Reviewerly/exHarmony huggingface dataset:
Shot Segmentation Based on Feature Fusion and Bayesian Online Changepoint Detection

Shot segmentation is an important technology in video analysis. Traditional shot segmentation methods usually need to set thresholds in advance. Due to the diversity of shot types, it is usually difficult to set appropriate thresholds for these segmentation. In this paper, a new shot segmentation method is proposed, which combines feature fusion with Bayesian online changepoint detection. Firstly, the HSV quantitative color features of video frames are extracted and a new feature MEP is constructed. The comprehensive similarity of MEP features of two adjacent frames is calculated. Then, Bayesian online changepoint detection algorithm is applied to detect the comprehensive similarity. The location of the changepoint detected is the position of shot segmentation in the video. The experimental results show that Bayesian online changepoint detection has the ability to distinguish different shots. The average Recall and Precision of our method are over 0.90, which is more accurate than the results of the methods which used to compare with our method.
A Two-Stage Approach for Commonality-Based Temporal Localization of Periodic Motions

We present an unsupervised method for the detection of all temporal segments of videos or motion capture data, that correspond to periodic motions. The proposed method is based on the detection of similar segments (commonalities) in different parts of the input sequence and employs a two-stage approach that operates on the matrix of pairwise distances of all input frames. The quantitative evaluation of the proposed method on three standard ground-truth-annotated datasets (two video datasets, one 3D human motion capture dataset) demonstrate its improved performance in comparison to existing approaches.
SmartEdu: Dedicated Online Learning Evaluation Device Based on Android Smartphone

This paper discusses a dedicated online learning evaluation device, based on Android smartphone, which is able to offer an instant learning evaluation result while preventing cheating during the evaluation process. Before learning activities begin in a classroom, ideally the instructor knows the participants' knowledge about a learning topic. This requires a learning evaluation system that can measure the participants' knowledge instantly. Using this system, the instructor can focus on teaching a specific topic that has not been understood by the participants. This research proposes a solution for online learning evaluation process, using a customized smartphone called SmartEdu device, which can give instant results of the participants' knowledge. The SmartEdu devices, owned by the educational institution, are distributed to participants before the learning process begins and returned after the learning process finished. Using the SmartEdu device, a participant login to the SmartEdu application that runs on a server in the cloud or local data center. The SmartEdu devices connect to the server wirelessly through a specific access point that connected with the server. The SmartEdu devices are stored on a special mobile box (container) that has dockings to keep the devices secured during traveling, and recharged while the devices on the dock. Moreover, the devices will be automatically memory cleared while on the dock. This will prevent the device to be personalized by participants, and reduce the possibility of cheating.
Teaching graduates for successful employment and career planning as the university educational priority

The issues of career planning and building up, employment and graduates’ adaptation remain relevant and require new approaches to solving the problems of professional identity and formation in the modern world of labour and occupations. The graduates have difficulties in searching for a suitable job in their degree field mostly due to the lack of work experience. On the other hand, young people have great potential. They are quick to study, mobile; able to adapt to new situations and sensible in their approach to labour supplies. The task of a career advisor is to help young people to professionally identify themselves and acquaint them with modern theories of career building and employer requirements. The percent of employed graduates is established on the basis of statistical research and data processing. These are the data obtained in the course of graduates’ career monitoring. The main method of collecting data to study graduates’ employment is the method of dynamic and comparative monitoring. The subject of the research is the data obtained in the course of monitoring analysis. The purpose of the paper is to introduce the experience in developing student job-hunting skills, business career development and management in Nizhnevartovsk State University. The author introduces a modern vision of professional identity process based on psychological and sociological theories. The paper is grounded on the graduate employment studies and provides recommendations, forms and methods of interaction with students to assist successful graduate employment in their degree field
Análisis de señales para la detección de armónicos basado en el espacio complejo

This work presents harmonic detection through signal analysis in complex space. This method obtains the point-to-point división of the present sample by the last sample of the Lissajous curve which is generated by two signals in complex space. Then, the angle is calculated to each element to obtain the behavior. The obtained features provide numerical information of the frequencies that form a signal. This is obtained without space transformation or operation with high computational cost.
Target Image Mask Correction Based on Skeleton Divergence

Traditional approaches to modeling and processing discrete pixels are mainly based on image features or model optimization. These methods often result in excessive shrinkage or expansion of the restored pixel region, inhibiting accurate recovery of the target pixel region shape. This paper proposes a simultaneous source and mask-images optimization model based on skeleton divergence that overcomes these problems. In the proposed model, first, the edge of the entire discrete pixel region is extracted through bilateral filtering. Then, edge information and Delaunay triangulation are used to optimize the entire discrete pixel region. The skeleton is optimized with the skeleton as the local optimization center and the source and mask images are simultaneously optimized through edge guidance. The technique for order of preference by similarity to ideal solution (TOPSIS) and point-cloud regularization verification are subsequently employed to provide the optimal merging strategy and reduce cumulative error. In the regularization verification stage, the model is iteratively simplified via incremental and hierarchical clustering, so that point-cloud sampling is concentrated in the high-curvature region. The results of experiments conducted using the moving-target region in the RGB-depth (RGB-D) data (Technical University of Munich, Germany) indicate that the proposed algorithm is more accurate and suitable for image processing than existing high-performance algorithms.
TQR-Net: Tighter Quadrangle-Based Convolutional Neural Network for Dense Building Instance Localization in Remote Sensing Imagery

Building localization in remote sensing imagery (RSI) is widely applied in many geoscience and remote sensing areas. However, many existing methods cannot generate accurate building contours. In this paper, we propose an effective convolutional neural network (CNN) framework, Tighter Quadrangle Network (TQR-Net), to locate buildings with quadrangular contours in RSI. Here, TQR-Net can generate regular contours for each of building targets using a CNN branch which can predict tighter quadrangles in parallel. Then, we train and test TQR-Net on a large building dataset collected from Google Earth, and the experiment results demonstrate that the proposed method can generate high-quality building contours and significantly outperforms other CNN-based detectors.
Effects of the Digital Revolution on Teaching and Education

The paper analyzes results related to the didactic activity carried out for more than 30 years, but for the two centuries of interpenetration, where technological changes have put more challenges to education than ever before. It presents both institutional and individual ways of communication, relationship and relationship with students in order to obtain a quality education. A case study, based on the answers of students from different education cycles to a questionnaire written by the authors, completes the analysis. The study presents selective aspects of a wider analysis of electrical engineering, conducted in 2018, by the Association for Education in Electrical Engineering.
Research and Implementation of Security Technology in Campus Network Construction

The current campus network has become the basic equipment in campus construction. The safe and reliable campus network not only can utilize various resources inside and outside the schoolreasonably, safely and effectively, but also improve the working environment of the campus network, facilitate the management and maintenance of the campus network, and improve the reliability of the campus network. Therefore, it is especially important to build a reasonable campus network security system; Based on the security design in the network construction of a university campus network, this paper analyzes comprehensively the possible security problems, the current security status of campus network and the needs of campus network security. Based on the existing information organization structure of colleges and universities, this paper uses various management methods and technical methods to divide the campus network into various functional area modules, and deploys corresponding solutions in each regional module to solve the network security existing in the campus network. The problem is ultimately to protect the online system resources and services, and to alleviate the security threats of the campus network.
Wide-frequency Domain Position Actuation Control Signal Detection System Based on Wavelet Transform

The landing gear is one of the important components of the aircraft. It plays a key role in the safe take-off and soft landing of the aircraft. The pilot receives the position of the proximity sensor from the PACU (Position Actuation Control Unit) after issuing the command of the landing gear. The opening of the EE door and the retraction of the landing gear are controlled by the signal. In this thesis, the PACU ground simulator is designed for the PACU system of a certain type of aircraft landing gear. The ground simulator is used to obtain the wide frequency domain response signal and surrounding vibration noise signals of certain light aircraft model of the PACU proximity sensor. The wavelet transformed method is used to eliminate the vibration noise. The noise reduction processing is performed, and the curve of noise-reduced signal is compared with the curve of real signal. It is shown that error is within range. After testing, the ground simulator has a good function and the system is stable.
Embedding Rotate-and-Scale Net for Learning Invariant Features of Simple Images

Learning invariant features is important to computer vision tasks such as image classification or object detection. Rotation and scaling may dampen the classification/detection performance regardless of how deep nets are because most objects in image datasets are upright and have a suitable size. Existing methods often implicitly employ the data augmentation strategy to accomplish a better recognition performance. The problem with the data augmentation strategy is that it significantly increases the computational complexity and the training time. To address this problem, we propose Rotate-and-Scale Net (RSN) to be easily embedded in convolutional neural networks, making them invariant to rotation and scaling. The key insight of RSN is to mimic the recognition mechanism of human beings through parallel Siamese networks. It does not require data augmentation strategy hence have the advantages of having fewer parameters and needing fewer samples. We have validated the proposed method on three datasets including MNIST, MNIST-12k, MNIST-scaled and MNIST-rand datasets. Experiment results show that RSN compares favourably to the state-of-the-art in classifying/recognising rotated and scaled images in some way.
A Comprehensive Solution to the Problem of the Development of Drawing Skills with the Help of Didactic Equipment

The authors of the article propose to use the didactic complex for morphological analysis in order to comprehensively solve the problem of drawing skills development at the beginning stage of training design students. This didactic complex includes visual didactic equipment and multimedia kit. In the course of the study general pedagogical methods were used: scientific and methodological literature analysis, pedagogical process planning, working methodology approbation. The project conception process was based on the system design methodology. The theoretical basis of the study is the works on the system design theory and the art education theory. The authors describe the requirements that the designer must take into account when designing didactic equipment; represent the structure of the didactic equipment and multimedia kit; offer options for working with elements of the didactic complex for morphological analysis.
Research Progress Discussion on Deep Language Signal and Information Processing

Abstract This article focus on the progress discussion of deep speech signal and information processing. It will combine theory with practice, and deeply analyze the research progress of speech recognition technology, speech blending technique, and speech intensified technique. Based on the big data and cloud computing, the conclusion of valuable information can be effectively identified through deep speech signal and information processing technology. Hope it will help the relevant units.
Eye-Tracking Data Analysis During Cognitive Task

This work investigates the use of eye-tracking as a method for analysis of mental effort in cognitive tasks. From a trivial task of counting objects, the proposal of this work is to present a study on the reactions of the nervous system through visual stimuli to the cognitive system. Our experimental results show that there is a relationship between the cognitive load and pupillary diameter variation, reinforcing the idea that the pupil is a sensitive indicator of mental effort. We believe that pupil diameter measurement can be used as a performance descriptor in cognitive tasks.
Developing a Microservices Software System with Spring Could – A Case Study of Meeting Scheduler

The traditional monolithic architecture is to implement the function modules of the application and execute them on the same service port. The entire application system must be repackaged and deployed if there is a program change. With the increase of requirements, the coupling relations between modules become more and more complicated which results in inflexible function expansion and difficult maintenance. Microservices architecture divides a single application into several independent executed services with its business logic and communicates with each other using the REST API or message queue. Therefore, the scalability and maintainability of the system are improved by features such as independent update and independent deployment. This study implements a Meeting Scheduler monolithic software system using traditional object-oriented software development process. To transform the software into a microservices architecture, the Spring Cloud framework is used to implement the required microservices in the Meeting Scheduler. After completing the transformation from monolithic to microservices architecture, this study explores the development experience of microservices software and establishes a microservices architecture transformation process for software engineers to analyze, design, implement and deploy a software based on microservices.
Learning Based Image Selection for 3D Reconstruction of Heritage Sites

In this paper, we propose learning based pipeline with image clustering and image selection methods for 3D reconstruction of heritage site using cleaned internet sourced images. Cleaned internet sourced images means the images that do not contain an image with text, blur, occlusion, and shadow. 3D reconstruction of heritage sites is one of the emerging topics and is gaining importance as efforts are made to digitally preserve the heritage sites. 3D reconstruction using internet-sourced images is challenging as they often contain thousands of images taken from the same viewpoint. We propose to use autoencoders to extract robust features from images to cluster similar parts of heritage sites. We propose to use the image selection algorithm to select images from each cluster with the removal of redundant images. We demonstrate the proposed pipeline using available 3D reconstruction pipeline for a variety of heritage sites which contain one cluster to eight clusters and obtain better visual 3D reconstruction.
Analysis of Random Mixed Image Encryption Algorithm Based on QoS

In this paper, a hybrid chaos image encryption method which distinguishes the transmission quality of communication network is proposed. The algorithm combines chaos encryption algorithm with wavelet transform. First, the digital image is decomposed by wavelet to generate approximate image, low-frequency horizontal component, low-frequency vertical component and high-frequency component. The communication parties can encrypt only approximate graph in the network with poor transmission quality by using the random hybrid chaos time series proposed in this paper. In the good transmission quality network, each component can be encrypted and transmitted at the same time. Finally, the original image can be restored lossless by wavelet reconstruction. The experimental results show that the auto-correlation, cross-correlation, run-length and balance characteristics of the encryption sequences generated by this algorithm are excellent. On the premise of avoiding the complex operation of high-dimensional chaos mapping, the encryption intensity and cracking difficulty of the system are greatly improved, and the problem of image security requirements under different conditions is effectively solved.
Salient regions detection in satellite images using the combination of MSER local features detector and saliency models

Salient regions detection in satellite images using the combination of MSER local features detector and saliency models
Rural Libraries in China: Towards Educational and Informational Equality of Population

The article discusses the policy of the People’s Republic of China to expand, develop and modernize the network of rural libraries, introduce new standards of activity and innovative forms of work aimed at equalizing the imbalance between the city and village by increasing the cultural and educational level and overcoming the information poverty of local residents. The author characterizes the government programs of the People’s Republic of China in this area, adopted over the past two decades: “Cultural Information Resource Sharing Project” (2002), “Comprehensive Cultural Station Construction Project” (2006), “Farmer’s Reading Rooms Project” (2007), “Working Opinions on the Promotion of the National Art Gallery, Public Library, Cultural Centres and Stations Free to All” (2011), “Public Electronic Reading Room Construction Plan” (2012), “Support Plan for Libraries in Poor Areas” (2014), as well as the “Plan for Modernizing the System of Providing Public Services in the Sphere of Culture” and the “National Program for Promoting Reading” for 2015—2020. The article considers the structure of the library network in rural regions of China and the functions of its structural units, financing and human resources of rural libraries, the organization of stationary and extension library services, the requirements for premises, collections, technical equipment and the provision of remote access to information sources. Special attention is paid to the implementation of programs in rural regions of the country to promote digital reading and connect libraries to the services of the National Digital Library (under the guidance of the National Library of China). The article outlines the main problems existing in rural libraries of the People’s Republic of China, and the ways of their solution proposed by Chinese specialists. The author emphasizes that the Chinese experience may be of interest to Russia, taking into account the challenges facing our country in sustainable development of rural areas, which is not feasible without improving the standard of living of the rural population and providing it with high-quality educational, cultural and information services.
An End-to-End Named Entity Recognition Model for Chinese

Abstract Named entity recognition is an important basic task in natural language processing. This paper proposes a named entity recognition method for end-to-end and efficient deep-loop neural networks. Using BERT to train sub-vectors as raw input enables the model to obtain more comprehensive text information, and at the same time, the BiLSTM network is focused on the attention mechanism, so that the network pays more attention to the key information in the text and ignores the redundant information to improve the recognition efficiency of the model. Finally, the relationship between any two tags is captured by the CRF layer, and the entire sentence is decoded and predicted. Experiments show that the method performs well on MSRA corpus.
Encryption Application Using Verifiable Secret Sharing Scheme

Secret sharing scheme is used to produce a secret key obtained from a calculation against a certain number of keys in a group. The problem occurs when one or more keys in the group are fake or intentionally faked. A verifiable secret sharing system is proposed in this paper so that it detects any fake keys in a group before being used for resulting the right secret key. Initial system definitions are the basis for writing codes in its system development. Units and integration test is implemented when all units of the system is ready. Repetition is applied to its development stages until the test results show that all system functionalities are working as expected and the system has succeeded in detecting fake keys in the group.
Web Security Using User Authentication Methodologies: CAPTCHA, OTP and User Behaviour Authentication

When we refer to the Banking Systems then the security is at a higher stake since the time internet crossed roads with the banks. The data security is very critical to be managed since the last few years due to various hacking techniques. When we are so much dependent on web then it creates a dread of loss to our data. The statistics also reveal that 15 million people across United States become a victim to Identity Theft, online. There is a collective loss of $50 billion. 100 million Americans faced problems due to these online data thefts or Identity Thefts. The paper discusses the methodologies for CAPTCHA, OTP and UBA for user authentication and we also discuss about the web security through these methods.