Reviewerly/exHarmony huggingface dataset:
Deep Learning Detector for Large-Scale MIMO Systems with Low-Resolution ADCs

A large-scale multiple-input multiple-out (LS-MIMO) transmission scheme with low-resolution analog-to-digital converters (ADCs) has become one of the promising techniques for 5G and future wireless networks. In this paper, we investigate the power of a deep-learning network in detecting LS-MIMO signals when the resolution of the ADCs is limited to just a few bits. We found that the performance of the deep-learning detector is sensitive to the resolution of the input signals. And thus, it desires to train a specific deep-learning detector for each level of the resolution. Furthermore, the deep-learning detector can deliver equal or better performance than the belief propagation detector. At the high level of signal-to-noise ratio, the deeper the network is, the better performance of the detector is improved. This makes the deep-learning detector a promising technique to detect large-scale MIMO signals to achieve good performance while keeping the complexity manageable.
Tracking and Calculating Speed of Mixing Vehicles Using YOLOv4 and DeepSORT

Today, strong development of socio-economic has promoted participation in traffic. As a result, traffic management is becoming more and more difficult. To effectively solve the problem, artificial intelligence (AI) applications are applied for the improvement of urban traffic management and administration. Therefore, we propose an intelligent algorithm for monitoring and detecting vehicles. We use data collected from cameras and apply deep learning technology to track objects in the paper. The proposed algorithm uses YOLOv4 combined with DeepSORT for tracking and calculating the speed of detected vehicles. Results show that the proposed algorithm improves accuracy up to 95% which is suitable to apply for real applications.
Generating and Analyzing Program Call Graphs using Ontology

Call graph or caller-callee relationships have been used for various kinds of static program analysis, performance analysis and profiling, and for program safety or security analysis such as detecting anomalies of program execution or code injection attacks. However, different tools generate call graphs in different formats, which prevents efficient reuse of call graph results. In this paper, we present an approach of using ontology and resource description framework (RDF) to create knowledge graphs for specifying call graphs to facilitate the construction of full-fledged and complex call graphs of computer programs, realizing more interoperable and scalable program analyses than conventional approaches. We create a formal ontology-based specification of call graph information to capture concepts and properties of both static and dynamic call graphs so different tools can collaboratively contribute to more comprehensive analysis results. Our experiments show that ontology enables merging of call graphs generated from different tools and flexible queries using a standard query interface.
Challenges and Triumphs Teaching Distributed Computing Topics at a Small Liberal Arts College

Introducing undergraduate students to key concepts of distributed computing has become almost essential as the world continues to embrace cloud-based solutions to daily problems and as research continues to grow in scale requiring distributed re-sources. Although distributed computing is an important part of the computer science curriculum, it can be difficult to introduce at some institutions. We explore some key challenges associated with introducing distributed computing into the computer science curriculum at a small, liberal arts college. We focus on an initial failure introducing a specialized distributed computing course too soon and relay the successes and failures experienced over a one year span of incorporating key distributed computing concepts across multiple systems-level courses. We discuss lessons learned from our first foray into teaching distributed computing and provide recommendations for new adopters of distributed computing curriculum based on our experiences.
Stochastic Approach for Simulating Quantum Noise Using Tensor Networks

Noisy quantum simulation is challenging since one has to take into account the stochastic nature of the process. The dominating method for it is the density matrix approach. In this paper, we evaluate conditions for which this method is inferior to a substantially simpler way of simulation. Our approach uses stochastic ensembles of quantum circuits, where random Krauss operators are applied to original quantum gates to represent random errors for modeling quantum channels. We show that our stochastic simulation error is relatively low, even for large numbers of qubits. We implemented this approach as a part of the QTensor package. While usual density matrix simulations on average hardware are challenging at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n &gt; 15$</tex> , we show that for up to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$n \underset{\sim}{&lt;} 30$</tex> , it is possible to run embarrassingly parallel simulations with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$&lt;1\%$</tex> error. By using the tensor slicing technique, we can simulate up to 100 qubit QAOA circuits with high depth using supercomputers.
Research on Object Detection Method of Four-Electric Equipment in Rail Transit Based on Yolo

Rail transit is a complex system, there will always be a variety of errors in the actual project to bring unnecessary losses. This research aims to increase users’ understanding of equipment by detecting the types of four-electric equipment in rail transit, so as to reduce the occurrence of misuse and omission of equipment by equipment users in the project. In this paper, we introduce dilated convolution in the Yolov3 network structure and use different dilation rates for different scales of network output, which can effectively improve the prediction effect of the network; in addition, we improve the loss function of the network to obtain better detection effect. Experiments show that the network detection speed is 53f/s, and the detection accuracy reaches 83.18%, which is 3.23% higher than the original Yolov3 network, which effectively improves the detection effect.
A Context Approach to Improve the Data Anonymization Process

Today, the protection of personal data is an important step in the development of an information system. This awakening of consciousness is happening as businesses grapple with growing volumes of data. No one wants to publicly expose their users’ data. The objective is not only to avoid sanctions but also bad media coverage and image damage when a company is the victim of a data breach. Personal and sensitive data should be confined to production environments and should not be copied to test environments, which poses a risk to its integrity. They should not be accessible in development and test databases to comply with GDPR (General Data Protection Regulation) regulations and to protect company data from potential breaches. Anonymization is a recommended technique for replacing personal data with non-identifying data for use in a test environment. This paper presents a socio-technical approach to data anonymization using the Contextual Graphs formalism which can help to easily represent user practices and gradually add them to an experience database. This can be used to improve the anonymization process in non-production environments.
Technology-Enhanced Mathematics Trails for Out-of-School Learning of the Application of Mathematics

Mathematical trails offer students the opportunity to apply learned mathematics outside of school or in the urban environment. This enables key mathematical activities, such as modelling or problem solving. Relevant quantities must be estimated, measured, or calculated. Mathematics trails can be supported by technology, with students using smartphones or tablets. Geo-localization apps are used to guide students from station to station on the mathematics trail and present the tasks. The chapter shows the added value that the use of digital support by the app Actionbound can provide for learning mathematics.
Blockchain-based Model for Trading Smart Contracts for Shared Energy Generation in Brazil

Blockchain development is expected to bring significant contributions to electrical grids. Mainly due to the security requirements, real-time operation and encrypted communication features of this technology. Such features provide ways to shorten the process and carry out direct and secure energy trading through smart contracts. In order to circumvent the impediments imposed by Brazilian regulation with regard to trading smart contracts for shared energy generation, this paper describes a blockchain project, explaining the business rules and focusing on energy issues. A basic blockchain implementation is also shown in order to explain peer-to-peer transactions.
Convergence between technology and education for sustainable development in Latin America

The use of new technologies in education (computers and other devices) is a key factor that allows cost reduction, since physical material is no longer necessary and everything can be done through a program or app, making it easier for students and teachers to search and deliver quality information quickly and efficiently in real time. The objective of the work is to emphasize the strength of technology in higher education to favor integration, the modest but encouraging opportunities and results that have been achieved, as an ecumenical and dynamic factor in the integration process. The methodology is qualitative in approach, since a documentary analysis is developed through the collection of material, books and articles that allow us to reflect on the possibility of carrying out more in-depth studies on the convergence between education and technologies. The results reflect a technological evolution of Education 4.0 and the concepts that support higher education in the digital era, the pedagogical and academic trends that support it, and its impact on the virtualization of higher education. In the conclusions we perceive the new trends in digital education, the pandemic by covid-19 accelerated changes in study methods with the obligation of virtual study through similarities that describe the convergences and divergences between educational conceptions and technologies.
Technologies in the Pharmaceutical Industries and Medical Health Care

This review aims to illustrate upcoming technological developments in the pharmaceutical industries and healthcare facilities may look in the near future. In order to achieve this, we examine recent technologies and advanced medical developments in healthcare as well as in the pharma industries. Such as Artificial intelligence which provides an understanding between process parameters and different formulations. Blockchain is a sophisticated database that stores data in a way that makes it impossible to alter or hack the system. Clouding Technology enhances the drug discovery process. In the Future hospitals will need room for scanning and 3D printing since they can create virtually anything, including medical devices and human body components, and also produce drugs for every individual. Robotics is widely used in surgery as well as in chemical handling in laboratories. IT (Information Technology) is a database that helps in gathering information in surgery departments, hospitals, labs, and clinics. Our geriatric populations' quality of life can be maintained with the aid of new, technologies and innovations in health care. To overcome these obstacles, medical technology, as well as pharma industries, as well as pharma industries must unite and promote, high-quality methods while incorporating them into many related fields.
Visualization Analysis of Information Literacy Education Research Based on Knowledge Graph

This paper makes a visual analysis of the research data of information quality education in China. Through the visualization software CiteSpace, the scientific knowledge graph is presented to show the subject structure and research track of information literacy education research in China. This paper also put forward many suggestions for the development of this field, which provided help for a quick and comprehensive grasp of this field, and also provided a reference for the development of this subject and subsequent research.
Blockchain-Based Secure and Efficient Ride Sharing System

The attractive advantages of ridesharing include reduced traffic congestion and shared travel costs for users and drivers. However, most existing rideshare systems rely on an intermediary to coordinate the service, creating a single point of failure and raising privacy issues about exposure through internal and external assaults. The suggested approach allows drivers to provide ridesharing services directly to riders without needing a central hub or reliable intermediary. Sharing trips may teach passengers and drivers about transportation logistics without requiring them to change their plans or costs. The suggested system employs a time-locked technique to solve these problems. A membership deposit system for ridesharing services uses smart contracts and zero-knowledge evidence gathering. In short, the driver and the passenger need to put up some deposit to prove they are serious about using the blockchain. Later, a driver must show the blockchain that he or she was at the agreed-upon pick-up location at the appointed time.
Non-Gaussian entanglement of magnetically coupled modes: A dynamical analysis

The quantum entanglement of two connected harmonic oscillators via angular momentum yielding a magnetic coupling [Formula: see text] is discussed in this study. The corresponding Hamiltonian is diagonalized by using three canonical transformations, and then the stationary wave function is obtained. The Schmidt decomposition is used to explicitly determine the modes [Formula: see text], with [Formula: see text], [Formula: see text] and [Formula: see text] being two quantum numbers associated with the two oscillators. We summarize our findings by looking at the effects of anisotropy [Formula: see text], [Formula: see text], asymmetry [Formula: see text], and dynamics on entanglement. (i) With increasing [Formula: see text], the entanglement grows exceedingly large. (ii) The sensitivity to [Formula: see text] is determined by [Formula: see text] and [Formula: see text]. The physical parameters and quantum numbers play a great role in the periodic resuscitation of entanglement.
Word Ambiguity Identification using POS Tagging in Automatic Essay Scoring

Automatic Essay Scoring (AES) is one of the evaluations carried out by teachers to measure their students. AES is an interesting topic and looking for better accuracy. In AES, the test documents are the student’s answers, and the ground truth is the teacher or book answers. Essay answers from students can consist of one or more sentences. The formation of words in a sentence can affect the meaning of the sentence. In Indonesia, some words can have more than one meaning (polysemy), which can lead to ambiguity of meaning. One example of an Indonesian word with an ambiguous meaning is ‘bisa’. Based on Indonesia Dictionary (KBBI), it has three meanings (capable, toxic substance, and greeting shaman in the traditional ‘pingitan’ ceremony). This research attempts to overcome the ambiguity by integrating POS tagging into the text preprocessing phase before calculating the similarity between student answers and book answers using cosine similarity. The test results show that these approaches can produce an accuracy of up to 79%.
Application Analysis of Large Data and Net of Things Technology in the Construction of Intelligent Library

Modern social intelligence technology has gradually penetrated into people's lives, such as big data and the Internet of Things, which have been widely used in all walks of life. For library construction and management, traditional book management and utilization efficiency is relatively low. The introduction of big data and Internet of Things technology has brought great convenience to traditional manual management, data recording, literature statistics and other work, making the library more convenient to serve a wider range of people. This paper analyzes the current situation of library service innovation under the background of big data and Internet of Things technology, and explores the impact of new technologies on book knowledge services. On this basis, this paper puts forward the concept of intelligent library and discusses the intelligent construction of library. This paper summarizes the development status and related research status of intelligent libraries at home and abroad, and reconstructs a set of intelligent library construction schemes that meet the current technical status and user needs.
Internet of Things (IoT) Authentication and Integrity Model using MBTSKHF One Time Password (OTP)

The Internet of Things is a network of physical objects like sensors, actuators, and software. The purpose of connecting is to exchange data with other objects and systems over the internet, enabling us to enhance data collection, minimize human efforts, save time, and make decisions. Secure that network is the most important IoT challenge, so we use ways to securely access all objects in the IoT network that are known with IoT authentication. Most of the attacks come from plain security problems, for example, the weakness of passwords, these techniques have some disadvantages; Password depends on user memory, and most people use default password which is vulnerable to attacks. This paper compares different IoT authentication schemes. Also, present an analysis of the different generation One Time Password (OTP) schemes like Lamport OTP, Elliptic Curve, and HOTP. The paper provides a simple light model using OTP-based MBTS KHF (Moataz, Basheer, Tarek, Salwa keyed hashing function). our model achieves high-level security with a very shorter key size and solves key size and key store problems than the other algorithms. Also, the paper model prevents users from initializing multiple connections for authentication to prevent attackers from guessing OTP.
Metaverse Virtual Art Assets That Is Breaking Through the Confinement of Materials in View of Authenticity and Immortality

The conservation by the metaverse cloud computing technology that is breaking through the confinement of materials which supply the virtual art assets solve not only the debate of artwork restoration, but also the storage space for our abundant art assets. A participatory culture of the meme generation estimates that we can combine the virtual and physical artwork so as to guide the public to better understand the artwork and improve the aesthetic environment of society in the digital world. Therefore, the creator’s spirit of sacrifice for art can achieve immortality.
Basic search algorithms in Python

The research is mainly about the Python implementation of three basic algorithms: Depth-First Search, Breadth-First Search and A* Search. Besides, the paper introduces some of the auxiliary knowledge and theories: the four criteria for measuring algorithms, three kinds of queues, and grid-based simulation. While other coding languages like C++ and Java may focus on algorithm more and may have lots of templates and other solved works, Python seem not to focus so much on this, and OOP (object-oriented programming) is the major topic of high-level Python coding. Thus, constructing algorithms and mapping (or simulating real-world situations) indeed become a challenge.In this work, two simulations are made by generating classes: 1. grid-based world 2. graph and vertex. Grid based world introduces coordinates and heuristic functions, which constructs the environment suitable for greedy algorithms. Graph and vertex use nodes to represent different states in the of the world, and using frontier-based search, the nodes will be explored step by step from the initial state until the goal state is reached. After the environment and algorithms are constructed, finally, analysis for the three algorithms are presented in the conclusion part according to the criteria mentioned.
The supplemental definition of dynamic behavior of partially observable object for phasily limited control task

each dynamically active object, regardless of its own nature, has limited energy, which limits its ability to change state coordinates. The research has scientific importance for non-stationary objects, which do not allow to estimate the state coordinates directly by measuring system, and the prediction of behavior of these coordinates is complicated by interparametric relationships in the object. The solution is possible by combining the dynamic game on minmax estimates and by the next descending by quadratic criterion, which does not disturb the limitations, which are adequate to real capabilities of the object. The rough of control system are explained by providing only the necessary descending conditions as a formal approximation of a confidence space terms of a complex of space sets, which give the lower and the upper approximation of the original behavior of space of object's variables.
A Global Pointer based Entity Relation Extraction Method for Chinese Pulmonary Nodule Medical Records

To facilitate research on pulmonary nodule medical records for physicians, this paper proposes an entity relation extraction model which bases on Global Pointer, using embedded pre-trained language model RoFormer as upstream encoder, Exponential Moving Average optimization method and Fast Gradient Method for adversarial training. The proposed model can also analyze the parent-child relations on contextual semantics, and then process them into structured data. The experimental results show that this model improves the extraction effect significantly compared with the traditional methods, and the F1 value can reach 86.2% in the Chinese pulmonary nodule medical records dataset.
Generalized Net Model of the Second Phase of the General Claim Process – First Court Instance

In the present paper an application of the apparatus of Generalized nets is proposed for modeling the second phase of the general claim process – first court instance. The advantages of using such model are very different, some of them are expressed in helping to detect and eliminate unnecessary complications in the process itself, leading to its simplification and optimization, presenting a complex process simpler and more understandable, for scientific and teaching needs etc.
Metrological Aspects in Inteligent Eye-tracking Systems

Eye-trackers are tools for measuring and recording the movement of the eyeballs. The advancement of technology implies their accuracy increase, which broadens their use in intelligent systems from supporting work, learning to medical diagnostics. The success of using the eye-tracker depends on selecting a device with appropriate metrological parameters. Meanwhile, no objective, standardized measurement methods give repeatable and reproducible test results. Therefore, comparing the equipment available on the market is difficult. To solve this problem, numerous research centres work on appropriate metrics resistant to the technical parameters of the instrument. Another issue is research into hardware properties with human observers. The individual variability of the participants unnecessarily increases the variance of the results. This article discusses both problems and presents a solution that allows to eliminate the human factor from the procedure for determining the metrological properties of the eye-tracker.