Reviewerly/exHarmony huggingface dataset:
Hand Recognition and Motion Analysis using Faster RCNN

Traditionally wired keyboard and mouse were used as inputting devices to the computer system. These models had many drawbacks like hardware bulkiness and inefficiency due to delay. In this paper the new proposed system will input data using hand recognition and motion analysis. Webcam is used as the primary device to capture the hand gesture. These images are preprocessed to remove noise and for bit reduction. After the image preprocessing feature extraction and segmentation are done. CNN algorithms are used for object detection by identifying the features of the hand. For the system to identify the gesture, a number of images are used for training the system. This process is known as Features training. Once the features and the gestures are recognized, it is mapped to a particular function of the mouse and keyboard.
Vertex radius of curvature fabrication error measurement of aspheric surface based on aberration analysis in partial compensation interferometry

Vertex radius of curvature (VROC) is one of the most important shape parameters to determine the properties of an optical conicoid surface. Precisely measuring the VROC error is critical for manufacturing and aligning optical conicoid. In general, the VROC error is measured directly by curvature fitting from profile measurement data from contact or noncontact testing. And to our knowledge there is no effective way to measure VROC error with non-null interferometry. In this paper, partial compensation interferometry (PCI) with aberration analysis is presented for determining the VROC error. PCI is a kind of non-null interferometry proposed by the authors aiming at testing conicoid or generally aspherical surface figure error (SFE). SFE is defined as the irregular difference between the measured and nominal surface. It mainly comes from local manufacture error and can be calculated from interferograms with digital moiré phase-shifting (DMPSI) method. Here we suppose SFE has already been measured with PCI. Then we measure the VROC error with aberration analysis of the residual wavefront at the exit pupil of the interferometer. Simulations are done to verify the method, and the results show that the relative measuring accuracy is less than 0.003%.
Guitar Pickup: Measurement of its Two-Dimensional Nonlinear Function

published or not.The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.L'archive ouverte pluridisciplinaire
Development of automated lay-up robot system for jointing process of GRP pipes

The joining process for glass reinforced plastic (GRP) pipes is external and internal. Currently, internal and external connections are performed manually, and there are frequent delays in the process, excessive labor costs, and safety problems. An automated process using robots has advantages such as rapid processing, reduction of manpower, and safety. In this study, we developed a pipe root with an automated tape layered machine (ATL) to improve the bonding process inside the GRP pipe. A safety assessment was performed when the load generated during the development of the pipe root and the operation of the robot was applied to the GRP pipe. From the results of the configuration and performance tests of the developed robot, it was shown that the developed robot was sufficiently safe to operate inside the GRP pipe and that the required automation process capability was satisfactory.
Image Denoising Based on Wave Atoms

A new method for image denoising was presented，which colligated the strong point of wave atoms transform and Cycle Spinning. Due to lack of translation invariance of wave atoms transform，image denoising by coefficient thresholding would lead to Pseudo-Gibbs phenomena. Cycle Spinning was employed to avoid the artifacts. Experimental results show that the method can remove noisy and remain edges, while Pseudo-Gibbs phenomena are controlled efficiently, and can get better visual effect and PSNR gains compared with the methods like simplex wave atoms or wavelet denoising using Cycle Spinning.And in heavy background noise, this advantage is significant.
Application of RXD Algorithm to Word Vector Representation for Keyword Identification

Word embeddings in Natural Language Processing have seen exponential growth in recent years. Various methods have been developed to map words into vector space representations while preserving semantic and syntactic relationships. These methods have been successfully applied to a variety of applications, such as information retrieval and document classification. One such method, based on a co-occurrence matrix, is Global Vectors for Word Representation (GloVe). This paper proposes to apply RXD algorithm, an unsupervised hyperspectral image processing anomaly detection algorithm, to the vector representation of words generated by GloVe. The output will be keywords that identify some of the essential ideas in a corpus. Experimental results show that RXD outperforms the standard cosine similarity method in finding anomalous words that capture important ideas contained in documents represented by multi-dimensional word vectors.
Santa Claus Algorithm: Agent-Based Consensus Preprocessing Method for Scalability Improvement in Private Blockchain Environment

Fabric is a modular and extensible open-source system for deploying and operating permissioned blockchains and one of the Hyperledger projects hosted by the Linux Foundation (www.hyperledger.org).Fabric is the first truly extensible blockchain system for running distributed applications.It supports modular consensus protocols, which allows the system to be tailored to particular use cases and trust models.Fabric is also the first blockchain system that runs distributed applications written in standard, general-purpose programming languages, without systemic dependency on a native cryptocurrency.This stands in sharp contrast to existing blockchain platforms that require "smart-contracts" to be written in domain-specific languages or rely on a cryptocurrency.Fabric realizes the permissioned model using a portable notion of membership, which may be integrated with industry-standard identity management.To support such flexibility, Fabric introduces an entirely novel blockchain design and revamps the way blockchains cope with nondeterminism, resource exhaustion, and performance attacks.This paper describes Fabric, its architecture, the rationale behind various design decisions, its most prominent implementation aspects, as well as its distributed application programming model.We further evaluate Fabric by implementing and benchmarking a Bitcoin-inspired digital currency.We show that Fabric achieves end-to-end throughput of more than 3500 transactions per second in certain popular deployment configurations, with sub-second latency, scaling well to over 100 peers.
An Unsupervised Approach for 3D Medical Image Registration

Deformable image registration is of great importance in many clinical applications. In this work, we propose an unsupervised end-to-end registration method for 3D medical images. The proposed method takes a pair of moving and fixed images as input and directly estimates the spatial transformation parameters, which enable spatial transformation layer to generate the registered image. In particular, the registration network is designed in the underlying M-Net architecture that consists of encoding path, decoding path, left leg, and right leg. Moreover, we introduce a novel loss function to guide the training. The proposed method is evaluated on the public brain image dataset ADNI. Experimental results demonstrate that our method achieves promising performance.
Evaluation of Power Consumer Value Based on Matter Element Extension Model

With the further advance of the “New Electricity Reform”, the status of power consumers as the main power consumption can’t be ignored. The method to evaluate power consumer value and select partners from an enterprise’s perspective becomes increasingly significant. An electric power consumer value estimation index system of three aspects including the current value of power consumers, potential value of power consumers and loyalty of power consumers, with five secondary indicators, 18 tertiary indicators is constructed. The assessment model of electric power consumer value on the basis of matter-element extension was established, including establishment of matter-element matrix in classical domain, matter-element matrix in nodal domain, matter-element matrix to be measured, index normalization processing, index weight determination by analytic hierarchy process, and proximity degree calculation based on ideal interval method. Finally, taking power consumer company A as an example, the paper makes an empirical study and applies the matter-element extension model-based power consumer value evaluation research model to the evaluation process of company A. The result shows that the matter-element extension based power consumer value evaluation model has the advantages of intuitive results and clear concept, which can effectively evaluate the power consumer value.
Remote Access Control Model for MQTT Protocol

The author considers the Internet of Things security problems, namely, the organization of secure access control when using the MQTT protocol. Security mechanisms and methods that are employed or supported by the MQTT protocol have been analyzed. Thus, the protocol employs authentication by the login and password. In addition, it supports cryptographic processing over transferring data via the TLS protocol. Third-party services on OAuth protocol can be used for authentication. The authorization takes place by configuring the ACL-files or via third-party services and databases. The author suggests a device discretionary access control model of machine-to-machine interaction under the MQTT protocol, which is based on the HRU-model. The model entails six operators: the addition and deletion of a subject, the addition and deletion of an object, the addition and deletion of access privileges. The access control model is presented in a form of an access matrix and has three types of privileges: read, write, ownership. The model is composed in a way that makes it compatible with the protocol of a widespread version v3.1.1. The available types of messages in the MQTT protocol allow for the adjustment of access privileges. The author considered an algorithm with such a service data unit build that the unit could easily be distinguished in the message body. The implementation of the suggested model will lead to the minimization of administrator’s involvement due to the possibility for devices to determine access privileges to the information resource without human involvement. The author suggests recommendations for security policies, when organizing an informational exchange in accordance with the MQTT protocol.
Segmentation of Text-Lines and Words from JPEG Compressed Printed Text Documents Using DCT Coefficients

Summary form only given. Segmenting a document image into text-lines and words finds applications in many research areas of DIA (Document Image Analysis) such as OCR, Word Spotting, and document retrieval. However, carrying out segmentation operation directly in the compressed document images is still an unexplored and challenging research area. Since JPEG is most widely accepted compression algorithm, this research paper attempts to segment a JPEG compressed printed text document image into text-lines and words, without fully decompressing the image. During JPEG compression, the non-overlapping 8×8 DCT blocks encode text contents of two adjacent text-lines and words without leaving any visible clue for segmentation. This paper proposes two stage algorithms for segmentation of text-lines and words by intelligently analyzing approximate text-line and word boundaries using the DC coefficient during the first stage. In the second stage, AC coefficients of selected DCT blocks are used to extract exact line and word boundaries. The experimental results on a JPEG compressed document data set (with variable spacing between lines and words, different font sizes and styles) shows a good computational performance.
Real-Time Classification of Twitter Data Using Decision Tree Technique

The data which comes from e-commerce site is unstructured text data. Text mining is becoming an important field in research for finding valuable information from unstructured texts. Data which contains an unstructured text which stores large volume of valuable information cannot exclusively be used for any process by computers. Therefore, we want a definite process strategies, techniques and algorithms in order to extract this meaningful information which is done by using text mining. Classification of these user opinions is an Information Extraction and Natural Language Processing task that classifies the user opinions into various categories like in the form of positive or negative. In these paper, we can build a classifiers based on SVM and decision tree classification algorithm to identify the opinions and classify them onto categories, and also, we can compute the performance measure of these classifiers and also compare the classification algorithms performance based on their accuracy, and we can say that decision tree perform better as compared with SVM. In this, we can also classify the real-time tweets review into various emotions and polarity through decision tree classification model.
La lingua russa all’università e l’incontro con il testo letterario. La traduzione come esperienza interculturale

This article, based on the authors’ experience of teaching Russian language to University students, reflects on the position and the use of literary text, especially on translation exercise, in this specific context. The author suggests looking at translation as educational goal, and not as means to reach (or test) linguistic competence. This suggestion is argued by reflecting on the multiple values of the meeting with text, such as exercising independent thought, experimenting and using creativity. Also, an important point is the discovery of the ‘mistake’ and its implication in the context of translation. In conclusion, the author proposes an approach that should be as open as possible to a cultural reading of texts and to the awareness of the cultural implication of translating, which might be useful not only for developing a more sensitive perception of language mechanisms but also for the education goals as whole.
Mutation Variations in Improving Local Optima Problem of PSO

This paper experiment on various concepts in performing mutation to lessen trap in a local optima problem of Particle swarm optimization (PSO). The first concept is when to perform mutation. The earlier mutation favors exploration more than exploitation and usually leads to slow convergence, while the late mutation tends to have opposite characteristics. The second concept is the reset of a known best position (GBEST) when trapping in local optima. The reset reduces the chance of trapping in the same local optima but may lead to slower convergence. On the other hand, mutations without reset best position exploit previous knowledge and converge faster if the GBEST closes to optima. The performances of each concept are compared using 27 benchmark test functions. The results are mixing, but the early mutation without reset GBEST perform better in many of test function.
Web Data Mining Technology and Network Information Security Precautions

Abstract Based on Web data mining technology to discuss with the security of network information. This paper herein first briefly introduces the Web data mining technology. Then it analyzes how to construct the network information security model under the condition of Web data mining. Finally, the network security model is discussed by using Web data mining technology which may provide reference for readers.
More Problems with Quantum Computing

In theory, so long as there is no noise and no gates are applied, an arbitrary state of N qubits remains intact. This is true only if the energies of all qubits are exactly equal, which is hadrly possible. Otherwise, there will be a free evolution of the system defined by its energy spectrum. Also it is still not possible to factor the number 15 by Shor’s algorithm, and error correction is still non-existant.
THE EXPERIENCE OF USING THE RESULTS OF RESEARCH WORK BY ENGLISH TEACHERS IN PEDAGOGICAL PRACTICE WITH THE TECHNOLOGICAL UNIVERSITY STUDENTS

Information about the paper titled "THE EXPERIENCE OF USING THE RESULTS OF RESEARCH WORK BY ENGLISH TEACHERS IN PEDAGOGICAL PRACTICE WITH THE TECHNOLOGICAL UNIVERSITY STUDENTS" at IATED Digital Library
Higher education enrolment in Sub-Saharan Africa: determinants and policy implications

This paper investigates the factors that determine higher education enrolment (HEE) in selected Sub-Saharan African (SSA) countries over the period 1980-2015. The hypothesis of the paper is that certain factors have significant positive effects on HEE in the region. A panel auto regressive distributive lag (P-ARDL) is adopted as the estimating technique and the results suggest that there is no long- or short-run relationship between HEE and GDP per capita. Furthermore, while the impact of variables such as secondary school graduates (SSG), population growth rate (PGT) and employment rate (EMR) on HEE is positive and significant in the long run, the reverse is true for population age group (PAG). Short-run causality tests conducted to detect if pairs of independent variables would jointly affect HEE suggest that the results are reliable. The error correction model (ECM) value of −0.024202 suggests a possible 2.4% speed of adjustment in the system from the short-run deviation to the long-run equilibrium. These results imply that improvement is possible in HEE in the long run if policy makers act on the identified variables of interest.
A Flexible and Interpretable Framework for Predicting Anomalous Behavior in Industry 4.0 Environments

A method called interpretable anomaly prediction is introduced in this paper. The proposed methodology allows us to handle prediction issues in industry 4.0 settings by using regularized logistic regression as core model. In particular, in contrast to anomaly detection algorithms which permits to identify if the current data are anomalous or not, the proposed technique is able to predict the probability that future data will be abnormal. Furthermore, feature extraction and selection mechanisms give insights on the possible root causes leading to failures.
Blockchain Technology and Its Applications

Like other new generation information technologies such as IoT, big data, AI, and cloud, cryptocurrency and blockchain became buzz words in both industry and academia due to their advantageous features. With the features like decentralization, transparency, immutability, blockchain technology became more famous and is emerging in almost all fields like banking, education, healthcare, government, and real estate. Blockchain technology was introduced in the year 1991. It came into existence after this technology was created for bitcoin, a digital cryptocurrency by Santoshi Nakamoto in the year 2008. Since then, the blockchain is evolving rapidly. Even though blockchain usage is in high demand in all the sectors and it has received attention from many international organizations, most of the people lag in knowledge of blockchain technology and Cryptocurrency and how exactly they work. This chapter explores more in detail what blockchain technology is, how it works, and its applications.
LEGO ROBOTICS TEXTBOOK: SOLUTIONS FOR CREATING CONSTRUCTIONS AND MANUALS

This article deals with LEGO robotics textbook developed at the Department of Computer Science and Educational Technology, Faculty of Education, University of West Bohemia in Pilsen. The textbook is focused on the support of developing computational thinking of pupils in the upper primary school with the help of LEGO Mindstorms EV3 kit. The textbook contains eleven educational units including the manuals how to create the constructions of robots as well as the methodical support for teachers. The textbook has been made since 2018 and currently the second version aimed at testing at schools is being published. The first version of the textbook was verified in education and the comments of the teachers were taken into consideration during the last year. Furthermore, the process and outcomes of creating the robotic constructions used in the textbook are described in this article. Also, the models of robots used in the textbook are introduced. The problems which were necessary to be solved during robot constructions and the final form of robots are mentioned. Then the possibilities of making the manuals for building the LEGO robots are introduced and advantages and disadvantages of available applications are described. In the end some chosen comments of teachers and pupils about the robotics constructions which we received in the first phase of testing the textbook are presented.
Queuing Analysis for Content Placement and Request Scheduling in Data Center

The paper considers the joint optimization on the content allocation and content request scheduling in a data center. The queuing analysis with both M/M/1 and M/G/1 assumption on the content request arrival and service time is presented, which shows how the content placement scheme affects the content request scheduling and how the content request scheduling policy can further influence the content placement scheme. A content request scheduling optimization procedure in achieving the smallest average waiting time of clients' requests is proposed. The numerical results are given to show the performance efficiency.
RETRACTED: Method of Constructing the Innovation Service Platform of Colleges and Universities based on Artificial Intelligence

Abstract With the promotion of AI to national strategy, it will have a profound impact on various industries in China. Colleges and universities should follow the trend of the times, seize the pace of the “Ai” era, and apply “Ai” to the service platform of colleges and universities. The purpose of this paper is to study the application of artificial intelligence in service platform. First, the paper analyzes the technology of artificial intelligence, puts forward the way that artificial intelligence can build university innovation service platform, and defines the construction method of University wechat innovation service platform. Using the method of questionnaire, based on the theoretical analysis and network survey, the questionnaire is designed. The users of the regional university library are selected as the survey objects, and the questionnaire is distributed within the scope of the University. The experimental results show that in the investigation of the reasons for the readers’ infrequent use of the library’s personalized services, according to the investigation of all the problems that may lead to the readers’ infrequent use of the library’s services, 48.2% of the readers expressed that they did not understand the library’s information resources; 38.85% of the readers thought that the library’s services were lack of personalization and pertinence and were open Communication with new media platform is also the inevitable direction of the development of University Libraries and service systems in China.