Reviewerly/exHarmony huggingface dataset:
Adaptive interpolation with maximum order close to discontinuities

Adaptive rational interpolation has been designed in the context of image processing as a new nonlinear technique that avoids the Gibbs phenomenon when we approximate a discontinuous function. In this work, we present a generalization to the method giving explicit expressions for all the weights for any order of the algorithm. It has a similar behavior to weighted essentially non oscillatory (WENO) technique, however because of the design of the weights in this case is more simple, we propose a new way to construct them obtaining the maximum order near the discontinuities. Some experiments are performed to demonstrate our results and to compare them with standard methods.
Towards a New Mobile Educational Model

The development of mobile technologies and wireless networks encourages more research on Mobile Learning. Reviewing irregular verbs on a bus or organizing a training schedule on a Smartphone is becoming more common today. Mobile learning complements and enhances existing learning systems. Its development has been slowed in the early 2000s by both technical limitations and lack of dedicated teaching models. This article focuses on educational issues and proposes a solution by adopting the Method for Engineering Learning Systems MISA. Our work aims to identify basic elements, key characteristics and dimensions for developing the appropriate content for mobility. These elements are the basis for customization of the MISA method. Indeed, the different steps of MISA are governed by operating principles which ensure greater consistency and flexibility. Taking into account the specifications of Mobile learning in the development of these principles, we can adapt MISA to design a mobile learning system.
Research on Innovative Approaches to College English Teaching Based on Information Technology

The rapid development of internet and the information age of big data have brought great opportunities and challenges to college English teaching. The construction of information technology-based education promotes the modernization of education in China, enriches the teaching resources, enhances the interaction between teachers and students, and provides an important tool for teachers to collect and analyze teaching data conveniently. The application of information technology in college English teaching enriches teaching forms, improves teaching interactions, stimulates and cultivates students’ interests, and improves teaching efficiency. It is of great significance to explore how to make better use of information technology to improve college English teaching.
High-speed High-resolution Image Capture by Using Phase-shift Photographing for Periodic Motion of Machine Element

This paper describes an improvement of our proposed pseudo-high-speed high-resolution photographing method. We have been developing the method by using phase-shift photographing with a typical consumer camera instead of using an industrial high-speed camera whose installation cost is much higher than that of the consumer camera. In our previous work, we confirmed our method enables high-speed photographing even using the consumer camera. However, due to the weakness of an image sensor, shutter speed could not be increased, and then motion blur appeared in the captured image. Even if the shutter speed can be increased, captured images are so dark not enough to recognize a target object. In this paper, we solve this problem by overlaying multiple images captured at the same phase timing.
Generalized Universal Coding of Integers

Universal coding of integers (UCI) is a class of variable-length code, such that the ratio of the expected codeword length to $\max\{1, H( P)\}$ is within a constant factor, where H(P) is the Shannon entropy of the decreasing probability distribution P. However, if we consider the ratio of the expected codeword length to H(P), the ratio tends to infinity by using UCI, when H(P) tends to zero. To solve this issue, this paper introduces a class of codes, termed generalized UCI, such that the ratio of the expected codeword length to H(P) is within a constant factor K. The definition of generalized UCI is proposed, and then the coding structure of generalized UCI is introduced. Finally, the asymptotically optimal generalized UCI is presented.
A highlight removal method of components with high reflective surface measurement based on binocular vision

Binocular stereo vision technology plays an essential role in the intelligent manufacturing system due to the advantages of high accuracy and non-contact. However, for the measurement of components with highly reflective surfaces such as metal and ceramic, the specular reflections affected by the complex light field lead to the failure of feature matching and the decrease of measurement accuracy. This paper proposes an imaging strategy for binocular vision and a high dynamic image processing method to suppress the effect of specular reflection for stereo matching. Firstly, the mechanism of highlight generation in the image is analyzed by combining the illumination reflection theory of the BRDF model. Then, a binocular vision system with a parallel optical axis is built to capture images under different illumination conditions. The image processing algorithm of high dynamic range image fusion is studied, and an algorithm based on tone mapping and weight fusion is implemented to remove the high-lights. Finally, an experiment was performed to verify the effectiveness of the proposed method by a robust and fast matching algorithm. An image evaluation method based on BRISQUE further demonstrates the effectiveness of the method. Compared to the original images, the quality score of the HDR images is lower, which means that the processed images are of better quality. Moreover, the method provides an increase of 23.33% in image matching accuracy, which verifies the availability applied in the measurement of highly reflective surface components.
Machine Learning Techniques for Keystroke Dynamics

Conventional security mechanisms such as token-based and knowledge-based authentication mechanisms are losing importance in the present era of immense technological development in cyber threats. Password and pin are examples of these mechanisms. Keystroke biometrics is a promising solution for ensuring cybersecurity in both standalone and connected systems. Keystroke biometrics is a subset of behavioral biometrics and distinguishes users based on their typing patterns. The performance of a user authentication system utilizing keystroke biometrics depends on the extracted features and classification techniques. The objective of this paper is to compare three different learning techniques namely support vector machine, random forest and logistic regression, in the context of keystroke biometrics. Time-based features are extracted from a publicly available dataset. These features are analyzed with above mentioned machine learning algorithms, and the performance of these algorithms is compared. Hyperparameter tuning and cross-validation are performed to further enhance the performance. Experimental results demonstrate that Random forest is the most efficient with accuracy of 0.85 and F1 score of 0.74. The accuracy obtained with support vector machine and logistic regression is 0.76 and 0.63, respectively.
Socio-technical Security: User Behaviour, Profiling and Modelling and Privacy by Design

Security risk to information exists in many forms and guises; being human and non-human, and those directed from inside and outside of an organisation. Traditional mitigation methods have predominately focused upon applying layers of reactive security solutions, triggered by breaches to defined rules and processes. In order to counter the risk to information posed by individuals from within an organisation, behavioural research is increasingly becoming a crucial element in the design of automated security tools to identify and respond to anomalous and malicious behaviour. Accurate user profiles and threat models may enable the effective and efficient deployment of user behaviour analytics systems, which in turn enable the proactive mitigation of threats before they cause harm to people, property, including intellectual property, or premises. The consideration of personal characteristics and role-related behaviours during the design of security systems can protect the privacy rights of individuals, improve business effectiveness and cost efficiencies for organisations. In an increasingly mobile world, next generation and anticipatory security risk systems are needed to respond to the shift that people are becoming the new security perimeter.
A Study on Digital Watermarks for Audio Signals Using Phase of Frequency Signals in Addition to the Other Methods

In this paper, we focus on a digital watermarking method for voice signals recorded by a digital voice recorder especially in conferences. We will discuss some requirements for detecting falsifications in the voice signal, because the conference record has the probability that a conclusion is changed for only a falsification in a little time interval. Then, we will propose an enhanced watermarking scheme using phase of frequency signal in addition to our previous methods, and assess its soundness.
Aspects of university digitalization using 1C technologies

Currently, digitalization is an important task for any large organization. Digitalization is also important for universities activities. The current state of digitalization of Derzhavin Tambov State University, the main advantages of implementing an integrated automation system on the 1C: Enterprise platform are considered: the use of a single platform and development language; end-to-end data movement within one system; availability of regular updates; docking with federal information systems. We describe the use of a number of software products. “1C: PROF. University” allows to automate the accounting, storage, processing and analysis of information about the main processes of a higher educational institution: admission to a university, tuition, tuition and graduation, calculation and distribution of the workload of the teaching staff, etc. “1C: Document management of a state institution” helps to minimize paper document management; reduce the risk of document loss; structuring documentation according to the approved nomenclature, etc. “1C: Automated scheduling. University” allows to systematize the scheduling process; productively use the classroom fund; monitor the workload of teachers, etc. “1C: ITIL. Enterprise information technology management” at the university helps in obtaining more complete and accurate information; creating a different entry point for applications from users; increasing the speed of processing applications, etc. We consider issues at the initial stage of implementation and ways to solve them.
Hybrid Attention Mechanism Guided Convolutional Neural Network for Breast Cancer Histology Images Classification

Objective: Breast cancer is the most vulnerable type of cancer for women, examination of histopathological sections is the gold standard for diagnosing cancer. However, the high complexity and the increasing number of pathological images make the work of pathological diagnosis extremely time-consuming, and the sharp increase in the workload of pathologists will also cause the diagnosis results to be subjectively affected. Therefore, the development of an automated and accurate method for histopathological images analysis is critical to assist pathologists in their work. Methods: In this paper, we propose a deep learning method guided by the hybrid attention mechanism for fast and effective classification on the hematoxylin & eosin stained breast biopsy images. Firstly, this method takes advantages of DenseNet and utilizes the information of the feature map. Afterward, attention and channel attention are used to guide the extraction of the most useful visual features. Results: With the use of five-fold cross-validation, the best model obtaines an accuracy of 96.10% on the BACH2018 dataset. We also evaluate our method on other datasets, and the experimental results demonstrate that our model has reliable performance. Conclusions: This study indicates that our histopathological image classifier with a hybrid domain attention-guided deep-learning model for breast cancer shows significantly better results than the latest methods. It has great potential as an effective tool for automatic evaluation of digital histopathological microscopic images for computer-aided diagnosis.
Online teaching system of Japanese translation course based on P2P network

in order to further improve the quality of Japanese teaching, this paper puts forward a design method of online teaching system of Japanese translation course based on P2P network, mainly for the detailed design of the system hardware structure framework and system function module, and optimizes the software module function and operation steps, on this basis, the system test is carried out. Through the implementation of the system, the stability and effectiveness of the online teaching system of Japanese translation course based on P2P network is good, which can significantly improve the teaching efficiency and students' Japanese learning effect, and is worthy of promotion and application.
Pair work in informatics lessons as one of the forms of organization of educational cooperation of students

The article discusses the types of work in pairs that can be used in informatics lessons, provides methods and techniques that can be applied to implement this type of activity. The emphasis is placed on the fact that pair work allows you to improve the quality of assimilation of educational material, is a kind of stepping stone for preparing students for work in a group, makes it possible to acquire the most important skill — the ability to study independently. The material of the article contains specific examples of interactive methods and tasks that can be used to organize paired work at different stages of an informatics lesson. Their use in the classroom will help teachers to efficiently organize pair work and educational cooperation of students, will contribute to the formation of their communicative competency.
Research on Segmentation Algorithm of Workpiece Character Image Based on FCN-ELM

In an industrial scene, in order to deal with the character segmentation problem on each workpiece, multiple complex steps such as image preprocessing are required, and then image segmentation processing of the workpiece character is performed. Aiming at the complex preprocessing process in the workpiece character recognition process, a workpiece character image segmentation algorithm based on the combination of FCN and ELM is proposed, that is, the convolution layer is mainly responsible for the feature extraction function in the FCN, and the difference of the input image is extracted Deep image features, remove the last fully connected layer of the convolutional neural network, and then use ELM instead of the fully connected layer, as a classifier to quickly classify image pixels, improve the classification accuracy, and then connect the convolutional layer to the extreme learning machine. The classified image pixels are used as the input of the convolutional layer to perform an up-sampling operation, and the generated feature thumbnails need to be restored to the dimensions of the original image. The experimental results show that the improved algorithm improves the accuracy compared with the original FCN algorithm.
How ENI Can Improve Procurement Through Blockchain Technology

The study aims at investigating the potential use of blockchain technology in procurement processes. To better understand how the procurement process works, the case study of Eni is analyzed. Eni seeks to decarburize all its products by 2050, and its fight towards the energy transition is committed to working with suppliers ready to support it in this vision. After understanding the procurement process within Eni and identifying the potential uses of blockchain within these processes, the chapter proves that blockchain could be a powerful tool for the procurement process, especially for supplier qualification.
Design and Application of Customer Services Business Middle Platform for Opening Service Capabilities of Electric Power Marketing

The customer services business middle platform is an important digital approach and effective tool for the electric grid enterprise to improve the customer services, enhance the electric power supply services, promote the marketing lean management and optimize the energy consumption policies, helping to push forward the digital transformation of the enterprise. The paper first introduces the design methodology of the business middle platform based on the whole process of business domain modelling, service architecture, service design, service implementation and service governance. It describes the evolution of opening the service capabilities of the shared service centres from the multichannel business platform to the customer services business middle platform, and elaborates the core service capabilities of these shared service centres. It gives the hierarchical design of the business middle platform architecture, and takes the key business scenarios such as electricity charging and accounting, electricity business expansion as examples to elaborate the technical solutions of the business middle platform, and puts forward the key design points and the technical design elements. Taking the innovative scenarios such as two-dimensional barcode for validating electric power supply transfer, residential energy efficiency management, and electric power demand response as examples, it illustrates the means of supporting various agile product innovations and application development with the opened service capabilities of the business middle platform. In the future, the business middle platform will be required to strengthen the horizontal collaboration with other business middle platforms to provide strong support for cross-professional business of the electric grid enterprise, and to output the service capabilities via the capability aggregation platform, for striving to build an open and win-win energy internet application ecosystem.
The analysis of picture storybooks aimed at pre-school children in terms of child rights violations

Books introduce children to social life and provide them with the opportunity to expand their imaginary worlds.Pre-school children are influenced by books more than adults.Children can identify themselves with the heroes in the books and choose to act like them.Therefore, the features of the heroes in children's picture books, what they go through, and the intended message of the story have significant importance in terms of children's development.This study aims to analyze children's picture books aimed at children who are 3-6 years old in terms of child rights violations.Phenomenological pattern, which is among qualitative research methods, was used in the study.The 30 books, which constitute the data set of the study, were chosen firstly by determining the publishers, and secondly through random sampling method.The data of the study were sorted out using descriptive analysis.In order to find the messages that are directly or indirectly conveyed in children's picture books, "the sentences in the books" were analyzed.The analysis of the data is based on the four sub-themes of child rights; namely, "Survival, Protection, Participation, Development" rights.This study found that development rights were violated the most.Then came survival and protection violations.No violation as to participation rights was observed.Finally, suggestions were made about the study.
PCB chip pin detection based on line structure light

Printed Circuit Boards (PCB) are widely used, in which the PCB chips are the control core of the whole PCB Board and the pins of the chip are very important in the soldering process. Aiming at this demand, a laser triangulation detection platform based on line structured light is designed. The system emits a laser beam through the semi-conductor laser, which is diffusely reflected by the pin of the target object and its solder, and is then imaged on CMOS to form a point cloud pattern through weighted total least square method. Then, the height of each pin, the distance between each pin and the height change of PCB plane are calculated by the depth map. Fit the straight line of the lead edge by the least square method, measure the distance from the straight line to the straight line to get the distance between the leads, and use the change of the distance to judge whether the lead is misaligned.
Multi-Panda Tracking

Multi-Panda Tracking (MPT) is a video-based tracking task for panda individuals, which is conducive to the observation and measurement of distribution and status of pandas. Different from tracking general objects such as pedestrians and vehicles, MPT is extremely challenging due to the indistinguishable appearances and diversified postures of pandas. In this case, existing tracking methods cannot appropriately tackle with the excessive occlusion between different panda individuals, hence suffering from identity switch, missing and inaccurate detections. To address these problems, we propose a simple yet effective MPT framework in the tracking-by-detection paradigm, which is benefited both from a short-term prediction filtering module and a discriminative feature learning network. In particular, the short-term prediction filtering module introduces similarity learning to enhance the temporal consistency among detections, which is capable of supplementing the missing detections and discarding false positive detections. Besides, the discriminative feature learning network leverages a two-branch network to learn both local and global discriminative features, so as to distinguish different panda individuals with a very similar appearance with a subtle difference. To evaluate the proposed method, we annotate a large-scale MPT dataset, named PANDA2021, which is particularly challenging due to the similar appearance and dramatic occlusion between panda individuals. Experiments on PANDA2021 demonstrate that the proposed MPT method significantly outperforms the competing methods. Moreover, experimental results on pedestrian tracking dataset MOT16 further demonstrate that the proposed MPT method achieves comparative performance with competing methods.
Research on the Integrated Development of AR Technology and Rural Red Research Tourism

AR technology superimposes computer-generated virtual worlds on the real world, which redefines the coexistence mode of physical space and Internet, and has a broad application prospect. In this paper, the practical application of AR technology in research tourism through a case is introduced and the necessity and advantages of integrating AR technology into rural red research tourism are discussed and analysed. Finally, two ways of integrating AR technology into rural red research are proposed, namely, reappearing historical scenes and activating historical buildings.