Reviewerly/exHarmony huggingface dataset:
CAKG: A Framework for Cybersecurity Threat Detection of Automotive via Knowledge Graph

With the increasing complexity and connectivity of vehicles, ensuring their security has become a critical concern. In this study, we propose CAKG: A Framework For Cybersecurity Threat Detection Of Automotive Via Knowledge Graph, achieved with a knowledge graph for vehicle vulnerability and threat intelligence. We integrate existing cyber security knowledge bases to analyze potential attack surfaces and scenarios specific to automobiles. By using keyword extraction and text similarity analysis, we identify threats relevant to the event produced by Intrusion Detection Systems(IDS) in automotive. Moreover, we leverage another knowledge graph to analyze attack logs gained from actual vehicles, enabling us to further correlate security events and product situational analysis. Our framework provides a holistic perspective on vehicle security, facilitating threat modeling and enhancing our understanding of potential attack scenarios.
Image defogging algorithm based on physical prior and contrast learning

Deep learning-based defogging methods can generate defogging results with high evaluation indexes end-to-end through the training of a large amount of data, but most of the existing methods do not make use of physical a priori with better defogging effects, and the use of synthetic data does not cope well with practical application scenarios due to the difficulty of obtaining supervised data, and the generalisation and robustness of the trained models are difficult to be guaranteed. Therefore, to address the above problems, this paper incorporates physical a priori such as non-local, dark channel and bright channel into deep learning, and introduces the contrast learning method in self-supervised learning, which constrains the distance between the data by the extracted features, ensures the effective use of the real data, and improves the model&apos;s defogging quality and generalisability. In order to meet the high-quality requirements of computer vision systems for images, an interactive tool is designed through relevant software and calls the function of the haze removal algorithm designed in this paper to realise the functions of capturing real-time scene images and removing haze from images in different ways.
Analysis and Optimization of the K-Means Algorithm in Determining Course Scheduling

Preparation of course schedules is the core activity of learning and learning. This is felt by study programs, where assignments are arranged through lecturer assignments, to class determination and class schedule dissolution, therefore the right application is needed to be able to arrange schedules automatically, then by using the k-means method you can arrange schedules correctly , in designing this application requires a prototyping application development method which gives good results where the clusters formed reach 17 clusters where the course schedule is made with the results of the Means Sequence Error in cycle 1 which is 65.66% with an accuracy of 54.06%. so that it is continued in cycle 2 the MSE value is 87.55% with an accuracy of 84.03%. The K-Means algorithm can accurately determine course schedules in the faculties of computer science and information technology.
Perancangan Game Sederhana Perancangan Game Sederhana Menggunakan Scratch Programming Sebagai Media Pembelajaran Visual Bagi Anak Usia Dini

This study aims to design a simple game using Scratch Programming as a visual programming language learning media for early childhood. This article describes the implementation stages of game design and the evaluation of learning media carried out. The literature review reviews the advantages of Scratch Programming as a learning medium for children and previous related research. In the implementation of game design, game concepts are designed using Scratch Programming, and simple game examples are generated. Evaluation of learning media is carried out to collect evaluation data from participants using relevant methods. The results of the evaluation of learning media and the discussion of research findings provide information about the effectiveness of game design using Scratch Programming. The results of this study indicate that designing simple games using Scratch Programming can be an interesting and effective learning medium for young children in learning visual programming languages. The implication of this research is further development in game design and the use of visual programming languages in early childhood education. Suggestions for further research are to involve more participants and explore more complex programming concepts.
SYSTEM FOR RETRIEVAL AND VISUALIZATION OF DATA FROM THE INTERNET

The article presents a system that dynamically displays the availability of language datasets and language models found in large repositories such as Hugging Face. The goal of developing such a system is to demonstrate that, outside of English, the datasets and language models required for advancements based on or utilizing language technologies and artificial intelligence have either moderate or fragmented support. At the same time, the description of the system architecture introduces readers to easy-to-use instruments such as Node-RED, MariaDB, and Grafana, which offer a wide range of application opportunities in solving various tasks like crawling and collecting data from the Internet, storing information in a database, and data visualization in a clear and functional manner. Each of these tasks, as well as their combinations, can be used to carry out student projects at the senior high school level of education.
EKSPERIMEN MEDIA PEMBELAJARAN “I-SLAMI” GUNA MENINGKATKAN MOTIVASI BELAJAR PENDIDIKAN AGAMA ISLAM SISWA TUNA RUNGU DI SIDOARJO

The spread of Covid-19 which is so dangerous is a factor for learning to be carried out online. Online learning cannot be carried out effectively, some students admit that they have difficulties when learning online, this makes student learning motivation decrease. Likewise for deaf students who have limited hearing, one of the materials that is difficult for teachers to convey is Islamic Religious Education (PAI). Based on this, the authors conducted research with the learning media experiment "I-Slami" to increase the learning motivation of deaf students. The aims of this study were 1) to describe the experimental results of the "I-Slami" learning media in increasing the learning motivation of deaf students in Islamic religious learning, 2) to determine the effect of the "I-Slami" learning media in increasing the learning motivation of deaf students. The method used in this study was experimental, with a true design experimental approach, namely to test the "I-Slami" application by forming 2 groups, namely the experiment and the control, so that the authors could compare the results of the treated and untreated groups. The results of the study were obtained from the Wilcoxon test with a sig value of 0.012 &lt;0.05 so that the I-Slami application could increase student learning motivation, and an effect of 12% was obtained, the T-test results obtained a sig. 2-tailed 0.00 &lt;0.05 which means there are differences in learning motivation between the control and experimental groups
The Impact of Social Media Information Literacy on Malaysian Youth’s Emotional Intelligence

Social media has evolved into a network that helps users find information. Social media platforms like Facebook, Twitter and Instagram are now important sources of up-to-date news and information. In order to give people the ability to assess, inform about potential threats or effects, and be aware of false information in the network, social media information literacy (SMIL) has been developed. However, that social media can have negative emotional effects that decrease in emotional quotient (EQ) among young people will directly lead to social problems like crime. In this quantitative study, Malaysian youth between the ages of 19 and 40 were examined to determine the impact of social media information literacy (SMIL) on emotional intelligence (EQ). 241 students from three universities in Malaysia who were selected through proportional stratified random sampling and simple random sampling made up the respondents. Data are gathered using a "Google Form" questionnaire and data analysis uses descriptive and inferential statistical analysis to get the results. Social media information literacy (SMIL) and emotional intelligence (EQ) were found to be significantly correlated by Pearson correlation inference analysis. The results of this study have implications for institutions seeking to develop human capital, technology, and media. Other organizations interested in exploring the field of social media information literacy (SMIL) and emotional intelligence (EQ) can use it to meet the sustainable development goals (SDG) in digital sustainability as recommended by UNESCO.
The Semiotic Analysis of Advertisement Design in Cross-cultural Communication : A Case of Huawei

This purpose of this study is to exam advertisement design in cross-cultural communication, focusing on understanding how advertisements can be designed to resonate with people of different cultural backgrounds. For the data collection of the study, the advertisements presented by Huawei in the European and American markets were collected as samples for an analysis. Through sorting out the types and forms of the texts and advertisements presented in the European and American markets, the study has applied a qualitative content analysis method to conduct as a case study in order to explore the inner meanings and intention to succeed cross-cultural communication. Researching on the system construction and presentation of advertisement design of Huawei brand, this study analyzes the text, image, and product symbol systems of advertising, and explains the meaning and connotation of advertising symbols in light of the advertising semiotics. In conclusion, advertisement designers should develop a corresponding advertising forms and contents, so that enterprises can fully appeal the culture and custom of their target countries, and produce the advertisements through sense of semiotic resonance.
Comparative Study of Mass Shape Based on BI-RADS Mammography Classification with Histopathological Grading in Breast Cancer

Background: Breast cancer can be diagnosed using imaging modalities and histopathology. The description of the mass shape found via mammography needs to be confirmed by an anatomical pathology examination. Therefore, research regarding the comparison of mass shape based on BI-RADS mammography classification with histopathological grading of breast cancer patients is important. Objective: Analyzing the differences in mass shape based on the BI-RADS mammography classification between histopathological grading of breast cancer patients at Dr. Soetomo General Hospital Surabaya. Method: This type of research is an analytical observational study with a comparative approach using patient medical records in the form of age data, mammography examinations of breast cancer patients who were diagnosed based on histopathology results at Dr. Soetomo General Hospital Surabaya during the period January 2017 to December 2021. Results: Total breast cancer samples at Dr. Soetemo General Hospital Surabaya for the period January 2017 to December 2021 is 229 data. Breast cancer patients are dominated by the age group 40 – 49 years (37.6%), the majority of masses are found in the right breast (54.1%), the shape of the mass is predominantly irregular (86.5%), the most histopathological grading is in grade 3 (53.3%), and the comparison of mass shape between histopathological grading had a value of p = 0.137 (p > 0.05). Conclusion: Breast cancer patients at Dr. Soetomo General Hospital Surabaya for the period January 2017 to December 2021 is dominated by the 40 – 49 year age group. Most of the masses were in the right breast. The most common mass shape found was irregular and the most frequent histopathological grading was grade 3. There were no differences in mass shape between histopathological gradings.
Media Pembangkit Gelombang Skala Laboratorium

In the design of offshore building structures, calculations are required by looking at the factors that occur in the ocean. A big factor that occurs is the disturbance force of waves which can disrupt the strength of the building structure to be created. For this reason, this research makes a wave generating media device on a laboratory scale. With this tool, efforts are also made to resemble the original wave, where the deeper it is, the smaller the strength of the wave formed. This effort is an implementation of the wave forms that occur in the open sea. The results of the design of a wave generating media device measuring 3690x830x940 mm. From wave observations and calculations, it was found that the wavelength was 0.5m and the amplitude was 0.01m. It was concluded that the type of wave characteristic produced by this tool was categorized as an airy wave.
GCN-based Entity Relation Extraction Method for Power Marketing Data

Power marketing text data contains more specialized terms in specific fields, and there are multiple nested text entities, therefore the relationship between entity recognition is more difficult. In this paper, a graph convolution-based entity relation extraction model PMRE for power marketing data is proposed. Firstly, using the span representation annotation method, the model extracts the bidirectional representation of text depth by using RoBERTa as the encoder layer, and uses the whole word masking strategy for pre-training. Then the feature representation is passed to the graph convolutional layer, and using multi-head attention mechanisms to capture the weights of relationships between words in the text across multiple dimensions, and the semantic dependency tree is constructed and then fed into the graph convolutional neural network, and the distance dependency problem solved by the spatial features between entities is obtained. Finally, the features are fed into the multilayer perceptron layer for entity relationship classification. In the process of model training, the cross-entropy loss function is used to obtain the maximum likelihood value of the predicted label and the target label. Using the power marketing data supplied by the Southern Power Grid as an example, the precision and F1 score of the relation extraction model in this paper reached 83.80% and 82.16%, respectively, compared with the benchmark model, recall, precision and F1 score of this model are significantly enhanced, indicating that the model proposed in this paper has a good solution effect on entity relation extraction of power marketing text data with complex entity nested and many professional terms.
The Impact of Cybercrime in Modern Generation Based on Systematic Literature Review Analysis

Cybercrime is a term for any illegal activity that uses a computer as its primary means of commission. Due to the pervasive presence of the internet, the modern generation faces unprecedented challenges posed by cybercrime. Cybercrime has brought a lot of impacts to individuals, societies, and institutions in contemporary times. Sadly, it has become one of the most worrying issues in the current world. This study was done to determine the impact of cybercrime in modern generation. This research employs a qualitative approach by conducting a systematic literature review utilizing the PRISMA method. Moreover, it incorporates the outcomes of prior studies by employing a screening process to identify and critically access each one, thereby reestablishing their significance with the current study. The results of the study found impacts of cybercrime in modern generation which are financial consequences, expanding security budget, social implications, information security concern, and psychological and emotional toll.
SAYAP PALACE MEMORIAL: RECONSTRUCTION OF THE LOST MALAY CULTURE

The Sayap Palace is a relic of the Pelalawan Kingdom, located in Pelalawan Regency. This palace was built during the reign of Sultan Assyaidi Syarif Hasim. The purpose of this article is to describe the process of the establishment of the Sayap Palace, its role in people’s lives, and its use in the field of education. This article uses the historical method with descriptive analysis techniques and literature studies. After the end of the reign of the Pelalawan Kingdom, the Sayap Palace was no longer occupied and then collapsed. The Sayap Palace’s restoration took place twice, in 2003 and 2015. As a cultural heritage, the Sayap Palace has an essential meaning for the people of Pelalawan in particular and Riau in general. At the end of this article, we will also discuss how the Sayap Palace can be utilized in education.
Implementasi Model Teams Games Tournament untuk Meningkatkan Kemampuan Numerasi Siswa Sekolah Dasar

Numeracy has an important role in helping students to be able to solve problems that can be encountered in the surrounding environment. This research is Classroom Action Research (PTK) aimed at improving students' numeracy skills through the application of the Teams Games Tournament (TGT) model in mathematics subjects. This research method is Classroom Action Research (PTK) which is carried out in 2 cycles consisting of 4 stages, namely planning, implementation, observation and reflection. The subject of this research was class V at SDN 34 Lubuklinggau with a total of 19 students. Data collection techniques are observation, interviews, and tests. Data analysis techniques use average score or percentage techniques. The results of this research show that the application of the Team Games Tournament (TGT) model can improve the mathematical numeracy skills of class V students at SDN 34 Lubuklinggau. The average percentage of students' numeracy abilities in the pre-cycle was 21.1% in the first cycle to 47.4%, then in the second cycle it increased to 68.42%. This research concludes that the application of the Teams Games Tournament (TGT) model can improve the mathematical numeracy skills of class V students at SDN 34 Lubuklinggau in mathematics lessons.
Pengembangan Media Buku Cerita Digital Pada Pembelajaran IPS Materi Kerajaan Islam Kelas IV Sekolah Dasar

This research is the development of digital storybook media in social studies learning material on the Islamic kingdom in grade IV elementary school. This was done because of students' lack of interest in learning social studies in elementary schools. This research aims to design, test the feasibility and determine the response to digital storybook media in elementary schools. The method used in the research is Design and Development using the ADDIE model development which includes 5 stages, namely analysis, design, development, implementation and evaluation. Research participants consisted of material experts, linguistic experts, media experts as well as users, namely teachers and students, to obtain the results of the feasibility assessment of the learning media that had been created, as well as responses from users. The data analysis techniques used include data collection, data presentation, data reduction and drawing conclusions to answer the proposed problem formulation. Therefore, the digital storybook learning media was designed using Canva and ibispaintX as application platforms. Responses from material experts, media experts and language experts received very good responses and were worth testing with elementary school students. The response from student users and teachers received a positive response. From these responses, digital storybook media is suitable for use in learning and has received positive responses from students and teachers.
Application of PID Control System in Mecanum Wheelchair

This research centers on the design and implementation of a control system for an electric wheelchair equipped with Mecanum wheels. The study details a comprehensive research methodology starting with the creation of a block diagram to guide system design, hardware selection, and overall implementation. The electric wheelchair system incorporates power resources, input devices, and energy output mechanisms, utilizing a 24 VDC battery and a joystick with a 10K ohm potentiometer connected to an Arduino Due microcontroller. The operational workflow of the system is defined, enabling the wheelchair to respond to joystick commands for forward, left turn, right turn, and other movements. A PID control system is employed to regulate motor movement, enhancing control precision. The Cohen-Coon tuning method is used to determine the PID controller's gain, ensuring efficient closed-loop control. Results from PID controller experiments under P control and PD control are presented, demonstrating the system's responses for different gain values. Optimal performance is observed with a Kp value of 80 and Kd value of 1.2, showcasing improved response speed, reduced rise time, enhanced setting time, and lower percent overshoot. In conclusion, the combined proportional and derivative control system, specifically with Kp = 80 and Kd = 1.2, proves to be effective in enhancing the Mecanum wheelchair's performance. This study provides valuable insights into precise parameter adjustments for optimal control in Mecanum wheelchair applications.
The financial sector of emerging markets based on digital technology evolution in the banking sector - The Ghanaian experience

Evaluating the financial sector of emerging markets based on digital technology evolution is crucial, as the market tends to exhibit greater fragility than in the developed markets. As a result, this study is conducted to provide a deeper understanding of the old and new realities of the financial sector of emerging markets and conducts both qualitative and quantitative analyses of technology impacts on financial sector of emerging markets. Further, the study has developed models to help emerging markets leverage digital technology to achieve sustainable financial sector growth. In addition, the SmartPLS modeling was applied to show the linkages between the characteristics of the financial sector in emerging markets and digital technologies.
Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection

Anomaly detection (AD), aiming to find samples that deviate from the training distribution, is essential in safety-critical applications. Though recent self-supervised learning based attempts achieve promising results by creating virtual outliers, their training objectives are less faithful to AD which requires a concentrated inlier distribution as well as a dispersive outlier distribution. In this paper, we propose Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation (UniCon-HA), taking into account both the requirements above. Specifically, we explicitly encourage the concentration of inliers and the dispersion of virtual outliers via supervised and unsupervised contrastive losses, respectively. Considering that standard contrastive data augmentation for generating positive views may induce outliers, we additionally introduce a soft mechanism to re-weight each augmented inlier according to its deviation from the inlier distribution, to ensure a purified concentration. Moreover, to prompt a higher concentration, inspired by curriculum learning, we adopt an easy-to-hard hierarchical augmentation strategy and perform contrastive aggregation at different depths of the network based on the strengths of data augmentation. Our method is evaluated under three AD settings including unlabeled one-class, unlabeled multi-class, and labeled multi-class, demonstrating its consistent superiority over other competitors.