Reviewerly/exHarmony huggingface dataset:
Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning

Relational graph neural networks have garnered particular attention to encode graph context in knowledge graphs (KGs). Although they achieved competitive performance on small KGs, how to efficiently and effectively utilize graph context for large KGs remains an open problem. To this end, we propose the Relation-based Embedding Propagation (REP) method. It is a post-processing technique to adapt pre-trained KG embeddings with graph context. As relations in KGs are directional, we model the incoming head context and the outgoing tail context separately. Accordingly, we design relational context functions with no external parameters. Besides, we use averaging to aggregate context information, making REP more computation-efficient. We theoretically prove that such designs can avoid information distortion during propagation. Extensive experiments also demonstrate that REP has significant scalability while improving or maintaining prediction quality. Notably, it averagely brings about 10% relative improvement to triplet-based embedding methods on OGBL-WikiKG2 and takes 5%-83% time to achieve comparable results as the state-of-the-art GC-OTE.
Neural Networks for Quantum Inverse Problems

Quantum Inverse Problem (QIP) is the problem of estimating an unknown quantum system $\rho$ from a set of measurements, whereas the classical counterpart is the Inverse Problem of estimating a distribution from a set of observations. In this paper, we present a neural network based method for QIPs, which has been widely explored for its classical counterpart. The proposed method utilizes the quantum-ness of the QIPs and takes advantage of the computational power of neural networks to achieve higher efficiency for the quantum state estimation. We test the method on the problem of Maximum Entropy Estimation of an unknown state $\rho$ from partial information. Our method yields high fidelity, efficiency and robustness for both numerical experiments and quantum optical experiments.
Liminal Design: A Conceptual Framework and Three-Step Approach for Developing Technology that Delivers Transcendence and Deeper Experiences

As ubiquitous technology is increasingly mediating our relationships with the world and others, we argue that the sublime is struggling to find room in product design primarily aimed at commercial and transactional goals such as speed and efficiency. We suggest a new category of products to promote deeper and more meaningful experiences, specifically those offering liminality, transcendence, and personal transformation. This paper introduces a conceptual framework and related three-step design approach that looks at narrative participation in design through abstractions to promote, hold and deepen more complex emotions. We explore implications from a theoretical point of view and suggest some liminal product design ideas as examples of how the model might be applied in practice.
Effectiveness of the Inquiry-Based Method in English Language Teaching of Ukrainian University Students Through Technology-Enabled Learning

The requirements of the time and significant changes in the educational system with emphasis on distant learning due to the Covid-19 pandemic force teachers to reconsider methods, approaches, techniques, and tools in foreign language teaching to ensure the effectiveness of the learning process. This study describes the implementation of the inquiry-based method in the process of English language acquisition by Ukrainian university students specializing in cybernetics and information technology. It aims to determine the effectiveness of inquiry-based learning in developing Ukrainian university students’ comprehension and communication skills in professional English through technology-enabled learning. The main research question is to investigate the benefits and challenges of inquiry-based learning for Ukrainian university students to ensure impactful results. The methodology presupposes activities that encourage the independent and collaborative acquisition of the material, increase learners’ intrinsic motivation, enhance communicative and digital skills, and provoke critical thinking and meaningful learning. The teacher becomes a facilitator and organizer directing students’ learning process, fostering their active thinking and interest. It contributes to their better comprehension and meaningful study. The research findings proved the undeniable benefit of the inquiry-based method for university students as it develops their curiosity, inspires deeper understanding and learning, and motivates them to make discoveries and achievements.
Online Multivariate Anomaly Detection and Localization for High-dimensional Settings

This paper considers the real-time detection of anomalies in high-dimensional systems. The goal is to detect anomalies quickly and accurately so that the appropriate countermeasures could be taken in time, before the system possibly gets harmed. We propose a sequential and multivariate anomaly detection method that scales well to high-dimensional datasets. The proposed method follows a nonparametric, i.e., data-driven, and semi-supervised approach, i.e., trains only on nominal data. Thus, it is applicable to a wide range of applications and data types. Thanks to its multivariate nature, it can quickly and accurately detect challenging anomalies, such as changes in the correlation structure and stealth low-rate cyberattacks. Its asymptotic optimality and computational complexity are comprehensively analyzed. In conjunction with the detection method, an effective technique for localizing the anomalous data dimensions is also proposed. We further extend the proposed detection and localization methods to a supervised setup where an additional anomaly dataset is available, and combine the proposed semi-supervised and supervised algorithms to obtain an online learning algorithm under the semi-supervised framework. The practical use of proposed algorithms are demonstrated in DDoS attack mitigation, and their performances are evaluated using a real IoT-botnet dataset and simulations.
Software Cost Estimation Practices Using RASCH Measurement Model: An Indonesian Regional Government Evidence

Software cost estimation (SCE) can be substantial challenges in software development as it could yield inaccurate results. The SCE failure influences project sustainability which might lead to additional costs and times to complete the project. Previous research has provided empirical evidence that the unsuccessfulness of software cost estimation in public sectors is higher than in private sectors. This is due to the actual cost not in line with the estimation cost. The objective of this paper is to determine the SCE practices in the regional government of Indonesia. This research adopts both quantitative and qualitative approaches. The quantitative approach was conducted by distributing questionnaires to government employees who are involved in cost estimation. RASCH model software was used to analyze the data. The qualitative approach involved interviewing personnel in the cost estimation process in regional government. This research involved seven government agencies in West Sumatera Province, Indonesia. The findings of this study show that current practices of SCE in the regional government of Indonesia are not effective although there is a budget ceiling (pagu anggaran) and owner estimate cost (harga perkiraan sendiri). This paper highlights the reasons for inaccurate results of SCE in public sector due to five factors which are: people who have authority to estimate the software cost, time of the estimation, no tool to estimate the software cost, the frequency of changing the scope and requirements of the project, and the number of changes of scope and requirements. However, this research may not include all the factors that influence software cost estimation in government projects yet. There might be other factors that might influence SCE in the public sector. These factors can assist the regional government of Indonesia to effectively and quantitatively analyze the factors that significantly impact software development in Indonesian regional government context. Those factors can be included as parameters in estimating the software cost and also to enhance the software cost estimation process. Thus, it can reduce the risk of the project from overrunning and over budget.
BİLİŞİM SİSTEMLERİ ARAŞTIRMA ALANINDAKİ GENİŞLETİLMİŞ GERÇEKLİK YAYINLARININ METİN MADENCİLİĞİ VE DOĞAL DİL İŞLEME (NLP) TEKNİKLERİ YOLUYLA ANALİZİ

The aim of the study is to cluster and to classify the scientific papers regarding Extended Reality indexed in Web of Science database. To achieve this goal, Extended Reality related publications were located and gathered from the database. NLTK library was used for tokenization, stop words removal, and lemmatization operations. The TF-IDF vectorizer method in the Sklearn library was used to convert words to vector format. Then, the keywords of the publications were clustered using K-Means. The keywords in each cluster were searched throughout the abstract of each publication. The publication was labeled as the name of the cluster wherein the largest number of keywords matches the words in its abstract. Then, Support Vector Classifier, and Multinomial Naïve Bayes machine learning algorithms and Gated Recurrent Unit deep learning algorithms were conducted for classification. The results of deep learning and machine learning have been compared and this comparison yielded that the dataset is more suitable for deep learning in comparison to machine learning. Accuracy values are reported as 90.4%, 77.2%, and 99.8% for Support Vector Classifier, Multinomial Naïve Bayes, and Gated Recurrent Unit respectively. This study provides evidence that the GRU architecture is more effective than the classical machine learning algorithms.
Delineating The Relationship Between Innovation Strategy And Strategic Planning on Small Firm

The aim of this paper is to establish and delineate a relationship between innovation strategy and strategic planning toward firm performance based on both theories resource-based view and diffusion innovation theory. Successful firms are always aware to effectively implement these strategies as a powerful resource, in order to ensure its survival among current and potential rivals. Therefore, this paper review previous studies and find a critical gap in the literature, since very few studies that investigate the two variables as a strategic resource in single research hence, this paper will fill the emerged gap and provide several implications for policymakers and related stakeholders.
Promoting websites of scientific libraries

The author examines various aspects of website promotion in scientific and technical libraries. Possible ways and vectors of website promotion based on existing sections of websites and Internet portals are suggested, e. g. dissemination of information on sci-tech developments. Digital exhibitions, news, accounts in social media and at video hostings, etc. The option of scientist’s personal account is discussed: using these accounts enables access to the full range of services presented in scientific and technical libraries, while the feedback is also provided. Promotion through methodological and consulting support is discussed. The experience of Pushchino Research Center Library is shared. The author concludes that the integrated approach is needed to promote websites and portals of sci-tech libraries based on the information on library services and capabilities and on science popularization.
A NEW METHOD FOR DEHAZING OF UAV REMOTE SENSING IMAGES BASED ON IMPROVED DARK CHANNEL PRIOR

Abstract. Aiming to solve the problem of loss of important image information, such as blurred details and low contrast, caused by fog, haze and other meteorological influences in the slope monitoring process of UAV remote sensing images, a new method of improving dark channel image dehazing based on channel-weighted analysis and compensation function is proposed by a training of multilayer perceptron (MLP) in this study. First, based on the dark channel prior principle, the original hazy UAV image is mapped to obtain the estimated values of atmospheric light and rough transmittance. Next, by counting the RGB three-channel values of the pixels in the high-brightness regions, and analyzing the scattering of the RGB three-channel values in the haze, a color recovery module of atmospheric light is constructed, and the estimated value of atmospheric light is optimized. Then, according to the global transmittance, the compensation boundary value is determined and a functional relationship between different brightness regions and the increment of transmittance is established as a compensation function to optimize the rough transmittance. Finally, perform secondary optimization on the rough transmittance with the multi-layer perceptron (MLP) to obtain a smoother transmittance value. The experimental results show that the image processed by the proposed method has good contrast. The color saturation and authenticity are effectively maintained. And the detailed information of the mountain recorded by the image is better restored, which can provide a real data basis for slope monitoring.
Libraries in the digital world: On the status renewal

The author analyzes the problem of foreign libraries’ changing status in the digital world. During the recent decade of rocketing digitalization of various aspects of social life, the libraries have been demonstrating their ability to solve many complicated sociotechnological problems related to information structure reorganization, introduction of access management models, and improvement of user services. The author focuses on antagonistic interaction of digitalization and democratization processes in the circumstances of global information capitalism: along with commercialization of access to digital content secured by monopolistic providers of scientific databases and substantial digital colonization of the countries with underdeveloped technological infrastructure, the initiatives of open access licensing and “copyleft” system, etc., take place. The experience of libraries MIT (USA) is analyzed where the technological priorities are balanced with the public access to controlled data arrays to secure the high status of libraries in the global digital future. The author examines the emerging digital library paradigm in the process of progressive adaptation to the e-civilizational infrastructure within the concepts “libraries 1.0” (comprising websites, servers, HTML-format, integrated information systems), “libraries 2.0” (social media, blogs, service-oriented platforms, XML, RSS), and “libraries 3.0” (Linked Open Data, personal area networks, cloud storage, sematic web).
Blockchain analysis of the Bitcoin market. (Part 2)

The detailed analysis of the Bitcoin network and its main participants. The expert authors (Igor Makarov, London School of Economics, Antoinette Schoar, MIT Sloan School of Management) completed the study authorized by the National Bureau of Economic Research (NBER), the US-based private agency. The Bitcoin network is defined as a new database comprising many of public and proprietary sources to link bitcoin address to real object, and an extensive set of algorithms to extract information on market key players behavior. Three major pieces of analysis of the Bitcoin eco-system were conducted. First, the authors analyze the transaction volume and network structure of the main participants on the blockchain. Second, they document the concentration and regional composition of the miners which are the backbone of the verification protocol and ensure the integrity of the blockchain ledger. Finally, they analyze the ownership concentration of the largest holders of Bitcoin. The researchers found that 1/3 of all bitcoins issued were owned by 10,000 individual investors. They conclude that the high concentration makes the first cryptocurrency market vulnerable to hypothetical hacker attack. The translator notes that paraphrasing English text in Russian was rather challenging due to the newness of the financial agenda and introduction of the term entity extensively used in the Western countries though new to Russia. Nevertheless, it is necessary to introduce readers to the bitcoin technology which will be also practical and useful for the library and information community.
Blockchain technology in supply chains

Aim: Blockchain technology (BCT) is a relatively new technological development, promising strong gains in the areas of product traceability and visibility, end-to-end coordination (E2E), governance, and efficiency of supply chains. The aim of this study is to gain a better understanding of the impact of BCT on these performance measures.&#x0D; Design / Research methods: Hypotheses were tested with survey data from 119 supply chain professionals from Northern American SMEs.&#x0D; Conclusions / findings: The results confirm the positive impacts of BCT on all performance measures. E2E coordination is the integration of information, goods, and money within an organisation or supply chain. E2E coordination appeared to benefit from the use of BCT, enabling information sharing in a safe way. The findings suggest that BCT use fosters E2E coordination, which in its turn also positively affects financial performance.&#x0D; Originality / value of the article: Despite the increasing interest in and use of, BCT, there is little empirical evidence for the effect on supply chain performance. Many studies are anecdotal and lack empirical evidence.&#x0D; Implications of the research (if applicable): Companies should acknowledge the impact of BCT use on the various supply chain performance measures. Implementing and using BCT is likely to foster improvement in a wide range of performance indicators. &#x0D; Limitations of the research (if applicable): Companies use different types, versions, varieties, and forks of blockchain, all having their own strong and weak points. Future studies could investigate and include the nuances within different forks of BCT.
Our Unique Scholar Fellow. On the occasion of the 80-th anniversary of Valery Pavlovich Leonov

The unique portrait of Valery P. Leonov, outstanding bibliologist, bibliography and library scientist, former long-term director of the Library of the Academy of Sciences is based on the digest of his scholarly works. Valery P. Leonov enjoys word-wide popularity and impeccable scholarly reputation. He interprets the written records, book and library esoterically. He pays serious attention to the phenomenon of serendipity or insight. It was he who introduced the processoriented concept of library science, and he advocated his concept at the highest bodies of the Russian Academy of Sciences. Valery P. Leonov’s works, as well as his personal experience evidence on the way of high-caliber professional in the library community.
Comparative analysis of bibliometric indicators of Russian journals in agroengineering

The results of the bibliometric analysis of scientometric indicators of scientific journals in the sphere of agricultural mechanization and electrification are presented. The publications were selected based on SRSTI (State Rubricator of Sci-tech Information, GRNTI). All national journals in the area were analyzed. The selected bibliometric indicators provide for the multirater assessment of the journals. These are: citation five-year impact factor, loadings, and self-citation coefficient. Russian Science Citation Index (RSCI) Database served as the source for the data on every journal. Finally, five most significant publications were chosen, with three of them already included in the RSCI Database, and the remaining two – being recommended for inclusion. The completed comparative analysis permits to identify the most demanded journals for each indicator. The Scientific Journal of KubSAU is the most cited one, also leading in the number of loadings. The Agricultural Machinery and Technologies Journal demonstrates the highest impact factor. The Tractors and Agricultural Machinery Journal shows the lowest self-citation coefficient. The factors to increase the use of scientific serials are discussed. The obtained results may be used to increase authority and citation of publications in agroengineering, and to support their acquisition to the sci-tech library collections.
Character and Learning Outcomes of Civics in VCT Learning Assisted by Audio Visual Media

This research was conducted because of Civics' low character and student learning outcomes due to ineffective use of learning models and media. This study aims to analyze whether there is an effect of the VCT learning model assisted by audio-visual media on the character and learning outcomes of fifth-grade Civics students. This research is a quasi-experimental study with a post-test-only control group design. The research population was 170 students, with a sample of 74 students determined by group (intact group) with the Gugus random sampling technique. Student character data was collected by questionnaire, and an objective test collected student learning outcomes of Civics. The analysis technique uses descriptive analysis and manova. The calculation results of the average character score of 85.10 are in the very good category. Civics learning outcomes of 81.90 are in the very good category, while the score obtained in the control class is the character score of 80.29, including the very good category. The Civics learning outcome score of 68.14 is in a good category. Based on these results, it can be concluded that the VCT learning model assisted by audio-visual media positively affects fifth-grade Civics' character and learning outcomes. Therefore, the problem of the gap between the expectations of the 2013 curriculum and the facts in the field regarding the character and learning outcomes of Civics for fifth graders has been resolved by the VCT learning model assisted by audio-visual application media.
The concept of recommendatory bibliography in the works by E. K. Bespalova within the context of modern library and information sciences

The authors discuss the scientific legacy of Professor Emilia Konstantinonva Bespalova (1930–2007), prominent figure in the library and information sphere, Doctor of Science in Pedagogy. Her life and professional career will stay put in in the glorious history of Russian intelligentsia, which has always been distinguished by diligence and selfless worship to culture and education. Bespalova’s legacy is vast and diverse. Her works cover the relevant topical problems of the library and information sphere and are highly demanded to this day. However, many aspects of her work have been understudied, in particular, her contribution to the recommendatory bibliography. For the first time, the authors analyze Bespalova’s views on recommendatory bibliography and her methodological concepts she was developing since 1970. The conceptual content of Bespalova’s Cand. Sc. thesis work is illuminated. In her works, Bespalova introduced the concept of recommendatory bibliography comprising terminological evolution, origins, characteristics of this subtype of national bibliography, periodization and author definition of the term “recommendatory bibliography”. The concept has been developed in the later works. The authors offer conceptual analysis of these works.