Reviewerly/exHarmony huggingface dataset:
Improving Power System Information Security: Analysis of the Saturnin Cipher Algorithm

New power systems require efficient and secure communication technologies to facilitate information exchange between various devices and systems. Among these, encryption technology is key to ensuring communication security. The lightweight block cipher algorithm, Saturnin, is similar to the AES algorithm and maintains good security even in resource-limited environments. Therefore, it can be applied to various devices in the power system, such as smart meters, sensors, controllers, etc. An impossible differential analysis was conducted on the Saturnin algorithm to identify potential security vulnerabilities, thereby enhancing the security of the power system. Firstly, based on the structural characteristics of the Saturnin algorithm, sufficient conditions for the 3.5-round impossible differential distinguisher of the Saturnin algorithm were proposed and proven. Using these sufficient conditions, 64 distinguishers can be quickly constructed and divided into four categories. Secondly, these four categories of distinguishers can be extended forward by two rounds to obtain four attack paths. These four attack paths not only have the same plaintext structure but also have a large number of common key bits. By utilizing these two characteristics, the complexity of the attack scheme can be improved. Combining early plaintext death analysis techniques, a 5.5-round impossible differential attack scheme for the Saturnin algorithm was proposed. The data, storage, and time complexity are 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">176.88</sup> chosen plaintexts, 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">143.88</sup> algorithm scale, and 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">176.91</sup> times 5.5-round encryption respectively. This is currently a visible impossible differential attack scheme against the Saturnin algorithm.
Learning Heterogeneous Relation Graph and Value Regularization Policy for Visual Navigation

The goal of visual navigation is steering an agent to find a given target object with current observation. It is crucial to learn an informative visual representation and robust navigation policy in this task. Aiming to promote these two parts, we propose three complementary techniques, heterogeneous relation graph (HRG), a value regularized navigation policy (VRP), and gradient-based meta learning (ML). HRG integrates object relationships, including object semantic closeness and spatial directions, e.g., a knife is usually co-occurrence with bowl semantically or located at the left of the fork spatially. It improves visual representation learning. Both VRP and gradient-based ML improve robust navigation policy, regulating this process of the agent to escape from the deadlock states such as being stuck or looping. Specifically, gradient-based ML is a type of supervision method used in policy network training, which eliminates the gap between the seen and unseen environment distributions. In this process, VRP maximizes the transformation of the mutual information between visual observation and navigation policy, thus improving more informed navigation decisions. Our framework shows superior performance over the current state-of-the-art (SOTA) in terms of success rate and success weighted by length (SPL). Our HRG outperforms the Visual Genome knowledge graph on cross-scene generalization with ≈ 56% and ≈ 39% improvement on Hits@ 5* (proportion of correct entities ranked in top 5) and MRR * (mean reciprocal rank), respectively. Our code and HRG datasets will be made publicly available in the scientific community.
GMTI and GMTIm via Fractional Fourier Transform and GLRT in SAR

In synthetic aperture radar (SAR) signal processing, the images of the moving targets are displaced and unfocused due to their unknown motion parameters. Therefore, different methods have been suggested for ground moving target indication and ground moving target imaging to detect the moving targets and estimate their motion parameters. In this paper, noting the linear frequency modulation of the SAR transmitted signal, we propose a method that employs the fractional Fourier transform (FrFT) as a tool for signal detection, and signal parameter estimation. Specifically, for the detection of the SAR echo signal, the generalized likelihood ratio test (GLRT) is derived by means of the FrFT. The proposed detector is further modified to possess the constant false alarm rate property. The performance of the proposed method and its effectiveness in SAR imaging for moving targets are evaluated through simulations and examples.
Research on the Comprehensive Reform and Innovative Development of Postgraduate Education in Colleges and Universities Under the Background of Big Data

Emphasizing the development and application of big educational data technology in the field of postgraduate education and teaching is an effective way to achieve the goal of modernization of postgraduate education in my country.This paper aims at the reform of graduate course education and teaching, from the aspects of teaching concepts, teaching organization and guidance, teaching methods, teaching management and evaluation, etc., focusing on promoting the reform of postgraduate training mechanism, innovation of training mode, and construction of quality assurance system is the key to comprehensively deepening reform, emphasizing coordination and overall advancement are important considerations for comprehensively deepening reforms, and improving the construction of institutional systems is the fundamental guarantee for comprehensively deepening reforms.
Penerapan Algoritma Finite State Machine Pada Game “Knight And King” Dengan Metode Game Development Life Cycle

&lt;p&gt;Salah satu jenis permainan yang digemari yaitu &lt;em&gt;platformer 2D&lt;/em&gt;. Jenis permainan ini semakin popular saat ini, karena kepopuleran permainan &lt;em&gt;mobile&lt;/em&gt; dan &lt;em&gt;platformer&lt;/em&gt; yang muncul di &lt;em&gt;mobile&lt;/em&gt;. Penelitian ini berupa perancangan permainan &lt;em&gt;mobile platformer 2D&lt;/em&gt; dengan menerapkan algoritma &lt;em&gt;finite State machine&lt;/em&gt; untuk memberi kepintaran terhadap musuh, dan metode &lt;em&gt;gamedevelopment life cycle&lt;/em&gt; sebagai metode perancangan permainan agar &lt;em&gt;game&lt;/em&gt; menjadi lebih menarik dan interaktif. Penelitian ini dilakukan dengan kuesioner dan pengembangan &lt;em&gt;prototype&lt;/em&gt;. Hasil penelitian ini adalah dapat membuat permainan &lt;em&gt;mobile&lt;/em&gt; dengan algoritma finite &lt;em&gt;Statemachine&lt;/em&gt; dan metode &lt;em&gt;game development life cycle.&lt;/em&gt;&lt;strong&gt;&lt;/strong&gt;&lt;/p&gt;
RESEARCH ON THE MOTIVATION FOR CHOOSING THE TEACHING PROFESSION AND REASONS FOR LEAVING AMONG YOUNG TEACHERS

This article examines the interrelationship between satisfaction with the choice of the teaching profession and the reasons for leaving the education system. The main reasons for leaving teachers (working conditions, organizational climate, administrative burden, etc.) are also examined. The research finds that people , who are satisfied with their choice of teaching profession, are less likely to leave school because of the workload, routine of the profession, poor student behavior, salary or heavy administrative burden. Peer support is also important for young teachers. This support can create a positive and empathetic work environment that supports motivation and job satisfaction. This creates a school community where teachers feel supported and important. In addition, peer support can encourage young teachers to participate in training, workshops and professional development. This improves the quality of their teaching practice and makes them more effective and competent in the school.
FACILITATION IN EDUCATION

Today, it is generally accepted that pedagogical science is going through a transitional stage related to the renewal of both the content and the forms of the educational process. Education is one of the most important subsystems of the social sphere of the state, which provides the process of obtaining by a person systematized knowledge, skills and abilities in order to use them effectively in his professional activity. In the conditions of an information-saturated space and new educational technologies, a person-oriented learning paradigm, teachers are faced with a situation where the purpose of education is to facilitate change and teaching. Facilitation in learning is an issue that entered didactics for theoretical discussion in the 1990s. It means supporting, creating opportunities for the cooperation of learners in their efforts for effective learning, through it the facilitation, flexibility and accessibility of learning is achieved. The process of collecting information is simplified. A facilitative approach requires assisting students to collaborate and independently carry out activities with an expected synergistic effect. The teacher-facilitator is again a key player in learning, but not at the expense of student learning and responsibilities. He does not rule, but facilitates others to do this for themselves. The following qualities are necessary for the formation of the innovative culture of a teacher-facilitator: 1) attitude towards children as developing subjects; 2) culture of human interaction; 3) relation to oneself as a developing subject. Facilitation is believed to be more effective in group learning or in stimulating students’ creativity.
VARIABLE RELATIONS BETWEEN THINKING AND IMAGINATION IN SOLVING COGNITIVE TASKS IN 6-8-YEAR-OLD CHILDREN IN CONSTRUCTIVE-VISUAL ACTIVITIES

The investigated problem is considered in the context of adaptation to learning and can be represented in the dimensions of the complex construct „learning abilities“. Within this construct, the criteria „cognitive learning abilities“, „motivation“ and „psychomotor“ are defined, which cover the significant aspects of schooling.
PROJECT-BASED LEARNING FOR DEVELOPMENT OF CREATIVE THINKIG, KEY SKILLS AND COMPETENCIES IN PRESCHOOL AGE

Dynamic changes in all areas of modern life also change the ways in which we learn and educate. We are increasingly required to think entrepreneurially, to have the ability to make independent decisions, to adapt in unfamiliar situations. Education meets these requirements through the application of new methods and technologies aimed at forming lifelong learning attitudes, for the acquisition of key competences laid down in the European Reference Framework. This report pay attention to the possibilities of project-based learning to achieve a new type of pedagogical interaction, to form key competences and to develop the creativity and imagination in the children. We share the activities approved in our own pedagogical practice under the „Design Champions“ program of the „Red paper plane“ organization. The program provides an opportunity to develop the skills of the XXI century, which are divided into functional literacy, competencies, character qualities. Emphasis is placed on how the project-based learning method and the principle of „learning by doing“ can be applied. The additional methods and techniques used support the achievement of knowledge and skills laid down in state educational standard for preschool education, create various inter-subject connections and form key competences needed by modern children and young people. The proposed technology helps not only to achieve better educational results for children of preschool age, but also to a higher quality of acquired knowledge and practical skills.
ART PROJECTS IN PHYSICS AND ASTRONOMY EDUCATION IN 9TH AND 10TH CLASS

Modern trends for more and more visualization and interactivity, both in educational and scientific literature and resources, as well as in the educational process, lead to new ideas and approaches in education at different levels. This text presents an author’s approach for innovative practices in the teaching of physics and astronomy in the 9th and 10th grades, where the possibilities of visual arts and technologies are a means of fulfilling creative projects in the field of both sciences. These practices took place at the First English Language High School in Sofia. The report presents and analyses art projects made by 9th and 10th grade students which have been aimed at 5th to 7th grade students. This approach, on the one hand, provokes a greater interest in the subjects included in the compulsory curriculum of physics and astronomy, on the other hand, it develops creativity and opportunities for realising creative ideas and skills with the help of innovative technologies.
An Efficient Traffic Sign Classification and Recognition with Deep Convolutional Neural Networks

Driver safety assisted driving, and autonomous driving all depend on automated traffic sign recognition.The most popular deep learning method for recognizing traffic signs is convolutional neural networks.(CNNs).This paper presents a useful technique for automatically detecting images of traffic signs.When employing the two common traffic sign photo datasets GTSRB, our method makes use of our CNN model architecture and performs the best.It aids the driver in safely operating the motor vehicle.The amount of time and effort drivers spend manually evaluating and recognizing traffic signs is excessive.This work provides an autonomous traffic sign identification using a convolutional neural network.Our work here introduces a unique CNN architecture with an Adam optimizer and a batch size of 128 to improve the efficiency of traffic sign recognition.Results based on a complex network were more accurately produced by a convolutional neural network (CNN).With 99.81% precision and a minimum of losses, our system learns from the GTSRB dataset, which contains 43 traffic classes, to identify the correct class of an anonymous traffic sign.The results, however, are better than those of the prior research, which examined this approach's accuracy and efficiency in recognizing traffic signs despite poor weather and hazy image circumstances.
Processing of Reference Ambiguity and Long-Distance Anaphora

This chapter aims at solving the two residual problems — reference ambiguity and long-distance anaphora. Section 2 centers on an investigation into the tendencies in determining attachment sites when the context fails to provide necessary cues.
Multi-Grained Attention Network with Mutual Exclusion for Composed Query-Based Image Retrieval

The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Composed Query-Based Image Retrieval (CQBIR)</i> task aims to precisely obtain the preserved and modified parts, based on the multi-grained semantics learned from the composed query. Since the composed query includes a reference image and the modification text, not just a single modality, this task is more challenging than the general image retrieval tasks. Most previous methods attempt to learn preserved and modified parts via different attention modules and fuse them as a unified representation. However, these methods have two intrinsic drawbacks: 1) The different granular semantic information of the composed query is neglected, which results in the fact that learned preserved and modified parts are irrelevant to correct semantics. 2) The preserved and modified parts learned by previous methods have obvious overlaps, which may lead the model to obtain sub-optimal preserved and modified regions. To this end, we propose a novel method termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Multi-Grained Attention Network with Mutual Exclusion (MANME)</i> to address the above problems. Our MANME method mainly consists of two components: 1) A multi-grained semantic construction for obtaining various textual and visual semantic information. 2) An attention with mutual exclusion constraint for reducing the degree of overlap between preserved and modified parts. It adequately utilizes the various granular semantic information and effectively refines the learned preserved and modified parts. Extensive experiments and further analyses on three widely used CQBIR datasets demonstrate that our proposed MANME method achieves new state-of-the-art performance on the CQBIR task.
Cross-shaped Adversarial Patch Attack

Recent studies have shown that deep learning-based classifiers are vulnerable to malicious inputs, i.e., adversarial examples. A practical solution is to construct a perceptible but localized perturbation called patch, making the well-trained models misclassified. However, most existing patch-based adversarial attacks focus on designing patches with localized rectangles, squares, or grids, ignoring the effect of the non-local patch. In this paper, we propose a novel cross-shaped patch attack paradigm (CSPA), a simple yet efficient and effective adversarial attack in Black-box scenarios. Specifically, the cross-shaped patch consists of two line segments intersected and perpendicular to each other at the midpoint. These two line segments are designed to be sufficiently thin and long to reach the four corners of the input image nearly. Thus, the patch has a globalized perturbation capacity while preserving its continuousness. The content and location of cross-shaped patch are then iteratively optimized by a carefully contrived random search-based algorithm to maximize this global property. Comprehensive experiments are conducted on four benchmark datasets against various victim networks. The results show that the proposed CSPA outperforms the existing patch-based attacks regarding both attack success rate and query efficiency by a large margin. Specifically, compared with the baselines, CSPA increases the success rate by up to 20% on ImageNet and reaches 100% on the CIFAR-100 and CIFAR-10 datasets. Meanwhile, CSPA reduces the average number of queries by up to 7 times. Even for the white-box attack scenario, our designed cross-shaped patch can still be applicable, achieving state-of-the-art performance.
Dedication

Subject Astronomy and Astrophysics Mathematical and Statistical Physics Computational Physics Collection: Oxford Scholarship Online
Appendix: RSA encryption

Subject Astronomy and Astrophysics Mathematical and Statistical Physics Computational Physics Collection: Oxford Scholarship Online
A Study on the Processing Pattern of Adverbs of Degree in Machine Translation —Focusing on the translation from Japanese to Korean—

Aspects of the adverbs of degree in machine translation are divided into large and small degrees.BR Large-degree adverbs are represented by certain adverbs in correspondence with Korean. “あまり(amari),” which contains a number of negative evaluations was found to be “너무 (neomu)”, and “とても(totemo),” which has only limited usage of pure degree was found to be “매우(maeu)” and “아주(ajou).“ In addition, it can be seen that “かなり(kanari)”, “ けっこう(kekkou),” “ずいぶん(zuibun),” “だいぶ(daibu),” and “なかなか(nakanaka),” which are used in pure and quantitative degrees have neutral evaluations that are converted into “꽤(kkawe)” and “상당히(sangdanghi).”BR Word order variation in misuse and transformation appeared in “けっこう”, “ずいぶん,” “だいぶ”, “とても”, and adverbial omissions appeared in “ずいぶん”, “とても”, and “かなり.“ “ずいぶん” especially was one of the prominent adverbs in transformations in addition to word order variation and omission.BR “少し(sukoshi)” and “ちょっと(chotto),” which represent small degree adverbs, were largely found to be “조금(jogeum)” and “좀(jom)” in Korean correspondence. In addition, examples such as changing the positions of adverbs, omitting repeated adverbs, and transforming adverbs into natural contexts appeared. In particular, the secondary functions of “ちょっと” such as request, consent, call, and restraint also occurred in machine translation.
A Virtual Reality Simulator for Timber Fabrication Tasks Using Industrial Robotic Arms.

Virtual Reality (VR) simulators are well known applications for immersive spaces. When it comes to Human-Robot Collaboration(HRC), training and safety are important aspects that can be supported by simulators. In this demo, we propose a workflow between ROS and a VR application that allows the use of real robot programming plans to control the robot’s digital twin. We also provide the results of a short evaluation that was done with 6 experts, where they provided insights for future improvement and use cases. Our demo is the first step towards a full integrated system where path planning and fabrication steps can be tested with users without any of the risk and cost that are involved when using real industrial robots.
Enhancing machine translation with quality estimation and reinforcement learning

In recent times, our research has focused on training large language models and exploring their potential.With the emergence of Chat-GPT, it has been demonstrated that it is possible to fine-tune language models in a task-agnostic way.The success of ChatGPT is attributed to the reinforcement learning method, which integrates human feedback into the language model fine-tuning process.As a part of our research, we initially adapted the method of reinforcement learning for a specific task, which is machine translation, respectively.In this paper, we propose a novel approach to enhance machine translation with reinforcement learning and quality estimation methods.Our proposed approach uses reinforcement learning to learn to adjust the machine translation output based on quality estimation feedback, with the goal of improving the overall translation quality.We evaluated our approach on the WMT09 dataset for English-Hungarian language pair.We conducted an analysis to show how our approach improves the quality of machine translation output.Our approach offers a promising avenue for enhancing the quality of machine translation and demonstrates the potential of utilizing reinforcement learning to improve other natural language processing tasks.
Enhanced Community Through Augmented Reality: Social Benefits of Pokémon Go

Pokémon Go is an augmented reality game in which players travel through the real world catching fictitious creatures using a smartphone. Based on the game’s rewards for social interaction and visiting historical sites, we hypothesized that Pokémon Go would enhance players’ sense of belonging to their community. We recruited players to participate in a brief, anonymous survey at Pokémon Go events and via social media. The survey measured personal demographics, game-related demographics, sense of belonging to the community where participants play Pokémon Go, and questions regarding whether participants have met someone, visited a new location, or patronized a new business through playing Pokémon Go. 449 respondents completed the survey. 88% reported meeting someone through playing Pokémon Go, 78% reported visiting a new location, and 35% reported patronizing a new business. Pokémon Go level significantly predicted sense of belonging to the community in which participants play Pokémon Go as well as the odds of meeting someone, visiting a new location, and patronizing a new business. Results suggest that Pokémon Go strengthens players’ sense of belonging and engagement with their community.