Reviewerly/exHarmony huggingface dataset:
A Structure-Aware Deep Learning Network for the Transfer of Chinese Landscape Painting Style

Recently, deep learning technology has made a breakthrough in computer vision, image processing, and other fields. Some researchers suggested neural style transfer method using a convolutional neural network (CNN). They established the correlation of features in a neural network to be treated as the style. However, their performance is unacceptable for Chinese landscape painting. According to the property of the Chinese landscape painting, this paper proposes a novel two stage style transfer method that imitates multiple styles of Chinese landscape painting based on deep learning. The structure of an input photo was simplified in the first stage. Then, the result of the first stage was transferred into the final stylized image in second stage. A generative adversarial network (GAN) is applied to train in each stage. Besides, a novel loss function was proposed to keep the shape of the content image. Finally, our method haves successfully imitated several styles of Chinese Landscape ink painting.
Multi-agent Path Finding for Indoor Quadcopters

We study the planning-acting loop for the multi-agent path finding problem (MAPF). MAPF is a problem of navigating agents from their start positions to specified individual goal positions so that agents do not collide with each other. We focus on executing MAPF plans with a group of Crazyflies, small indoor quadcopters, for which we developed a platform that integrates decision theoretic planning and plan execution modules. Our platform can be used for testing suitability of variants of MAPF for execution with real agents. We show how to modify the existing continuous-time conflict-based search algorithm (CCBS) to produce plans that are suitable for execution with the quadcopters. Our finding is that the CCBS algorithm allows for extensions that can produce safe plans for quadcopters, namely cylindrical protection zone around each quadcopter can be introduced at the planning level.
A Bibliometric Analysis of the Evolution of State-of-the-Art Blockchain Technology (BCT) in the Agrifood Sector from 2014 to 2022

In recent years, BCT has garnered significant attention from researchers worldwide. The technology in question is a distributed database system characterised by its decentralised nature and lack of reliability. BCT has been widely adopted by numerous governments and scholars across various sectors for a number of years. Blockchain technology also involves highly innovative and advanced concepts. Given the increasing interest among scholars in the academic community regarding the agrifood supply chain, the objective of this study was to investigate BCT and its potential for application in the fields of food and agriculture. This research paper presents a bibliometric analysis of articles on the utilisation of BCT in the fields of food and agriculture. This study discusses scholarly articles that have been published in esteemed academic journals and conferences. Through our bibliometric analysis, we aimed to discern the recurring trends and themes within the research on BCT in relation to agrifood systems. Furthermore, this study examines a diverse array of research domains, prominent scholarly publications, leading publishing platforms, prominent funding institutions, and the prospective trajectory of future research. This study also presents the prominent patterns and themes within this field through an analysis of the most influential scholarly articles, authors, countries, and keywords found in the existing literature. Hence, this research employed various analytical techniques, including analyzing the co-occurrence of author keywords, bibliographic coupling analysis, network view map analysis, and co-citation analysis. This study holds promise as a valuable learning resource for aspiring researchers seeking to acquire compelling and pertinent information about research outcomes from studies on the utilisation of BCT in the field of smart agriculture.
GA evolved CGP configuration data for digital circuit design on embryonic architecture

Embryonic architecture that carries self-evolving design with fault tolerant feature is proposed for deep space missions. Fault tolerance is achieved in the embryonic architecture due to its homogeneous structure. The cloning of configuration data or genome data to all the embryonic cells makes each cell capable of selecting required cell function using selective gene. The primary digital circuits of avionics are implemented on the fabric, where the configuration data in Cartesian Genetic Programming (CGP) format is evolved through customized GA. The CGP format is preferred over LUT format for the circuit configuration data due to its fixed data size in case of modular design. Further the CGP format enables fault detection at embryonic cell level as well as logic gate level. The various combinational and sequential circuits like adder, comparator, multiplier, register and counter are designed and implemented on embryonic fabric using Verilog. The circuit performance is evaluated using simulation. The proposed PHsClone genetic algorithm (GA) design with parallel-pipeline approach is to achieve faster convergence. Four concurrent PHsClone GA executions (four parallel threads) achieve convergence for the 10 times faster for a 1-bit adder, and 3 times faster for a 2-bit comparator.
A History of the P.A. Cherkasov Fundamental Electronic Library (1992–2023)

This work examines the history of the P.A. Cherkasov
Methodological Aspects of Content – Based Strategies in Classroom Managerial Activity

The cardinal changes in the socio-economic situation that have taken place in recent decades, the intensive development of market relations and integration processes have also affected the sphere of higher education, since, like many countries of the world, they find themselves in a situation of intense competition, which imposes special responsibility on managerial activity and requires current and future teachers of universities to master such an area of scientific knowledge and management practice in education.For pedagogical science, it is relevant to comprehend educational management as an interdisciplinary multidimensional phenomenon, identify the pedagogical aspects of this phenomenon, and comprehend the concepts and strategies of educational management in domestic and foreign pedagogy.The pedagogical component of this phenomenon is associated with the content and methods of organizing the educational process, with the transmission and formation of collective and individual knowledge.At the same time, these processes are carried out in organizations of various types: schools and universities, enterprises, public organizations.The implementation of the control function involves: monitoring progress and attendance, identifying possible problems for each student.The control of activity is understood as the realization of self-control of the class teacher, the student team and each student as an individual This research paper describes the problems of the methodological aspects of content-based strategies in classroom managerial activity and specifics of the designated technology, the advantages of its implementation in higher educational science, comparing the difficulties that the academic staff of the university may face when implementing it.The paper examines the contradictions faced by teachers in specific aim and teachers of specialized disciplines, and gives a critical assessment of how well curricula and programs meet the needs of teachers and students.The appropriate sides and disadvantages of using the technology of CBS in the organization of classes in order to help teachers effectively plan their activities are also
Evaluating Model Differencing for the Consistency Preservation of State-based Views.

While developers and users of modern software systems usually only need to interact with a specific part of the system at a time, they are hindered by the ever-increasing complexity of the entire system.Views are projections of underlying models and can be employed to abstract from that complexity.When a view is modified, the changes must be propagated back into the underlying model without overriding simultaneous modifications.Hence, the view needs to provide a fine-grained sequence of changes to update the model minimally invasively.Such fine-grained changes are often unavailable for views that integrate with existing workflows and tools.To this end, model differencing approaches can be leveraged to compare two states of a view and derive an estimated change sequence.However, these model differencing approaches are not intended to operate with views, as their correctness is judged solely by comparing the input models.For views, the changes are derived from the view states, but the correctness depends on the underlying model.This work introduces a refined notion of correctness for change sequences in the context of model-view consistency.Furthermore, we evaluate state-of-the-art model differencing regarding model-view consistency.Our results show that model differencing largely performs very well.However, incorrect change sequences were derived for two common refactoring operation types, leading to an incorrect model state.These types can be easily reproduced and are likely to occur in practice.By considering our change sequence properties in the view type design, incorrect change sequences can be detected and semi-automatically repaired to prevent such incorrect model states.
One-Way Model Transformations in the Context of the Technology-Roadmapping Tool IRIS.

CONTEXT: Today's industry heavily depends on the collaboration of multiple companies that have to exchange a lot of information.When these companies use technology roadmapping and model-driven development, this leads to the exchange of very large models, which is governed by competition laws, and the companies' interest in protecting their intellectual property. OBJECTIVE:We suggest an automated one-way model transformation approach to remove content worth protecting from a given model in the context of the graphical technology-roadmapping modeling tool IRIS.METHOD: We elaborate constraints that an obfuscated model must fulfill.Based on these, we systematically identify and analyze appropriate one-way transformations to enable the desired level of obfuscation, implementing a proof of concept implementation in IRIS.Our approach first transforms the model into a flattened constraint system and uses nine selected transformations-ranging from constant folding to the tailoring of expressions-to create a new model without the sensitive content.We evaluate our transformations according to a set of predefined properties and constraints regarding their effects on the behavior of the model and the inferable information.LIMITATIONS: Our obfuscation concerns the model and the embedded formulas but does not deal with individual data, which may be subject to privacy-related issues.RESULTS: We find that the identified transformations are applicable in practice and that they can remove a lot of sensitive information from a given model.Future work includes dealing with individual data and protecting against reverse-engineering attacks by domain experts.
Strategizing about AI technology adoption

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings The paper develops a strategic decision-making framework that introduces six types of AI strategies, that can inform SMEs Originality/value The briefing saves busy executives, strategists, and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
A journal name semantic augmented multi-dimensional feature fusion model for scholarly journal recommendation

Recommending appropriate academic journal to researchers has become a time-consuming and challenging task. In this paper, we propose a Journal Name Semantic-enhanced Multidimensional Feature Fusion Journal Recommendation (JNSMFFJRec) model that both integrates journal name semantic information and capture deep semantic information. The model is the first of its kind to fuse multi-dimensional feature based on BERT layer and tow-tower layer, that only requires the abstract and the title of a manuscript to identify academic journal. Compared to advanced benchmark models, the experiments based on the real dataset Information System and Management (ISaM) of Scopus show that the performance of the proposed academic journal recommendation model outperforms. Specifically, the Mean Average Precision improved by 1.34%-19.42%; the Mean Reciprocal Rank improved by 3.56%-59.79%; the TOP-5 Recall improved by 1.72%-43.94%; and the result Diversity improved by 2.4%-18.6%.
Teman Sebaya dan Pengaruhnya terhadap Penggunaan Narkoba pada Remaja Kelas 12 di SMK Taruna Bhakti Cianjur

Introduction: The development of today's era has affected a person's behavior, especially the effect of peers. Peers can affect behavior, the effect is in the form of positive effect and negative effect. The effect of peers plays an important role in drug use, this is because it is a condition of convenience to be accepted by members of their peer group. Objectives: This study aims to determine the relationship between peers’ effect on drug use in adolescent class 12 at Taruna Bhakti Cianjur Vocational School, 2021. Method: This study used quantitative research with correlation research and used a cross-sectional design where the population in this study was 12th-grade students at SMK Taruna Bhakti Cianjur with a total sample of 82 students. The sampling technique used is random sampling. The instrument consisted of 2 questionnaires, namely the peer influence questionnaire and the drug use questionnaire which the researcher made himself. Data analysis used in this study was univariate and bivariate analysis using the chi-square test. Result: Found the results of the analysis relationship between peers’ effect on drug use it is found that there are as many as 38 (46,3%) respondents to peers effect positive effect on drug use make use of. while the respondent to peers effects a negative effect on drug use, there 26 (53,7%). The statistical test results obtained the value of pvalue= 0,002 smaller than 0,05. Conclusion: there is a relationship between peers’ effect on drug use in adolescents. According to the doctor's advice, it is wiser to use drugs.
Novelty Seeking Multiagent Evolutionary Reinforcement Learning

Coevolving teams of agents promises effective solutions for many coordination tasks such as search and rescue missions or deep ocean exploration. Good team performance in such domains generally relies on agents discovering complex joint policies, which is particularly difficult when the fitness functions are sparse (where many joint policies return the same or even zero fitness values). In this paper, we introduce Novelty Seeking Multiagent Evolutionary Reinforcement Learning (NS-MERL), which enables agents to more efficiently explore their joint strategy space. The key insight of NS-MERL is to promote good exploratory behaviors for individual agents using a dense, novelty-based fitness function. Though the overall team-level performance is still evaluated via a sparse fitness function, agents using NS-MERL more efficiently explore their joint action space and more readily discover good joint policies. Our results in complex coordination tasks show that teams of agents trained with NS-MERL perform significantly better than agents trained solely with task-specific fitnesses.
Keep the Ball Rolling: Analyzing Release Cadence in GitHub Projects

Release cadence is the measure of time between software releases, both internal and external. Few studies analyze popular open-source projects’ release cadence and use. In this work, we gathered over 8,000 GitHub projects from four popular programming languages; Go, Java, Python, and Ruby. Project were categorized into slow, modern, rapid, and rapid+ release cadence groups. We determined that only 13% of projects had a rapid release cadence of under 30 days. Applying NLP and topic modeling, we extracted the top 5 frequent topics for programming languages and obtained insights into their common uses. For example, Go projects are commonly used for Kubernetes tooling, while Ruby projects often leverage Rails for web development. We observed no significant relationship between frequent topics and the release cadence categories. This finding suggests release cadences are independent of the type of software delivered for a programming language.
A Combined Countermeasure Against Side-Channel and Fault Attack with Threshold Implementation Technique

Side-channel attack (SCA) and fault attack (FA) are two classical physical attacks against cryptographic implementation. In order to resist them, we present a combined countermeasure scheme which can resist both SCA and FA. The scheme combines threshold implementation and duplication-based exchange techniques. The exchange technique can confuse the fault propagation path and randomize the faulty values. The threshold implementation technique can ensure a provable security against SCA. Moreover, it can also help to resist the FA by its incomplete property and random numbers. Compared with other methods, the proposed scheme has simple structure, which can be easily implemented in hardware and result in a low implementation cost. Finally, we present a detailed design for the block cipher light encryption device (LED) and implement it. The hardware cost evaluation shows our scheme has the minimum overhead factor.
Technologies and Digital Competences in Portuguese Education: History of its Integration in Pedagogical Practices since the Beginning of the 20th Century

This study aims to analyse the evolutionary context of the introduction of technology in Portuguese schools, from the beginning of the 20th century to the present day, and to identify the digital competences of Portuguese teachers at different educational levels. The analysis, qualitative and quantitative in nature, allowed us to conclude that technologies had a slow diffusion in Portuguese schools, because of the scarcity of resources and residual investment in teacher training, giving the use of technology in school a more irregular and playful character rather than truly integrated in pedagogical practices to promote the quality of learning. Although in recent years there has been still some conservatism in the use of technology, very focused on its instrumental use, there have been more practices with pedagogical intent and more focused on the active participation of students, also noting the growing importance of teacher training in this field of digital technologies, with the aim of making teachers more competent and fluent in the pedagogical use of digital. Furthermore, the study focused on the teachers' perception of their digital competences in three dimensions: the teachers' professional and pedagogical competences and the students' competences from the DigCompEdu framework and the self-assessment questionnaire of digital competences built from the same framework - DigCompEdu Check-In. The analysis of the answers obtained in this questionnaire (collected from the participation of 434 teachers of Basic and Secondary Education and 118 of Higher Education) showed that teachers need to increase their levels of digital proficiency through specific training, since they present, globally, a moderate level of digital proficiency - level B1 -Integrators- being the areas 4 - Evaluation - and 6 - Digital empowerment of students, the ones that present the greatest weaknesses. Keywords: history of education, educational technologies, Portugal, teachers' digital competences, teachers' training
Message from the MSR 2023 Data and Tool Showcase Track Co-Chairs

On behalf of the entire Program Committee, it is our pleasure to welcome you to the Data and Tool Showcase Track of MSR 2023!The goal of this track is to provide a forum to actively promote and recognize the creation of reusable datasets and tools that are designed and built not only for a specific research project, but for the MSR community as a whole.This year, the Data and Tool Showcase Track has received 42 submissions for review.The papers went through a rigorous review process with at least 3 reviewers.Papers were evaluated and discussed against detailed evaluation criteria (value, usefulness, reusability, and availability for datasets and tools, and quality, clarity, and relevance for papers), according to our published review guidelines.We encouraged reviewers to be active and constructive in their review and asked them to discuss until a consensus was reached, even if their initial assessments differed.We are pleased to report that the Program Committee has accepted 22 papers for publication and presentation at the conference, resulting in an acceptance rate of 52%.Similar to previous years, we do not have a threshold for the acceptance rate.
Data Recovery from Encrypted Image and Recovering Image

This paper refers to the data hiding technique in an encrypted image and restoring image as it was before to its fullest. There are three bids of the framework to this process, which are a content owner, data hiding and recipient. The content owner encrypts the image with ciphertext making it an encrypted image. Data hider channelizes encrypted image into 3 different channels and adds each with additional bits in order to obtain marked encrypted image. At the recipient end, the noise from the image could be removed consuming the extraction key and the image obtained will be intact as original. Utilizing RDH_EI method, we not only receive secret information but also, the image is recovered using progressive recovery.
The use of robotics in the education of students with special educational needs

The increasing number of children with special needs requires the improvement of methods in education by reducing the barriers to learning. Some research conducted on students with special needs concluded that students were ready to plan, initiate, and continue even a difficult project. In this sense technology can offer all students new possibilities, possibilities to learn and practice various important cognitive and social skills. There are indications that children with Special Educational Needs, with the help of educational robotics, have managed to maintain their attention and increase their participation in the educational process.
Application of Convolutional Neural Network in Accurate Breast Cancer Identification

As one of the most common cancers in women, breast cancer has the highest incidence in the world.Nearly 600,000 people die from breast cancer each year, and early detection is essential for breast cancer treatment.In recent years, the rapid development of artificial intelligence has provided unprecedented ideas for the precise diagnosis and treatment of breast cancer.In this paper, the practical application of artificial intelligence convolutional neural network in breast cancer recognition is studied, which greatly improves the detection speed and saves a lot of time for doctors to further judge the condition.