Reviewerly/exHarmony huggingface dataset:
Research on aero-engine blade surface detection based on three datum points integrating algorithm

Aiming at the application of a 2D laser profile sensor in the detection of an aero-engine blade surface, a three-point alignment transformation algorithm based on a single-standard ball is proposed. In the algorithm, the standard ball is used to measure the coordinate conversion reference, and the three characteristic points, such as the center of the ball, the vertex, and the side extremum, are scanned by using a laser sensor once. When measuring the rotated blade, the laser sensor scans again, and the coordinate values of the three feature points in the new coordinate system are obtained through coordinate conversion technology. With these three pairs of feature points as the reference point for coordinate transformation and using a three-point alignment transformation and stitching algorithm, the 3D reconstruction of the blade profile measurement point cloud data can be accurately realized. The experimental results show that the 2D laser profile sensor can realize the on-line and fast detection of the aero-engine blade surfaces less then10 µm.
Continuous Credit Networks and Layer 2 Blockchains: Monotonicity and Sampling

To improve transaction rates, many cryptocurrencies have implemented so-called "Layer-2" transaction protocols, where payments are routed across networks of private payment channels. However, for a given transaction, not every network state provides a feasible route to perform the payment; in this case, the transaction must be put on the public ledger. The payment channel network thus multiplies the transaction rate of the overall system; the less frequently it fails, the higher the multiplier.
Augmented Reality Shopping System Through Image Search and Virtual Shop Generation

In this paper, we introduce an intelligent augmented reality shopping system that supports image search and 3D virtual shop generation. By capturing an image of the product that the user is looking at, and using image search, we can recommend similar products to the user. Based on the spatial understanding techniques, we developed a 3D virtual shop interface that would be automatically generated in the user’s physical room, where products are arranged around the room at appropriate locations. With the virtual shop display, users would be able to interact with the products’ life-size virtual models by full-hand manipulation. Our system provides more natural interactions such as grabbing and touching. We also carried out an evaluation study for using our system, the participants’ feedback shows that our system provides a better shopping experience with its intuitive search process, immersive shop display, and natural interactions.
Towards a Secure Data Exchange in IIoT

Industrial Internet of Things (IIoT) plays a central role in the Fourth Industrial Revolution, with many specialists working towards implementing large scalable, reliable and secure industrial environments. However, existing environments are lacking security standards and have limited resources per component which results in various security breaches, e.g., trust in between the components, partner factories or remote control units with the system. Due to the resilience and its security properties, combining blockchain-based solutions with IIoT environments is gaining popularity. Despite that, chain-structured classic blockchain solutions are extremely resource-intensive and are not suitable for power-constrained IoT devices. To mitigate the referred security challenges, a secure architecture is proposed by using a DAG-structured asynchronous blockchain that can provide system security and transactions efficiency at the same time. Use-cases and sequence diagrams were created to model the solution. The achieved results are robust, supported by an extensive security evaluation, which foster future developments over the proposed architecture. Therefore, as the proposed architecture is generic and flexible, its deployment in diverse customized industrial environments and scenarios, as well as the incorporation of future hardware and software, is possible.
Method for Heterogeneous Identification Resolution Technology of IoT Based on Hyperleger Fabric

The Internet of Things identification refers to the name tags used to identify different Internet of Things objects and is the basis and prerequisite for information communication and various applications. In the Internet of Things identification analysis related technology, due to the lack of a unified standard, there are multiple identification types. These identification analysis services cannot be connected, and are prone to single-point failure and single-point control. This will lead to the inability to make full use of the Internet of Things resources and limit the rapid development of the Internet of Things. In this paper, we build a heterogeneous identity resolution service node peer-to-peer network structure by using the multi-chain characteristics of Hyperledger Fabric. By introducing the Geni coefficient, we build a competitive incentive mechanism based on the reputation value of resolution nodes to ensure fairness among resolution nodes. And we propose a heterogeneous identity resolution service mechanism. Finally, we design experiments to verify the effectiveness and reliability of heterogeneous identity resolution services based on Hyperledger Fabric.
PENGEMBANGAN MEDIA PEMBELAJARAN E-LEARNING BERBASIS WEB PADA MATA PELAJARAN SISTEM OPERASI KELAS X SMK ADZKIA PADANG

Based on preliminary observation of the learning process on Sistem Operasi at Grade X Teknik Komputer Jaringan (TKJ) SMK Adzkia Padang shows that, learning process is not running optimally. This is due to the limited resources and time in learning and the media used in the learning process still has deficiencies especially for the installation of the operating system. Based on the phenomenon, the purpose of this research is to develop a web-based e-learning media that is valid, practical, effective. Research phase includes define, design, develop, and disseminate. The results showed that web-based e-learning media is valid based on the assessment of each aspect by the validator. Web-based e-learning media is considered very practical based on teacher and student responses. In addition, web-based e-learning media is effective with an average value of 85% in classical and t arithmetic with a value of 2.223 is greater than t table with a value of 2.093. This shows that, web-based e-learning media otherwise effective use as a medium of learning in improving student learning outcomes. Based on the research findings can be recommended that web-based e-learning media is one of the alternative learning media that can be used on learning of the sistem operasi.
Provable, Scalable and Automatic Perturbation Analysis on General Computational Graphs

Linear relaxation based perturbation analysis (LiRPA) for neural networks, which computes provable linear bounds of output neurons given a certain amount of input perturbation, has become a core component in robustness verification and certified defense. The majority of LiRPA-based methods only consider simple feed-forward networks and it needs particular manual derivations and implementations when extended to other architectures. In this paper, we develop an automatic framework to enable perturbation analysis on any neural network structures, by generalizing exiting LiRPA algorithms such as CROWN to operate on general computational graphs. The flexibility, differentiability and ease of use of our framework allow us to obtain state-of-the-art results on LiRPA based certified defense on fairly complicated networks like DenseNet, ResNeXt and Transformer that are not supported by prior work. Our framework also enables loss fusion, a technique that significantly reduces the computational complexity of LiRPA for certified defense. For the first time, we demonstrate LiRPA based certified defense on Tiny ImageNet and Downscaled ImageNet where previous approaches cannot scale to due to the relatively large number of classes. Our work also yields an open-source library for the community to apply LiRPA to areas beyond certified defense without much LiRPA expertise, e.g., we create a neural network with a provably flat optimization landscape. Our open source library is available at this https URL.
METHOD OF EVALUATION OF FUNCTIONAL SECURITY OF INFORMATION TECHNOLOGIES FOR CREATION OF WARRANTY AUTOMATED SYSTEMS

The components of ensuring the warranty of automated systems, which are subject to increased requirements in connection with their use in many sensitive areas of public activity, including national security and defense, critical industrial technologies, energy and communications, banking, environmental protection , technologies of legitimate distance learning, etc. Certain components can significantly affect the quality and reliability of information services in regulatory conditions. In particular, the special role of the functional security of the cryptographic subsystem in terms of supporting the performance of the automated system for its tasks and functions in general, as well as in terms of ensuring the confidentiality and integrity of information. The components of the cryptographic subsystem have been identified, the poor or incorrect operation of which negatively affects the security of these subsystems. The types of the most dangerous attacks on these subsystems are analyzed, their classification from the point of view of possibility of realization in modern scientific and technical conditions and depending on capacity of available computing means and technologies on the basis of which the most real and dangerous variant of realization of remote attacks on software implementation of cryptographic subsystem is defined. . Based on the analysis, a method for evaluating the quality of cryptographic transformations based on a modified algorithm for solving the problem of finding solutions of systems of linear equations with distorted right-hand parts using the so-called decoding based on "lists" of first-order "shortened" Reed-Muller codes is proved. the correctness of the proposed algorithm.
Informational Shortage as a Component of Media Title’s Attractiveness

The relevance of the study is stipulated by the main role of the Internet publications titles in solving the issue whether it is necessary for user to read the text of publication. To interest the reader the authors use today the titles with omissions and ambiguity. The objective of the given research is to find out the mostly used language means, which are used by cross media journal-ists in order to create the titles with intrigue component. The following methods of analysis were used during the study: the method of entire selection from cross media texts; the descrip-tive method for defining the way of creating intrigue and finding out the reasons of such phe-nomenon; the methods of analysis and synthesis for systematization and classification of col-lected intrigue components. As a result of the study 11 quite widely used lexical semantic and grammatical means, which contribute the creation of titles with the elements of intrigue were found. Among the lexical semantic means the following ones can be mentioned: usage of hyponyms instead of genetic terms; usage of words with abstract meaning; semantic perceptional themes; emotional expres-sive attributes and polysemic lexemes. The morphological and syntactical means of creating the intrigue include pronouns and adverbs of general indicating semantics, interrogative and relative pronouns and adverbs, some kinds of one-member sentences, contextually incomplete sentenc-es, absence of adverbial modifier of time and place, which creates the time and space ambiguity, and the particle no before the name of the subject or object of the action. In the conclusion it is summarized that the above mentioned means increase the interest of the reader, encourage him/her to read the whole article, which is the main aim of the journalists’ work. In such a way the rates of website’s attendance and the popularity of author are also increased.
Information Security on Portuguese Statutory Auditors firms

Since clients' information used by audit firms is one of the main work objects for the auditors, it is important to have efficient information security policies, given the confidentiality required in information treatment. Using an online questionnaire, this study addresses this important question by assessing the current scenario of the audit firms within the scope of applied PSIs, regardless of the size of the organizations. This study presents contributions applied with the impact to important data about the current context of Information Security in the scope of professionals who work directly with financial audits: main policies adopted related to the use of technology, perspectives for updates and improvement in information security policies and the relationship between the dimension of Statutory Auditors' firms and PSIs.
Representation Sharing for Fast Object Detector Search and Beyond

Region Proposal Network (RPN) provides strong support for handling the scale variation of objects in two-stage object detection. For one-stage detectors which do not have RPN, it is more demanding to have powerful sub-networks capable of directly capturing objects of unknown sizes. To enhance such capability, we propose an extremely efficient neural architecture search method, named Fast And Diverse (FAD), to better explore the optimal configuration of receptive fields and convolution types in the sub-networks for one-stage detectors. FAD consists of a designed search space and an efficient architecture search algorithm. The search space contains a rich set of diverse transformations designed specifically for object detection. To cope with the designed search space, a novel search algorithm termed Representation Sharing (RepShare) is proposed to effectively identify the best combinations of the defined transformations. In our experiments, FAD obtains prominent improvements on two types of one-stage detectors with various backbones. In particular, our FAD detector achieves 46.4 AP on MS-COCO (under single-scale testing), outperforming the state-of-the-art detectors, including the most recent NAS-based detectors, Auto-FPN (searched for 16 GPU-days) and NAS-FCOS (28 GPU-days), while significantly reduces the search cost to 0.6 GPU-days. Beyond object detection, we further demonstrate the generality of FAD on the more challenging instance segmentation, and expect it to benefit more tasks.
Ensembles and Cascading of Embedded Prototype Subspace Classifiers

Deep learning approaches suffer from the so called interpretability problem and can therefore be very hard to visualise.Embedded Prototype Subspace Classifiers is one attempt in the field of explainable AI, which is both fast and efficient since it does not require repeated learning epochs and has no hidden layers.In this paper we investigate how ensembles and cascades of ensembles perform on some popular datasets.The focus is on handwritten data such as digits, letters and signs.It is shown how cascading can be efficiently implemented in order to both increase accuracy as well as speed up the classification.
Sign Language Identification Using Image Processing Techniques

In everyday life, computers handle a large amount of data from different sources and formats such as sensors, databases, social networks, texts, etc. In addition to this process, people need to use different communication devices that enrich and facilitate human-computer interaction (HCI). As a result, there is a need to develop computational techniques that allow the search for patterns or characteristic data in images, audio waves, or electrical pulses, among others, to carry out tasks that only humans can do better so far. In this way, to improve both the User Experience (UE) and the ease of interaction with computers, various approaches to natural interaction have been proposed, including digital image processing and acquisition from various data sources such as a sensor like Kinect. In this study, the processing of images obtained from a digital camera is approached to characterize them by using basic computer vision techniques. The paper presents the development of a prototype for supporting people who speak sign language to know if the sign they are doing is correct.
Development of a methodology to study the expenditures of working time in a research library

The key task of each library is to ensure its high performance. Under the conditions of limited economic resources, the rational use, first of all, of labor resources, is of particular importance. The study of the working time of library specialists allows the solvation of a set of issues related to the organization and rationing of their work. However, this type of research is conducted in libraries rather rarely. Problems of studying the working hours of specialists and employees remain without due attention. The existing methods have been developed and are intended primarily for industrial production and the study of workers’ labor. Libraries have to adapt them basing on their goals, tasks, and capabilities. The purpose of the article is to present the results of the development and testing of an original methodology to study the expenditures of working time of specialists in order to normalize labor in the Far Eastern state research library (DVGNB). The author compares the methods of data obtaining, evaluates the possibility of using different types of observation in library, and justifies the choice of the photo-timing method. The main attention is paid to the technology of observation. The main points of the preparatory stage are described in detail and that of processing the obtained data. As a result, the methodology to study the expenditures of working time and labor processes is tested, and it can be used in library practice to determine the structure of production activities and time for their implementation, to rationalize techniques and methods of work, to identify reasons for non-compliance of targets, unsustainable expenditures and loss of working time, to determine quantitative characteristics of personnel potential, etc.
Competence approach as a methodological basis for the professional training of future teachers: to the problem of transformation of the traditional educational paradigm

The article reveals the problem of the need to transform the traditional paradigm model of domestic pedagogical education. The author proves that the dominance of this paradigm does not contribute to the further progressive development of Russian professional pedagogical education. The author considers the competence approach as a methodological basis for professional training of future teachers.
Nonparametric Bayesian Method for Robot Anomaly Monitoring

In this chapter, we introduce an anomaly monitoring pipeline using the Bayesian nonparametric hidden Markov models after the task representation and skill identification in previous chapter, which divided into three categories according to different thresholds definition, including (i) log-likelihood-based threshold, (ii) threshold based on the gradient of log-likelihood, and (iii) computing the threshold by mapping latent state to log-likelihood. Those method are effectively implement the anomaly monitoring during robot manipulation task. We also evaluate and analyse the performance and results for each method, respectively.
Language Agnostic Hate Speech Detection

The growth in social Web platforms in the past years has brought an increase in displays of online hate speech. This subject is considered as a critical matter in the Web community, since it can be related to potentially dangerous actions that affect individuals and groups in the physical world. The automatic detection of this type of expressions has been the center of several investigations over the past few years. However, most research on this subject has been done for the English language and on rather limited datasets. In addition, although some works approach the problem from a multilingual perspective, analyzing different language separately, across-lingual perspective of this problem has not been used so far.
Contextualization of the Augmented Reality Quality Model through Social Media Analytics

Augmented Reality applications are gaining popularity while maintaining novelty.Many industries are utilizing the user interface type, and use cases are becoming repeat patterns of problem solutions.Despite this rising popularity, quality has not matured nor has the technology become mainstream.Novelty must be approached as risk, and risk must be evaluated for and tested to assure adequate levels of quality.Quality itself can also be vague and have contextual definition.For these reasons, a quality model for augmented reality was created.This work analyzes over two hundred thousand tweets, collected during 2019 and 2020, relating to augmented reality technology, and contextualizes various data points to the established AR Quality Model.The education industry had the highest mentions among the tweets within the scope of this research while the tweets labeled to the transportation industry had the highest sentiment.Furthermore, the tweets were shown to illustrate the needs of testing against the characteristics within the quality model; presence, perspective, interaction, portability and persistence.
Enabling transparent hardware acceleration on Zynq SoC for scientific computing

In a quest for making FPGA technology more accessible to the software community, Xilinx recently released PYNQ, a framework for Zynq that relies on Python and overlays to ease the integration of functionalities of the programmable logic into applications. In this work we build upon this framework to enable transparent hardware acceleration for scientific computations for Zynq. We do so by providing a custom NumPy library designed for PYNQ, as it is the de-facto scientific library for Python. We then demonstrate the effectiveness of the proposed approach on a biomedical use case involving the extraction of features from the Electroencephalography (EEG).