Reviewerly/exHarmony huggingface dataset:
Collections of the Central Scientific Library named after Yakub Kolas of the National Academy of Sciences of Belarus as a “haven of cartesianism”

T This article is devoted to exposing and considering the most unique and interesting book monuments stored in the collections of the Central Scientific Library named after Yakub Kolas of the National Academy of Sciences of Belarus. It reveals the features of some copies of the French philosopher and naturalist Rene Descartes’ works dated to the XVII–XX centuries. The main part of the research is based on studying the traces of existence of individual copies from the National Library of the National Academy of Sciences of Belarus, including the lifetime edition of Rene Descartes "Discours sur la method". The description of these copies’ specific features (stamps, records, marks of previous owners) is presented. This study aim consists in demonstrating the need to identify rare and valuable monuments of book culture stored in libraries and often hidden from the employees themselves. The methods used in the study are that of heuristic search and attribution of copies of book culture. The article reflects one of the most relevant and productive areas of research work in academic libraries: that is search, identification and scientific description of book monuments stored in their collections, and their presentation in electronic repositories. The identification of 14 works by Rene Descartes and the description of the most interesting of them has become the result of the study. The material is interesting for library specialists working with rare and ancient documents and engaged in the study and popularization of library collections.
PHP code smells in web apps: Evolution, survival and anomalies

Context: Code smells are considered symptoms of poor design, leading to future problems, such as reduced maintainability. Except for anecdotal cases (e. g. code dropout), a code smell survives until it gets explicitly refactored or removed. This paper presents a longitudinal study on the survival of code smells for web apps built with PHP. Objectives: RQ: (i) code smells survival depends on their scope? (ii) practitioners attitudes towards code smells removal in web apps have changed throughout time? (iii) how long code smells survive in web applications? (iv) are there sudden variations (anomalies) in the density of code smells through the evolution of web apps? Method: We analyze the evolution of 6 code smells in 8 web applications written in PHP at the server side, across several years, using the survival analysis technique. We classify code smells according to scope in two categories: scattered and localized. Scattered code smells are expected to be more harmful since their influence is not circumscribed as in localized code smells. We split the observations for each web app into two equal and consecutive timeframes, to test the hypothesis that code smells awareness has increased throughout time. As for the anomalies, we standardize their detection criteria. Results: We present some evidence that code smells survival depends on their scope: the average survival rate decreases in some of them, while the opposite is observed for the remainder. The survival of localized code smells is around 4 years, while the scattered ones live around 5 years. Around 60% of the smells are removed, and some live through all the application life. We also show how a graphical representation of anomalies found in the evolution of code smells allows unveiling the story of a development project and make managers aware of the need for enforcing regular refactoring practices.
Approach for Efficient Triple Pattern Extraction Information Retrieval in Ontology

E-learning is an effective tool for education than what is currently provided by any of the available computer aided tutoring, or learning management systems. Semantic Web is a collection of information that is linked to each other and process by machine in global scale. It can be seen as globally connected database. Here we proposed a combined methodology for better information retrieval by using similarity measurement and visiting frequency and triplet pattern extraction. The primary intention of this paper is to improve the learning capability. triple patterns extraction is essential to convert the incoming learners query to Ontology browsing query (SPARQL).After extracting the triple patterns from the input query is used to build the query for receiving exact information in the ontology content.
Cyber-Crime Victimization through Social Media: An Exploratory Study of Victims in Hyderabad, Pakistan

This qualitative exploratory study used data from Hyderabad, Sindh law enforcement authorities. The researcher interviewed 30 cybercrime victims, 14 females and 16 males aged 19-32, and also collected factual records of 349 social media-related cybercrimes. The study's goals were achieved using thematic analysis. The study's goals are to determine which types of cybercrime are committed on social media, which platform is most often used, and the characteristics of cyber victims. According to the findings, the most common social media cybercrimes are investment/financial scams, online job fraud, sending obscene content, harassment, defamation, religious hate content, and identity theft. Moreover, Facebook, WhatsApp, Gmail, TikTok, Messenger, Twitter, and LinkedIn are all popular cybercrime victimization sites. Interviews with cyber victims highlighted the hallmarks of online victimization, including cyber-relationship addiction, wanting attention/popularity, compulsive online purchasing, and gullibility. The accompanying research also offers practical suggestions for preventing social media cyber victimization.
Political Economic Perspectives on the Development of the Middle East and North Africa

The objective of this study is to examine the Middle East and North Africa (MENA) region and its challenges from the perspective of development with a goal to break down and make better sense of what seems to be the complexities and 'idiosyncrasies' of this region. The primary issues and concerns for the MENA countries have largely been perceived and dealt with through the vantage point of addressing conflicts in the geopolitical and historical context. In light of this, applying developmental approach that is multidisciplinary to understand and meet the challenges of the MENA region in a fundamental way would have many benefits, opening a new window of opportunities, academically and policy wise. From such stance, this paper focuses on and explains what are considered to be the three fundamental and core 'conditions' or tasks for the countries in the region: state-building and nation-building; participatory development; and capability of state. The importance of looking at the 'big picture' of the reality in the manner of reflection and metacognition is underscored.
Organization of geography week for institutions of general secondary education as a form of realizing the teacher's creative potential

The importance of geography in modern life is rather difficult to overestimate, because it is precisely thanks to it that we understand the phenomena and processes that take place in the world and have a different nature (natural, social, economic). That is why this science is an integral part of students' education, a subject that affects the formation of schoolchildren's worldview. However, often children may not fully understand why they need to study this discipline, or even not be interested in it at all. Actually, that is why it is relevant to consider the methodology of organizing and holding subject weeks in geography. During their implementation, many forms of work are used at the same time, which contribute to the interest of students in the specified subject. However, the subject week is not only a special form of learning, but also a period when the teacher can reveal his creative potential as fully as possible. The imagination of the teacher and the variety of forms, methods and means in the aggregate can help to create such a complex of activities that will not only increase the motivation of students to study and prove to them the benefits of geography as a science, but will also be a kind of useful leisure for them, will allow them to show their own abilities, orient themselves in choosing a profession and acquiring important communication skills: testing yourself as a leader or working in a team with other schoolchildren. During the organization of the subject week, the teacher can show his own creativity, using both existing forms of extracurricular work and filling them with new content, and creating and implementing new ones. The week of geography is an opportunity for the subject teacher to prove himself and introduce novelty into the educational process. As the analysis of the experience of pedagogical workers and our own showed, one should always take into account the school's capabilities and the age characteristics of students and create such activities that would be interesting for students and at the same time informative.
ACCOUNTING INFORMATION SYSTEM PERFORMANCE ANALYSIS

Purpose – This study aims to determine the performance of accounting information systems at PT. Bumi Jasa Utama.&#x0D; Design/methodology/approach – The analytical method used is a narrative analysis method with a descriptive qualitative approach to find out how the performance of the accounting information system at the company PT. Bumi Jasa Utama.&#x0D; Findings – The results of the study found that the current performance of the accounting information system at the company PT. Bumi Jasa Utama shows that the company's information system has been used properly.&#x0D; Originality – The data of this study were obtained from primary data and secondary data with data collection techniques through observation, interviews, documentation, and literature studies as well as testing the validity of the data based on triangulation of sources, techniques, and time conducted at PT. Bumi Jasa Utama.&#x0D; Keywords: Accounting Information System Performance, Accounting Information System&#x0D; Paper Type Research Result
TF-IDF Implementation for Similarity Checker on The Final Project Title

Students of the Software Engineering Technology Study Program, Department of Information Technology, Politeknik Negeri Padang, is required to compile a final project to complete their study period. In the implementation of the final project, several parties have involved such as the KBK team whose job is to check whether the proposed title is appropriate or not. The main issue undertaken by KBK is whether the title submitted has been used or not. The method used by KBK in checking the availability of titles was by looking at the titles of the final projects that have been submitted by previous students. The examination process carried out by the KBK, it took a long time. By utilizing the Cosine Similarity algorithm and TF-IDF, it is expected that it will make it easier for KBK to check the availability of final project titles. Cosine similarity is a method used to calculate the degree of similarity between 2 or more documents. While the TF-IDF Algorithm is a method used to weight a word in a document. The object of testing in this study was the title of the student’s final project. The process of calculating the level of similarity of documents started from the preprocessing stage, then proceeds with weighting using TF-IDF and calculating the level of similarity used the Cosine Similarity algorithm. The final result found that system could calculate the degree of similarity of the title of the student’s final project. From the results of testing the process of calculating the degree of similarity of titles using the cosine similarity algorithm can be undertaken quickly.
Implication of portfolio assessment as A method of teaching in scholastic education

Teaching is aptly synonymous with guiding, nurturing, upbringing and something that is of prime importance so far as teaching in schools is concerned. Portfolio Assessment is one of the tools of alternate evaluation which encourages the process of self-learning and self-evaluation. The paper outlines the significance of teaching in a student's overall academic growth as well as personality by implication of portfolio assessment. Despite the importance of teaching, the overall outcomes are far from ideal. The present qualitative research aims at constructing a background to analyze why and how teaching at schools can prove as an ice-breaker in a students' future endeavors.
Designing with Security in Mind

Ken Munro, of Pen Test Partners, talks to Neil Tyler about the urgent need to design with security in mind
Adaptive Fusion of Navigation Solutions from Measurement Subsets

A popular method for integrity monitoring is solution separation originally developed for GPS/GNSS. When applied to multisensor integrated navigation in GPS/GNSS-degraded and denied environments, an inertial navigation system (INS) serves as a core sensor to provide the baseline solution while others offer aiding data to reduce the inertial drifts. To maintain the integrity of such an integrated solution, a decentralized estimator can be used in which an aiding sensor is processed by a separate filter to estimate the error states of INS and of its own. The individual filters are then combined into solution subsets designed in such a way that when a fault occurs, it can be timely detected, identified, and excluded. The optimal solution can be recovered from fault-free solution subsets when the individual filters are uncorrelated. However, non-zero correlation exists due to the simple fact that they rely on the same inertial data. For instance, at the system startup time, subset estimates are fully correlated, resulting in a singularity in the fusion weighting matrix. As a result, a test condition is sought to check on individual filters for cross-correlation. A scalar quantity, referred to as vector correlation index (VCI), is introduced to characterize the overall correlation between local filter estimates. Furthermore, a numerical issue may develop when the subset estimates become highly correlated and the weighting matrix, though short of being singular, has a large condition number, thus amplifying the effect of noise in measurement data. To address this issue, an adaptive fusion scheme is set forth in this paper in which a diagonal loading is applied to the weighting matrix to ensure the resulting condition number stays below a certain level while not altering the optimal weighting too much for minimal error covariance. In this paper, both simulation and experimental data are used to illustrate the adaptive fusion scheme with tradeoffs between complexity (adaptive tuning vs. fixed loading; singular values vs. individual state components) and performance (transient vs. steady state estimation errors). Experimental data include GNSS/Odometer/LiDAR (2D and 3D)/INS.
Build Content Ecosystem Based on Blockchain Technology

The increasingly mature blockchain technology is of great significance for improving the level of ecological governance of online content.In this paper, based on the technique of block chain system foundation and the content of the traditional management mode, put forward the necessity of ecological management main body participation content more, discusses the big data and artificial intelligence, personal information and copyright protection, block chain education with the combination of multi-agent cooperative governance, and put forward based on chain technology to realize the block chain technology can assign the content of ecological management, Build a trusted blockchain ecosystem.
Tools for Landscape Analysis of Optimisation Problems in Procedural Content Generation for Games

The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in game-oriented research and industry. A special class of these methods, which is commonly known as search-based PCG, treats the given task as an optimisation problem. Such problems are predominantly tackled by evolutionary algorithms. We will demonstrate in this paper that obtaining more information about the defined optimisation problem can substantially improve our understanding of how to approach the generation of content. To do so, we present and discuss three efficient analysis tools, namely diagonal walks, the estimation of high-level properties, as well as problem similarity measures. We discuss the purpose of each of the considered methods in the context of PCG and provide guidelines for the interpretation of the results received. This way we aim to provide methods for the comparison of PCG approaches and eventually, increase the quality and practicality of generated content in industry.
Exploration of the Problems of Virtual Currency and Potential Solutions

In recent years, virtual currency has become an international hot topic.At the same time, virtual currency also ushered in unprecedented development.How to effectively regulate virtual currency becomes a problem worth discussing.This paper first analyses the development of virtual currency with Bitcoin as the representative.It is concluded that virtual currency has great instability, which means that there are some problems with virtual currency.The problems of virtual currency are mainly reflected in the potential impact on the market and loopholes in legal regulation.Therefore, the regulatory measures proposed in this paper are also analyzed from two aspects of market operation and legal regulation.In addition, Central Bank Digital Currency (CBDC) is also a good idea.
Lane Change Classification and Prediction with Action Recognition Networks

Anticipating lane change intentions of surrounding vehicles is crucial for efficient and safe driving decision making in an autonomous driving system. Previous works often adopt physical variables such as driving speed, acceleration and so forth for lane change classification. However, physical variables do not contain semantic information. Although 3D CNNs have been developing rapidly, the number of methods utilising action recognition models and appearance feature for lane change recognition is low, and they all require additional information to pre-process data. In this work, we propose an end-to-end framework including two action recognition methods for lane change recognition, using video data collected by cameras. Our method achieves the best lane change classification results using only the RGB video data of the PREVENTION dataset. Class activation maps demonstrate that action recognition models can efficiently extract lane change motions. A method to better extract motion clues is also proposed in this paper.
Inverse Covariance Intersection Fusion CKF algorithm based on Joint Optimization

For nonlinear multi-sensor systems with unknown cross-covariances, an inverse covariance intersection fusion Cubature Kalman filtering algorithm based on joint optimization (genetic algorithm and BP network) is proposed. Firstly, each local estimate is obtained through the Cubature Kalman filter (CKF). And then combined with the batch inverse covariance intersection (BICI) fusion algorithm, the BICI-CKF algorithm is proposed, which can effectively solve the fusion estimation problem of nonlinear system with unknown cross-covariances. Finally, in order to obtain the optimal weighting coefficients of the BICI-CKF algorithm, a joint optimization method based on genetic algorithm and BP network is proposed. This method can not only improve the fusion accuracy, but also significantly increase the fusion speed. The simulation example verifies the effectiveness of the algorithm.
Application of probabilistic methods of geoinformatics for the study and estimation of earthquakes circumstances

The struggle of mankind against the consequences of strong and catastrophic earthquakes has been going on throughout its history, and so far, success in this field is rather modest. This is due to the complexity and inaccessibility of objects for studying deep geological processes that lead to defor-mation and destruction of the Earth's crust, in which seismicity is manifested. Earthquake risk assess-ment for earthquake mitigation is one of the most important issues for a country where such natural disasters can occur. Tectonic and structural-geological studies using modern space remote sensing tools and their integration with spatial data in a geographic information system (GIS) environment are becoming increasingly popular among scientists. Ruptures and associated surface deformation due to ground shaking can be observed with remote sensing data. The use of remote sensing methods to rec-ognize the displacement of faults was carried out in Isfahan (Iran). Based on the obtained data, a map of seismic activity was compiled with field checks and laboratory data analysis. Thus, the purpose of the article is to show the possibilities of geoinformatics for the study of earthquakes. This will increase resilience to future earthquakes, especially for those historic buildings and bridges that are over 400 years old.
Quantum computing for data science

I provide a perspective on the development of quantum computing for data science, including a dive into state-of-the-art for both hardware and algorithms and the potential for quantum machine learning
End-to-end evaluation of practical video analytics systems for face detection and recognition

Practical video analytics systems that are deployed in bandwidth constrained environments like autonomous vehicles perform computer vision tasks such as face detection and recognition.In an end-to-end face analytics system, inputs are first compressed using popular video codecs like HEVC and then passed onto modules that perform face detection, alignment, and recognition sequentially.Typically, the modules of these systems are evaluated independently using task-specific imbalanced datasets that can misconstrue performance estimates.In this paper, we perform a thorough end-to-end evaluation of a face analytics system using a driving-specific dataset, which enables meaningful interpretations.We demonstrate how independent task evaluations, dataset imbalances, and inconsistent annotations can lead to incorrect system performance estimates.We propose strategies to create balanced evaluation subsets of our dataset and to make its annotations consistent across multiple analytics tasks and scenarios.We then evaluate the end-to-end system performance sequentially to account for task interdependencies.Our experiments show that our approach provides consistent, accurate and interpretable estimates of the system's performance which is critical for real-world applications.
GeoHexViz: A Python package for the visualizing hexagonally binned geospatial data

Geospatial visualization is often used in military operations research to convey analyses to both analysts and decision makers.For example, it has been used to help commanders coordinate units within a geographic region (Feibush et al., 2000), to depict how terrain impacts vehicle performance (Laskey et al., 2010), and inform training decisions in order to meet mission requirements (Goodrich et al., 2019).When such analyses include a large amount of point-like data, combining geospatial visualization and binning -in particular, hexagonal binning given its properties such as having the same number of neighbours as sides, the centre of each hexagon being equidistant from the centres of its neighbours, and that hexagons tile densely on curved surfaces (Carr et al., 1992;Sinha, 2019) -is an effective way to summarize and communicate the data.Recent examples in the military and public safety domains include assessing the impact of infrastructure on Arctic operations (Hunter et al., 2021) and communicating the spatial distribution of COVID-19 cases (Shaito & Elmasri, 2021) respectively.