Reviewerly/exHarmony huggingface dataset:
Sistem Aplikasi Supervisi Kunjungan Kelas pada Guru Madrasah di Kota Banda Aceh

Educational process is acceleration of the globalization of technology education system that demands to be able to collaborate as a new era of educational development, especially in the supervision of learning, for supervised learning the technique, especially in supervising classroom must adjustments to the way in providing surveillance technology utilizing information technologybased teaching. This study focuses on how to design an application system supervisory class visits and how to test its performance. The goal this application is to be supervision media to effective supervisor, and to efficient supervisor duty to supervision to madrasah at Banda Aceh. This study using methods of descriptive, evaluative, and experimental, as study materials, the data collected through observation, interviews, and documentation are analyzed descriptively by means of inductive thinking. While the methods used in building applications system design is based on a structured approach is by using the waterfall method, a tool for designing applications in the form of Map Data Flow and Data Flow Diagram. While supporting software uses Microsoft Excel as a spreadsheet application program that is familiar among the data processing and calculation reports. Based on the results of the development through the design and testing of application programs on a madrasah classroom supervision in Banda Aceh, the results showed: 1) Development of application program supervision to the madrasah classes in Banda Aceh has been through a series of software engineering process from design to testing in accordance with the needs of supervisors in evaluating the quality of teaching and learning processes of teachers; 2) the performance of the overall application program can work in accordance with their respective functions that can help supervisors, fast, precise, and accurate.
Standardscaler's Potential in Enhancing Breast Cancer Accuracy Using Machine Learning

The major consequence of breast cancer is death. It has been proven in many studies that machine learning techniques are more efficient in diagnosing breast cancer. These algorithms have also been used to estimate a person's likelihood of surviving breast cancer. In this study, we employed machine learning algorithms to predict breast cancer. A total of 569 breast cancer datasets were obtained from kaggle sites. Some of the machine learning algorithms that we use are K-Nearest Neighbor (KNN), besides Random Forest (RF), there is also Gradient Boosting (GB), then Gaussian Naive Bayes (GNB), Vector Support Machine (SVM), and then Logistic Regression (LR). Before algorithms were used to train and test breast cancer datasets, StandardScaler was leveraged to transform training datasets and test datasets for improved algorithm performance. As a result of this utilization, the performance measurement carried out succeeded in producing high accuracy. The highest results were obtained from the Logistic Regression algorithm with an accuracy value of 99%. The value of precison is 99% benign, and 100% malignant. The recall results are 100% benign, and 98% malignant. The F1-Score results show 99% benign, and 99% malignant. It is hoped that this research can help the medical party to determine the next step in dealing with breast cancer.
Interpretation of a Literary Text in the Cinema: V.S. Rozov's Play “Forever Alive” and M.K. Kalatozov's Film “Cranes Are Flying”

The article explores film screening as a special form of literary text. Within the framework of the study, the concept of cinema screening, its classification and features of types, “strengths” and “weaknesses” of this format are considered. The problems arising during the transfer of literary works of art to the cinema screen are also characterized, which are the subject of controversy at the present time. The study of these issues is carried out not only in theory, but also in practice, which is presented in the form of a comparison of V.S. Rozov's play "Forever Alive" (1943) and the movie M. K. Kalatozova “Cranes are Flying” (1957). In addition to identifying the differences between the original literary work and its transfer to the language of cinema, expressed in deviation from following the literary fiction text, added episodes and expansion and reduction of individual storylines of the original, the creative task is determined, and how exactly it was achieved. The main research methods: analysis of scientific literature on the subject of the study, used for a detailed examination of film screening as a special form of literary text, analysis of critical studies, biographical literature, archival documents, as well as comparative analysis (they were used when comparing the original literary text (V.S. Rozov's play “Forever Alive”) and its film adaptations (M.K. Kalatozov's film “Cranes are Flying”)). As a result of the conducted comparative analysis, a conclusion is drawn that contains answers to the questions: which type of film adaptations does this film belong to, what is it expressed in, and also the reasons that led to this result are revealed.
A Smart Kumbung For Monitoring and Controlling Environment in Oyster Mushroom Cultivation Based on Internet of Things Framework

Oyster mushroom (Pleurotus Ostreatus) is a fungus-like plant that is often cultivated in Indonesian agriculture. Oyster mushroom is raised by manipulating environmental parameters, so that it can grow in the provided Kumbung. Oyster mushroom requires a temperature that is used, which ranges from 23°-28°C, for humidity used between 70% -90% and for light intensity it requires light of ±300 lux. In this study, a system was designed to carry out automatic monitoring and control in real time based on the Internet of Things (IoT) which integrates DHT22 humidity and temperature sensors, BH1750 light intensity sensors and NodeMCU as a microcontroller with measurement results sent to the Firebase database. In addition, a water pump connected to the sprayer nozzle is installed in this system to maintain the humidity of the oyster mushroom curd. From the test results, the system can work automatically to stabilize temperature, humidity, and light intensity according to the ideal parameters.
SQL Injection Detection Using RNN Deep Learning Model

SQL injection attacks are a common type of cyber-attack that exploit vulnerabilities in web applications to access databases through malicious SQL queries. These attacks pose a serious threat to the security and integrity of web applications and their data. The existing methods for detecting SQL injection attacks are based on predefined rules that can be easily circumvented by sophisticated attackers. Therefore, there is a need for a more robust and effective method for detecting SQL injection attacks. In this research, we propose a novel method for detecting SQL injection attacks using recurrent neural networks (RNN), which are a type of deep learning model that can capture the syntax and semantic features of SQL queries. We train an RNN model on a dataset of benign and malicious SQL queries, and use it to classify queries as either benign or malicious. We evaluate our method on a benchmark dataset and compare it with the existing rule-based methods. Our experimental results show that our method achieved high accuracy and outperformed the rule-based methods for detecting SQL injection attacks. Our research contributes to the field of web application security by providing a new and effective solution for protecting web applications from SQL injection attacks using deep learning. Our method has both practical and theoretical implications, as it can be easily integrated into existing web application security frameworks to provide an additional layer of protection against SQL injection attacks, and it can also advance the understanding of how deep learning models can be applied to natural language processing tasks such as SQL query analysis.
Pelatihan Pemanfaatan Media Fokusky Bagi Guru SMK di Tinambung Kabupaten Polewali Mandar

One of the efforts to realize the function of national education is to create conditions and atmosphere that can foster students' interest in learning. Solusiky is software for internet-based presentations. Apart from presentations, Solusiky can also be used as a tool to explore and Solusiky is superior because this program uses Zooming user interface (ZUI), which allows Solusiky users to zoom in and out on presentations. There are no presentation media options other than Power Point. The problems that occur are (1) Students tend to get bored with the presentation media currently used. (2) There is no training on new presentation media. (3) Lack of knowledge on how to use the Solusiky application. PKM activities can increase the knowledge and insight of partners or teachers regarding the use of Solusiky learning media and become a reference for several learning media options that can be used. Implementation of community service hybrid learning media training for teachers at Tinambung Vocational School, Polewali Mandar Regency, had a good impact
Pelatihan Simulasi Untuk Program Nc dengan CAD/CAM Software Mastercam X5 Bagi Mahasiswa Jurusan Pendidikan Teknik Mesin Fakultas Teknik UNM

This activity on applying science and technology to the community aims to: (1) Increase student knowledge regarding NC/CNC. (2) Increase students' ability to create drawings according to the positions and axes in the NC/CNC coordinate system (3) Increase knowledge about software that is widely used in industry. The conditions and problems faced are: Students are not yet familiar with the MasterCam X5 Software. This problem becomes the basic reference for the need to carry out training. Competencies of Mechanical Engineering Education Department students who are prepared as teaching staff at the vocational school level. The curriculum structure contains NC/CNC machining courses which require a simulation program in the form of CAD/CAM software which can produce programs or G-code (CNC programming language), so that this training becomes a trigger or socialization of the use of MasterCam X5 software with CAD content which is software. to create a product design. The output of the activity is: Mastery of MasterCam X5 which results in increased student knowledge in terms of understanding the hierarchy of making NC/CNC programs
AI-DRIVEN STRUCTURAL HEALTH MONITORING FOR THE TALLEST CURVED CONCRETE SKYSCRAPER

With the rapid increase in the construction of tall buildings around the world, ensuring their safety and structural integrity has become of paramount importance. This paper focuses on the Al-Hamra Tower, a remarkable skyscraper standing at an impressive height of 412.6 meters (1,353’-6”) in Kuwait City in Kuwait, and explores the role of Structural Health Monitoring (SHM) as a powerful tool for assessing building conditions, detecting damage following extreme events, and optimizing cost-saving strategies. Among the various factors that can lead to building failures, extreme events such as earthquakes in the Gulf Region pose the greatest threat. If damage conditions are not promptly identified, they can leave the structure vulnerable to further deterioration. Early diagnosis of damage is not only crucial for the safety of occupants but also proves to be cost-effective, as repairing minor damage is generally more affordable than addressing major structural failures. This paper presents an advanced AI-powered SHM system specifically developed for the Al-Hamra Tower. The study delves into the implementation of a dense array of instrumentation strategically placed throughout the tower to capture and measure its structural response under different loadings, including wind, seismic activity, and thermal effects. The SHM system incorporates an automated triggering mechanism that responds to predefined events, such as earthquakes, and promptly sends text and email notifications to alert relevant authorities. By highlighting the case study of the Al-Hamra Tower, this research underscores the critical importance of SHM for tall and critical buildings, offering invaluable insights into the design and implementation of effective SHM systems for future skyscrapers. Keywords: AI, SHM, machine-learning, earthquake, tall-building, multi-sensing, big-data, analytics, early-warning, seismic-design, neural-network
Pendampingan Operator Komputer Pada Bagian Kepegawaian Kantor Camat Praya Lombok Tengah

Developments in the field of technology at this time provide a significant contribution and influence to the world of government. Management of government data such as data on employees, communities and other elements so that the process of conveying information becomes faster and more structured. With the assistance of optimizing observation activities carried out with students who get higher knowledge. The implementation method goes through several stages starting with the observation or observation stage, the activity implementation stage and the evaluation or monitoring stage. The obstacle experienced was that the participants just found out about the report, and they did not understand employee data reports. Because they are not used to only recording incoming and outgoing data that is used to achieve the many planned activities, the utilization of computer operator assistance in the personnel department is good so that it is very easy to receive important information and programs. Services are carried out informally and flexibly. Giving material begins with introducing recording and bookkeeping to participants, then also explaining the importance of ability or knowledge in implementing counselling activities. Increasing the level of understanding of computer operators about the importance of recording employee data reports in the office, utilization and use of computer resources is carried out according to the method that has been planned, namely through the stages of data collection, implementation of activities and evaluation. Participants gave positive responses to the activities that had been carried out.
The Application and Impact of Digital Printing Technology in Higher Education Teaching

Digital the rapid emergence of digital printing technology has sparked extensive research and attention in the field of higher education teaching. This paper aims to delve into the practical application of digital printing technology in university teaching and the profound impact it brings. Firstly, through a comprehensive analysis of the background of digital printing technology, we will reveal its development process, key characteristics, and its applicability in the educational domain. In terms of case studies, we will conduct a detailed analysis of the practical use of digital printing technology in various academic disciplines at universities, exploring its specific effects on textbook production, classroom teaching, and academic research. By comparing different cases, we will highlight the advantages of digital printing technology in improving teaching efficiency and promoting interdisciplinary integration. Additionally, the paper will focus on the potential impact of digital printing technology on higher education and student experiences. Through surveys and analysis of teachers' and students' perspectives, we will evaluate the potential effects of digital printing technology in enhancing student learning experiences, fostering innovative thinking, and promoting personalized education. This section will provide crucial information for university decision-makers regarding technological investments. Overall, through a comprehensive study of the application of digital printing technology in university teaching, this paper aims to gain a profound understanding of how this emerging technology fundamentally changes the patterns and experiences of higher education teaching, offering valuable insights for the future development of educational technology.
Viral Sequences Data Management Resources

The outbreak of the COVID-19 disease has presented novel challenges to the research community, which is rushing towards the delivery of results, pushed by the intent of rapidly mitigating the pandemic effects. During these times, we observe the production of an exorbitant amount of data, often associated with a poor quality of describing information, sometimes generated by insufficiently tested or not peer-reviewed efforts. But we also observe contradictions in published literature, as it is typical of a disease that is still in its infancy, and thus only partially understood.
Reform and Practice of Architectural Technology Courses in the Context of Digital Transformation of Architecture—Taking Architectural Physics as an Example

Under the general trend of digital change, "digital architecture" formed by the integration of digital technology and the construction industry is an important kernel for the upgrading and transformation of the construction industry. As important curriculum support for architecture majors, architectural technology courses need to rapidly adapt to digital change to meet the market and national strategic needs. The traditional technical courses are faced with the problems of string theory, weak informationization, short class time, and poor integration with engineering. Therefore, how to improve students' engineering application ability and digital technology under the condition of existing class time is the main purpose of this study. Digital technology is not only embodied in the teaching means, but also should be embodied in the teaching content. This study takes the course "Building Physics" as an example, and proposes a hybrid teaching method based on "SPOC + offline subject investigation mode", which is based on high-quality online resources, adding virtual simulation technology of actual engineering, and forming "engineering research" subject groups according to the interests and abilities of the students, through which the students can learn about the engineering application through the "engineering research" subject groups. "Students form engineering research groups according to their interests and abilities, internalize and extend their classroom knowledge in the form of "project research", and carry out the new "online + offline" learning mode, which provides teaching ideas for other technical courses.
Study on the Influencing Factors of Occupational Stress and Coping Methods of Railway Youth Police

To understand the influence factors of occupational pressure of young police officer in railroad public security, the young police officer of a railroad public security office were taken as the research object. The questionnaire survey method and interview method were used to conduct research on the occupational pressure problem of young police officer. The occupational pressure sources of young police officer were analyzed from the aspects of work, organization, interpersonal relationship, society, etc. The existing police coping experience of occupational pressure in foreign countries was referred to, and the public security organs of the police were enriched to reduce pressure means. The young police were scientifically organized and managed, in order to alleviate the occupational pressure of the young police, so that the young police could play their positive role in work and life in a better way.
Variance Matters: Detecting Semantic Differences without Corpus/Word Alignment

In this paper, we propose methods for discovering semantic differences in words appearing in two corpora. The key idea is to measure the coverage of meanings of a word in a corpus through the norm of its mean word vector, which is equivalent to examining a kind of variance of the word vector distribution. The proposed methods do not require alignments between words and/or corpora for comparison that previous methods do. All they require are to compute variance (or norms of mean word vectors) for each word type. Nevertheless, they rival the best-performing system in the SemEval-2020 Task 1. In addition, they are (i) robust for the skew in corpus sizes; (ii) capable of detecting semantic differences in infrequent words; and (iii) effective in pinpointing word instances that have a meaning missing in one of the two corpora under comparison. We show these advantages for historical corpora and also for native/non-native English corpora.
IOL Research Machine Translation Systems for WMT23 Low-Resource Indic Language Translation Shared Task

This paper describes the IOL Research team’s submission systems for the WMT23 low-resource Indic language translation shared task. We participated in 4 language pairs, including en-as, en-mz, en-kha, en-mn. We use transformer based neural network architecture to train our machine translation models. Overall, the core of our system is to improve the quality of low resource translation by utilizing monolingual data through pre-training and data augmentation. We first trained two denoising language models similar to T5 and BART using monolingual data, and then used parallel data to fine-tune the pretrained language models to obtain two multilingual machine translation models. The multilingual machine translation models can be used to translate English monolingual data into other multilingual data, forming multilingual parallel data as augmented data. We trained multiple translation models from scratch using augmented data and real parallel data to build the final submission systems by model ensemble. Experimental results show that our method greatly improves the BLEU scores for translation of these four language pairs.
The Path to Continuous Domain Adaptation Improvements by HW-TSC for the WMT23 Biomedical Translation Shared Task

Zhanglin Wu, Daimeng Wei, Zongyao Li, Zhengzhe Yu, Shaojun Li, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Yuhao Xie, Lizhi Lei, Hao Yang, Yanfei Jiang. Proceedings of the Eighth Conference on Machine Translation. 2023.
SentAlign: Accurate and Scalable Sentence Alignment

We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. Given user-defined parameters, the alignment algorithm evaluates all possible alignment paths in fairly large documents of thousands of sentences and uses a divide-and-conquer approach to align documents containing tens of thousands of sentences. The scoring function is based on LaBSE bilingual sentence representations. SentAlign outperforms five other sentence alignment tools when evaluated on two different evaluation sets, German-French and English-Icelandic, and on a downstream machine translation task.
Improving Transformer-based Program Repair Model through False Behavior Diagnosis

Research on automated program repairs using transformer-based models has recently gained considerable attention. The comprehension of the erroneous behavior of a model enables the identification of its inherent capacity and provides insights for improvement. However, the current landscape of research on program repair models lacks an investigation of their false behavior. Thus, we propose a methodology for diagnosing and treating the false behaviors of transformer-based program repair models. Specifically, we propose 1) a behavior vector that quantifies the behavior of the model when it generates an output, 2) a behavior discriminator (BeDisc) that identifies false behaviors, and 3) two methods for false behavior treatment. Through a large-scale experiment on 55,562 instances employing four datasets and three models, the BeDisc exhibited a balanced accuracy of 86.6% for false behavior classification. The first treatment, namely, early abortion, successfully eliminated 60.4% of false behavior while preserving 97.4% repair accuracy. Furthermore, the second treatment, namely, masked bypassing, resulted in an average improvement of 40.5% in the top-1 repair accuracy. These experimental results demonstrated the importance of investigating false behaviors in program repair models.