Reviewerly/exHarmony huggingface dataset:
Natural Scene Text Detection Algorithm Based on Improved DBNet

There are many problems in text detection, such as large scale differences of high-resolution image features and poor multi-scale feature fusion, we propose an improved algorithm based on dbnet. On the basis of the feature fusion module, we add a atrous Convolution network with kernel-shared pooling to increase the receptive field, so that higher-level semantic information can be obtained in the feature fusion network, and through the shared kernel, the number of model parameters can be reduced, the computational cost can be reduced, and the detection accuracy can be improved. At the same time, we add the attention mechanism into the residual network to suppress the complex background noise and promote the information interaction between channels. In the loss function, we use dice loss partially to solve the imbalance of positive and negative sample data. Our experimental evaluation is on ICDAR2013 and ICDAR2015 datasets. The experimental results show that the algorithm has a certain improvement in accuracy and F value.
WB-GWS: An IoT-Oriented Lightweight Gateway System Based on White-Box Cryptography

The Internet of Things (IoTs) has been widely applied for convenient data gathering. Therefore, the security and privacy issues related to IoT applications attract more and more attentions. Secure data transmission plays pivotal role of the security of IoT applications. However, there are still many IoT devices do not support cryptographic functions due to their constrained resources. Moreover, cryptographic key storage also becomes a practical security context problem in resource-constrained devices. In this paper, an IoT-oriented lightweight gateway system, which is named WB-GWS, is proposed by using white-box cryptography. WB-GWS is designed for the secure data transmission in typical IoT applications, and reduces the risk of key leakage in the white-box security context. The performance of WB-GWS is analyzed amongst different platforms. The experiment results support that WB-GWS can meet the security requirements of IoT applications with low-rate data transmission.
Research on contract review and management methods based on artificial intelligence

In recent years, with the continuous enhancement of contract management to enterprise, the improvement of business integration management level, as well as the rapid development of information technology and the Centralized planning of informatization construction of the group of companies, the current contract management system can no longer fully fulfill the requirements of the business from contract management. In order to enhance the intelligence ability of contract audit and management, the research of contract audit and management methods based on artificial intelligence have been proposed. In the aspect of contract audit based on artificial intelligence, the paper proposes to construct the business architecture to contract audit, clarify the contract audit business processing process, and provide the function of auxiliary audit. The process of contract management based on artificial intelligence takes risk early warning as the core index for management, designs an intelligent question and answer system based on artificial intelligence, and finally realizes the contract management based on artificial intelligence.
A dialogue replacement data augmentation method based on comparing belief state and dialogue acts

Training a dialogue generation model requires large-scale, high-quality dialogue data. Data augmentation is a common method to expand a dataset. Some common data augmentation methods such as back-translation and synonym replacement are used to augment dialogue datasets, but these methods are only aimed at word or sentence level changes and do not consider the relationship between dialogues to generate new dialogue data and the meaning of the generated sentences may conflict with the context of the dialogue. To solve this problem, a new data augmentation method is proposed for expanding the task-oriented dialogues. Solve the problem of insufficient training data by looking for a dialogue in the original dataset, then replacing the dialogue after comparing the belief state and dialogue acts. Experimental results on MultiWOZ dataset show that this method can improve the Combined Score by 0.99, 0.24 and 1.5 respectively compared with the data augmentation method at the character-level, word-level and the sentence-level.
Political Internet discourse as a subject of linguistic research: definition and characteristics

The article is devoted to the study of political discourse within the virtual space – an "artificial" world created in recent decades with the help of information technologies, where individuals are able to communicate with each other over vast distances, modeling their own personality at will. The research, in particular, is aimed at studyinh how political communication changes in the virtual reality, what linguistic and extralinguistic means are used by political actors when communicating with their electorate and between each other. Using the categories proposed by T. van Dijk, the article proposes the use of new characteristic features for Internet discourse, such as speaker's anonymity, semi-formal tone of communication, more open and competitive expression of opinions, emotionality, etc. for the analysis of communication within the virtual space. The article proposes a clarification of the definition of political discourse, highlights its most important features, defines differences in communicative strategies depending on the gender of the speaker or political actor. With the help of the proposed categories and based on the works of such prominent scholars as R. Wodak, L. de Saussure and T. van Dijk, the article provides a new definition of the concept of political Internet discourse, which is aimed at a more complete consideration of the interaction between individuals within the virtual space. It is suggested to use the categories proposed by T. van Dijk for the analysis of communication within the virtual space, which will allow to single out communicative situations that are directly related to the political sphere. By comparing communicative situations in the "artificial" world with the physical one, it is argued that a characteristic feature of political Internet discourse is the transfer of extralinguistic components through textual communication. It is clarified that in many communicativesituations between political actors and other users, the latter act as the information recipients, limited only to the ability to interact with other recipients. In conclusion, it is suggested to understand political Internet discourse as actions of a linguistic and extralinguistic nature, related to the political sphere and implemented in the virtual space by political actors and ordinary users; actions, which are characterized by the possibility of anonymous subjectivity, semi-formality, a more open and competitive nature of expressing opinions, etc., and in which the transfer of extralinguistic components is achieved mainly through text communication. Based on the categorical clarifications made in the article, strategies for further Internet discourse analysis are developed.
PENINGKATAN BUDAYA LITERASI DENGAN PELATIHAN MENULIS PUISI DI SMA MUHAMMADIYAH 3 KOTA TANGERANG

Writing quality poetry requires good ideas and imagination, this can be obtained by getting used to it through literacy culture. There are still many students who are not familiar with literacy, this is because they are used to knowing something, it is enough to just look at the applications on the device without reading with understanding, so the results obtained are not optimal. Based on this, the Community Service lecturer team followed up on problems in the field. One of the efforts made to improve literacy culture is by holding poetry writing training at SMA Muhammadiyah 3 Tangerang City. The method used in implementing this community service is the productive method. The productive method used is by producing literary works in the form of poetry with a literacy culture. This service activity is divided into three stages, namely the preparation, implementation, and evaluation stages. Students are very enthusiastic about participating in online poetry writing training. This is evidenced by several questions posed to the informants. Students who were previously unfamiliar with a variety of poetry became more aware of the genre of poetry so that they could understand which type of poetry was made.
EXPERIENCE OF CONDUCTING LABORATORY CLASSES IN THE DISCIPLINE "METROLOGY, STANDARDIZATION, QUALITY SYSTEMS" IN THE CONDITIONS OF MILITARY STATUS AND THE COVID-19 PANDEMIC USING DISTANCE EDUCATION FORMS

The current conditions of the three-year Covid-19 pandemic and the martial law in Ukraine have significantly affected the process of studying at Ukrainian universities. First of all, it is necessary to achieve maximum activation and visualization of distance learning. This is facilitated by the use of various digital teaching aids to reduce the time required to present the necessary information and modern technologies in education that facilitate the presentation of material. The transition of the educational process to formats using distance learning has become a challenge for the entire higher education system. At the same time, technical disciplines are recognized as the most affected due to the focus on the development of practical skills and the weak coverage of the curriculum by available digital solutions. Based on personal experience, the authors agree with the views in the professional community on training in quarantine related to the COVID-19 pandemic and martial law, not as a remote but as an emergency remote, which requires the resumption of measures to compensate for the lost time in training, as well as solving technical and methodological problems. The article considers the main directions and the most relevant and promising, according to the authors, ways to use new information technologies in the educational process of students in laboratory classes in the discipline "Metrology, Standardization, Quality Systems" in martial law and pandemic COVID-19 using remote forms of education. The authors, based on personal experience, confirmed by an anonymous survey of a group of students, suggest combining the use of learning platforms such as Zoom and Moodle in laboratory classes. The article presents the results of an anonymous questionnaire, analyzed them. As an example, the method of conducting laboratory classes with a universal protractor UM and a smooth micrometer, using distance learning. The materials of the lesson include addresses of links to video lessons, individual tasks for preparation for the laboratory lesson, individual task for laboratory work in the form of tables.
Choice-Driven Contextual Reasoning for Commonsense Question Answering

The task of question answering is to find the most appropriate answer for an input question in natural language from a given custom knowledge base of information. While the performance of question answering systems has been significantly improved, they still struggle to answer questions that require commonsense reasoning. To capture common sense beyond associations, a challenging dataset CommonsenseQA for commonsense question answering is proposed. As a result, several models have been developed for tackling this challenge. But existing approaches are still limited in handling contextual representation and reasoning. In this paper, we propose a model for commonsense question answering by implementing a form of choice-driven contextual reasoning through novel encoding strategies and choice differentiation mechanisms. We have conducted experiments on major baselines for commonsense question answering and our experimental results show that the proposed model significantly outperforms strong baselines.
Computer Assisted Design of Intelligent E-Certificate System Based on Blockchain Technology

The university e-certificate system based on block chain as data storage platform is a key research topic.The data stored in the blockchain is immutable and strengthens the security of data.This paper proposes a block chain-based e-certificate management scheme for colleges and universities, realizing the sharing of e-certificates between students and third-party data users without infringing on students' privacy. In this paper, the system model of private chain and alliance chain construction scheme is used. The university server stores the ciphertext of students' e-certificate, the private chain stores the hash value and keyword index of the ciphertext of student's certificate, and the alliance chain stores the security index composed of keyword index. The security search of keywords in the alliance chain is realized, and the sharing of electronic certificate by third party data users is realized by proxy re-encryption algorithm.
Continuous variable quantum teleportation in a dissipative environment: Comparison of non-Gaussian operations before and after noisy channel

We explore the relative advantages in continuous-variable quantum teleportation when non-Gaussian operations, namely, photon subtraction, addition, and catalysis, are performed before and after interaction with a noisy channel. We generate the resource state for teleporting unknown coherent and squeezed vacuum states using two distinct strategies: (i) Implementation of non-Gaussian operations on TMSV state before interaction with a noisy channel, (ii) Implementation of non-Gaussian operations after interaction of TMSV state with a noisy channel. The results show that either of the two strategies could be more beneficial than the other depending on the type of the non-Gaussian operation, the initial squeezing of the TMSV state, and the parameters characterizing the noisy channel. This strategy can be utilized to effectively improve the efficiency of various non-Gaussian continuous variable quantum information processing tasks in a dissipative environment.
The relationship between job satisfaction and intention to quit a job: mediating factor job burnout

The study explores the aspects of job satisfaction related to the employee's intention to quit the job in the presence of job fatigue and can help decision-makers and administrators in the Jordanian private banking sector retain highly qualified employees. The current research attempted to investigate the relationship between job satisfaction through its dimensions (satisfaction with pay, satisfaction with promotion, satisfaction with co-workers, satisfaction with emergency bonuses, satisfaction with the nature of the work, satisfaction with communication with the organization), and the intention to quit a job through its dimensions (remuneration, nature of work? Health problems and ineffective driving). The study was conducted on Jordanian commercial banks. The descriptive analytical method was used through a sample selected from the study community represented by (Alhli-Bank, Arab Bank, and Arab Islamic Bank). After conducting the tests, the study concluded that there is a significant correlation between job satisfaction in its dimensions and the intention to quit smoking. The study recommends motivating employees by reviewing wages, promotions, and emergency bonus policies in light of the results.
Epidemiological and quality of life analysis of patients with ANOCA

Introduction: A portion of patients affected by angina has ANOCA (angina with non-obstructive coronary arteries). Objectives: To determine the epidemiological and quality of life aspects of individuals with angina without coronary obstruction. Material and methods: This is an observational cross-sectional study, conducted by applying questionnaires (SAQ-7 and SF-36) in patients undergoing catheterization in a single hospital from September 2021 to June 2022, and who did not have significant coronary artery obstructions (≥50%). Results: Patients had a mean age of 59.2 years and 60.47% of the sample was female. The main comorbidities found were dyslipidemia (81.4%); hypertension (81.4%); and anxiety (55.81%). Regarding lifestyle habits, 67.44% of patients were sedentary and 34.88% were smokers. According to SAQ-7, for physical limitation, 34.88% patients were in the poor to fair grade. The quality of life had the worst results, with 86.05% of the sample presenting poor to fair. For SF-36, limitations for physical and emotional aspects had median of zero and functional capacity of 25. Discussion: ANOCA patients presented impacts mainly on quality of life, functional capacity, physical limitations, and limitations due to emotional problems, which is in agreement with literature data. Conclusion: Despite de absence of obstructive coronary lesions, patients with ANOCA have significant comorbidities and quality of life impairment, requiring atention from their physicians.
Investigation on the Education Status of Chinese Excellent Traditional Culture in College Students

With the continuous development of China, China's excellent traditional culture has been more and more people pay attention to, many traditional culture industries develop rapidly, but in the university campus, Chinese excellent traditional culture education still has many problems. This paper mainly adopts the way of questionnaire, through the classification, merger, analysis and summary of the questionnaire, forming a clear understanding of the current situation of college students' excellent traditional culture and education of college students, on this basis of in-depth research and put forward relevant measures.
Correlations and energy in mediated dynamics

Abstract The minimum time required for a quantum system to evolve to a distinguishable state is set by the quantum speed limit, and consequently influences the change of quantum correlations and other physical properties. Here we study the time required to maximally entangle two principal systems interacting either directly or via a mediating ancillary system, under the same energy constraints. The direct interactions are proved to provide the fastest way to entangle the principal systems, but it turns out that there exist mediated dynamics that are just as fast. We show that this can only happen if the mediator is initially correlated with the principal systems. These correlations can be fully classical and can remain classical during the entangling process. The final message is that correlations save energy: one has to supply extra energy if maximal entanglement across the principal systems is to be obtained as fast as with an initially correlated mediator.
Alleviating shortcut learning behavior of VQA model with context augmentation and adaptive loss adjustment

Despite the impressive improvements of Visual Question Answer (VQA), it still remains a challenge of how to avoid the suffering of spurious correlations from textual content to answer. Previous researches have shown that due to the existence of language bias in the VQA dataset, VQA models may tend to capture superficial statistical correlation and suffer from the poor generalization capability in the out-of-distribution data. To alleviate the biases caused by language modality, we propose a method of context augmentation and adaptive loss adjustment, which can alleviate shortcut learning behavior of VQA models. Specifically, the existence of language bias is due to the high co-occurrence frequency of categories and the words in “Question”, therefore, we propose to use “Paraphrase Generation” to produce paraphrases with diverse contexts, so as to mitigate such correlation. Secondly, we use adaptive loss adjustment to adjust the importance of samples, that is, reduce the importance of bias-aligned samples and improve the importance of bias-conflicting samples, so as to guide the model to capture the intrinsic attributes that are beneficial to generalization. The experiments have demonstrated the feasibility and validity of our method on a variety of VQA models.
Interpolation-aware models for train-test consistency in mixup

Mixup is a learning principle that trains a neural network on convex combinations of pairs of examples and their labels. Despite of its good performance, there is an inherent inconsistency between training and testing in mixup, which makes theoretical understanding difficult and hurts the performance in some cases. In this work, we propose λ-mixup to alleviate this inconsistency. Specifically, λ-mixup reformulates the model to take the interpolation coefficient (𝜆) as input as well, so that a class of models indexed by 𝜆 is learned and we can select one specific coefficient or multiple coefficients for ensembles depending on the testing distribution. We theoretically demonstrate that, with enough data and model capacity, λ-mixup can recover the original conditional distribution. Moreover, we conduct image classification tasks on multiple datasets, including CIFAR-10, CIFAR-100 and Tiny-Imagenet, showing that comparing with mixup, λ-mixup exhibits better generalization, calibration and robustness to adversarial attacks and out-of-distribution transformations.
Multi-kernel non-local neural network for semantic segmentation

As a milestone in semantic segmentation, Non-Local Block (NLB) efficiently enhances the ability of regular convolutional neural networks in capturing long-range dependencies. From the view of mathematical modeling, NLB is based on a single Gaussian kernel. Existing works suggest that multi-kernel methods generally get more powerful performance in edge detection, which is crucial to image segmentation. Motivated by this consideration, we design a Multi-Kernel Non-local Block (MKNLB). As expected, the proposed MKNLB exhibits excellent behaviors when being used in semantic segmentation. Additionally, with the distributive law of matrix multiplication, the complexity of its implementation is comparable to that of the standard NLB. Theoretical analyses and preliminary experiments on benchmark datasets both support the same conclusions.
Process modeling of area air defense and anti-missile based on OODA-BPMN

Aiming at the problems of low control accuracy and low execution efficiency of air defense anti-missile concentrated fire shooting strategy, this paper studies the process mapping and execution method of air defense anti-missile concentrated fire based on the combination of OODA loop and BPMN. Firstly, the concentrated fire shooting model is established, and BPMN model of concentrated fire shooting process is built according to OODA loop Theory, then the process model is executed by Cloud Native Command and Control platform, and the execution efficiency and control precision of the model are analyzed. Compared with the traditional concentrated fire shooting scheme, the concentrated fire shooting process modeling with OODA-BPMN and Cloud Native theory has the characteristics of module replaceable, high control precision, fast response and multi-instance parallel execution.