Reviewerly/exHarmony huggingface dataset:
Quantum supremacy in a superconducting quantum processor

The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. We have used a programmable superconducting processor to create quantum states on 53 qubits, corresponding to a "parallel computation" of 10 million trillion states. For a simple algorithm, our Sycamore processor takes about 200 seconds to run a quantum circuit a million times - the equivalent task for a state-of-the-art classical supercomputer would take approximately 10,000 years. This dramatic increase in speed compared to all known classical algorithms is an experimental realization of quantum supremacy, heralding a much-anticipated computing paradigm.
Predictive condition-based monitoring for low utilisation motor driven flood risk management infrastructure 

This paper describes the ambition of the Environment Agency to develop and trial predictive condition-based monitoring systems for its mechanical and electrical flood risk management equipment.The aims, objective and research methods for this project are described.The challenge of developing any predictive capability for flood risk management assets which, typically have a low frequency of operation and therefore a paucity of data, is discussed.Some practical suggestions to overcome this specific challenge are presented.
Robust Watermarking Method using QIM with VSS for Image Copyright Protection

This paper proposes a new watermarking method for digital image by composing the DWT-QIM based embedding with visual secret sharing (VSS) method. Firstly, the watermark image is separated into $n$ shares by using the $k-out-of-n$ method, called $(k,n)$ visual secret sharing. One of share is employed in order to embed into the original image for copyright protection. Another $(n-1)$ of shares are registered with Vietnam Copyright Department. When the dispute happens, the verifier can extract the watermark information from the watermarked image, then, decode it with $(k-1)$ shares chosen from $(n-1)$ shares to achieve the copyright information. Our experimental results show that our proposed method works efficiently on the digital images.
Algorithmic Concept-Based Explainable Reasoning

Recent research on graph neural network (GNN) models successfully applied GNNs to classical graph algorithms and combinatorial optimisation problems. This has numerous benefits, such as allowing applications of algorithms when preconditions are not satisfied, or reusing learned models when sufficient training data is not available or can't be generated. Unfortunately, a key hindrance of these approaches is their lack of explainability, since GNNs are black-box models that cannot be interpreted directly. In this work, we address this limitation by applying existing work on concept-based explanations to GNN models. We introduce concept-bottleneck GNNs, which rely on a modification to the GNN readout mechanism. Using three case studies we demonstrate that: (i) our proposed model is capable of accurately learning concepts and extracting propositional formulas based on the learned concepts for each target class; (ii) our concept-based GNN models achieve comparative performance with state-of-the-art models; (iii) we can derive global graph concepts, without explicitly providing any supervision on graph-level concepts.
Perceptually enhanced super-resolution reconstruction model based on deep back projection

以SRCNN（super-resolution convolutional neural network）模型为代表的超分辨率重建模型通常都有很高的PSNR（peak signal to noise ratio）和SSIM（structural similarity）值，但其在视觉感知上并不令人满意，而以SRGAN为代表的拥有高感知质量的GAN（generative adversarial networks）模型却很容易产生大量的伪细节，这表现在其PSNR和SSIM值通常都较低。针对上述问题，提出了一种基于深度反向投影的感知增强超分辨率重建模型。该模型采用双尺度自适应加权融合特征提取模块进行特征提取，然后通过深度反向投影进行上采样，最终由增强模块增强后得到最终输出。模型采用残差连接与稠密连接，有助于特征的共享以及模型的有效训练。在指标评价上，引入了基于学习的LPIPS（learned perceptual image patch similarity）度量作为新的图像感知质量评价指标，与PSNR、SSIM一起作为模型评价指标。实验结果表明，模型在测试数据集上PSNR、SSIM、LPIPS的平均值分别为27.84、0.7320、0.1258，各项指标均优于对比算法。
VISTA, Visual and Inertial Sensor for recogniTion of human Activities

Over the last years, human activity recognition has gained considerable success due to the importance to understand what a person is doing during normal daily activities. The correct understanding of human-being activities is playing a fundamental role also in the field of Human-robot interaction. Indeed, robots can collaborate with humans and help people to perform their actions. The recognition of activities can be achieved by exploiting different kinds of sensors, such as inertial or visual ones. However, no single modality sensor can cope with all the situations that occur in the real world. The VISTA dataset as a unique compromise for the recognition of activities of daily living between datasets based on visual sensors and the ones based on the inertial ones. Particularly, the unique values of the VISTA dataset are: Daily Actions and Activities. For VISTA actions selection we referred to the Cornell Activity Dataset (CAD-60) and the MSR Daily Activity 3D Dataset. Ten actions in common between the two datasets were selected. Then, these actions were combined in five activities (i.e. scene) of daily living. Multimodal data. VISTA dataset proposes the combination of RGBD cameras and inertial sensors positioned on the fingers and the wrist of the subjects. This allows creating a complete and heterogeneous dataset, in which the big movements of the body can be captured by the visual sensors and the fine ones by the inertial ones. Multiple views. One of the drawbacks of using a vision system is the camera occlusion that can occur if the subject is not positioned frontally to the camera. VISTA dataset provides the simultaneous video record from two different perspectives, frontal and lateral, with the purpose to investigate whether the use of a multimodal approach could improve the accuracy of the recognition when the subject is not in a frontal position, thus to mimic more realistic operative conditions. Human-Robot Interaction. VISTA dataset was acquired from the interaction with the Pepper robot. The participants interacted with the robot and performed what it was explaining and requiring. We envisage several applications in which our dataset can be used. For instance, action and scene recognition, analysis of transition between actions, development of customized machine learning algorithms, comparison of approaches using different sensor modalities, just to name a few. The implications of such research efforts are important in the field of activity recognition. but also in the field of Human-robot interaction, since the understanding of the actions and the context can improve the robot perception ability.
The Effects of Home Training Prescription Using Fitness Bag on Metabolic Disease Risk Factors and Fatigue Stress in Obese Male University Students

This study was conducted in order to improve health and feel physically satisfied with obese male college students who are unable to exercise normally in the recent corona 19 era. The exercise was easily carried out in the form of home training prescription using the Fitness Bag, for a total of 8 weeks, 3 times a week to watch TV at home and follow along. Metabolic disease-related factors and fatigue stress were measured twice 0 week and after 8 weeks, and the following conclusions were drawn from the measurement results. As a result of home training using a fitness bag, positive results were found in all items except diastolic blood pressure among the risk factors for metabolic disease in the exercise group. As a result of home training using a fitness bag, a positive result was found in the fatigue stress in the exercise group.<BR> Summarizing the above results, the effect of exercise by reducing metabolic disease risk factors and reducing fatigue stress with Fitness Bag exercise, one of the home training events, for obese male college students who could not exercise properly in the era of Corona 19. Appeared positively. Separately, if obese college students participate properly with their own will at home without using outdoor or indoor sports facilities for exercise centers or sports activities, I think that they will relieve and prevent obesity and lead a healthy college life. As for the exercise program, if self-made home training is more concrete, it is thought that exercise programs that can see various effects will be developed.
Using Social Media for Marketing Library Services in Libraries of Iran, Tehran, and Shahid Beheshti Medical Universities

Introduction: The use of social media for marketing library services of academic libraries is growing day by day. The purpose of this study is to investigate the use of social media in marketing services of libraries of Iran, Tehran and Shahid-Beheshti universities of medical sciences.Methods: The study used a survey method. The questionnaire was used for data collection. The study population included all librarians working in the libraries of Iran, Tehran and Shahid-Beheshti universities of medical sciences with at least a bachelor's degree in librarianship. Descriptive and analytical statistics were used to analyze the data by Spss24 software.Results: The status of using social media for marketing library services in libraries of Iran, Tehran and Shahid-Beheshti universities of medical sciences, based on 4P marketing mix, was as follows: in price components (cost-benefit) with an average of 2.4, location (social media) with an average of 2.36, product (library services) with an average of 2.29, and promotion components with an average of 2.27. Their level of use in all four components was relatively unfavorable.Conclusion: Due to the unfavorable level of using social media for marketing library services in these universities, it is necessary to encourage more effective planning to hold retraining and in-service courses in the areas of marketing, social media tools and content production in these media to encourage medical Librarians to know and use these tools in library services.
The Hierarchy in the Temporary Interaction Micro-processes that Precede the Breaking Points of Focal Attention in an Object of the New Media

Normal-vision users carry out various types of temporary interaction micro-processes through a wide range of New Media Objects and their work systems, for the execution of several activities of daily living as well as to obtain information. In Mexico, cultural studies have been carried out to obtain an approximation to the phenomenon. A great diversity of characteristics have been observed in the interaction processes in the relationship: user - technological device - object of the new media. Hierarchy of three temporal micro-processes has been detected through static networks techniques in the process of interaction of a user with a Website object with screen technology. In this sense, it was observed that the breaking points in Focal Attention Processes are linked to internal factors related to the user from the activation of specific sensory mechanisms such as motors. In turn, it was observed that the activation of some motor mechanisms are linked to emotional responses. In the same way, it was observed that the emotional responses of the user in the interaction processes with the work system are hierarchized by a hybridization of two temporal micro-processes, and they are joined with the sensitive qualities of the visual symbols. The objective of these studies is to promote reflections on the use of a great variety of technological devices and their heterogeneous objects with a better focalization in different environments such as learning, work, entertainment, among others. As well as in areas of knowledge such as Design, Human Factors, Cognitive Ergonomics, just to mention a couple of them.
Technical Report - Knowledge for University Mathematics (KUM) and Mathematics Online Assessment System (MOAS)

This report describes the main background, scope and questions of the connected research projects MOAS and KUM and contains a documentation of the measurement instruments applied in these projects up to the data collections in the year 2020.
Social Virtual Agents and Loneliness: Impact of Virtual Agent Anthropomorphism on Users’ Feedbacks

Conversational agents such as robots or chatbots are today proposed as a solution to modern societys’ issues such as loneliness. This paper explores the effect of the evolution of a conversational agent appearance (Replika©) on user reviews (~ 85 000) through the use of Reinert’s method for text analysis. Results showed differences in the size of thematics issued from the analysis before and after the update such as help with mental health, companionship and visual and conversational anthropomorphism.
Updating Parameters of Fitts’ Law Based on Multi Monitor Command and Control System

At present, the previous studies on the parameters of Fitts’ law in the command and control system interface are mostly carried out in a single monitor system. However, with the increase of the complexity of the command system, the amount of information that needs to be displayed becomes more and more large, so the system needs to display information with the help of multi monitor, and cross-screen operation is also needed for the operation of the system. In the multi-monitor command and control system, aiming at the mouse click behavior, this study uses Fitts’ law to model. Through the analysis of the collected data, the functional relationship between the movement time, the motion amplitude and the width of the target area is updated under the multi monitor command and control system, and the time of predicting the human-computer interaction of the multi monitor command and control system is quantified. The new fitting function can provide strong support for man-machine interface design and human factor engineering research of multi-monitor command and control system.
Research on Edge Service Composition Method Based on BAS Algorithm

Edge services are transferred data processing, application running, and implementation of some functional services from cloud central server to network edge server to provide services. Combined edge service can effectively reduce task computation in the cloud, shorten transmission distance of processing data, quickly decompose task of service request, and select the optimal edge service combination to provide service for users. BAS is an efficient intelligent optimization algorithm, which can achieve efficient optimization and neither need to know the specific form of function nor need gradient information. This paper designs an edge service composition model based on edge computing and proposes a method about edge service composition by BAS optimization algorithm. Our proposed method has obvious advantages in service composition efficiency compared with service composition method based on PSO or WPA heuristic algorithm. Compared with cloud service composition method, our proposed method has advantages of shorter service response time, low cost, and high quality of user experience.
A Robust Lightweight Data Security Model for Cloud Data Access and Storage

In this paper, an efficient lightweight cloud-based data security model (LCDS) is proposed for building a secured cloud database with the assistance of intelligent rules, data storage, information collection, and security techniques. The major intention of this study is to introduce a new encryption algorithm to secure intellectual data, proposing a new data aggregation algorithm for effective data storage and improved security, developing an intelligent data merging algorithm for accessing encrypted and original datasets. The major benefit of the proposed model is that it is fast in the encryption process at the time of data storage and reduced decryption time during data retrieval. In this work, the authors proposed an enhanced version of the hybrid crypto algorithm (HCA) for cloud data access and storage. The proposed system provides secured storage for storing data within the cloud.
A Study of Certain Characteristic Features of Various Printed Documents To Determine The Type Printer Used in Forensic Investigations

Printed documents are very frequently encountered in forensic cases as disputed or questioned documents. With increasing number of such cases, the printer inspection in has become a major requirement in questioned document examination in recent years considering the extensive use printers in document creation in comparison to handwritten papers. Also, the counterfeiting of printed documents by various printers have been recorded at a large scale in last two decades. In such cases, it is very much required by the investigators to examine and identify the type of printer used and to establish a linkage of the questioned document with the alleged printer. The current study is focused on the examination, analysis and identification of various types of printed documents on the basis of their specific characteristics including resolution, edge contrast, letter roughness and feathering formed from diverse printers to differentiate and classify them for forensic questioned document examination and to assist the forensic expert and questioned document examiner thorough such investigations. In this study three types of printers i.e. two inkjet printers, two laser printers, and two different dot-matrix printers were used to collected the printed documents. The samples were analyzed using Projectina Inspec-8 and Stereomicroscope. Each printer has its uniqueness in printing documents, and this study aims to figure out that particular uniqueness at the documents after printing from the alleged printer. The observations revealed substantial differences in the letter’s characteristics. This study may be a useful to discriminate the documents printed from different types of printers.
An Advanced Approach on Focused Crawling with Anchor Text

Title: An advanced approach with focused crawling for various anchor texts is discussed in this paper. Background: Most of the search engines search the web with the anchor text to retrieve the relevant pages and answer the queries given by the users. The crawler usually searches the web pages and filters the unnecessary pages which can be done through focused crawling. A focused crawler generates its boundary to crawl the relevant pages based on the link and ignores the irrelevant pages on the web. Methods and Findings: In this paper, an effective focused crawling method is implemented to improve the quality of the search. Here, three learning phases are considered namely, content-based, link-based and sibling-based learning are undergone to improve the navigation of the search. In this approach, the crawler crawls through the relevant pages efficiently and more relevant pages are retrieved in an effective way. Study Objective: The objective of the study is that more number of relevant pages is retrieved for different anchor texts with three learning phases using focused crawling.
Improvising with Architecture

In Pea Soup a self-stabilizing phase shift network nudges the pitch of audio feedback to a different resonant frequency every time the feedback starts to build. The familiar shriek is replaced with unstable patterns of hollow tones, a site-specific raga reflecting the acoustical personality of the room. These architectural melodies can be influenced by movement in the space, other sounds, or even by a draft of cold air. This essay covers the history of the work, from its earliest iteration in hardware when the author was a student in the 1970s through its software reconstruction in the early 2000s, as well as its influence on the author’s subsequent musical projects.
PENGARUH PENERAPAN ASYNCHRONOUS LEARNING DAN MOTIVASI BELAJAR TERHADAP HASIL BELAJAR

Penelitian ini bertujuan untuk mengetahui pengaruh penerapan Asynchronous Learning dan Motivasi Belajar terhadap Hasil Belajar Administrasi Pajak peserta didik kelas XII Akuntansi Sekolah Menengan Kejuruan. Penelitian ini merupakan penelitian ex-post-facto dengan pendekatan kuatitatif. Populasi dalam penelitian ini adalah seluruh siswa kelas XII Jurusan Akuntansi Keuangan dan Lembaga sejumlah 162 peserta didik dan jumlah sampel yang diambil sebanyak 64 siswa. Metode pengumpulan data menggunakan angket/kuesioner. Uji prasyarat analisis data meliputi uji Normalitas, linearitas, uji multikolinearitas, dan uji heteroskedastisitas. Teknik analisis data yang digunakan dalam penelitian ini adalah analisis regresi sederhana dan analisis regresi ganda. Hasil penelitian menunjukkan terdapat pengaruh positif dan signifikan antara penerapan Asynchronous learning terhadap hasil belajar administrasi pajak. Adanya pengaruh positif dan signifikan antara motivasi belajar terhadap hasil belajar administrasi pajak. Hasil penelitian juga menunjukkan pengaruh positif dan signifikan secara bersama-sama antara penerapan Asynchronous learning dan motivasi belajar terhadap terhadap hasil belajar administrasi pajak. THE EFFECT OF ASYNCHRONOUS LEARNING IMPLEMENTATION AND LEARNING MOTIVATION TOWARD LEARNING OUTCOMES AbstractThis study aimed to determine the effect of the application of Asynchronous Learning and Learning Motivation on Tax Administration Learning Outcomes for Class XII Accounting Vocational High School students. This research was an ex-post-facto research with a quantitative approach. The population in this study were all students of class XII of the Department of Financial Accounting and Institutions with a total of 162 students and the number of samples taken as many as 64 students. The data collection method used a questionnaire/questionnaire. Prerequisite tests of data analysis included normality, linearity, multicollinearity, and heteroscedasticity tests. The data analysis techniques used in this research were simple regression analysis and multiple regression analysis. The results showed that there was a positive and significant effect between the application of Asynchronous Learning on the learning outcomes of tax administration. There is a positive and significant influence between learning motivation on tax administration learning outcomes. The results also show a positive and significant effect jointly between the application of Asynchronous learning and learning motivation on the learning outcomes of tax administration
Le regole della grammatica e le regole del testo. Riflessioni in chiave didattica

This contribution proposes a reflection on the nature of grammatical rules. First of all, a distinction is made between rules that govern the abstract system of language and rules that delimit the perimeter of correctness at a given historical moment. Subsequently, the differences between grammatical and textual rules are analyzed, highlighting that the latter operate on the level of effectiveness rather than correctness and present themselves as “fluid” rules, principles of good functioning of the text in its fundamental components. On the bases of these deliberations, it emphasizes the importance of a didactics based on the dimension of textuality. Finally, the paper offers some suggestions on how to make the best use of textual rules in teaching writing and, in particular, in the collective rewriting of ambiguous or ineffective texts.