Reviewerly/exHarmony huggingface dataset:
TINGKAT KETERBACAAN BUKU TEKS BAHASA INDONESIA KURIKULUM MERDEKA UNTUK KELAS X SMA/SMK

The ever-changing curriculum means that teaching materials, mainly textbooks, also continue to change. This change is not offset by the quality of textbooks discourse, which still not be appropriate to the students' readability level. This is shown in various studies that have been carried out, including by Yazidi et al. (2017), Saroni et al. (2017), Ginanjar (2020), and Susanti (2021), which resulted in the finding that the readability level of textbooks still does not match the students' readability level. This study aims to describe the readability of the Merdeka Curriculum Indonesian Language Textbook for Class X SMA/SMK entitled Intelligent Smart in Indonesian Language and Literature for Class X SMA/SMK. The method used in this study is a qualitative descriptive method-readability measurement formula using Fry Graph. The number of inner texts calculated using the Fry Graph is 23 texts. Based on the study result, 3 texts matched the legibility level of class X students, and 20 texts id not match the readability level of class X students. Twenty texts that did not match the readability level of class X students consisted of 1 text with a readability level that was too high/difficult, 17 texts with a readability level that was too low/easy, and 2 texts that did not match any readability level/invalid. Calculation of the readability level using the Fry Graph in the Indonesian Merdeka Curriculum Textbook for Class X SMA/SMK shows that the readability level of the Indonesian Merdeka Curriculum Textbook for Class X SMA/SMK entitled Smart Smart in Indonesian Language and Literature for Class X SMA/SMK is still not following the readability level of class X students.
Aplikasi Pemodelan 3 Dimensi Router Mikrotik RB433AH. RB450, RB800, RB951G-2HnD dan Haplite Berbasis Augmented Reality dan Firebase

MikroTik is a company engaged in internet service providers and internet service connectors from wireless internet service providers, a lot of use and utilization of MikroTik products. MikroTik products for example are RB433AH Router Board and RB951g-2hnd. This RB433AH Router Board and RB951g-2HnD are used by Kediri Polytechnic students as learning media for subjects related to Computer Networks, while RB450, RB800 and hAP lite are used for Access Points. However, there is a problem when the system reset function on the application is not successfully executed so it must reset by hardware reset on the Router Board. The method of operation of devices connected to the Router Board such as LAN cables, antennas, LAN Cards and PCIE for the first time is used for laymen who still do not understand, so a solution is needed to inform the user how to operate the RB433AH and RB951G-2HND routers. Therefore, an application is prepared that can scan images and then display the 3-dimensional model of the Router in Augmented Reality to help the operation of the RB433AH Router Board and RB951G-2HND and present the comments section for problem solving. Applications are presented in mobile devices by utilizing Vuforia Augmented Reality and Realtime Databases from Firebase.
Evaluating dehazing techniques on artificial and satellite land surface images

Many image-based recognition tasks are highly susceptible to different types of natural phenomena like foggy weather, snow, or rain. The participating media will likely obscure important details necessary for these algorithms to work correctly. Still, these aspects could be recovered in certain situations with prior information about the underlying light interactions. This could be done with certain heuristics or with the nowadays popular deep-learning based methods. In this paper, we review and compare the results of two approaches to remove or scale down the effects of foggy weather. We also examine how these results can be applied to high resolution satellite images of land surfaces.
3DL-PS: an image encryption technique using 3D logistic map, hashing functions and pixel scrambling techniques

This paper presents an efficient image encryption scheme that uses a 3D logistic map, SHA-512, and pixel scrambling techniques. Firstly, two secret keys are generated using two different user-provided keys and the input image. Image pixels are altered using the values obtained upon the iteration of the 3D logistic map to increase the complexity of the algorithm. Further, different fragments of various sizes are swapped depending on the secret keys. Finally, a jumbling technique mixes the pixels horizontally and vertically in a completely dynamic way using secret keys. The keyspace of the algorithm is large enough to resist brute force attacks. The encrypted image has been analysed against classical attacks such as chosen-plaintext, chosen-ciphertext, known-ciphertext, known-plaintext, and statistical attacks. Key sensitivity analysis and noise resistance analysis have also been performed. The results prove that the algorithm is resistant to several renowned attacks, enabling usage in various real-time applications.
Language communication functions

The communicative function contributes to the formation of three aspects that make up the nature of language (the ideological tool; the signic nature of language). These three aspects are intimately linked and inseparable on the common basis of the social nature of language. To understand the social nature of language, it is first necessary to understand the functions of language. Starting from the above statement, we choose to learn the communication function of the language as an object to gradually approach other functions of the language and the ultimate goal is to understand the nature of the language.
A Kalman Filter based Low Complexity Throughput Prediction Algorithm for 5G Cellular Networks

Throughput Prediction is one of the primary preconditions for the uninterrupted operation of several network-aware mobile applications, namely video streaming. Recent works have advocated using Machine Learning (ML) and Deep Learning (DL) for cellular network throughput prediction. In contrast, this work has proposed a low computationally complex simple solution which models the future throughput as a multiple linear regression of several present network parameters and present throughput. It then feeds the variance of prediction error and measurement error, which is inherent in any measurement setup but unaccounted for in existing works, to a Kalman filter-based prediction-correction approach to obtain the optimal estimates of the future throughput. Extensive experiments across seven publicly available 5G throughput datasets for different prediction window lengths have shown that the proposed method outperforms the baseline ML and DL algorithms by delivering more accurate results within a shorter timeframe for inferencing and retraining. Furthermore, in comparison to its ML and DL counterparts, the proposed throughput prediction method is also found to deliver higher QoE to both streaming and live video users when used in conjunction with popular Model Predictive Control (MPC) based adaptive bitrate streaming algorithms.
Student-Led Mentoring System Designed to Lower Barriers for Graduate School Applicants

Ocean and Earth science graduate school admissions processes can be bewildering. Unwritten expectations and small professional circles, compounded by oceanography’s history of colonialism, sexism, and racism, advantage those privileged enough to navigate as insiders. Thus, even more holistic graduate admissions processes may be inequitable. Here, we share (1) a model for effective peer-to-peer support, Applicant Support &amp; Knowledgebase (ASK), and (2) insights into challenges faced by under-supported applicants. We aim to generate a discussion about the bias in and inaccessibility of the US-based ocean science graduate school entry process and how peer-to-peer programs like ASK can contribute to a tapestry of solutions that address these inequities.
Yoga Pose Detection for Human Rehabilitation Using Deep Leaning

Abstract: Yoga is an ancient science and discipline originated in India 5000 years ago. It is used to bring harmony to both body and mind with the help of asana, meditation and various other breathing techniques It bring peace to the mind. Due to increase of stress in the modern lifestyle, yoga has become popular throughout the world. There are various ways through which one can learn yoga. Yoga can be learnt by attending classes at a yoga centre or through home tutoring. It can also be self-learnt with the help of books and videos. Most people prefer self-learning but it is hard for them to find incorrect parts of their yoga poses by themselves. idea behind this yoga pose detection project using deep learning or neural network learning is that yoga popularity is increasing day by day because of its benefits. Doing yoga helps us physically, mentally as well as spiritually. Because of this many people nowadays are doing it regularly. The main idea of this project is to help the people to recognize which yoga pose they are doing with the help of this detection technique. Yoga which involves 8 rungs and limbs of it, which includes Yama, Niyama, Asana, Pranayama, Dharana, Dhyana and Samadhi. To easily help people understand which pose they are performing via images, video recording by classifying it, we are implementing this project because of this people will incline towards doing more as they will get help to identify which pose they are doing very easily.
TOTP Generator App

Abstract: A Time-based One-Time Password (TOTP) validator is interposed between a principal and a network service. The validator interacts with a mobile application (app) on the mobile device associated with the principal to` dynamically supply a validator secret. The secret and, perhaps, other information are processed by the app to generate a TOTP when the principal attempts to access a protected resource of the network service. The validator independently generates the TOTP and compares the app generated TOTP, and on a successful match, a principal's access device is redirected for access to the protected resource.
Main problems that threaten the teaching-learning process

The problems that threaten the teaching-learning process are diverse, however they are not always adequately recognized in the educational environment nor addressed. Thus, the objective of this study is to reflect on the main problems that threaten the teaching-learning process in basic general education. For this purpose, a systematic review investigation is carried out in Scopus, Science Direct, Scielo and EBSCO databases on the topic, considering the last 5 years of publication, obtaining 43 reviews of which 14 met the parameters for inclusion in the study. The results show an important approach to social problems associated with education due to its impact on it, such as migratory conflicts, family violence, school violence, sexual violence, street situations, substance and alcohol abuse, depression, as well as derived from inadequate intercultural processes, impact of social networks or poor quality of education. The problems that threaten the teaching-learning process are diverse, however they are not always adequately recognized in the educational environment nor addressed. Thus, the objective of this study is to reflect on the main problems that threaten the teaching-learning process in basic general education. For this purpose, a systematic review investigation is carried out in Scopus, Science Direct, Scielo and EBSCO databases on the topic, considering the last 5 years of publication, obtaining 43 reviews of which 14 met the parameters for inclusion in the study. The results show an important approach to social problems associated with education due to its impact on it, such as migratory conflicts, family violence, school violence, sexual violence, street situations, substance and alcohol abuse, depression, as well as derived from inadequate intercultural processes, impact of social networks or poor quality of education.
DESIGNING INFORMATION SYSTEM BASED ON WEBSITE FOR KLINIK PRATAMA AT POLITEKNIK PENERBANGAN SURABAYA

A clinic is a small public healthcare facility established to provide care to outpatients. Klinik Pratama is a clinic that operates in the field of community health services. Located in Jemur Andayani, Siwalankerto Subdistrict, Klinik Pratama has been conducting its business processes effectively. However, there is a minor deficiency, which is the lack of a website that encompasses information about the clinic, including its profile, services, clinic promotions, and facilities. With this website, it is hoped to instill confidence in patients and encourage them to use the services provided by Klinik Pratama. Patients can learn about the clinic's profile, services offered, the latest news about the clinic, and the available facilities at Klinik Pratama. This endeavor is closely related to the increasing use of technology in supporting daily human activities. The research method for this website design involves the waterfall method and testing using the black box method. The waterfall method comprises five stages: Requirement, Design, Implementation, Testing, and Conclusion. By utilizing the waterfall method and black box testing technique, researchers can easily make improvements if there are errors or bugs in the coding. The results of identifying the requirements are still in abstract form, so they need to be refined and designed into a list of functional requirements that can then be visualized into a use case diagram. Based on the design of functional requirements, the author outlines scenarios for each function, resulting in a flow that can be implemented into program code.
The Mediating Effects of Country of Origin on the Relationship between Hate and Purchase Avoidance Intention

Despite general acceptance of the critical effects of hate toward a specific nation on customer response in the global market, the mechanisms underlying such effects have not been sufficiently confirmed. To fill this gap, this research considers three sub-components of hate, namely, historical hate, economic hate, and social hate, and tests the structural relationship among hate, country of origin (COO), purchase avoidance intention. Using survey data from 256 Koraen consumers recognizing Japan, we find that three sub-components of hate play different roles in the ‘hate→country of origin→purchase avoidance intention’. In particular, the COO does not mediate the historical hate-purchase avoidance intention. And the COO partially mediates the historical hate-purchase avoidance intention. In contrast, the COO fully mediates the social hate-purchase avoidance intention. Finally, this research also discusses the managerial and research implications.
METHOD OF CREATING AN INFORMATION SYSTEM FOR MONITORING INFECTIOUS PATIENTS

In the context of the COVID-19 pandemic, infectious disease information systems are widely used and promoted to prevent the spread of the pandemic (mainly in the form of mobile applications). Many countries have offered their apps to improve contact tracing and thus reduce the number of infections. However, the level of adoption of such applications has been and remains relatively low, which, obviously, given their massive use and effectiveness, has been largely influenced by issues related to privacy and anonymity, as well as the perception of potential users of the price-benefit ratio. Thus, the task of creating information systems for monitoring infectious patients is still relevant today. Therefore, our study is devoted to the development of a method and an information system for monitoring infectious patients.&#x0D; The article develops a method for creating an information system for monitoring infectious patients, which, unlike the known ones, is based on intelligent analysis of data on the geolocation of patients and contact persons, and provides the ability to design an information system for controlling infectious patients. The purpose of the information system for monitoring infectious patients is to prevent the spread of epidemics and pandemics by tracking patient contacts and reducing the number of infections. The tasks of the information system for monitoring infectious patients are to track the self-isolation of infectious patients and their contacts, identify the most "infected" buildings, districts, cities, etc. based on intelligent analysis of data on infectious patients and their contacts.&#x0D; The designed mobile-oriented information system for monitoring infectious patients can be used to prevent the spread of the pandemic by tracking contacts and reducing the number of infections. The design of screen forms, reports, implementation, testing and commissioning of the information system for monitoring infectious patients will be carried out by the authors in the course of their further research.
Reduce Anxiety about Public Speaking through Group Guidance Using Symbolic Modeling Techniques

The research was based on the results of interviews in the pre-study. It was found that there were still students who had anxiety in public speaking in class VI SD Negeri 1 Sajira, Lebak Regency, in the 2021/2022 academic year. This study aimed to determine the effectiveness of group guidance with symbolic modeling techniques to reduce public speaking anxiety. This study uses a pre-experimental research design with One Group Pre-test-Post-test Design. Determination of the sample using the purposive sampling method. The research subjects comprised six students with a high public speaking anxiety category and two students with low public speaking anxiety. The method of data collection in the study was obtained through a questionnaire. Research results showed an average of 115. On the pre-test, with a percentage of 93%, while 51 with a percentage of 73% in the post-test. Grade VI students of SD Negeri 1 Sajira, Lebak Regency, for the 2021/2022 academic year. For future researchers, this research can be developed using different techniques to obtain better results. Furthermore, future researchers are expected to be able to enrich the literature review on public speaking anxiety by developing the approach applied.
Practical, high-speed Gaussian coherent state continuous variable quantum key distribution with real-time parameter monitoring, optimised slicing, and post-processed key distillation

Abstract Gaussian coherent state continuous variable quantum key distribution has gained interest owing to its security and compatibility with classical coherent optical fibre networks. For successful system deployment it is necessary to implement practical high speed systems which distil keys efficiently. Here, we demonstrate a Gaussian coherent state continuous variable quantum key distribution system at a 50 MHz symbol rate. Unlike most demonstrations to date which measure excess noise and infer key rates from this, we record signals in real time and distil keys. We also demonstrate, for the first time, slice reconciliation with optimised guard bands to maximise achievable secret key rates. Using this optimisation with multilevel slicing, a record 5 Mb/s secret key rate after a transmission distance of 25 km is achieved. This is a significant improvement on the 3 Mb/s secret key rate which is achieved with single level optimised slice reconciliation.
Beyond Legal Frameworks and Security Controls For Accessing Confidential Survey Data: Engaging Data Users in Data Protection

With growing demand for data reuse and open data within the scientific ecosystem, protecting the confidentialy of survey data and privacy of data subjects is increasingly important. Doing so requires more than legal procedures and technological controls; it requires social and behavioral intervention. In this research note, we delineate the disclosure risks of various types of survey data (e.g., longitudinal data, social network data, sensitive information, biomarkers, and geographic data), the current motivation for data reuse, and challenges to data protection. Despite rigorous efforts to protect data, there are still threats to protection of confidentiality in microdata. Unintentional data breaches, protocol violations, and data misuse are observed even in well-established restricted data access systems, indicating that the systems may all rely heavily on trust. Creating and maintaining that trust is critical to secure data access. We suggest four ways of building trust; User-Centered Design Practices; Promoting Trust for Protecting Confidential Data; General Training in Research Ethics; and Specific Training in Data Security Protocols, with an example of a new project 'Researcher Passport' by the Inter-university Consortium for Political and Social Research. Continuous user-focused improvements in restricted data access systems are necessary so that we promote a culture of trust among the research and data user community, train both in the general topic of responsible research and in the specific requirements of these systems, and offer systematic and holistic solutions.
Go-Game Image Recognition Based on Improved Pix2pix

Go is a game that can be won or lost based on the number of intersections surrounded by black or white pieces. The traditional method is a manual counting method, which is time-consuming and error-prone. In addition, the generalization of the current Go-image-recognition methods is poor, and accuracy needs to be further improved. To solve these problems, a Go-game image recognition based on an improved pix2pix was proposed. Firstly, a channel-coordinate mixed-attention (CCMA) mechanism was designed by combining channel attention and coordinate attention effectively; therefore, the model could learn the target feature information. Secondly, in order to obtain the long-distance contextual information, a deep dilated-convolution (DDC) module was proposed, which densely linked the dilated convolution with different dilated rates. The experimental results showed that compared with other existing Go-image-recognition methods, such as DenseNet, VGG-16, and Yolo v5, the proposed method could effectively improve the generalization ability and accuracy of a Go-image-recognition model, and the average accuracy rate was over 99.99%.
Managing Requirements

In this chapter, you will learn why you need to manage your requirements, learn how requirements have been managed over time, learn what types of tools you can consider to control your requirements, and finally discover what data elements associated with your requirements you will need to capture with your shall statements.
Action Behavior Learning Based on a New Multi-Scale Interactive Perception Network

Action recognition is a fundamental research topic in the field of video understanding, but classical action recognition relies on a large amount of manually annotated video data, which limits its development. Small sample action recognition is a promising topic that can overcome the dependence on large-scale annotated data. However, the current small sample action recognition has a series of shortcomings such as temporal singularity and a lack of perception of global information. Therefore, this work proposes an interactive perception network by designing a multi-scale temporal feature extraction module to capture global temporal dependencies between all frames and local temporal information between frames. Then the algorithm proposes a cross scale matching strategy to achieve robust matching between videos with different motion speeds, maximizing the consistency between local and global features of the same type of action. Finally, the experimental results on the SSV2 dataset and the HMDB51 dataset show that the proposed method outperforms the current mainstream methods. Compared with the backbone network, which is the most advanced method of ResNet, this method achieved performance improvements of 0.8% and 0.4% on HMDB51 and SSV2, respectively.