to the ability to research, design and manage. The general professional and professional competencies of a graduate of this field (specialty) should be formulated in the main educational program of each university. It is recommended to develop educational standards for the levels of training for the relevant fields of activity (science, technology, pedagogy, medicine, etc.). The need to improve the management system of training for the modern economy is shown.
Education master’s degree students’ creative activity enhancement by means of immersion technology

Introduction. The necessity of master’s degree students’ creative activity enhancement during their future professional activity of a foreign language teacher in a higher school simulating and insufficient development of a technological aspect of the problem highlight the search for perspective pedagogical ways, among them on the basis of immersion technology. The aim of the research is to develop and implement master’s degree students’ creative activity enhancement experimental program which discovers methodological and technological support of the process studied and also identification and scientific justification for pedagogical conditions for its effective implementation. Materials and methods. 68 master’s degree students of the first and second courses of Voronezh state pedagogical university and Bunin Yelets State University (Russian Federation) participated in the pilot study. The level of master’s degree students’ creative activity was diagnosed on the basis of K. Zamfir’s method (A. Rean’s modification) of studying professional activity motivation; V. I. Andreev’s test “Self-development and self-education abilities assessment”, the authors’ questionnaire; the method of expert assessment; the method of self-evaluation and portfolio’s developments. The data processing was carried out on the basis of the χ2-Pearson statistical test. Research results. The first developed program of education master’s degree students’ creative activity enhancement on the basis of system, personal and activity oriented, professionally oriented approaches and identified pedagogical conditions for its implementation using the immersion technology potential allow to develop deliberately and gradually motivational, cognitive, activity oriented and reflexive component of creative activity. Effectiveness and appropriateness of the authors’ program and pedagogical conditions for education master’s degree students’ creative activity enhancement were proved (χ2 = 9.460 &gt; χ20,05). Conclusion. The program predicts a tutorially methodological set development contributing to organization and technique support of education master’s degree students’ creative activity enhancement.
Mining Data on Computing Majors Knowledge Game

Computing as a discipline is still very young, and there is much confusion about distinguishing the majors within the discipline. In the early 2000's, paper surveys were administered to distinguish between five computing majors: Computer Science (CS), Information Technology (IT), Information Systems (IS), Computer Engineering (CE), and Software Engineering (SE). Since then, Data Science, Cybersecurity, and other new majors have joined the computing discipline. We explored participants' current knowledge of modern computing majors at our institution via a modern web-based word cloud matching game. Word clouds were created by scraping Oregon Institute of Technology course descriptions for computing majors: applied mathematics (Math), data science (Math), cybersecurity (Business Management), and Computer Systems Engineering Technology (CSET) majors including embedded systems engineering technology, software engineering technology, and computing engineering technology. We invited 97 incoming freshmen to participate; 26 did. Our results showed that computing majors within departments are more difficult for participants to distinguish than computing majors across departments. Majors within the CSET department were most varied in results with embedded systems technology being the most confusing to participants. The applied mathematics major in the mathematics department was the easiest for participants to distinguish. Limitations of our work include a small sample and computing disciplines specific to our institution. Our contributions include an automated way to generate major descriptions using existing resources (catalog entries), an updated approach to collecting data that may be more motivating for students, and an updated list of computing majors including the emerging majors Data Science and Cybersecurity.
Research on watermarking removal algorithm based on deep learning

Noise2noise is a classical algorithm for image denoising in neural network deep learning. In this paper, some improvements are made to Noise2Noise (N2N for short), such as changing the underlying network of the original network to empty convolution, using SRResNet in SRGAN to improve the image quality, and selecting an adaptive parameterized Relu activation function. At the same time, the improved N2N algorithm is trained and tested by using self-built watermark data set. Experimental results show that the improved N2N algorithm can achieve good watermark removal effect, and can not only remove single visible watermark, but also remove large-scale watermark images in batches, which has strong practical value for image restoration and other fields.
Diagnostic Accuracy of Combining Sonoelastography with Mammography in Solid Breast Lesions Keeping Histopathology as Gold Standard

&lt;p&gt;&lt;strong&gt;Background and objective:&lt;/strong&gt; Breast cancer is the most common malignancy in females. Early diagnosis can help in reducing the morbidity and mortality associated with this disease. Sonoelastography has shown to be a valuable tool in early detection of breast cancer. The aim of the study was to evaluate the diagnostic accuracy of combining sonoelastography with mammography in diagnosing malignant solid breast lesions taking histopathology as a gold standard.&lt;br /&gt;&lt;strong&gt;Methods:&lt;/strong&gt; A descriptive cross-sectional study was carried out at the Department of Radiology, Shaikh Zayed Medical Complex/Federal Post-Gradaute Medical Institute (FPGMI), Lahore, Pakistan during six months period from 1st September, 2018 to 31st March, 2019. Female patients &amp;gt; 35 years of age and presenting with suspected malignant breast masses were included. Mammography and sonoelastography of the lesions were done. Finally, the patients were referred for tru cut biopsy. Diagnostic accuracy was calculated for mammography, sonoelastography and their combination.&lt;br /&gt;&lt;strong&gt;Results:&lt;/strong&gt; A total of 200 female patients were enrolled with a mean age of 50.8 (&amp;plusmn; 8.6) years. Mammographic findings suggestive of malignancy (BI-RADS category IV and V) were present in 96 (48%) cases. Elastography showed finding of malignancy (Score 4 and 5) in 96 (48%) cases. Combined sonoelastography and mammography diagnosed malignancy in 112 (56%) cases. Histopathologically confirmed malignancy was seen in 110 (55%) cases. The sensitivity and specificity of mammography (76.3 % and 77.7%) and sonoelastography (77.3% and 87.7%), were comparable. The combination of mammography and sonoelastography showed a higher sensitivity (90.9%) and specificity (86.6%). The combination showed a diagnostic accuracy of 89% followed by sonoelastography (82%) and mammography (77%) alone.&lt;br /&gt;&lt;strong&gt;Conclusion:&lt;/strong&gt; Combination of sonoelastography and mammography can significantly enhance the diagnostic accuracy of breast carcinoma. Females may be offered mammography or ultrasonography in combination with sonoelastography for routine testing.&lt;/p&gt;
Investigation on the influence of WeChat public account on the teaching and learning of chemistry based on fuzzy search and mathematical statistics in large datasets

In the information age, the way people receive information is becoming more and more diversified. The popularity of WeChat provides a new way for information dissemination. WeChat public accounts have gradually been tapped to assist the teaching and learning of chemistry, which greatly promotes teaching and learning efficiency. By investigating the application of domestic WeChat official accounts in chemistry based on fuzzy search and mathematical statistics in large datasets, this article suggests that chemistry official accounts are currently mainly used in chemistry in universities, while there are very few applications in basic middle school chemistry fields. The application and research of public accounts in basic chemistry has a broad space for development.
Implementation and study of user strategies within a custom video game environment

research-article Share on Implementation and study of user strategies within a custom video game environment Authors: Nick Iliadis Ionian University, Greece Ionian University, GreeceView Profile , Stergios Palamas Ionian University, Greece Ionian University, GreeceView Profile , Phivos Mylonas Ionian University, Greece Ionian University, GreeceView Profile Authors Info & Claims PCI 2021: 25th Pan-Hellenic Conference on InformaticsNovember 2021 Pages 45–51https://doi.org/10.1145/3503823.3503832Online:22 February 2022Publication History 0citation22DownloadsMetricsTotal Citations0Total Downloads22Last 12 Months22Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Pengaruh Sistem Informasi Akuntansi, Komitmen Organisasi dan Disiplin Kerja Terhadap Kinerja Pegawai Skpd Di Kota Makassar

This research aims to know and analyze Accounting Information System to SKPD in Makassar, either simultaneously or partially, and also organizational commitment and work discipline to officer performance at organization to reach target. This research object is financial management staff at SKPD in Makassar as subject with number of respondent 54. Data obtained in this are primary data from staff through the distribution of questionnaires obtained from SKPD in Makassar. Data analytical method in this research applies regression analysis is using multiple regression analysis by SPSS program. Result showed that: variable Accounting Information System, Organizational Commitment and Work Discipline significantly and simultaneously have a positive impact to The Quality of financial management staff at SKPD in Makassar
Thank you to our referees <b>April 8, 2021–May 31, 2022</b>

I’ve always been fascinated by fractals, especially the Sierpinski gasket, shown at right, and in a beautiful pyramidal arrangement in the background of this spread. To make such a gasket, all you do is remove the interior of the middle equilateral triangle (the upside down one) over and over again, at successively smaller and smaller scales. What results is something that is more than one dimensional, but less than two dimensional—in fact, it can be shown to have dimension D, where D is given by the relation 2D=3, or D ≈ 1.585…. In this issue of TPT, we feature on page 410 a paper by Charles Creffield, “Fractals on a Benchtop: Observing Fractal Dimension in a Resistor Network,” where he details how his students set up resistors in a similar network and mimic fractal resistance effects … doubly fascinating! I wanted to share this imagery with you in appreciation of the hundreds of generous, smart, and gracious individuals who serve as TPT referees. When I look over this list of names, I see many of the people I admire most in the world, and it makes me optimistic in a way that few things can these days. If you see someone you know in this list, please find a way to express your thanks for all they do for TPT and for physics teachers and students everywhere. When I imagine all the connections between the people on this list, it calls to my mind all of the connections between the dark regions in the figure at right—a Sierpinski gasket of physicists, held together by their common ideas. What could be more fun to think about!? Thank you, again, dear referees; you are the glue that holds this community together, in my view.
Replicability Analysis

In the previous chapters, we have discussed statistical significance testing in the world of NLP, connected between evaluation metrics and the suitable significance tests, and presented the selection process in a simplified version of a relatively intuitive decision tree. Following, we extended our discussion to statistically sound comparison between non-deterministic models such as DNNs. However, we have only addressed the use of one dataset per comparison. Nowadays, with the ever-growing amount of textual data from various languages, domains, and genres, evaluating NLP algorithms on multiple datasets has become a standard, as such a multitude of tests ensures a consistent performance across heterogeneous setups.
Boolean Logic and Truth (Values)

Logic is the basis of proof. The history of logic takes place literally over thousands of years. While valid reasoning has been around even longer, logic, which studies the principles of valid reasoning, has been around since at the very least ancient Babylon. However, some of the logic which is commonly encountered in modern society has only been around for a surprisingly short period of time. Boolean logic, invented by George Boole (1815-1864), the logic on which all of computer science and the modern information age is founded, has only been around from the mid-19th century onward.