Reviewerly/exHarmony huggingface dataset:
PAN-DeSpeck: A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

SAR images commonly suffer from speckle noise, posing a significant challenge in their analysis and interpretation. Existing convolutional neural network (CNN) based despeckling methods have shown great performance in removing speckle noise. However, these CNN-based methods have a few limitations. They do not decouple complex background information in a multi-resolution manner. Moreover, they have deep network structures that may result in many parameters, limiting their applicability to mobile devices. Furthermore, extracting key speckle information in the presence of complex background is also a major problem with SAR. The proposed study addresses these limitations by introducing a lightweight pyramid and attention-based despeckling (PAN-Despeck) network. The primary objective is to enhance image quality and enable improved information interpretation, particularly on mobile devices and scenarios involving complex backgrounds. The PAN-Despeck network leverages domain-specific knowledge and integrates Gaussian Laplacian image pyramid decomposition for multi-resolution image analysis. By utilizing this approach, complex background information can be effectively decoupled, leading to enhanced despeckling performance. Furthermore, the attention mechanism selectively focuses on key speckle features and facilitates complex background removal. The network incorporates recursive and residual blocks to ensure computational efficiency and accelerate training speed, making it lightweight while maintaining high performance. Through comprehensive evaluations, it is demonstrated that PAN-Despeck outperforms existing image restoration methods. With an impressive average peak signal-to-noise ratio (PSNR) of 28.355114 and a remarkable structural similarity index (SSIM) of 0.905467, it demonstrates exceptional performance in effectively reducing speckle noise in SAR images. The source code for the PAN-DeSpeck network is available on .
Time Highlighted Multi-Interest Network for Sequential Recommendation

Sequential recommendation based on a multi-interest framework aims to analyze different aspects of interest based on historical interactions and generate predictions of a user’s potential interest in a list of items. Most existing methods only focus on what are the multiple interests behind interactions but neglect the evolution of user interests over time. To explore the impact of temporal dynamics on interest extraction, this paper explicitly models the timestamp with a multi-interest network and proposes a time-highlighted network to learn user preferences, which considers not only the interests at different moments but also the possible trends of interest over time. More specifically, the time intervals between historical interactions and prediction moments are first mapped to vectors. Meanwhile, a time-attentive aggregation layer is designed to capture the trends of items in the sequence over time, where the time intervals are seen as additional information to distinguish the importance of different neighbors. Then, the learned items’ transition trends are aggregated with the items themselves by a gated unit. Finally, a self-attention network is deployed to capture multiple interests with the obtained temporal information vectors. Extensive experiments are carried out based on three real-world datasets and the results convincingly establish the superiority of the proposed method over other state-of-the-art baselines in terms of model performance.
Topic-Aware Abstractive Summarization Based on Heterogeneous Graph Attention Networks for Chinese Complaint Reports

Automatic text summarization (ATS) plays a significant role in Natural Language Processing (NLP). Abstractive summarization produces summaries by identifying and compressing the most important information in a document. However, there are only relatively several comprehensively evaluated abstractive summarization models that work well for specific types of reports due to their unstructured and oral language text characteristics. In particular, Chinese complaint reports, generated by urban complainers and collected by government employees, describe existing resident problems in daily life. Meanwhile, the reflected problems are required to respond speedily. Therefore, automatic summarization tasks for these reports have been developed. However, similar to traditional summarization models, the generated summaries still exist problems of informativeness and conciseness. To address these issues and generate suitably informative and less redundant summaries, a topic-based abstractive summarization method is proposed to obtain global and local features. Additionally, a heterogeneous graph of the original document is constructed using word-level and topic-level features. Experiments and analyses on public review datasets (Yelp and Amazon) and our constructed dataset (Chinese complaint reports) show that the proposed framework effectively improves the performance of the abstractive summarization model for Chinese complaint reports.
A Data Consistency Insurance Method for Smart Contract

As one of the major threats to the current DeFi (Decentralized Finance) ecosystem, reentrant attack induces data inconsistency of the victim smart contract, enabling attackers to steal on-chain assets from DeFi projects, which could terribly do harm to the confidence of the blockchain investors. However, protecting DeFi projects from the reentrant attack is very difficult, since generating a call loop within the highly automatic DeFi ecosystem could be very practicable. Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing, and no method could promise the non-existent of reentrant vulnerabilities. In this paper, we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract, so that we can prevent the attackers from abusing the inconsistent smart contract state. Compared to the existing resolutions of front-running, code audit, and modifier, our method guarantees protection results with better flexibility. And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan. The results prove that our method could efficiently prevent the reentrant attack with less running cost.
Text Extraction with Optimal Bi-LSTM

Text extraction from images using the traditional techniques of image collecting, and pattern recognition using machine learning consume time due to the amount of extracted features from the images. Deep Neural Networks introduce effective solutions to extract text features from images using a few techniques and the ability to train large datasets of images with significant results. This study proposes using Dual Maxpooling and concatenating convolution Neural Networks (CNN) layers with the activation functions Relu and the Optimized Leaky Relu (OLRelu). The proposed method works by dividing the word image into slices that contain characters. Then pass them to deep learning layers to extract feature maps and reform the predicted words. Bidirectional Short Memory (BiLSTM) layers extract more compelling features and link the time sequence from forward and backward directions during the training phase. The Connectionist Temporal Classification (CTC) function calcifies the training and validation loss rates. In addition to decoding the extracted feature to reform characters again and linking them according to their time sequence. The proposed model performance is evaluated using training and validation loss errors on the Mjsynth and Integrated Argument Mining Tasks (IAM) datasets. The result of IAM was 2.09% for the average loss errors with the proposed dual Maxpooling and OLRelu. In the Mjsynth dataset, the best validation loss rate shrunk to 2.2% by applying concatenating CNN layers, and Relu.
Designing Learning for Transfer of Learning: Focusing on the IB MYP

The goal of education can be said to be the cultivation of ‘competence’. This is because ‘competence’, the ability to solve problems by transferring the results of learning, is required to dynamically cope with the uncertain and variable future society. Setting the goal of education as the development of competence reflects the shift in perception that education should be able to contribute to the sustainable development of mankind in the future society. Cultivation of competence begins with transferring the results of learning to real life. Curriculum around the world places learning for transfer in the direction of instruction and assessment. Among them, the IB MYP provides an empirical learning framework to transfer learning to life. This learning framework includes learning contents such as knowledge, skills, valuesㆍattitudes, the context in which learning should be transferred, and a circular teachingㆍlearning model for developing competencies. The 2022 revised Korean national curriculum also aims to transfer learning and develop competency, the learning framework of the IB MYP can provide an example of developing a learning model for the settlement of the 2022 revised curriculum. In this paper, I draw implications for the settlement of the 2022 revised curriculum by examining the learning design process for transferring learning using the IB MYP framework.
A Study of Overseas Chinese-English Content Synchronization and Cooperative Teaching Mode: A Case Study of the Chinese Course in Banki Donat Primary School, Pécs, Hungary

This study examined how the Chinese-English content synchronization and cooperative teaching mode was implemented. It came to the conclusion that this teaching mode was significant for Chinese teachers, the Hungarian assistant teacher, and the growth of Chinese language courses, but there were some problems as well. And this study analyzed these problems and proposed improvement measures for these problems from three perspectives: the Chinese and foreign teachers, the school and the Confucius Institute. In order to promote the improvement and development of the Chinese-English content synchronization and cooperative teaching mode, we hope to provide some effective assistance to Chinese teachers who will participate in this cooperative teaching mode in the future. At the same time, we would also like to make some suggestions to promote this cooperative teaching mode to the win-win direction, in order to promote the local Chinese teaching in Hungary.
Electronic evidence in the practice of the determination of the norms to explore the wechat records as an example

Nowadays, with the popularity of weibo, relying on the app to form a variety of records, gradually by the parties as proof of the facts of a case submitted to the court as evidence, the formation of the "weibo evidence" more and more appear in all kinds of civil and commercial cases, similar to the internet electronic evidence has also become the main form of electronic evidence. Before the legal status of electronic data was recognized, WeChat records had the ability to prove the facts of the case, but because of the lack of corresponding legislative provisions and supporting mechanisms, it has been excluded. Therefore, this paper from the background of the times, analyze the current legislative status of microsoft record evidence and practical application of the status quo, identify the microsoft record evidence and electronic evidence of the similarities and differences, microsoft record evidence as electronic evidence of the necessity of the analysis, and finally on the application of the microsoft record evidence of the difficult problem, to put forward the author's personal thinking and feelings.
A Study on the Application of Artificial Intelligence in Supply Chain :A Machine Approach

Purpose The study aims to identify trends, assess research status by country and SCOR standard processes, and provide machine learning-based classification methods in the research area.Methods Qualitative analysis is conducted on a total 493 literature data. And nine machine learning models to classify the SCM process are performedResults Artificial intelligence in Supply Chain research has been consistent since 1998, with a noteworthy concentration from 2017 to 2023. High-performing models (XGBoost, LightGBM, CatBoost) achieve F1 values exceeding 70% and AUC values over 80%, effectively classifying literature data into SCOR's 6 processes.Conclusion In Supply Chain research, focus is on 'Enable' for decision support and 'Plan' for predictive optimization,. This addresses global AI-driven efficiency demands for strengthening domestic supply chains. Korea's 1% contribution requires policy-driven activation. Employing ML-based classification enhances future analysis, allowing ongoing research and easy referencing for national and corporate endeavors.
Grammatical Intricacy in Product Descriptions and Advertisement Videos: Lesson from IKEA

This study analyzed grammatical intricacy (GI) found in written and spoken texts represented by 20 product descriptions and 20 advertisement videos of IKEA. The data were collected purposively from IKEA’s official website and YouTube Channel. The objectives of this study were to investigate the complexity of IKEA product descriptions and advertisement videos using GI and to identify which text has a higher average GI score. This study applied a descriptive qualitative method and formula proposed by Eggins to calculate the complexity of the texts. The analysis process included identifying the clauses and sentences based on Hogue &amp; Oshima’s theories, counting the number of clauses and sentences, and calculating the GI score. The results showed that (1) product descriptions and advertisement videos composed by IKEA possessed a low level of complexity as the average GI score of both texts is below 2.00. (2) Advertisement videos reach a higher score (1.74) compared to product descriptions (1.57); however, the difference is not significant. The results of this study may contribute to two important implications, both theoretically and practically. Theoretically, the results enrich the knowledge on grammatical intricacy. Practically, this study provides an insight for marketing practitioners to compose marketing discourse with strong messages to lure customers’ attention.
Peningkatan Literasi Keuangan dan Kepedulian Ekonomi Anak berbasis Pretend Play bagi Orang Tua

Purpose: The level of financial literacy of the Indonesian people is still relatively low, making it necessary for citizens to have an increase in financial literacy. This is especially so for children, because this consumptive behavior is starting to be imitated by children along with the increasing number of advertisements on TV and social media. This community service activity (PKM) aims to provide financial literacy assistance to young children by using the pretend play method which is very appropriate for the stages of early childhood development in order to increase the habit of saving money Methodology: This activity was carried out using mentoring and socialization methods as well as a grand launching of books and financial literacy media Result: The event ran smoothly and was full of appreciation from the participants who attended. The context of play makes children happy in learning activities which will have an impact on increasing children's interest in learning. So, with an increase in children's interest in learning, it is hoped that the child's initiative will emerge in carrying out activities related to what is being studied. Limitations: Teach children to love saving Contribution: Parents are able to understand how important financial literacy is for early childhood and know the pretend play learning method in teaching financial literacy to children. In addition, this assistance can increase efforts to like to save in early childhood
Security from Physical Assumptions

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.
Quantum Money

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.
Distributing Keys

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.
From Imperfect Information to (Near) Perfect Security

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.
Background Material

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.
Fault-tolerant Cloud Workflow Scheduling with Uncertain Task Execution Time

Resource performance fluctuation and resource failure become two main factors that affect task execution in cloud systems, especially for deadline-constrained workflow instances with precedence relationships among tasks. Lots of cloud workflow scheduling algorithms have been designed for fault tolerance or performance fluctuation separately while less work consider these two issues simultaneously. In this paper, an algorithm named FCWSU is proposed to fault-tolerant scheduling workflows with uncertain task execution time caused by resource performance fluctuation in clouds. A novel workflow scheduling architecture is designed in FCWSU to mitigate the delay propagation caused by either performance fluctuation or failure of VMs. A PB (Primary-Backup) model based scheduling algorithm is proposed for cloud resource failure tolerance. Experiment results show that FCWSU can provide better scheduling strategy for deadline-constrained workflows than corresponding competitors.
Quantum Tools and a First Protocol

This book offers an accessible and engaging introduction to quantum cryptography, assuming no prior knowledge in quantum computing. Essential background theory and mathematical techniques are introduced and applied in the analysis and design of quantum cryptographic protocols. The title explores several important applications such as quantum key distribution, quantum money, and delegated quantum computation, while also serving as a self-contained introduction to the field of quantum computing. With frequent illustrations and simple examples relevant to quantum cryptography, this title focuses on building intuition and challenges readers to understand the basis of cryptographic security. Frequent worked examples and mid-chapter exercises allow readers to extend their understanding, and in-text quizzes, end-of-chapter homework problems, and recommended further reading reinforce and broaden understanding. Online resources available to instructors include interactive computational problems in Julia, videos, lecture slides, and a fully worked solutions manual.