Reviewerly/exHarmony huggingface dataset:
Structured Compression of Convolutional Neural Networks for Specialized Tasks

Convolutional neural networks (CNNs) offer significant advantages when used in various image classification tasks and computer vision applications. CNNs are increasingly deployed in environments from edge and Internet of Things (IoT) devices to high-end computational infrastructures, such as supercomputers, cloud computing, and data centers. The growing amount of data and the growth in their model size and computational complexity, however, introduce major computational challenges. Such challenges present entry barriers for IoT and edge devices as well as increase the operational expenses of large-scale computing systems. Thus, it has become essential to optimize CNN algorithms. In this paper, we introduce the S-VELCRO compression algorithm, which exploits value locality to trim filters in CNN models utilized for specialized tasks. S-VELCRO uses structured compression, which can save costs and reduce overhead compared with unstructured compression. The algorithm runs in two steps: a preprocessing step identifies the filters with a high degree of value locality, and a compression step trims the selected filters. As a result, S-VELCRO reduces the computational load of the channel activation function and avoids the convolution computation of the corresponding trimmed filters. Compared with typical CNN compression algorithms that run heavy back-propagation training computations, S-VELCRO has significantly fewer computational requirements. Our experimental analysis shows that S-VELCRO achieves a compression-saving ratio between 6% and 30%, with no degradation in accuracy for ResNet-18, MobileNet-V2, and GoogLeNet when used for specialized tasks.
The Relationship between Perceived Organisational Support and Creative Performance of Employees: A Study from the Public Sector in Syria

The aim of this study is to determine the relationship between perceived organisational support (POS) represented by the following dimensions: behaviour of leaders towards subordinates, contribution to decision-making, support and self-assurance among employees, and the creative performance of employees, as well as whether there is a difference in level of perception of organisational support according to demographic variables (sex, functional age, scientific qualification). The research sample consisted of all 138 employees of the Syrian Telecommunications and Post Regulatory Authority (SY-TPRA). Using the analytical descriptive method, a questionnaire was designed and distributed throughout the sample. The findings indicate that POS has a strong positive correlation with the creative performance of employees, and that there is no difference in employees’ level of perception of the organisational support depending on the considered demographic variables. As far as the researchers are aware, this research is the first of its kind to be carried out in the telecommunications sector in Syria. Practically, this research will help decision makers improve the creative performance of staff on the one hand, and to develop management practices that are properly perceived by employees on the other.
An Actor-Critic Method for Simulation-Based Optimization

We focus on a simulation-based optimization problem of choosing the best design from the feasible space. Although the simulation model can be queried with finite samples, its internal processing rule cannot be utilized in the optimization process. We formulate the sampling process as a policy searching problem and give a solution from the perspective of Reinforcement Learning (RL). Concretely, Actor-Critic (AC) framework is applied, where the Actor serves as a surrogate model to predict the performance on unknown designs, whereas the actor encodes the sampling policy to be optimized. We design the updating rule and propose two algorithms for the cases where the feasible spaces are continuous and discrete respectively. Some experiments are designed to validate the effectiveness of proposed algorithms, including two toy examples, which intuitively explain the algorithms, and two more complex tasks, i.e., adversarial attack task and RL task, which validate the effectiveness in large-scale problems. The results show that the proposed algorithms can successfully deal with these problems. Especially note that in the RL task, our methods give a new perspective to robot control by treating the task as a simulation model and solving it by optimizing the policy generating process, while existing works commonly optimize the policy itself directly.
A Survey on Extraction of Causal Relations from Natural Language Text

As an essential component of human cognition, cause-effect relations appear frequently in text, and curating cause-effect relations from text helps in building causal networks for predictive tasks. Existing causality extraction techniques include knowledge-based, statistical machine learning(ML)-based, and deep learning-based approaches. Each method has its advantages and weaknesses. For example, knowledge-based methods are understandable but require extensive manual domain knowledge and have poor cross-domain applicability. Statistical machine learning methods are more automated because of natural language processing (NLP) toolkits. However, feature engineering is labor-intensive, and toolkits may lead to error propagation. In the past few years, deep learning techniques attract substantial attention from NLP researchers because of its' powerful representation learning ability and the rapid increase in computational resources. Their limitations include high computational costs and a lack of adequate annotated training data. In this paper, we conduct a comprehensive survey of causality extraction. We initially introduce primary forms existing in the causality extraction: explicit intra-sentential causality, implicit causality, and inter-sentential causality. Next, we list benchmark datasets and modeling assessment methods for causal relation extraction. Then, we present a structured overview of the three techniques with their representative systems. Lastly, we highlight existing open challenges with their potential directions.
Properly learning decision trees in almost polynomial time

We give an $n^{O(\log\log n)}$-time membership query algorithm for properly and agnostically learning decision trees under the uniform distribution over $\{\pm 1\}^n$. Even in the realizable setting, the previous fastest runtime was $n^{O(\log n)}$, a consequence of a classic algorithm of Ehrenfeucht and Haussler. Our algorithm shares similarities with practical heuristics for learning decision trees, which we augment with additional ideas to circumvent known lower bounds against these heuristics. To analyze our algorithm, we prove a new structural result for decision trees that strengthens a theorem of O'Donnell, Saks, Schramm, and Servedio. While the OSSS theorem says that every decision tree has an influential variable, we show how every decision tree can be "pruned" so that every variable in the resulting tree is influential.
On the Control of Flying Qubits

The control of flying quantum bits (qubits) carried by traveling quantum fields is crucial for coherent information transmission in quantum networks. In this paper, we develop a general framework for modeling the generation, catching and transformation processes of flying qubits. We introduce the quantum stochastic differential equation (QSDE) to describe the flying-qubit input-output relations actuated by a standing quantum system. Under the continuous time-ordered photon-number basis, the infinite-dimensional QSDE is reduced to a low-dimensional deterministic non-unitary differential equation for the state evolution of the standing system, and the outgoing flying-qubit states can be calculated via randomly occurring quantum jumps. This makes it possible, as demonstrated by examples of flying-qubit generation and transformation, to analyze general cases when the number of excitations is not reserved. The proposed framework lays the foundation for the design of flying-qubit control systems from a control theoretic point of view, within which advanced control techniques can be incorporated for practical applications.
Perception of nursing students towards educational quality in Khyber Pukhtankhwa Pakistan

Quality education is among the 17 Sustainable development goals recognized by the United Nations in September 2015. Quality education means that "Quality learners, a quality learning environment, quality materials, quality processes, and quality outcomes emphasize the necessity of focusing on all five key characteristics that are all vital aspects of education given by an education system". Objective: To assess the perception of nursing students towards educational quality in Khyber Pakhtunkhwa. Methods: A descriptive cross-sectional study was conducted in the nursing institutes of Khyber Pakhtunkhwa through a self-structured questionnaire from May 2022 to July 2022 having a sample size of 236. Results: The overall positive views of the students were (77%) towards the educational quality. The maximum mean score of students towards education quality was agree (45±9), then strongly agree (21±7), followed by neutral (14±3), strongly disagree (11±7), and disagree (9±6). Conclusions: There was a positive perception of students towards educational quality, but there are some factors that required paying attention.
Overparameterization and generalization error: weighted trigonometric interpolation

Motivated by surprisingly good generalization properties of learned deep neural networks in overparameterized scenarios and by the related double descent phenomenon, this paper analyzes the relation between smoothness and low generalization error in an overparameterized linear learning problem. We study a random Fourier series model, where the task is to estimate the unknown Fourier coefficients from equidistant samples. We derive exact expressions for the generalization error of both plain and weighted least squares estimators. We show precisely how a bias towards smooth interpolants, in the form of weighted trigonometric interpolation, can lead to smaller generalization error in the overparameterized regime compared to the underparameterized regime. This provides insight into the power of overparameterization, which is common in modern machine learning.
Web Content Strategy in Academic Libraries: Methods and Maturity

This paper presents a qualitative analysis of nine interviews with academic library practitioners discussing their approaches to Web content strategy work.Findings reveal shared challenges and suggest that, while awareness of content strategy appears to be growing, its practice remains intermittent for many.An updated version of a Content Strategy Maturity Model for Academic Libraries, reflecting participants' comments regarding planning, creation, delivery, governance, and user experience, provides a means to address these challenges flexibly within an institution's culture, resources, and circumstances.Participants also discuss the purpose of the library website and impact of the COVID-19 pandemic. Potential Limitations of MethodologyThe authors acknowledge that the recruitment methodology excluded individuals who were not identified as contacts via the earlier research study or who newly came into positions in the interim.Further, the time commitment inherent in an interview study may have dissuaded participation, and the extenuating circumstances of the pandemic
Artificial Intelligence and Civil Liability: Juridical Prospects and Legal Challenges

The benefits to individuals from the implementation and use of robots and other artificial intelligence applications are widely known. However, although the use of intelligent robots is not yet fully widespread, it is possible to anticipate that the introduction of these robots into society will present numerous moral, ethical and legal challenges. Currently, robots are considered products and they fall under Council Directive 85/374/EEC of 25 July 1985 on the approximation of the laws, regulations and administrative provisions of the Member States concerning liability for defective products. The European Union itself has expressed skepticism regarding the applicability of this directive to civil liability for damages that these autonomous and intelligent robotic systems may cause. The aim of this article is to identify and analyze what these challenges may be.
Media Systems as a Communicative Model of Current Educational Practices

Media communication systems are actively used in the current educational practice in the prevailing conditions of distance education and various blended learning forms. Since the pandemic began, media systems have been significantly improved and integrated into the educational process as digital tools that fully define the communication models of educational stakeholders. This article aims at a practical evaluation of the media systems’ use as communicative models of educational practices. The research methodology included a qualitative content analysis of educational media (platforms, social media, educational services) to classify communication models by the type of media systems used in education. The results show the dynamic of media systems development as the basis of communicative models of current educational practices. The study offers a classification of communicative models by the media type used in education: based on platforms, online services such as Student Response Systems (SRS); based on platforms – virtual educational services; based on social media; based on video conferences. Each communicative model has different communication goals and tools.
Construction of an RTD as Didactic Support for Non-Face-To-Face Lessons Due to COVID-19

As a result of the COVID-19 pandemic, there have been momentous changes in working in all sectors of the economy, including the education sector. The educational institutions where face-to-face lessons are taught overnight were forced to continue with distance classes (virtual and online). It is a reality that most schools and their communities were not prepared to deal with this atypical situation. Therefore, the objective was the development of a digital teaching resource (DTR) as pedagogical support, in online classes, of the Business Finance learning unit that is taught at the Escuela Superior de Cómputo (ESCOM) of the National Polytechnic Institute (IPN). Documentary analysis was carried out based on applied research, and the DTR was later built. This construction obeys the criteria considered for the elaboration of digital didactic resources proposed by the authors consulted, particularly in those required and evaluated by the Polytechnic Unit for Virtual Education (UPEV) of the National Polytechnic Institute (IPN), which focuses specifically on pedagogical, editorial, graphic and technical aspects.
Investigating the challenges of Criminology students in the course of Forensic Questioned Document Examination.

The sudden swift away from classrooms due to the pandemic outbreak, students and faculty members had greatly challenged in the lectures, practical examination of documents; presentation of examined signatures and; submissions of specimens used in signature and document comparison.This qualitative research used thematic analysis in describing the challenges among the third-year students who were enrolled in Forensic Questioned Documents Examination at the Data Center College of the Philippines.The researcher found out several themes under the category of lectures which includes: Accessibility of recorded discussion and limited lecture time; while in the Assessment this includes: themes of multiple online platforms and platform interruptions and lastly, as to Laboratory activity, themes were identified as development and reliability of specimens, quality resolution of uploaded standard specimen and self-study in which it was attributed to the problems encountered by the students in the course of Forensic Questioned Document Examination.Hence, the result of the study implied that creation of a system with specialized features intended for signature/handwriting comparison is highly encouraged.
Humanitarian aspect of formation of patriotic values of youth by the means of digital educational resources

The research is devoted to the problem of the humanitarian aspect of the use of digital technologies in the formation of patriotic values. The relevance of the indicated problem in the modern conditions of social development is stated. The events of recent years show how important it is to promptly solve the problems of the formation of patriotic values among youngsters. The implementation of the tasks of educating a patriot should be carried out at all levels of the education system. The research analyses the available material on digital support for the education system and innovative technologies for the introduction of e-learning; describes digital technologies that will help in solving the problem: registers of digital educational resources, Internet sites. Analysed electronic educational resources devoted to the formation of patriotic values. Conclusions are made about the effectiveness of using digital tools in the formation of patriotic values. It is claimed that the modern approach to the formation of patriotic values involves the use of new technologies that meet their interests and preferences. Digital technologies have significant didactic capabilities and their potential requires widespread employment in the educational process.
Actual problems of school education in the context of digitalization

The article is devoted to the study of the transformation of school education in the context of digitalization. The authors of the article reveal the main definitions of the concepts of “digitalization of education”, “digital education”, “digital learning”, “distance learning”. The features of the implementation of the digital educational environment in the school system of Astrakhan Region are considered, in particular on the example of MBOU Astrakhan Gymnasium No. 4. The advantages and disadvantages of digitalization of school education are revealed. The results of the study of actual problems of school education in the context of digitalization are presented.
Potential of digital learning environment in student career guidance

The article describes the potential of the digital learning environment in student career guidance. The authors study the factors that influence the design of students’ professional careers according to the changes in the digital environment and technology. The article considers the experience of student career guidance in the context of the digital learning environment. Particular attention is drawn to the practical and individualized approach of student career guidance in the higher school context. Examining the university’s experience resulted in arranging the challenges of student career guidance and proposing their solutions.
Challenges of digitalization of civic education of students in a socio-cultural safe educational environment

The objective of the article is to study the challenges of digitalization of civic education of students in a socio-cultural safe educational environment and to describe the ways to address them, based on the implementation of digital technologies presented in the form of Allan Carrington's Pedagogical Wheel. The methodological basis of the article is the theory of human security and humanization of education; informative-environmental, cybernetic, culturological approaches to civic education in the socio-cultural educational environment. The research methods included analysis, synthesis, and synthesis of the scientific literature, thesis research, and publications on the topic. Empirical methods: questionnaires, discussion, and survey (offline). The theoretical positions presented in the paper complement the main points of education digitalization, enriching the theory and methodology of pedagogical science.
Mechanisms of introduction of pedagogical design of multimedia educational products

Contemporary modernization of education takes place on the one hand under the influence of the evolution of society's expectations of its results, and on the other - the rapid spread of new technologies, the implementation of which would ensure the achievement of clear didactic results. Such technologies should include reproducible pedagogical design systems. They should be aimed at the optimal contextual solution of real pedagogical situations. The consideration of educational processes as isolated events in laboratory conditions leads to the detachment of mechanisms and methods for preventing and solving pedagogical risks from actual situations. The pedagogical means, methods, forms, techniques used should not be static, they require systematic adjustment and modernization in accordance with the ongoing processes in society, which involves the use of pedagogical design mechanisms that include various interactive means and also multimedia content. This article discusses the concept and characteristics of pedagogical design, the mechanisms and risks of its introduction using multimedia educational content in school. The study characterizes the advantages and risks of using a multimedia didactic context, the mechanisms of its introduction.
Estimation of the efficiency of use digital resources in elementary school in Astrakhan region

The study is devoted to the problem of digitalization of primary general education. The goal of digitalization in primary education is seen in its optimal adaptation to the successful solution of the intended pedagogical problems. The authors of the article clarify the definition of the concept of "digitalization of education", reveal the essence of the concept of "digitalization of primary education", provide substantiation of the theoretical and practical aspects of the topic. The article touches upon some aspects of the implementation into the practice of educational institutions of the main ideas of the Federal project "Digital Educational Environment". Digitalization of education covers all subjects of the educational process: students, teachers, parents of minor children. The pedagogical competence of primary school teachers in the use of digital education technologies is critical. The authors of the article describe the options for using digital resources in primary school and investigate the level of digital information technology skills of primary education teachers, as well as their use of digital resources in the educational process of primary school.
UQuAD1.0: Development of an Urdu Question Answering Training Data for Machine Reading Comprehension

In recent years, low-resource Machine Reading Comprehension (MRC) has made significant progress, with models getting remarkable performance on various language datasets. However, none of these models have been customized for the Urdu language. This work explores the semi-automated creation of the Urdu Question Answering Dataset (UQuAD1.0) by combining machine-translated SQuAD with human-generated samples derived from Wikipedia articles and Urdu RC worksheets from Cambridge O-level books. UQuAD1.0 is a large-scale Urdu dataset intended for extractive machine reading comprehension tasks consisting of 49k question Answers pairs in question, passage, and answer format. In UQuAD1.0, 45000 pairs of QA were generated by machine translation of the original SQuAD1.0 and approximately 4000 pairs via crowdsourcing. In this study, we used two types of MRC models: rule-based baseline and advanced Transformer-based models. However, we have discovered that the latter outperforms the others; thus, we have decided to concentrate solely on Transformer-based architectures. Using XLMRoBERTa and multi-lingual BERT, we acquire an F1 score of 0.66 and 0.63, respectively.