Reviewerly/exHarmony huggingface dataset:
An improved deep-learning monocular visual SLAM method based on local features

To improve the tracking performance of the Simultaneous Localization and Mapping (SLAM) system, this paper presents a monocular visual SLAM method based on deep learning second order similarity of local features. The local features are generated into descriptors from patches around key points in a frame using a deep neural network. It is applied to tracking, re-localization, and loop closure module to enhance data association. We also train a visual bag of words model to adapt to the local descriptors. Additionally, we use two adaptive strategies to improve the proposed method, one strategy refines key points detection with illumination intensity, and the other strategy reduces the possibility of tracking lost based on the ratio of outliers’ number in feature matching. We evaluate our method on two public datasets. The experimental results demonstrate the effectiveness of the system and also show that the adaptive strategies can increase tracking performance and improve the robustness in challenging conditions.
Research on multi-label long text classification algorithm based on transformer-LDA

Text classification is an important research area in the field of natural language processing. In view of the low efficiency of the traditional CNN and RNN algorithms for multi-label classification of long text due to timing and spatial displacement problems, this paper proposes a long text classification model with improved Transformer attention mechanism, and combines LDA topic classification algorithm to achieve multi-label classification of document length text. Firstly, the paper introduces the industry's solutions to the problem of multi-classification of long texts. Compared with traditional algorithms such as truncation method and pooling method, the PAPER proposes the LDA topic classification model combined with the improved Transformer-XL text classification model to extract text features with fine granularity, so as to classify texts with higher accuracy. Finally, comparative experiments show that the proposed solution has a significant improvement in P value, R value and F1 value compared with the traditional classification method in the field of long text multi-label classification.
EFDet-SPP: efficient anchor-free network for fine vehicle detection

Existing vehicle detection methods lack the fine vehicle detection algorithm. In order to improve the accuracy and applicability of anchor-based object detection models, a novel and practical vehicle Fine-grained identification network (EFDet-SPP) based on the EfficientDet is proposed. The improved network adds a Spatial Pyramid Pooling module (SPP) after the feature extraction network for concatenating features to enhance network learning capabilities, and multi-scale extraction of highly semantic features of images. Anchor-based predictions are converted to pixel-based predictions by combining FCOS's head network, eliminating the hyperparameters associated with anchor boxes. And with Mosaic, Copy-Paste data augmentation methods scale small object samples to achieve data sample balance. Experimental results show that the improved network has achieved 94.8% in the actual collected fine vehicle detection dataset, which is greatly improved compared with the EfficientDet network, and does not significantly increase the training parameters and calculation amount of the network.
Intelligent classification and identification of radar jamming signals

Aiming at the problem of intelligent classification and recognition of radar jamming signals, the convolutional neural network structure is studied. By optimizing the basic network, the normalization layer and activation layer is added to the LENET-5 structure to improve the accuracy of recognition results. The linear frequency modulation signal and amplitude modulation interference, frequency modulation interference, comb spectrum interference, slice reconstruction interference, intermittent sampling and forwarding interference are analyzed. Six signal models are used to generate data sets, and intelligent methods are adopted to realize classification and recognition.
Multi-objective optimization problem based on non-dominated sorting genetic algorithm

Multi-objective optimization problem is a very common problem in mathematical modeling and daily research [1]. It belongs to the planning problem, and its ultimate goal is to find the optimal solution under certain constraints [2]. In order to solve the multi-objective programming problem, we usually use the multi-objective programming function in MATLAB, or take the traditional intelligent algorithm to solve, but the traditional algorithm is easy to fall into local optimal solution, and the error is large, which cannot meet the actual needs [3]. Therefore, this paper proposes an improved genetic algorithm, that is, non-dominated sorting genetic algorithm (NSGA-II) to solve multi-objective optimization problems, in order to better meet the research and practical needs [4]. In order to verify its superiority, this paper uses two examples, by comparing the results of the traditional algorithm and the improved genetic algorithm, using the comprehensive evaluation method to analyze, and finally draws the conclusion that the improved genetic algorithm is superior to the traditional algorithm.
Negative comment recognition model based on lightGBM

With the popularization and rapid development of the internet, the negative impact caused by negative comments is exacerbated. The increasingly common negative comments on various video websites and social networking sites have exercised a malign influence on public opinion and caused adverse social consequences. This paper uses LightGBM to establish a high-performance negative comment prediction model. The data set selected in this paper is from the Internet movie database IMDB, in which positive and negative comments have been marked for our training model. After Bag of Words processing and TF-IDF processing of the dataset and substituting it into our training model, the researchers obtained the final model with an accuracy of more than 95%, which has a more satisfactory performance compared with the classical integrated model and the traditional binary classification model. Thus, it can be seen that this model has an advantage in identifying spiteful comments online.
Procedural Generation in 2D Metroidvania Game with Answer Set Programming

Video game designers often find themselves at a crossroad when designing levels; namely, many have a difficult time balancing the amount of control they want to have over what their levels look like [1]. If too little control is given, like in the case of pure perlin-noise generation, levels can end up with too much variation and unideal generations [2]. Softlock is an example of unideal generation in the case of metroidvania games, if the placement of keys cannot be easily controlled and end up being placed behind gates, the players can get permanently stuck [3]. Developers may usually hand-make all levels in order to try and prevent this from happening, however they risk spending too much effort and time on designing levels, resulting in a general lack of quantity in levels. Objectively speaking, both methods have their strengths and work well in specific genres of games, but limiting oneself to the boundaries of these methods does not fundamentally achieve both quantity and accuracy. This paper proposes an unique solution to this dilemma, providing automated generation of levels while also giving developers much more control over the overall output. Our method uses Answer Set Programming (ASP) to verify generation based on restrictions we place, guaranteeing the outcome to be what we want [4]. To demonstrate our method, we applied our solution to a 2D metroidvania game made in the Unity game engine and conducted quantitative tests to assess how well our method works as a level generator [5].
Algorithmic tacit collusion

Algorithmic collusion has the potential to transform future markets, leading to higher prices and harm to consumer welfare. And yet, algorithmic collusion may remain undetected and unchallenged, in particular when it is used to facilitate conscious parallelism. The risks posed by such undetected collusion have been debated within antitrust circles in Europe, US and beyond. Some economists, however, downplay algorithmic tacit collusion as unlikely, if not impossible. ‘Keep calm and carry on’ they argue, as future prices will remain competitive. This chapter explores the rise of algorithmic tacit collusion and responds to those who downplay it, by pointing to new emerging evidence and the gap between law and this particular economic theory. It explains why algorithmic tacit collusion is not only possible, but warrants the increasing concerns of many enforcers.
The Rogue Scholar releases its first catalog of science blogs

The Rogue Scholar blog archive today released its first catalog of science blogs, a total of nineteen science blogs that signed up for the Rogue Scholar via submission form and met the inclusion criteria: The blog is about science and in English or German (more languages will follow later, reach out to me if you can help).The full-text content is available via RSS feed and distributed using a Creative Commons Attribution license (CC-BY).The Rogue Scholar will launch in the second quarter of...
Design and implementation of teaching aided intelligent land resource management research platform based on J2EE technology

With the development and progress of cloud computing, big data, data analysis and mining, as well as the gradual promotion and application in the field of land resources, the discipline development and scientific research of land resource management have also received extensive attention. However, there is still room for development of the land resource management platform in the field of teaching assistance, and the scientific research development, data sharing and openness of land resources are still insufficient. It is an important and urgent challenge to realize the development and application of data. In this paper, through the analysis of the existing system architecture, an easy-to-expand research platform framework is established, using J2EE for architectural development, and modular integration of different functions, so that the intelligent land resource management research platform can better serve geography research workers in the field of research and majors in earth sciences, and provide reference and suggestions for land research work.
Ransomware

This chapter explores ransomware and its alarming rise to a leading cybercrime technique. Ransomware is a type of malicious software that infects a computer and encrypts the contents of the computer's hard drive. The cyber-criminals who infected the computer then demand the victim pay a ransom with cryptocurrency to decrypt their data. Ransomware began to spread in the late 2000s and mostly affected home users and ransom demands were only a few hundred dollars. But as cybercriminals realized the ease of use and willingness of victims to pay ransoms, they began to target corporations for larger ransom payments. Within 10 years, ransom demands were routinely over $1 million for large corporations and cybercriminal organizations began to offer ransomware-as-a-service to entice others to spread their ransomware for a portion of the ransom. The services are sold through hacker forums, direct web sales, and on the dark web. The world's law enforcement agencies have recognized the threat of ransomware, and there have been recent high-profile arrests of the operators and takedowns of the ransomware-as-a-service operations.
Peningkatan Hasil Belajar IPS Perubahan Wilayah Provinsi di Indonesia melalui Media Pembelajaran Interaktif di Kelas VI SDN Jarin 4 Kecamatan Pademawu Kabupaten Pamekasan Tahun Pelajaran 2020/2021

As one of the conditions for achieving educational and teaching goals in general is the teacher's ability to select, develop and produce media, elements of methods and media are elements that cannot be separated from elements or techniques to deliver learning material to arrive at the goal. This study aims to: describe the use of interactive learning media to improve social studies learning outcomes in changes in provincial areas in Indonesia, describe the level of mastery of student learning about changes in provincial areas in Indonesia by using interactive learning media in social studies class VI at SDN Jarin 4 Pademawu District. The use of the use of interactive learning media can improve social studies learning outcomes for changes in provincial areas in Indonesia for class VI, the highest score achieved by students reaches 100 (1 person). VI at SDN Jarin 4, Pademawu District. Of the 10 students, there are 90% or 9 students who have completed their studies and only 1 student (10%) has not completed their studies.
Penerapan Pembiasaan Literasi dalam Meningkatkan Minat Baca Peserta Didik di Sekolah Dasar Negeri 095205 Parbalokan

The purpose of this study was to find out literacy habituation in increasing students' interest in reading at State Elementary School 095205 Parbalokan. The focus of this research: 1) How to apply the school literacy movement at the habituation stage, 2) How to apply the school literacy habituation at the development stage, 3) How to apply the school literacy habituation at the learning stage. This study uses a qualitative approach and a type of phenomenological study. Subject handling methods using purposive and snowball. Methods of data collection using observation, interviews, and documentation, and data analysis using an interactive model with the steps of data collection. compaction, presentation of data, drawing conclusions and verification. Test the validity of the data using source and method triangulation. The results of this study indicate: First, the habituation stage is the activity of reading 15 minutes aloud or silently. Second, the development stage, namely reading 15 minutes before the lesson. Third, the learning stage that has been used in learning all subjects. Reading strategies used to improve students' understanding of reading in all subjects. Activities to respond to reading in the form of oral, written, artistic, craft and other activities in accordance with students' literacy activities. Learning takes place in the school library, classroom reading corner, school reading area and others. Academic awards consider student costs.
PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN VISUAL TERHADAP HASIL BELAJAR MAHASISWA PADA MATA KULIAH BAHASA INGGRIS

The purpose of this study was to determine the effect of the use of learning media on student learning outcomes in English courses. This research is a descriptive study with a quantitative approach to see how the effect of the use of visual learning media on student learning outcomes in English courses at the Department of Community Education - FIP Unimed. Based on the results of the research data analysis, it can be concluded that there is the large influence of the use of visual learning media on the learning outcomes of the Public Education students that indicated by the post-test results after being given treatment with visual learning media in English courses, then the lowest score obtained is 68 and the highest score is 93. The results of the calculation obtained an average score of 80.00, a standard deviation of 5.4, a variance score of 30.14, then a median score of 80 and a mode score of 84. From the data above, it shows that the results of the learning ability of Community Education students in the English course after being given treatment show a significant increase in Public Education students at the State University of Medan.
Pengaruh Media Google Earth Terhadap Materi Tata Letak Dan Denah Pada Peserta Didik Kelas IV SD Negeri 02 Papahan Tasikmadu Tahun Pelajaran 2022/2023

This research aims to investigate whether or not Google Earth has an influence on Layout and Floor Plan Material for Grade IV Students at SD Negeri 02 Papahan Tasikmadu in the 2022/2023 Academic Year. In addition, it is also to find out whether there are obstacles and benefits of Google Earth Media for Layout and Floor Plan Material for Class IV Students at SD Negeri 02 Papahan Tasikmadu for the 2022/2023 Academic Year. This research has a population of 32 students from Class IV A, namely SD Negeri 02 Papahan Tasikmadu for the 2022/2023 academic year with a saturated sampling technique. Furthermore, the data collection techniques used are observation and learning achievement tests. Observation is used to observe students' initial conditions before being given treatment and learning outcomes tests in the form of multiple choice questions after being given treatment. The analysis technique is carried out in 2 ways, namely: from the prerequisite test and the t-test. The prerequisite test consists of the normality test and homogeneity test. Meanwhile, the t-test uses the Paired Sample T-test. Analysis of the use of the t-test formula in the form of a Paired Sample T-Test yields, if a significant value is 0.001 &gt; 0.05, it can be said that H0 is rejected and Ha is accepted. In addition, the value of tcount = 16.030 can be compared with the value of ttable with the value of dk = (N-1) then (32-1) = 29 at a level at a significance level of 5% will have a ttable value of 2.042. When compared tcount and ttable then 16.030 &gt; 2.042. Alternative hypothesis (Ha), is accepted if tcount &gt; ttable. The next hypothesis could be "the influence of Google Earth media on Layout and Floor Plan Material in Grade IV Students at SD Negeri 02 Papahan Tasikmadu for the Academic Year 2022/2023" at a significance level of 5%.
Designing a Mobile-Messaging App-Based Teachers’ Community of Practice in India

A mobile-based messaging app (MMA) was implemented as a teachers’ community of practice in the Indian context through a large-scale educational initiative. The development process adopted a Design-based Research approach to test underlying theories in real-world settings. The researchers theorised the pedagogical affordances of the MMA Telegram using Davis and Chouinard's theoretical framework of affordances, defined as a relational process among users, designers, the environment, and the artefact. This paper discusses the iterative design process in detail. The findings showed that the MMA encourages accessibility and for teachers to showcase their practice in the online community of practice and refuses (does not allow) the development of the online community of practice as an epistemic community.
National Digital Identity: Current Landscape, Emerging Technologies and Future Directions

The proliferation of digital services has led to an increasing demand for secure and reliable digital identity verification, resulting in the development of national digital identity (NDI) systems.These systems provide individuals with a trusted method of verifying their online identity, a necessary prerequisite for accessing a wide range of services, such as banking, healthcare and government services.This review paper takes an in-depth look at the evolution of NDI systems and the advanced technologies that have improved their security and reliability.It looks at the notable NDI systems and digital identity programmes that have been introduced in different countries and analyses both their successes and limitations.In addition, the paper examines emerging technologies such as blockchain and their potential impact on NDI systems.Based on the assessment of these systems and technologies, practical recommendations and best practises are provided for the future development and implementation of NDI systems in other countries.
The Integrated Information System Implementation Strategy in Korlantas Polri Based on the Zachman Framework Approach

Traffic Police Corps (Korlantas Polri) is the executor of the main duties of the Indonesian National Police in the areas of security, safety, order and smooth traffic. Korlantas has some information that can be accessed by the public, namely information on congestion, accidents, traffic flow status, vital objects, road conditions, data and visual images from CCTV, public service conditions, and traffic infrastructure. However, these data are stand alone and not integrated with their respective applications and systems. The purpose of this study is to analyze the strategy for implementing an integrated information system at Korlantas Polri and what steps can be taken to integrate the existing system. This study uses the Zachman Framework which is adapted to Enterprise Architecture Planning (EAP) and qualitative data collection methods by interviewing stakeholders who are involved in managing information systems at Korlantas Polri. The results obtained are the need for a data warehouse by implementing an AI based integrated database system, Geospatial Information System, Business Intelligence and DSS, as well as Smart Visualization to visualize existing data. Then standardize the need for equipment and support for improving the ability of personnel in the IT field.&#x0D;
Supplemental Material: Geoheritage: Progress toward Preservation

&lt;p&gt; Table S1. Geoheritage video and Story Maps, aligned to the Next Generation Science Standards Earth and Space Science Disciplinary Core Ideas, with suggested free resources from SERC Carlton Teach the Earth Collection. &lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt;
Business Ethics in the Digital Transformation Era: Focusing on Big Data and Artificial Intelligence Technology

Recently, a sustainability management is becoming an essential business issue for organizations.Under this circumstance, the importance of business ethics, which is a management activity that balances the interests of shareholders and stakeholders, has emerged.Based on contingency theory, an ethical decision-making is influenced by the external environment.One of the major changes affecting businesses environment is a digital transformation.With the advent of the digital transformation era, which refers to dramatic changes in business models and ways of work using digital technology, the application of big data and artificial intelligence is increasing.However, previous research has focused only on the effect of digital transformation on organization outcomes or individual performance.There is a lack of study on ethical issues that may arise from the use of technology in organizations.Accordingly, this study examines the business ethics in the era of digital transformation.This study analyzed 21 journals in the field of management and IT to examine technology-related research trends in the field of business management.We also analyzed the topics of the Journal of Business Ethics and then identified the topics of technology and ethical management that are mainly dealt with in management research today.In particular, this study focuses on ethical issues in practice and research with artificial intelligence and big data, which are major technologies in the era of digital transformation, and provides various suggestions for solving ethical problem of digital transformation.This study can expand our knowledge of business ethics research and articial intelligence technology, and suggests future directions.