Reviewerly/exHarmony huggingface dataset:
PyWeCode: Towards a Collaborative Coding Framework based on the arcade Python Library

We present preliminaries ideas and a prototype implementation of a collaborative environment based on gamification aimed at teaching coding and software life cycle principles such as design, development, and testing to beginners. As a guide example, we consider a two player game in which each player can dynamically modify its strategy via a simple rule-based language. In this setting the player console plays the role of usual coding tools. However, the sprite controlled by each player can be viewed as a sort of reactive module that interacts with the other players within the chosen game. The game starts with a default strategy. During a game play, players can then adapt their strategy by updating the rules that govern the behaviour of their sprites. The prototype is designed on top of the Python arcade library extended with a communication middleware built on top of asyncio and zeromq to run the environment on a set of remote machines.
Data Sharing: An Analysis of Medical Faculty Journals and Articles

An increasing number of journals and publishers have data-sharing policies and data availability statements. This study examines data-sharing policies of faulty affiliated in medicine. More so, it addresses the following research questions: (1) What are the data-sharing policies of these research journals, (2) What is the relationship between data sharing, open access and journal impactor? and (3) What are current journal articles' applicability to Findable, Accessible, Interoperable and Reusable (FAIR) Sharing Principles. The data identified and examined in this study are retrieved from a visualization tool detailing authors, coauthors, articles, number of citations, grants that used visualization mapping to indicate the impact of research groups. This results in an analysis of sixty articles. Twenty-three percent of the journals have no research data policy, seventeen percent have strong data policies and sixty percent have policies that encourage research data sharing. Seventy-two percent of the journals are open access. All the articles are Findable, and a majority are accessible. There were challenges accessing articles' applicability to Interoperability and the results of reusability were inconclusive. Overall, data-sharing policies vary, no correlation between high impact factor and research data policies. Publishers with supportive data-sharing statements and journals with no policies create complexities in interpretation and application of data sharing. FAIR Sharing has mostly been implemented in the context of curated data more research is needed in its applicability to article data.
Quantum phase and nonclassical properties of a two qubits interacting with a radiation field in PACS-PHO

The problem of interaction falls between a two qubits and a radiation field based on PACS-PHO (Photon Added Coherent States of Pseudo-Harmonic Oscillator) without and with time-varying frequency of the field is considered in this paper. The solution with the analytic method for the wave function of the whole system is applied to describe different quantum measuring. We examine the entanglement between the quantum subsystems of the whole system by considering the qubits concurrence and qubit-field von Neumann entropy. We show the time evolution of the statistical properties of the PACS-PHO during their interaction with the two qubits. Finally, under the main physical parameters we reveal how the geometric phase of the system state can be affected and changed. Hence, according quantum mechanics this studying can open a new perspective for the experimental observation of macro realism.
Design of Dual-channel HD Audio and Video Recording and Playback Equipment Based on TMS320DM8168

Abstract In order to meet the needs of dual-channel high-resolution audio and video recording, storage, and playback, as well as important control scenarios such as shipboard, vehicle, and airborne, the need for long-term capture and recording of terminal screen information is convenient for post-event technical analysis, Service quality assessment, exercise deduction, and operation accident responsibility identification. Researched the high-performance DaVinci series chip TMS320DM8168 launched by TI, designed and implemented a record playback device that supports dual-channel high-definition video, using the compression algorithm of the H.264 encoding standard to achieve compression and storage of video data, Use advanced and mature technology, follow the generalized, modular and serial design ideas to ensure better applicability and higher reliability. After the design was completed, the functions of video capture, compression encoding and video playback were verified, and the performance and stability were tested. The delay of video capture and display is within 40ms, The equipment can support high-definition single-channel or dual-channel video input, and realize two channels video information is compressed and stored, while the video decompression is stable, the playback picture is clear, and there is no jitter. The system functions and performance reach the expected goals.
Augustine as "Naturalist of the Mind"

This paper, Augustine as "Naturalist of the Mind", is a linear portal to its associated graph-structured Tinderbox hypertext. The hypertext is one component of a research project arising out of a Philosophy seminar on Augustine as the preeminent bridge philosopher between the ancient world of Greece and Rome and the subsequent 1000 years of Western philosophy. The research project explores some surprising insights that emerged during this seminar from a deep study of Augustine's Confessions: Book 10-Memory. The purpose of the Augustine as "Naturalist of the Mind" Tinderbox hypertext is not only to be a multi-dimensional resource base for the research but also to provide an exploratorium where new materials can be added, new relationships created, and new research directions can be discovered and pursued.
Image Classification Algorithm Named OCFC Based on Self-supervised Learning

Deep learning has been successfully applied to computer vision, speech recognition and other domains. In image processing, the CNN model has been relatively mature in the training of labeled data. There are labeled data that need to be manually labeled in supervised learning, but now there are a large number of data without labels or with a small number of labels that need to be processed. We propose an image classification algorithm named OCFC based on self-supervised learning without manual labeling. After image preprocessing, features are extracted by three-layer Convolution Restricted Boltzmann Machine. Then the extracted feature clusters are labeled with pseudo-labels by Fuzzy C-means algorithm. Finally, the CNN model is used to classify and predict other image categories. The self-supervised learning model can be arbitrarily transferred to a shallow model or a deep model. The experimental results show that this method can effectively avoid the complexity of manually extracting features, and the accuracy on the STL-10 dataset reaches 82.7%.
Development of Reader Service System for Digital Library

Abstract Digital library is an extensible knowledge network system based on computer communication and sharing in the network environment. To meet the needs of digital library, a reader oriented reader service system for digital library is developed by using computer technology, communication technology and network technology. The system includes user management, book borrowing and returning, book reservation, book display, book review and other functions. Combined with the push function of mobile phone, the system realizes the purpose of carrying out book borrowing service for readers more efficiently. Through the integration of library service and digital communication, the reader service system of digital library can make readers enjoy digital information resources conveniently and quickly at any time and any place.
Analysis of Comprehensive Application of Data Information Logic in Subway Information Guidance System

Abstract In recent years, the integration of subway information system has developed into a network data service platform with new service functions and broad development prospects. Its essence is the overall planning and optimization of data resources and it provides scientific solutions for improving system functions and for enterprise decision-making and management. The data information logic model is a relatively new data integration processing method. It can edit, integrate and plan independent decentralized data information resources among each other into a unified resource library, identify the data in them and create corresponding directories. The source data information is determined so as to achieve sharing in the process of data inheritance. The main advantage of the data information logic model is that the system can still be used after the upgrade and is good at mining the hidden value of the data. The middleware model is currently the most used data integration solution in enterprises. It mainly uses visual logic diagrams to extract hidden information of enterprise data in advance to help users more clearly grasp the context of data resources.
Frame Segmentation in the Link Layer Bit Stream Data Based on Directed Graph

In order to implement parsing of the link layer protocol, a series of binary bit stream sequences must be splitted into frame structure data. Aiming at solving the problems in the segmentation of link layer bit stream, this paper proposes a segmentation algorithm of bit stream in the link layer based on directed graph. After mining double association rules between different sequences obtained by frequent sequence statistics, all double association rules are represented by directed graph, and a coordinate system is assigned to the directed sequence of nodes. All double association rules constructing the directed graph are integrated to the multiple association rules, the rationality of which is judged according to the judgment rule. The algorithm introduces the double association rules with the knowledge of directed graph and obtains the only multiple association rules as the output result, which eliminates redundant sequences of the output synchronization fields effectively.
A Cross-Field Construction Method of Chinese Tourism Knowledge Graph based on Expasion and Adjustment of Entities

Tourism involves comprehensive knowledge in many fields, such as geography, history, food, experience, etc., but now the result of knowledge retrieval and query of tourism topic is usually the knowledge in a single field, lacking effective correlation in different domains. Knowledge graph uses structured way or visualization technology to describe entity and entity relationship knowledge, and provides high-quality knowledge retrieval service for search engine users. However, now it is difficult to integrate field knowledge obtained from a variety of data sources to construct a domain knowledge graph. In this paper, we proposed a method from two aspects to construct the tourism knowledge graph. At one side, using specific tourism entities as seeds to establish different relationships such as historical association, food association, geographical association to integrate tourism entity attributes, increase the value of tourism entity attributes, so that the entity information in the tourism knowledge graph can be efficiently expanded; at another side, based on the process of cross-field entity adjustment with the help of annotation and scoring from domain experts and knowledge graph users, so as to construct the Chinese tourism knowledge graph efficiently and effectively. All these can lay the foundation for improving the retrieval and reply quality of tourism knowledge.
Research on Path Planning Method of Factory Intelligent Vehicle Based on RRT and Artificial Potential Field Method

In order to solve the problems of long and tortuous path, poor smoothness and poor trafficability in traditional RRT, this paper proposes a path planning algorithm based on the combination of RRT and artificial potential field.
Design of Phishing Simulation Dashboard Using Analytic Data Concepts

Abstract Security awareness is the main concern of phishing attack prevention. Every internet user will deal with a serious issue. Phishing is the falsification of messages that aims to retrieve important information from the recipient of the message. In a company, phishing becomes a serious problem because it can come to all employees suddenly. Employees who do not understand the dangers of phishing are the most dangerous threats because they are likely to be the main supporters of the success of phishing attacks. Understanding of phishing attack can be seen from the way the worker responds to incoming messages. A company makes a phishing simulation to find out the handling of the employee on a fake message came. One of the phishing simulation tools is web forgery. In this research, phishing simulations attack every employee in a company. The employee will receive a message that contains a field. The result will show a percentage of employee that successfully attacked. The results will be displayed on a dashboard after being processed using an analytic data concept. The processes of data analytic involve business intelligent software called QlikView. The software gives a percentage of the employee who opens the fake message and fills some data in the fields is about 13.9%.
Multiprotocol Authentication Device for HPC and Cloud Environments Based on Elliptic Curve Cryptography

Multifactor authentication is a relevant tool in securing IT infrastructures combining two or more credentials. We can find smartcards and hardware tokens to leverage the authentication process, but they have some limitations. Users connect these devices in the client node to log in or request access to services. Alternatively, if an application wants to use these resources, the code has to be amended with bespoke solutions to provide access. Thanks to advances in system-on-chip devices, we can integrate cryptographically robust, low-cost solutions. In this work, we present an autonomous device that allows multifactor authentication in client–server systems in a transparent way, which facilitates its integration in High-Performance Computing (HPC) and cloud systems, through a generic gateway. The proposed electronic token (eToken), based on the system-on-chip ESP32, provides an extra layer of security based on elliptic curve cryptography. Secure communications between elements use Message Queuing Telemetry Transport (MQTT) to facilitate their interconnection. We have evaluated different types of possible attacks and the impact on communications. The proposed system offers an efficient solution to increase security in access to services and systems.
Research on Strong Supervision Algorithm Model Based on Blockchain in E-government

In recent years, the research and application of blockchain applied in e-government has been increasing. The characteristics of blockchain, such as non-tamper, verifiable and inspirable, have been well applied in confirming the rights, accountability, and assessment of government data resources, and other unresolved problems over the years. Well, the decentralized feature is naturally inconsistent with the strong central feature of the government so that the application of common blockchain technology in e-government cannot support the government regulatory mechanism effectively. To solve this problem, this paper proposes a strong supervision model of blockchain based on the Threshold Ring Signature algorithm (TRS). Further experiments show that the process and results of signature voting by using this model. Compared with the common blockchain, the strong supervision model can control the error rate of the chain information and increase the flexibility of blockchain so as to enhance the integration application of blockchain and e-government.
Weaver: Efficient Coflow Scheduling in Heterogeneous Parallel Networks

Leveraging application-level requirements expressed in Coflows has been shown to improve application-level communication efficiency. However, most existing works assume all application traffic is serviced by one monolithic network. This over-simplified assumption is no longer sufficient in a modern, evolving data center which operates on multiple generations of network fabrics, an architecture that we define as Heterogeneous Parallel Networks (HPNs). In this paper, we present the first scheduler, called Weaver, that addresses the Coflow management problem in HPNs. To exploit HPNs fully, achieving high communication efficiency for applications is crucial, yet it is also challenging because of the complex traffic patterns in applications and the heterogeneous bandwidth distribution in HPNs. Weaver addresses these challenges at two levels. At the microscopic level, for each application, Weaver leverages an efficient algorithm to exploit the distributed bandwidth in HPNs, which we proved to be within a constant factor of the optimal. At the macroscopic level involving multiple applications, Weaver can adopt a range of application traffic scheduling policies as desired by the system operator. Under realistic traffic, Weaver enables HPNs to service Coflows as efficiently as a monolithic network with equivalent aggregated capacity.
Security Enhancement of Information using Multilayered Cryptographic Algorithm

This paper presents data security enhancement using the multilayer linear feedback shift register (LFSR) cryptographic technique to overcome the problem of data hacking. The information security is achieved with a One Time Pad (OTP) algorithm developed in multilayer which defines the signal transmission in the medium. The Pseudorandom Noise (PN) sequence created by the primitive polynomial is used to get the seed values that are used to characterize OTP functionality. The single-layered LFSR cryptography is analyzed with a cascaded LFSR cryptography technique to prove the security of digitized data. The authentication key generation circuits for various levels of bit handling in data communication systems are implemented in LFSR cascaded cryptography in both encryption and decryption process. The cascaded multilayer cryptography is analyzed for improved data security and the results based on operating frequency, power consumption, delay, and memory usage prove that it suits well for developing modern network-based applications.
SenOpinion: A New Lexicon for Opinion Tagging in Senegalese News Comments

The complexity of comments from the Senegalese on-line press is mainly due to ambiguity. This has led to customized abbreviations and the high presence of local languages. These factors make the current opinion mining tools ineffective. In view of this complexity, our objective is to suggest an opinion lexicon to process these types of data. This lexicon will take into account Wolof, French and urban language words and expressions. The significance of such a study is to provide our local languages with tools for automatic processing of natural languages.
Research on Management of Digital Library Based on Information Platform

Abstract How to improve efficiency and service level of digital library by means of computer technology is becoming an urgent problem in higher education. In this context, this paper is developed a new set of digital library management information system. This paper is studied structure of digital library, and we use case modeling to analysis Web platform module, database module, further build the overall system architecture, design main database table. In the process of implementation, database connection is configured, and we do a lot of tests for Web system platform module and reader-discuss-community module. Since the system is online, the website has maintained a good number of visits, and is welcomed by many teachers and students.
Network Analytics for Improving Students’ Cybersecurity Awareness in Online Learning Systems

Many universities have been widely delivering online courses via online learning systems that rely on the Internet in their execution. However, such systems often focus on the delivery of online courses while overlooking cybersecurity issues. To ensure the cybersecurity of the online learning environment, students and end-users must have appropriate knowledge and be aware of cybersecurity issues. This research identifies the key knowledge areas that belong to the students' cybersecurity awareness, namely internal threats, false identity authentication, and personal data leakage. It then proposes the network analytics approach to disseminate cybersecurity knowledge, by identifying the influential students from their social networks of online interactions in the online learning systems. A work-in-progress network analytics dashboard is presented, and future research actions are discussed in this paper.
Integrated Platform for Interactive and Collaborative Exploration of Tunnel Alignments

The planning of alignments in tunneling projects is a very complex and crucial process. It involves the consideration of numerous conditions and studies of different variants. Essential information depends upon the existing environment, i.e. on existing building structures and ground conditions. The collected information and results quantify metrics and parameters, which are used to define necessary constraints for alignment definition.
Deep Learning Based Recommender System Using Sentiment Analysis to Reform Indian Education

Deep learning is a subset of machine learning, also known as hierarchical learning. It is based on artificial neural network with various stages of representative transforms. Deep neural networks have been applied in different applications like image processing, speech recognition; market-basket analysis and students’ performance prediction to name a few. Now a day’s education is not limited to only the classroom teaching but it goes beyond that like Online Education System, Web-based Education System, Seminars, Workshops, MOOC courses. It’s a big challenge to extract sentiments from the huge data generated which is stored in the environments of Educational databases. Mining on educational databases can be done to extract the hidden sentiments of the students and their views about the education. Analyzing Students’ sentiments and their learning behavior towards the course, difficulties faced, time spent for the course duration in learning the concepts and worries or fears of students like whether they may pass or fail the Final Exam is of prior importance these days in educational institutes. These factors play a dominant role in reforming education. Tweets are gathered from twitter database and found that the obtained are in unstructured form. Preprocessing methods were applied to clean the data set and later classified tweets based on sentiments into classes namely positive, negative and neutral. In this Paper, sentiments of students are analyzed which can be further considered while making reforms in education. In this paper Educational tweets are extracted from Twitter using twitter API and preprocessed. After Preprocessing, clean data is trained and a Model is attained, on this test data is applied. Results are evaluated on few parameters like Balanced accuracy, Sensitivity and Specificity; Prevalence and Detection rate and found that deep learning technique achieves high performance.