Reviewerly/exHarmony huggingface dataset:
Deep Dynamic Memory Augmented Attentional Dictionary Learning for Image Denoising

Motivated by the advance of deep learning methods, deep unfolding methods such as deep convolutional dictionary learning have achieved great success in image denoising tasks. The main advantages are inheriting both the merits of deep learning (strong learning capacity) and traditional machine learning (powerful interpretable capacity). We observe that the update of dictionaries and coefficients is highly correlated with the previous iterative stage information for deep unfolding-based methods. However, most existing deep convolutional dictionary learning methods deal with each iteration step individually, ignoring the inner-memory within the stage and cross-memory across the stages. To alleviate these issues, we propose a dynamic inner-cross memory augmented attentional dictionary learning (M2ADL) network with attention guided residual connection module, which utilizes the previous important stage features such that better uncovering the inner-cross information. Specifically, the proposed inner-cross memory fully utilizes the previous stage’s hidden and last-layer information to learn the dictionary. In addition, we develop a dual attention-guided residual connection module to well exploit the deep feature learning ability to capture the spatial-spectral attention across the deep tensor-based features. Considerable experiments on both synthetic and real image datasets demonstrate the superiority of the proposed method over other state-of-the-art methods.
How to make e-resources in patent information more attractive?

The author examines the significance of patent information and the experience of the All- Russian Patent and Technical Library in presenting its original e-resources in patent information. She reviews the types of Library’s multimedia resources and discusses the ways to render the content on inventive activities acquired on the basis of the documents in the State Patent Collection.
WHAT STRATEGIES ARE USED FOR THE PAYMENT OF REQUIREMENTS DEBT IN SOFTWARE DEVELOPMENT?

The concept of technical debt in software development emerged by Cunningham (1992). Since then, this topic has been discussed and explored by several authors. There are types of technical debt corresponding to the phases of the software development cycle, such as requirements debt. This type of debt was initially mentioned by Ernst (2012), approximately 20 years after the introduction of the technical debt metaphor. This article aims to identify which are the strategies for payment requirements debt since the advent of the concept. The method used was literature review and content analysis with the application based on the PRISMA-P protocol, through descriptive research. The results, so far, reveal that there is still little discussion on the subject of technical debt of requirements. The main approach of the research refers to the types of technical debt of code and architecture. RESUMO O conceito sobre dívida técnica em desenvolvimento de software foi mencionado preliminarmente por Cunningham (1992). Desde então, esse tema vem sendo discutido e explorado por diversos autores. Há tipos de dívida técnica correspondentes com as fases do ciclo de desenvolvimento do software, tal como a dívida técnica de requisitos. Esse tipo de dívida foi mencionado inicialmente por Ernst (2012), aproximadamente 20 anos após a apresentação da metáfora de dívida técnica. Este artigo tem como objetivo identificar quais são as estratégias para pagamento de dívida técnica de requisitos desde o advento do conceito. O método utilizado foi revisão da literatura e análise de conteúdo com a aplicação baseada no protocolo PRISMA-P, mediante pesquisa do tipo descritiva. Os resultados, até o momento, revelam que ainda há pouca discussão sobre o tema de dívida técnica de requisitos. A principal abordagem das pesquisas, é referente aos tipos de dívida técnica de código e arquitetura. Palavras-chave: Dívida Técnica, Requisitos, Pagamento, Pagar, Software. Keywords: Technical Debt, Payment, PayOff, Requirements, Software.
CENTRAL BANK DIGITAL CURRENCIES: THE ADVENT OF ITS IT GOVERNANCE IN THE FINANCIAL MARKETS.

Central Bank Digital Currency (CBDC) can be defined as a virtual currency based on node network and digital encryption algorithm issued by a country which has a legal credit protection. CBDCs are supported by Distributed Ledger Technologies (DLTs), and they may allow a universal means of payments for the digital era. There are many ways to proceed, they all require central banks to develop technological expertise. Considering these points, it is important to understand the new IT governance in the financial markets due to CBDC and digital economy. Information Technology is an essential driver that will allow the new financial industry design. This paper has the objective to answer two questions through an updated Systematic Literature Review (SLR). The first question is What IT resources and tools have been considered or applied to set the governance of CBDC adoption? The second; Identify IT governance models in the financial market due to CBDC adoption. Bank for International Settlements (BIS) publications, Scopus and Web of Science were considered as sources of studies. After the strings and including criteria were applied, fourteen papers were analyzed. This paper finds many IT resources used in the CBDC adoption and some preliminary IT design related to the IT governance of CBDC, in the results and discussion section the findings are more detailed. Finally, limitations and future work are considered.
CONTENT AND COMPETENCES FOR TEACHING SOFTWARE DESIGN IN THE COMPUTER SCIENCE COURSE: A MAPPING OF CC-2020, RF-CC-2017 AND SWEBOK-V3.0 ASSETS

The teaching of Software Engineering in higher computing courses needs to adapt to new technologies and tools that arise all the time. The Soft- ware Design area has the challenge of integrating the diversity of techniques in order to present a solution to a given problem, however the treatment of this challenge is largely not reflected in the curricula of Computing courses. In this sense, the objective of this work is to develop the mapping of assets between the curriculum of ACM/IEEE, SBC and SWEBOK guide specifically for the Soft- ware Design knowledge area in the Computer Science course. To this end, the methodology of analysis of reference documents was used to develop the map- ping and the peer review process aimed at validating this mapping. As a result, we highlight the correlation between the assets of CC2020 and RF-CC-2017 in the vision of competencies and the mapping of contents between the three reference documents related to Software Design. O ensino de Engenharia de Software nos cursos superiores de computação precisam adaptar-se as novas tecnologias e ferramentas que surgem a todo momento. A área de Software Design possui o desafio de integrar a diversidade de técnicas com o objetivo de apresentar uma solução para determinado problema, no entanto o trato deste desafio, em grande parte não se reflete nos currículos dos cursos de Computação. Neste sentido, o objetivo deste trabalho é desenvolver o mapeamento de ativos entre os curriculum da ACM/IEEE, da SBC e guia SWEBOK especificamente para área de conhecimento Software Design no curso de Ciência da Computação. Para tal, utilizou-se a metodologia de análise dos documentos de referência para desenvolvimento do mapeamento e o processo de revisão por pares objetivando a validação deste mapeamento. Como resultados, destacam-se a correlação entre os ativos da CC2020 e RF-CC-2017 na visão das competências e o mapeamento dos conteúdos entre os três documentos de referência relacionados ao Software Design .
Effectiveness of presentation, practice and production method on the development of speaking fluency

This study was carried out due to the importance that speaking fluency has in communication management. In Santa Marianita de Jesus High School, students from the seventh year have successfully developed language skills like listening, reading, and writing. However, throughout an observation, it was found out that learners struggled with speaking fluency. The necessity of this study laid on the fact that the development of speaking fluency is crucial for an effective communication. The lack of effective communication was noticed since pupils could not share their thoughts, ideas, and feeling using English as the mean of communication. The general objective of this study was to evaluate the effects of presentation, practice, and production method in the development of speaking fluency among students. This study was carried out through a mixed approach, descriptive, exploratory methodology, and quasi-experimental design. The theoretical support was from books, papers, scientific magazines, and articles. To collect data, some instruments were used such as a pre-test, post-test, and an observation card to determine how effective PPP was to boost fluency during the intervention. Finally, results showed that it has statistically significant evidence at a=0.005 in speed, prosody, and coherence. This indicates that the PPP method contributes to speaking fluency, especially in prosody. This method PPP that belongs to the communicative approach allowed students to communicate in the target language effectively.
AI.R Taletorium: Artificial Intelligence 1001 Cyber Nights

AI.R Taletorium is an artificial intelligence-based collaborative learning environment based on Human-AI co-creation and social relationship development between users. AI.R Taletorium is designed to achieve a common creative experience between groups of users with different preferences, not necessarily at the same location. The system is built upon a character-centric interactive storytelling framework. AI follows users’ characteristics to transfer participants into the AI-generated story environment via avatars. Additionally, the multimodal interface helps users participate in the story creation and stimulate their perceptive and emotional engagement. In the 1001 Cyber Nights series of AI-created fairy tales, our focus is on the neural-network-based automated storytelling part of the AI.R Taletorium project. We are inspired by the 1001 Middle Eastern folk tales collection and Scheherazade, who fought for her life by telling stories for 1001 nights. We are using our AI.R Taletorium automated storytelling system to challenge AI creativity and imagination in creating fairy tales for children. As in the story of Scheherazade, we see this as a paradigm of AI’s creative effort toward its further emancipation.
EVALUATION OF SIMULTANEOUS IDENTITY, AGE AND GENDER RECOGNITION FOR CROWD FACE MONITORING

Nowadays, facial recognition combined with age estimation and gender prediction has been deeply involved with the factors associated with crowd monitoring. This is considered to be a major and complex job for humans. This paper proposes a unified facial recognition system based on already available deep learning and machine learning models (i.e., FaceNet, ResNet, Support Vector Machine, AgeNet and GenderNet) that automatically and simultaneously performs person identification, age estimation and gender prediction. Then the system is evaluated on a newly proposed multi-face, realistic and challenging test dataset. The current face recognition technology primarily focuses on static datasets of known identities and does not focus on novel identities. This approach is not suitable for continuous crowd monitoring. In our proposed system, whenever novel identities are found during inference, the system will save those novel identities with an appropriate label for each unique identity and the system will be updated periodically in order to correctly recognise those identities in the future inference iterations. However, extracting the facial features of the whole dataset whenever a new identity is detected is not an efficient solution. To address this issue, we propose an incremental feature extraction based training method which aims to reduce the computational load of feature extraction. When tested on the proposed test dataset, our proposed system correctly recognizes pre-trained identities, estimates age, and predicts gender with an average accuracy of 49%, 66.5% and 93.54% respectively. We conclude that the evaluated pre-trained models can be sensitive and not robust to uncontrolled environment (e.g., abrupt lighting conditions).
A Study on the Development of Anatomical Position Classification Model of Gastroscopy Data on Deep Learning

Gastric cancer is one of the main causes of cancer and death in Korea. Gastroscopy (EGD) is known as an effective gastric cancer screening technique. However, the quality of medical services is deteriorating as the doctor
DataHub and Apache Atlas: A Comparative Analysis of Data Catalog Tools

Big Data introduces a significant increase of complexity to projects, in which, the use of inadequate data will inevitably produce inadequate and incorrect analysis.Data Catalogs centralize the system's metadata into one place, providing a global view of the stored data, so it is essential to use appropriate data catalog tools.The choice of the tool that best suits the needs of the projects must be well-founded.This paper uses the OSSpal methodology, usually used for comparing open-source technologies, to do a comparative analysis of two tools: DataHub and Apache Atlas.
Blockchain based secure relay scheme for space-terrestrial integrated networks

The future 6G networks will integrates space and terrestrial networks to realize a fully connected world with extensive collaboration. However, how to build trust between multiple parties is a difficult problem for secure cooperation without a reliable third-party. Blockchain is a promising technology to solve this problem by converting the trust between multi-parties to the trust to the common shared data. Several works have proposed to apply the incentive mechanism in blockchain to encourage effective cooperation, but how to evaluate the cooperation performance and avoid breach of contract is not discussed. In this paper, a secure relay scheme is proposed based on the consortium blockchain system composed by different operators. In particular, smart contract checks the integrity of the message based on RSA accumulator, and executes transactions automatically when the message is delivered successfully. Detailed procedures are introduced for both uplink and downlink relay. Implementation based on Hyper-ledger Fabric proves the effectiveness of the proposed scheme and shows that the complexity of the scheme is low enough for practical deployment.
Certified

In the second of a new series on certification best practice, UL Solutions talks about the growing need for automated, digitalized compliance solutions in the field of wireless product testing.
Edge Computing Based Connected Autonomous Vehicles: A Discussion on Cyber-Attacks and Security Mechanisms

Edge Computing-based Connected Autonomous Vehicles (EC-CAVs) can fulfill the emerging demand for smart transportation on a global scale. Such innovations to transportation ecosystems can bring manyfold benefits from fully autonomous driving services to proactive vehicle monitoring and traffic management. However, given the complexity involved in the deployment of EC-CAVs, zero-tolerance safety, and security measures must be incorporated to avert vehicle immobilization, road accidents, disclosure of sensitive data, or any potential threats. In this article, we present a reference architecture of EC-CAVs to investigate existing and emerging cyber threats and thus, derive a common attack taxonomy for the EC-CAVs ecosystem based on our studies of academic literature and industry white papers. Subsequently, a discussion on security mechanisms is presented that can ensure safe and secure transportation of passengers from one destination to another using an EC-CAVs ecosystem.
Особливості орієнтацій у важких ситуаціях менеджерів туристичного бізнесу на різних етапах професіогенезу

The article presents the results of an empirical study of coping factors that reflect the content of types of orientations in difficult situations in tourism business managers at different stages of professional genesis. Based on the theoretical analysis of scientific sources, it is stated that the professional activity of personnel employed in the tourism industry is characterized by stress resulting from various problem situations. The scientific achievements of modern scientists on the problem of coping of stress by tourism managers are considered. It is noted that research on the coping behavior of tourism professionals intensified only during the COVID-19 pandemic, which caused a crisis in the tourism industry. The urgency of deploying research of coping strategies of managers in the psychology of tourism in a broader perspective is emphasized. The total sample consisted of 216 persons. The first group consisted of 144 fourth-year students majoring in Tourism. The second group included 72 specialists with experience in the field of tourism from 7 to 10 years. To solve the empirical problems, the questionnaire “Types of orientations in difficult situations” by K. Bytjuc’ka and O. Kornjejev was used to diagnose coping factors that outline the orientation of the research efforts to approach the problem situation or avoid difficult circumstances. Student’s t-test for independent samples was used for mathematical and statistical data processing. Significantly higher indicators for students are set on the scales «Striving for difficulties», «Obstacle orientation», «Escape», «Inaction» and «Insouciance». These data reflect a contradictory combination of orientations on rapprochement with the problem situation and its avoidance. The identified features of the types of orientations in difficult situations in students - future managers of the tourism business determine the likelihood of difficulties in forming their professional competence and ability to perform professional tasks. Specialists with professional experience demonstrate significantly higher performance on the scales «Thoroughness», «Threat alert» and «Opportunity orientation». The obtained empirical results prove the expediency of improving the psychological training of tourism professionals and emphasize the relevance of creating a program of psychological support and its implementation in the system of professional education of tourism professionals
[Multi-tissue segmentation model of whole slide image of pancreatic cancer based on multi task and attention mechanism].

Accurate segmentation of whole slide images is of great significance for the diagnosis of pancreatic cancer. However, developing an automatic model is challenging due to the complex content, limited samples, and high sample heterogeneity of pathological images. This paper presented a multi-tissue segmentation model for whole slide images of pancreatic cancer. We introduced an attention mechanism in building blocks, and designed a multi-task learning framework as well as proper auxiliary tasks to enhance model performance. The model was trained and tested with the pancreatic cancer pathological image dataset from Shanghai Changhai Hospital. And the data of TCGA, as an external independent validation cohort, was used for external validation. The F1 scores of the model exceeded 0.97 and 0.92 in the internal dataset and external dataset, respectively. Moreover, the generalization performance was also better than the baseline method significantly. These results demonstrate that the proposed model can accurately segment eight kinds of tissue regions in whole slide images of pancreatic cancer, which can provide reliable basis for clinical diagnosis.在全切片中分割不同组织对胰腺癌的诊疗十分重要，但目前面临内容复杂、样本偏少、样本异质性高等挑战。本文研究了胰腺癌病理切片八种类别的组织分割，通过引入注意力机制并设计分层共享的多任务结构，利用相关辅助任务显著提升模型性能。本文模型在上海长海医院的数据集上进行训练与测试，并在TCGA公开数据集上进行外部验证，在内部测试集上F1分数均高于0.97，在外部验证集上F1分数均高于0.92，且泛化性能显著优于基线方法。实验表明，本文模型可准确分割胰腺癌全切片图像中的不同组织，为临床诊断提供可靠依据。.
ngan Motivasi Belajar dengan Hasil Belajar Siswa pada Pembelajaran Tematik di Kelas IV Sekolah Dasar

The research aim to know there is or no correlation motivation in learning with student learning outcomes in thematic learning of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman. This type of research is quantitative research with correlation research methods. The amount of sample is 26 students, four grade of primary school 16 Enam Lingkung. The result of the research there is positive correlation an significant students motivation in learning with student learning outcomes in thematic learning of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman. This was proven from rhitung = 0.533 &gt; rtabel = 0.404, and significance value 0.000 &lt; 0.005. which means that Ha is accepted and Ho is rejected , so the hypothesis says "there is a correlation in learning motivation with student learning outcomes in thematic learning in of four grade of primary school on cluster two in subdistrict Enam Lingkung regency Padang Pariaman" accepted.
Pengaruh Model Flipped Classroom dan Motivasi Belajar terhadap Keterampilan Menulis Proposal Kegiatan Siswa Kelas XI

This study aimed to determine the effect of the flipped classroom model and learning motivation on the activity proposal writing skills of class XI high school students. The research was conducted at the UNP Laboratory Development High School with a total sample of 57 students, 27 students from the experimental class and 30 students from the control class. This type of research is quantitative research with experimental methods. The experimental design used is factorial design. The population of this study was class XI students at the UNP Laboratory Development High School who were enrolled in the 2022/2023 academic year. The research sample consisted of two classes: class XI IIS 3 and class XI IIS 4. Sampling was carried out using a purposive sample technique. The research instruments were performance tests and questionnaires. Based on research, the flipped classroom model has a significant effect on students' activity proposal writing skills, both for students who have high learning motivation and students who have low learning motivation. In addition, there is no influence between learning motivation and the flipped classroom model.
Form Scanner &amp; Decoder

In India, most of the people use a pen & paper for filling various application forms. Also, they are not comfortable with the English language. This project aims to automatically convert applications written in Hindi to English and therefore assists mainly the rural people who have the inhibition of first filling a form and that too in English. Technology may be all around us, but people are still congenial with the pen and paper. So, this project is based on the recognition of different handwritten characters written in Hindi language and converting them to English. It tries to develop a word recognition system to separate several Hindi words from handwritten forms using image segmentation techniques. Nowadays, all form reading processes are done digitally. This system will facilitate such processes in banking, agriculture, education, etc.