Reviewerly/exHarmony huggingface dataset:
Construction of Safe Transmission Model of Industrial Control Data Information in Internet of Things

The data information interaction between industrial control devices is frequent. Under the invasion of criminals, the leakage and tampering of industrial control data information occur frequently, which threatens the safety of industrial control data information transmission. Therefore, this paper puts forward a research on the construction of industrial control data information security transmission model of industrial Internet of Things. This paper analyzes the security vulnerabilities of MQTT (Industrial Internet of Things Communication Protocol), determines that the security transmission threats of industrial control data are data theft and man-in-the-middle attack, and explores the principle of industrial control data transmission. On this basis, TLS is used to encrypt the process of industrial control data transmission, and SEMA-E2C protocol is used to accurately authenticate the identities of both parties of industrial control data transmission, thus realizing the security transmission of industrial control data. The experimental results show that the minimum packet loss rate of industrial control data transmission obtained by using the constructed model is 3%, and the maximum safety factor of industrial control data transmission is 9.8, which proves that the constructed industrial control data transmission model is more secure.
A Novel Modulation Recognition Algorithm for Satellite Communication and TT&amp;C Signals

Electromagnetic signal modulation mode is one of the key elements of battlefield technical parameter information. This paper proposes an efficient modulation recognition algorithm for satellite communication and TT&C signals based on decision tree, which can accurately identify eight satellite modulation modes, including BPSK, QPSK, 2FSK, 4FSK, 16QAM, BPSK/PM, QPSK/PM and 2FSK/PM. The spectrum characteristics of the modulation methods commonly used in satellite communication and TT&C signals are firstly analyzed, and the main differences between and within categories of modulation methods of satellite signals are summarized; Then, rational feature parameters are selected and designed, and a complete modulation recognition process is proposed based on these parameters; Finally, the correctness and performance of the proposed recognition algorithm are evaluated by numerical simulation. The simulation results show that when the SNR (signal-to-noise ratio) of the proposed algorithm is more than 4dB, the modulation recognition accuracy of the eight satellite communication/TT&C signals can reach above 95%.
STRATEGIC PROJECTS OF THE UNIVERSITY AS A DRIVER FOR DEVELOPMENT OF THE REGION

Trends in the development of society show that the education system is on the verge of forming a new concept and new approaches to education. Reformatting the role of universities as major business players that set trends in innovation and professional training, the transition to a digital economy, and the formation of new global technology platforms.
Improvement of Chaotic Image Encryption Method Based on LDPC Code

Chaotic image encryption algorithm based on Low-Density Parity-Check (LDPC) code algorithm has the problem of high complexity and poor real-time performance. We choose the quasi-cyclic Low-Density Parity-Check (QC-LDPC) code instead of the Gallagher code in the algorithm and achieve better results than the previous one, especially in high-intensity noise. The watermark obtained by this method has high attack resistance and more resource saving in hardware. The QC-LDPC used in this paper is a code word constructed by the Fibonacci sequence, which has the advantages of small storage space, high flexibility, and high performance. Its excellent performance is also proved by its application in digital watermarking technology, which provides a reference for applying LDPC codes in more directions. Meanwhile, the practical applicability of LDPC digital image watermarking is further improved.
Research and Simulation of Population Forecast Based on BP Neural Network

According to the non-linear characteristics of population data. The BP neural network model for population prediction in China is established by analyzing and studying the structure design, number of neurons, transfer function and other aspects of the model. Based on the population data from 1961 to 2021 in China, the model was trained and simulated using MATLAB software. The results show that the trained model has high prediction accuracy and can be used for prediction. Finally, the training model is used to predict the population of China in the next 20 years. The results of the study can provide valuable reference for the decision-making of relevant departments.
Research on the Application of Blockchain Technology in Defense Engineering

In traditional national defense engineering management, there are problems such as lack of trust among project participants, difficulty in information supervision and traceability, information opacity and insecurity, and low degree of intelligence. In view of the shortcomings of traditional engineering project management methods, the construction based on blockchain technology It is hoped to provide reference for improving the efficiency of construction project management.
Research on intelligent language recommendation method based on emotion recognition

In this paper, an intelligent language recommendation method based on emotion recognition is proposed, mainly including text data acquisition and preprocessing from Chinese reviews, text feature extraction based on word embedding, emotion classification model based on deep learning, attention mechanism, etc. The experimental results show that the Chinese comment sentiment analysis model based on deep neural network proposed in this paper can accurately determine the user’s emotions contained in the text comments, and can adapt to the Chinese scene well. At the same time, the model in this paper guarantees the recognition efficiency.
Research on spatial data management and application

The characteristics of spatial data, such as wide variety, rapid growth of data production, and complex application, pose new challenges to spatial data information services. The research of this paper aims to meet the unified and efficient management of multi-source and heterogeneous data. Through data resource integration and information system integration, the ability of spatial data collection, aggregation, processing, analysis, sharing and service is comprehensively improved. Supported by service-oriented architecture, heterogeneous spatial data sharing based on Service GIS and data integration of multiple data sources based on different communication protocols, the system architecture is designed with spatial data exchange and service platform as the core. It supports the deployment of distributed spatial data management nodes. Under unified management and scheduling, all operations are published in the form of OGC services. Spatial data is stored in semi/unstructured files or structured tables. A unified, distributed and loosely coupled spatial information service system is built with the spatial data exchange and service platform which can provide basic and spatial data services and analysis and calculation services for existing and new information systems and application development. The spatial data application system establishes a big data resource pool of spatial information gathered from multiple channels, and realizes Informational, intelligent and standardized management in the whole process of data aggregation, data management, dynamic monitoring, business model building, decision support, etc. The system can provide comprehensive spatial data resource support, build an accurate spatial data service business model, and provide intelligent decision support for emergency rescue based on spatial data.
An efficient filtering technique for detecting traffic surveillance in intelligent transportation systems

A prospective system for traffic monitoring, vehicle surveillance, and vehicle control have become unavoidably necessary to support intelligent transportation systems (ITS) due to the rapid increase in vehicle numbers, traffic congestion, and security issues. Due to brightness changes, image subtraction, a standard method for recognising moving objects in films, is inefficient. Optimisation is needed for moving vehicle recognition and tracking despite the many methods available. The best car tracking algorithm for traffic footage with changing lights, backgrounds, and noises uses image and video processing. First, the input video is broken into frames of road visuals in various traffic scenarios. The input film is first split into frames of traffic scenes. A colour model distinguishes between road and car in these photographs. Noise removal creates the final image. Non-local means (NLMs) and trilateral filter (NLMTF), which eliminates Gaussian noise, is suggested here. Experimental results show that the suggested filter outperforms noise reduction algorithms like block matching and 3D filtering (BM3D), Shearlet transforms, and Mean filters in mean square error (MSE), peak signal-to-noise ratio (PSNR), and structure similarity index imatest (SSIM) and Python evaluation.
Creativity in education: managerial and psychological aspects

The main topic of the article is the issue of creativity in education, with the special emphasis of psychological and managerial aspects (can we manage creativity?). The importance of it especially high in the post-industrial era-based on information, knowledge, and creativity. As the goal behind education is the preparation of the student for the world, in which he or she will live and operate, it should aim at the stimulation of the student's creative potential. By nature, the human is a creative individual. The goal of education is the intellectual and individual development of the student, for which reason it should pursue the development of the student'screative potential and creative lifestyle. The four most important aspects of creativity are dispositions, achievements, process, and the environmental pressure. In the process of education, it is most important to concentrate on the development of creativity in the sense of disposition (creative potential). Needed for that is becoming as familiar as possible with the achievements of the great masters of culture, and learning to respect, collect, and register or record own achievements (however modest), mastering the basics of the creative process, and establishment of an environment favoring creativity.
Use of electronic educational resources in preparation of future educator of preschool education

The article discusses the problem of using electronic educational resources in teaching future educators methods of preschool education. The analysis of the study of the informatization of the educational process to achieve educational goals was presented. It was noted that electronic educational resources contribute to improving the quality of training of future specialists. Electronic educational resources have significant informational, didactic and communication capabilities. Electronic educational resources have the following functions: knowledge management, communication, joint student activity in macro and micro groups, knowledge control and assessment. Future educators learned about industry standards in higher education, the scientific foundations of professional activity, the essence of theoretical, methodological and technological training, the readiness of a future educator to learn methods of preschool education. The quality ofassimilation of teaching material by future educators depends on the use of electronic educational resources. It was found that the use of electronic educational resources is associated with the following aspects: educational and methodological aspects, such as the gradual assimilation of material by modules; organizational aspects, such as conducting training in a group and individually; aspects of control and evaluation, such as exercising control based on materials from a discipline. The consistent mastering by master's degree students of semantic modules of academic discipline by means of tools of electronic educational resources is presented. It is proved that future educators (master's degree students) understand the technological possibilities of using Prezi's multimedia presentation in education; they have the idea of a BibMe service for creating bibliographic references in the styles of APA, Chicago; students understand the synchronous andasynchronous modes of training for participants based on the program Adobe Acrobat Connect Pro; they own the technology and information tools of Moodle; they use Google Cloud cloud technology to implement the functions of communication, collaboration.
Socio-historical retrospective of the formation of educational systems: axiological principles

The article reveals the problem of cultural and educational processes in the context of socio-historical genesis of the axiological factor as the main factor for theformation of education and upbringing. The actualization of such a plan provides an opportunity to view the stages of development of education at the level of educational systems and the impact of value-semantic principles and moral and ethical norms of society on the formation of educational, cultural and upbringing. The author proves the fact that it is impossible to draw conclusions about the results of educational processes without systematizing the influences of society and public demands de jure and / or de facto existing at the level of education systems. The axiological factor has a decisive influence and depends on society's choice of value-semantic norms and guidelines as fundamental.
DISTRIBUTION AND MODERNIZATION OF ADVANCED PEDAGOGICAL PRACTICES IN THE LESSON PROCESS

The process of modernization in the socio-economic, cultural and educational spheres of the country has a direct impact on the system of continuing education. This, in turn, is an important characteristic of the modern educational environment and the improvement of educational paradigms with a special focus on the creative activity of students as a condition for the successful realization of personal potential requires the development of solutions to functional and conceptual problems.
Analysis of Accounting Information System in Supporting the Internal Inventory Control: A Case Study in Motorcycle Dealer

This study aims to analyse the inventory accounting system and its control in a company. The discussion in this study is to investigate accounting information system for spare parts inventory in supporting internal control at CV. X The data collection techniques are sourced from primary data and secondary data. The method used is descriptive qualitative method. The study revealed that the accounting information system for inventory was running well, evaluating from the recording method used by the company, namely the perpetual and computer-based method with an application called Komiaw, but in the reality there are several weaknesses, those are the existence of dual functions as well as discrepancies between the data of the goods and physical goods that are done by spare parts counter so as the repetition of inventory calculation occurred. Based on the results of this study, it showed that accounting information system for spare parts inventory can support internal inventory control in the company due to the implementation of the elements of accounting information system and the elements of internal control.
Detection of deepfakes using background-matching

In the recent years, the detection of deepfakes has become a substantial topic in image and video forensics. State-of-the-art blind detection methods can detect deepfakes from synthetic datasets with high accuracies. However, they struggle to classify deepfake material that underwent adversarial post-processing or fail to generalize to unseen video data. In this paper, a refined detection pipeline taking advantage of a semi-blind detection scheme is proposed. It combines background-matching with a state-of-the-art CNN-classifier. When classifying videos from the Deepfake Detection Challenge Dataset the CNN-classifier was previously trained on, the performance did not improve using the new detection scheme. However, the approach was able to achieve superior results on unseen data of the FaceForensics++ Dataset.
Evaluation of motion blur image quality in video frame interpolation

While slow motion has become a standard feature in mainstream cell phones, a fast approach without relying on specific training datasets to assess slow motion video quality is not available. Conventionally, researchers evaluate their algorithms with peak signal-to-noise ratio (PSNR) or structural similarity index measure (SSIM) between ground-truth and reconstructed frames. But they are both global evaluation index and more sensitive to noise or distortion brought by the interpolation. For video interpolation, especially for fast moving objects, motion blur as well as ghost problem are more essential to the audience subjective judgment. How to achieve a proper evaluation for Video Frame Interpolation (VFI) task is still a problem that is not well addressed.
Lightweight single pass numerical reading extraction for displays in the wild

Although considerable progress has been made in recognizing multi-character text from images, there are still cases where there is a lack of robust computationally-efficient methods that can execute on portable devices to read device displays in the wild. We specifically address the problem of parsing digits from 7 segment displays. Recognizing these displays is important for many tasks such as assisting users with tasks using augmented reality agents that need to verify actions or connecting legacy devices to the internet for process control using cheap cameras. Legacy techniques based on image processing operators and OCR are brittle whereas massive deep networks are too computationally expensive. We describe a computationally tractable VGG style backbone combined with a novel digit inference head that can be trained using a synthetic display generator with novel augmentations. We show the model trained on augmented synthetic data generalizes well to a corpus of real-world display images getting 97.8% single-frame accuracy and obtaining a throughput of 30 frames per second. We describe how the output can be further stabilized to improve accuracy through a kind of mode filtering.
Measuring camera information capacity with slanted-edges (Invited)

As Machine Vision (MV) and Artificial Intelligence (AI) systems are incorporated to an ever-increasing range of imaging applications, there is a corresponding need for camera measurements that can accurately predict the performance of these systems. At the present time, the standard practice is to separately measure the two major factors, sharpness and noise (or Signal-to-Noise Ratio), along with several additional factors, then to estimate system performance based on a combination of these factors. This estimate is usually based on experience, and is often more of an art than a science. Camera information capacity (C), based on Claude Shannon's ground-breaking work on information theory, holds great promise as a figure of merit for a variety of imaging systems, but it has traditionally been difficult to measure. We describe a new method for measuring camera information capacity that uses the popular slanted-edge test pattern, specified by the ISO 12233:2014/2017 standard. Measuring information capacity requires no extra effort: it essentially comes for free with slanted-edge MTF measurements. C has units of bits per pixel or bits per image for a specified ISO speed and chart contrast, making it easy to compare very different cameras. The new measurement can be used to solve some important problems, such as finding a camera that meets information capacity requirements with a minimum number of pixels, important because fewer pixels mean faster processing as well as lower cost.
Privacy preserving leak detection in peer-to-peer communication

During the pandemic the usage of video platforms skyrocketed among office workers and students and even today, when more and more events are held on-site again, the usage of video platforms is at an all-time high. However, the many advantages of these platforms cannot hide some problems. In the professional field, the publication of audio recordings without the consent of the author can get him into trouble. In education, another problem is bullying. The distance from the victim lowers the inhibition threshold for bullying, which means that platforms need tools to combat it. In this work, we present a system, which can not only identify the person leaking the footage, but also identify all other persons present in the footage. This system can be used in both described scenarios.
Biosensors for landing creative intent

The motivation for use of biosensors in audiovisual media is made by highlighting problem of signal loss due to wide variability in playback devices. A metadata system that allows creatives to steer signal modifications as a function of audience emotion and cognition as determined by biosensor analysis.
Integrity and authenticity verification of printed documents by smartphones

To this day, most important documents are still issued on paper. The security is based on the fact that the cost of creating a counterfeit must be unattractive for counterfeiters in relation to the expected profit. This results typically in using expensive printing equipment and substrate. This work introduces an approach which evaluates paper documents using any internet enabled device with a camera and a web browser like smartphones and tablets. Optical character recognition (OCR) is used to make text machine readable after the document is recognized and rectified. Digital signatures are then used to verify the authenticity and integrity of the data. Beyond that, the requirements of privacy, robustness and usability are satisfied. By using JAB Code, a high-capacity matrix code, the data to be verified can be stored directly on the document without having to use a database. This brings key advantages compared to database-bound systems in terms of security and privacy. The use of OCR achieves high usability.
Structure of Salp Swarm Algorithm

This chapter explains the theory of the salp swarm algorithm (SSA). The SSA can be easily implemented. Also, adjusting SSA parameters is easy. The fast convergence and high accuracy are the advantages of SSA. The SSA can be coupled with optimization algorithms to solve complex problems. SSA is an example of a strong algorithm. This algorithm has few parameters. The best solution in the algorithm will guide the other solutions. The SSA can be coupled with soft computing models for finding their parameter values.
Structure of Crow Optimization Algorithm

This chapter explained the structure and mathematical model of the crow optimization algorithm (COA). A characteristic of crows is hiding their food. COA’s mathematical model is defined based on the mechanism of hiding food. The algorithms can be used for solving complex problems such as the optimal operation of dam reservoirs, training soft computing models, optimal design of structures, and flood control. The COA can be easily implemented. The fast convergence is another advantage of COA. The COA has high efficiencies for solving multi-objective optimization problems. The COA can be easily coupled with different optimization algorithms.