Reviewerly/exHarmony huggingface dataset:
Densenet 3D for Violent Action Recognition in Surveillance Video Sequences

Automatic fight detection in video sequences is an important topic for surveillance systems. The use of machine learning techniques made possible the better detection of fight,however, the models have difficulties in identifying fights in asequence of events in real time, due to the multiple degrees of freedom in the video capture such as: lighting, focus, resolution etc. Therefore, in this work, we propose a model based on the3D Densenet Convolutional Network with space-time learning features for the detection of violent actions in surveillance videos sequences. We validatedour model with four datasets, three commonly used datasets aimed at fight detection and a newdata set collected from surveillance videos. Experimentation has demonstrated that our deep learning approach can discriminate fight scenes with significantly high accuracy and it is superior than other previous studies.
Enabling Disaster Predictions on IoT Scenarios with Transfer Learning

Information and communication technology have changed the way humanity sees the world around it. Faced with the maturation of the Internet of Things (IoT) and the possibilities offered by artificial intelligence, we have a more remarkable ability to observe and estimate things and situations based on information collected in the environment. This work investigates the use of transfer of learning as an enabling tool for monitoring remote locations,aiming at disaster prevention. The main objective is to provide a viable solution for bandwidthconstrained scenarios for data communication. As a way to validate the proposed architecture, we present results obtained in a prototype built in our laboratories that allows us toevaluate the accuracy of machine learning models under different conditions of transmission of monitoring data. The results demonstrate the effectiveness of the transfer of learning technique as one of the pillars for the scalability of a disaster monitoring system
Utilization of Management Information Systems in Ensuring The Academic Quality of Vocational School

This research aims to know the utilization of management information systems through android application by teachers and students in ensuring the academic quality of the institution. The analysis used is qualitative approach that is by interpreting data interactively and continuously. Research data collection is done by interview, observation and document study. This research found that with the android application it can guarantee academic quality and make it easier for teachers and students to obtain academic information with a simpler system including attendance, evaluation, discussion and delivery of material. However, not all student attitudes can be observed through this application. This system is relatively new and needs further development in order to provide maximum benefits in an effort to ensure the academic quality of the institution.
Lem Readings: A Summary of the Regular International Scientific Conference on Science Fiction

The article reviews the regular international scientific conference on science fiction – Stanisław Lem Readings. The conference is held since 2007 by the Department of Philosophy in collaboration with the Department of Russian and Foreign Literature and Public Relations of the Samara National Research University. The summary shows the history of the conference, formulates the main definitions of the category of science fiction, proposed by its participants, demonstrates the topics, genres, and key approaches that make up the problem field, lists its most eminent speakers. Lem Readings are currently an international platform for a regular interdisciplinary dialogue between philosophers of technology and futurologists, active engineers and scientists, anthropologists and sociologists. The basic principles of the conference – freedom of expression, professionalism, striving for the synthesis of heterogeneous systems – remain unchanged during the years, and they correspond to the idea of the science fictional as a possibility that can be realized.
A SURVEY ON SYMMETRIC-KEY AND ASYMMETRIC- KEY ALGORITHMS BASED CRYPTOGRAPHY

Information security is extremely important in terms of maintaining the security of information (text, image, audio, video) and its confidentiality, and as a result of the massive expansion in the field of technology and communications, and the emergence of the role of the internet, and for rapid communication in the transmission of this information (text, image, audio, video) There was a need to secure this information from penetration and make it incomprehensible to people who are not authorized to access this information (text, image, audio, video). Where many algorithms and techniques have appeared to protect this information, namely: Cryptography algorithms, and Steganography techniques. Cryptography is one of the techniques of information security, which studies the secure communication between the sender and receiver of the message, which is the process of converting plain text into cipher text through the use of mathematical operations. In our research paper, a comparative study and analysis of symmetric key and key asymmetric encryption algorithms in terms of effectiveness, key size, time, complexity, functionality, attacks, and research on the most prominent recent technologies such as AES, BLOWFISH, RC2, RC4, CAST, SERPENT, TEA, E-DES, RSA, DIFFIE HELLMAN, and DSA are the safest. Compared to other technologies, faster encryption time, security, speed, and flexibility according to the results
Designing a biometric fingerprint scanner-based, secure and low-cost electronic voting machine for India

A reliable electronic voting machine (EVM) is proposed and implemented in this study, which is integrated with a biometric fingerprint scanner to ensure a secure election process. This biometric EVM includes features such as an interactive user interface, hack-free design and master lock. The EVM system has the capability of registering user data and storing it in a database through proper authentication. Moreover, the system proposed lowers the requirement for human resources. This paper provides a detailed description of the systematic development of the hardware and software used. The software part includes algorithm development and implementation. A thorough and in-depth understanding of the data and the communication protocols along with the pathways used for storage of data in the devices is provided. Additionally, the cost of the system is 62.82% less than the officially existing EVM machines in India.
At the Border of Poetry and Music

This essay examines Ilmar Laaban’s “Ciel Inamputable” in the context of developing text-sound composition in Sweden during the 1960s and spectral analysis. Laaban’s improvisatory work is analyzed using primary source material and a “theory of oppositions” as codified by American music theorist Robert Cogan. The essay connects the scientific work of the Fylkingen language group to research in spectral analysis and linguistics directly to Laaban’s text-sound work. This is the first study to examine Laaban’s work using the technique of spectral analysis and one of the few essays in English to look in-depth at Laaban’s “Ciel Inamputable.”
A Quantum State Tomography Study of Google’s Sycamore gate on an IBM’s Quantum Computer

Quantum computers with superconducting qubits have made significant progress, pushing the lim-its of classical simulation. Google’s quantum AI and collaborators recently performed a supremacyexperiment using a new two-qubit universal gate called the Sycamore gate to generate randomquantum circuits on 53 qubits, equivalent to a computational state space of size 9 × 1015. How-ever, even in strictly-controlled laboratory settings; quantum information on quantum processors issusceptible to various disturbances, including undesired interaction with the surroundings and im-perfections in the quantum state. To address this issue, we demonstrate quantum state tomography(QST) experiments of the universal 2-qubit Sycamore gate using a different artificial architecturalsuperconducting quantum computer. We run the QST experiments in three distinct environments:noise-free, noisy, and on IBM’s Quantum genuine quantum computer. Our results provide insightsinto the efficiency of the implementations and sources of measurement errors, presenting comparablefidelities from both theoretical (ideal) expectations and experimental implementations.
Secure Your Passwords through Safe Wallet with a Smart Key and a Secret Key

We are in the phase where IT development is growing rapidly with the new technologies coming in always, let it be a new devices, new applications in phones, email services and so on, but one thing that has not changed is a use of passwords and its securities for these devices and applications. As a human being, it is difficult for us to remember so many passwords in our day-to-day life despite having other tensions, work, meeting, etc., towards our life. Remember when our passwords get exposed, that means we lost our identity and if it goes to unauthorized hands then it is very risky. So, keeping the passwords safe is the fore most important thing that everyone has to abide. To be concise, what if passwords are kept in a safe place like locker in a bank and are available to only authorized person. Here we discuss about having the passwords stored in the wallet using secret key and to open the locked list of accounts in the wallet there needs to be a smart key. The user must decide the smart key and the secret key and remember to be able to see the passwords. The method that is used to protect the passwords is by a distinct approach using AES algorithm. This entire method shows the additional security of having our passwords stored safely and reduces our stress on passwords retrieve.
Automatic Reading Method for Pointer Meter Based on Computer Vision

The pointer meter is an essential component of industrial facilities such as substations, oil fields, buildings, and construction. The readings represented by its pointer record various environmental parameters and equipment operating parameters of industrial facilities. The traditional manual meter reading method is time-consuming and requires professionals to operate it, which has a high demand on labor costs. Therefore, we propose a computer vision-based method for the reading of pointer meter. Through image local feature matching, the algorithm realizes the autonomous correction of image in-plane rotation, and effectively reduces the recognition error caused by image in-plane rotation. Moreover, this method can realize the function of automatic reading of the pointer meter without additional training. The results show that the readings obtained by the proposed method are close to those obtained by manual meter reading and meet the requirements of industrial use.
Path guidance method for unmanned vehicle based on improved potential field ant colony algorithm

In order to overcome the problems of traditional path guidance methods such as long-time consumption and many intermediate nodes in path planning results, a path guidance method for unmanned vehicles based on improved potential field ant colony algorithm is designed in this paper. From improved potential field function, pheromone update process and heuristic function three-angle improved potential field of ant colony algorithm, improve the obstacle avoidance ability of ant colony individuals and search capabilities, and then by determining the starting point and focus of elliptic search scope, in order to improve the optimal planning path searching efficiency and can achieve the optimal guide path. Experimental results show that the maximum time to generate the path guidance scheme is only 3.7 s, the maximum TPI of the road is only 0.27, and the intermediate nodes of the planned path are the least and all paths are the shortest.
Uncovering Asymmetries in Monetary Policy Transmission in the Economic Community of West African States: Dynamic Heterogeneous Panel Analysis

ABSTRACT As the Economic Community of West African States (ECOWAS) gravitates toward establishing a monetary union, characterized by a common central bank and a single currency, the eco, there is need for deeper knowledge of the monetary policy transmission mechanism to ensure the effective conduct of a common monetary policy in the region. This study investigates the existence of potential asymmetries in the transmission of monetary policy impulses and the implications for monetary policy effectiveness under a unified framework. It employs the dynamic heterogeneous structural panel vector autoregressive (VAR) modeling technique developed by Pedroni (2013), which allows for heterogeneous country-specific dynamics and accommodates cross-sectional dependencies. Based on quarterly data covering the period 1994–2016, the findings reveal statistically insignificant responses of real gross domestic product (GDP) and inflation in member countries to a common monetary policy shock, though the country-specific responses exhibit some asymmetries. The panel estimates for the region also do not produce statistically significant responses to the unanticipated monetary policy shock. In addition, the results indicate that the two plausible monetary transmission channels—the bank lending channel and the exchange rate channel—are either weak or inoperable at the level of ECOWAS and that could undermine the effective conduct of a common monetary policy within the proposed monetary union. Policy should, therefore, be directed at enhancing the transmission of monetary policy impulses in the region, including through far-reaching financial sector reforms, modernization of monetary policy frameworks, and the comprehensive harmonization of institutional and operational mechanisms of monetary policy across member countries.
El rol de docente universitario durante la enseñanza aprendizaje virtual, en época de pandemia, Covid-19

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Civil engineering organisations must mitigate cyber risks to protect infrastructure

Civil engineering organisations, particularly those operating critical infrastructure, are increasingly prone to attacks from cyber criminals. Alastair MacLeod of satellite communications specialist Ground Control examines how best to mitigate these potentially very damaging risks.
An Exploratory Qualitative Study on Examining Small Business &amp; Entrepreneurial Development: Issues in Franco-phone Sub-Saharan Africa. The Case of Senegal

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A Semantic Similarity Measure for Scholarly Document Based on the Study of n-gram

The performance of information retrieval systems is closely related to the ability of similarity measures to accurately determine the similarity value between documents or between a query and a document. In this paper, the issue of similarity measures in the context of scholarly documents is addressed. A semantic similarity measure is proposed. This similarity measure is able to exploit the metadata contained in the scientific articles, as well as the important n-grams identified in them. To evaluate the accuracy of our similarity measure, a dataset of articles is built as well as their similarity values manually estimated by human experts. Experiments performed on this dataset using Pearson correlation show that the similarity values obtained using the proposed measure are very close to those estimated by human experts.
A Study on the Application of Outline-making Learning Model to College Writing Education by Major

This study was conducted to find out what efficiency of OML applying, a problem-solving outline-making learning model, has on the college writing education currently pursued by universities. Among the college students who participated in the writing-related subjects of K University in Busan, a total of 90 students, 30 each by the classes of science and engineering, humanities and social sciences, and arts and physical education, participated in the study. Writing ability evaluation was performed three times without applying OML before OML education, and three times by applying OML after training. The writing genres used to analyze the effect of OML application were persuasive writing, expository writing, and reports, and each evaluation category was divided into five categories: grammar, content, expression, format and context. The application of OML showed a positive effect of increasing writing completeness in all three major fields in this study. Among the three major fields, the effect of OML was the highest in science and engineering field, followed by humanities and social sciences, and arts and physical education field. The results of the study were expected to be used as effective data for writing education in universities.
A Defensive Framework for Reflected XSS in Client-Side Applications

Cross-site scripting attack (XSS) is a common vulnerability that is exploited in modern web applications by entering advanced HTML tags and Java Script functions. An attacker could potentially use this vulnerability to steal users’ sensitive information, hijack user sessions or rewrite whole website contents displaying fake login forms. This class of attacks affects the client-side of a web application and is a critical vulnerability that is difficult to both detect and remediate for websites, often leading to insufficient server-side protection, which is why the end-users need an extra layer of protection at the client-side. In this paper, we analyze the best-known client-side XSS filters, study their mechanisms, structures and mentioned the advantages and disadvantages of each filter. This paper presents a novel XSS filtering model based on filtering rules, XSSFilter, uses Regular Expression in Xpath to detect reflected content, which makes it more robust for web sites that employ custom input sanitizations. We provide a detailed experimental evaluation to compare the four filters with respect to their usability and protection.
Exploring the Problems and Improvement of the University Yacht Class Using the Delphi Method

The purpose of this study is to analyze the problems of university yacht classes and suggest improvement using the delphi method measures to promote the future development direction of university yacht classes and further the qualitative and quantitative growth of marine leisure sports in universities. A group of experts involved in university yacht classes was selected as a population, and a total of 9 university yacht experts, university yacht administrators, and university yacht leaders were surveyed and studied using a purposeful sampling. Data processing analyzed the median, quartile, number of responses, and average for the degree of changeability and hope based on the linear formula, and the research results are as follows. First, the problems of university yacht classes were the lack of professional leaders, the lack of theory and practical skills, the qualty of classes decreased due to excessive staffing, the lack of post-class evaluation, the lack of equipment necessary for classes, and the lack of equipment storage facilities. Second, the improvement measures for the problems of university yacht classes were derived by training professional leaders, introducing self-directed education methods, organizing appropriate class personnel, applying systematic class programs step by step, supplying many equipment, and securing equipment storage facilities. Third, the possibility and degree of hope for the improvement of university yacht classes are highly likely to change and favor the degree of hope, such as securing a sense of safety and ethics, systematic post-evaluation after practice, centralized class due to weather problems, insurance registration and transfer of safety-related equipment.
Global quantum discord and von Neumann entropy in multipartite two-level atomic systems

We have computed the global quantum discord (GQD) and von Neumann entropy (VNE) of multipartite two-level atomic systems interacting with a single-mode Fock field. We use Tavis–Cumming model. We have explored how quantum correlations and quantum entanglement evolve with time in such systems. The quantum system is prepared initially in a mixed state and different parameters are varied to see how they affect the information processing in the system. The dynamical character of the GQD and VNE show an interplay between classical and nonclassical correlations. Photons in this model play an important role to assist the GQD and VNE and we observed that the effects of the field on the GQD and VNE reside in the time evolution of the system indicating that both atom and field states have become entangled. The GQD is assisted in a nonlinear fashion with the number of photons in the system. The GQD and VNE show linear behavior with each other in the dynamics of the system. The effects of intrinsic decoherence on the dynamics of the GQD and VNE are also studied. We have extrapolated the results for a large photon number on the system. We have studied the effect of the change in the size of the system on the maximum value of GQD and VNE and we have estimated the scaling coefficients for this behavior.
Language Identification Models for Short Medical Texts

In the context of SARS-CoV-2 transmission prevention, the short texts on the social networks are full of abbreviations, technical medical terms, slang words that are outside the native languages or pejorative jargon. In other words, the language identification issues are not trivial. In fact, always this task remained a challenge for short texts originating from social media, which abounds in hard-to-understand sequences of letters. Moreover, when the whole world is facing a “medical crisis”, the situation must somehow be controlled in order for the panic to not degenerate even more. As a result, we need enhanced tools that can help us speed up the process of detection of linguistic aspects of the online content. This paper presents a new method intended to identify the language of a Twitter collection related to COVID-19 subject, based on AI algorithms. The aim of this work is to optimally determine the main language in which a text is written, with the constrains given by the diversity of the short text language found in tweets. Therefore, to find an optimal solution for language detection, we evaluated the impact of several language detection algorithms for short texts. Moreover, the results of this analysis were used for the implementation of a new language detection model, focused primarily on the detection of the Romanian language of the gathered tweets. The results suggest that a hybrid approach which combines classic techniques looks like a realistic direction of research.
A New Prediction Algorithm for Perception Results of Mobile Games Users

The research of prediction algorithms for perception results of mobile games users is of great significance for network operators to find network problems and improve network quality. In the prediction process, optimization is of great significance fort the algorithm to improve prediction accuracy. In order to solve the shortcomings of prediction algorithms for perception results of mobile games users, an improved Harris Hawks Optimizer optimizing the BP neural network model is proposed. Initialize population by Bernoulli chaotic map; The nonlinear energy factor is adopted to better coordinate the global search and the local development; An improved Laplace operator is proposed to enhance the capability to look for the optimal solution. Through the test of 8 benchmark test functions, results show the improved Harris Hawks Optimizer has better convergence speed and higher precision than the other four algorithms. According to ITU-T standard, a mobile games users perception data set is established. Based on this data set, experiments verify that the proposed algorithm has better prediction ability and is suitable to predict perception results of mobile games users.