Reviewerly/exHarmony huggingface dataset:
ADVANCING MEDICAL EDUCATION THROUGH THE CINNAMON WEB APPLICATION

The cINnAMON EUREKA Traditional project endeavours to revolutionize indoor lighting positioning and monitoring through the integration of intelligent devices and advanced sensor technologies. This article presents the prototypes developed for various project components and explores their potential application in medical education, particularly for aspiring healthcare professionals. The current variant of the intelligent bulb prototype offers a comparative analysis of the project's bulb against commercially available smart bulbs, shedding light on its superior efficiency and capabilities. Furthermore, the initial smart bracelet prototype showcases its ability to collect and analyse data from an array of built-in sensors, empowering medical students to evaluate fragility levels based on accelerometer, gyroscope, orientation, and heart rate data. Leveraging trilateration and optimization algorithms, the intelligent location module enables precise monitoring of individuals' positions within a building, enhancing medical students' understanding of patient localization in healthcare settings. In addition, the recognition of human activity module harnesses data from the bracelet's sensors to classify different activities, providing medical students with invaluable insights into patients' daily routines and mobility patterns. The user's personal profile module facilitates seamless user registration and access to the comprehensive services offered by the cINnAMON system, empowering medical students to collect patient data for analysis and aiding doctors in making informed healthcare decisions. With the telemonitoring system, medical students can remotely monitor patients by configuring sensors in their homes, thus enabling a deeper understanding of remote patient management.
Development of Montik Media in the Environment I Live in for Class IV Student Learning Outcomes

The use of media in learning is an important aspect to support learning. There are many media that can be used in the learning system, especially in the elementary school environment. The media that can be used in the elementary school environment is to apply the MONTIK (Thematic Monopoly) media. Thematic Monopoly Media can be applied to elementary school students because the basis of student learning in elementary school is having fun while learning by using cards as a medium to convey material. The purpose of this study is to find out the making of thematic monopoly media and its application in integrated thematic learning for class IV at SDN Jogoloyo on the theme "My Living Environment". This research uses RnB research by prioritizing the development process in 5 stages, namely analysis, design, development, implementation, and evaluation. Data collection techniques in this study used 3 aspects, namely observation, interviews, and documentation. The results of the research conducted showed that thematic monopoly media for fourth grade students with the 8 sub-theme â€œMy Living Environmentâ€ theme at SDN Jogoloyo was an effective step in carrying out learning so that it could improve student learning outcomes in that class.
TRADISI GHATIB BEGHANYUT SEBUAH PERADABAN ISLAM PADA MASYARAKAT SIAK SRI INDRAPURA, RIAU

This paper is the result of research that aims to reveal the ghatib beghanyut tradition carried out by the people of Siak Sri Indrapura as the implementation of Islamic civilization. Siak Sri Indrapura as a Malay 'palace country' has a religious cultural heritage from the Siak Kingdom, which is still practiced today. The implementation of ghatib beghanyut is led by the ulama and is carried out jointly between the community and the leadership. This paper is an exploratory field research to get data about ghatib beranyut while this type of research is descriptive qualitative. The data collection technique was through observation, interviews and documentation, after which a content analysis was carried out. The results of the study found that ghatib beghanyut is a ritual tradition carried out by the people of Siak Sri Indrapura to reject the calamities that befell the community and the village. Rejecting reinforcements is done by means of remembrance and prayer on a boat while drifting without being rowed to follow the flow of the river by involving the community and state leaders. Dhikr and prayers are guided by local clerics. Ghatib beghanyut is the pronunciation of the Siak Sri Indrapura community which comes from the word 'ratib berhanyut'. The ghatib beghanyut tradition can be said to be the implementation of Islamic civilization which has fused with the people of Siak Sri Indrapura as a Malay country. Malay identical to Islam is a statement that is inherent and formed in its religious traditions and culture so that it becomes an important part in the development of sharia tourism promotion in Siak Regency where the implementation of this tradition involves umara, ulama and the community. The procession is full of remembrance and prayer to Allah SWT so that the people of Siak Sri Indrapura are always in a religious nuance that builds Islamic cultural behavior including always praying, believing in Allah's grace, trying to avoid disease, and strengthening brotherhood and unity.
ACTIVITIES OF COMPUTER SCIENCE TEACHERS IN THE PROCESS OF DEVELOPING MEDIA CULTURE AND MEDIA LITERACY IN UKRAINE AND ITS IMPLEMENTATION IN GENERAL SECONDARY EDUCATION INSTITUTIONS

The article studies the specifics of the computer science teacher’s activities regarding the formation of media culture of participants in the educational process in general secondary education institutions with the subsequent acquisition of information and digital competence and media literacy. The importance for all educators of the Concept of the introduction of media education in Ukraine, adopted in 2010, is substantiated, according to which today media culture should become a part of modern educational culture and a tool of mutually interested communicative interaction of all participants of the educational process involved in it in the general secondary education institutions. The stages of gradual rooting of media education in Ukraine and standardization of its content in conditions of external information aggression, media coverage of the events of the Russian-Ukrainian war are traced. It is emphasized that it is the media education, media literacy and media culture of the computer science teacher in the general secondary education institutions that will give him the opportunity to convey information at a high professional level, as well as to show the level of its perception. The importance of the spread of media culture and the introduction of media literacy in the general secondary education institutions by computer science teachers in lessons and thematic seminars with the help of information technologies (including web technologies) is emphasized. It is claimed that the activity of the computer science teacher, aimed at the formation of media culture, helps students and other participants of the educational process in the general secondary education institutions to avoid manipulation by the mass media; work with oppositely directed information; integrate media content; interpret the information received with the help of audio and video means; create your own media content (presentations, videos, multimedia blogs) and use it in social networks; and also apply media educational elements in their activities. It is shown that for the effective implementation of media education in the general secondary education institutions, computer science teacher should use various computer science methods, modern pedagogical tools, techniques, technologies (including information technologies in computer science), educational exercises and tasks. It is substantiated that the formation of knowledge about information and basic concepts of media literacy, skills of searching and systematizing media content, reflection and critical thinking during computer science lessons occurs in parallel with the assimilation of information technologies by students due to the application of media educational activities in the activities of the computer science teacher.
Upaya Meningkatkan Proses Dan Hasil Belajar IPA Melalui Model Problem Based Learning Kelas III Sekolah Dasar

This study began with the low student learning outcomes in class III caused by the learning process that is not optimal. This type of research is a classroom action research. This class action research includes the stages of planning, implementation, observation and reflection. The subjects of this study were students in grade III SDN No.152 / II Renah Jelmu with a total of 18 students. Data collection techniques used were tests and observation sheets. The research instruments used included the Learning Implementation Plan with the Problem Based Learning (PBL) model, test questions and observation sheets. The data analysis technique used is descriptive analysis while the research approach is quantitative. The research results obtained are as follows; (a) the teacher conducts learning interactively so that the learning process in cycle I runs well and increases in cycle II with very good criteria. (b) Students become active in the learning process, this is shown from the learning activities of students in the first cycle with good enough criteria and then increase in the second cycle with good criteria. (c) Problem Based Learning Model taught coherently will train students' understanding ability, this can be seen from the results of student learning that increased from cycle I only by 78% to 89% in cycle II with very good criteria.
A Study of Data Governance Methods Based on Non-Linear Evaluation of K-Domains

The current traditional data governance methods mainly ensure the overall quality of data through data quality inspection, and the lack of data fusion processing leads to poor data governance results. In this regard, a data governance method based on nonlinear evaluation of K domain is proposed. By formulating data cleaning rules, data are processed such as weight reduction, gap filling and deletion, and data fusion operations are performed according to the fusion table attributes by configuring fusion rules. Finally, the data consistency as well as wholeness is checked, and the actual effect of data governance is determined by the data quality score results. In the experiments, the proposed method is validated for the governance effect. The analysis of the experimental results shows that the proposed method takes significantly shorter time for data fusion and has better data governance performance when the proposed method is used to govern multiple sources of data.
Intelligent Association of CVE Vulnerabilities Based on Chain Reasoning

Vulnerability database data sources use semi-structured and unstructured data expression, which can provide convenience for researchers in vulnerability analysis and systematic study of vulnerability mechanism and vulnerability content. However, the traditional vulnerability database has some problems, such as weak correlation attribute, redundant data format and low visualization degree, which are difficult to be understood and analysed by machines. This paper proposes a CVE vulnerability intelligent association based on chain reasoning. By analysing the vulnerability description and the relationship between different vulnerability databases, investigating the software and systems affected by each vulnerability, linking relevant knowledge, inferring the hidden relationship of each vulnerability, building the relationship between the entity nodes of the vulnerability knowledge graph, and finally importing the data into the neo4j diagram database to build the vulnerability knowledge graph. By calculating the number of software associated with vulnerabilities, the CWE chain relationship is deduced, and the vulnerability knowledge graph constructed is used to conduct preliminary inference on the vulnerability scanning results, so as to obtain the hidden relationship between vulnerabilities and optimize the vulnerability scanning results.
Implementasi Manajemen Keuangan di SMA Labschool UNESA

Financial management is a science and art that discusses, examines, and analyzes how financial managers use all company resources to find, manage, and allocate funds. Financial management or commonly called learning can be explained as all company activities related to efforts to obtain company funds at low cost and use and allocate these funds efficiently. The purpose of the article is to describe how to implement financial management at Labschool Unesa High School. In this article the method used is qualitative by conducting interviews, observations and documentation studies. Labschool Unesa High Schoolhas good financial management by providing quality education to students for the success of the school in achieving its goals. In addition, this article also discusses financial management, how to overcome finances in urgent circumstances, budget plans, and so on related to this school.
Research on AGV path planning based on improved artificial bee colony algorithm

When a traditional Artificial Bee Colony (ABC) algorithm is used to study an Automated Guided Vehicle (AGV) path planning problem, the algorithm suffers from slow convergence and low search efficiency and easily falls into local optimal. These problems with using ABC algorithms are because of the shortage of them in the processing of adaptation degree information sharing. To address these problems, an Improved Artificial Bee Colony (IABC) algorithm was proposed. Firstly, chaotic mapping population initialization was introduced to accelerate the convergence of the algorithm while improving the algorithm’s ability at local exploitation and global exploration. Secondly, Euclidean distance was introduced into the search for the detection bee to determine the effective neighborhood and the optimal solution within the neighborhood selected to generate new honey sources. Finally, the IABC algorithm was used for AGV path planning. The simulation comparison experiments of AGV path planning based on ABC and IABC algorithms were conducted in a raster map, and the simulation results showed that the IABC algorithm had a faster convergence speed and better local search capability.
Noise-aware UAS flight path planning based on virtual flight simulation

This paper proposes a noise-aware flight path planning method to reduce the noise pollution caused by low-altitude flights of unmanned aerial systems (UAS) in urban areas. A noise assessment platform is used to obtain noise maps at discretized airspace blocks, considering sound reflection and absorption by obstacles, as well as diffraction and attenuation by the atmosphere. An improved cost-based A* algorithm is employed to search for the optimal path with the minimum sound exposure level. Virtual flight simulations demonstrate the effectiveness of the proposed method in reducing en-route noise exposure from flying drones. This cost-effective and efficient approach has the potential to benefit air traffic planning and management.
Modified CMIS Factors Predicting Chinese Women's Mental Health Information Seeking in Douyin

The popularity of Douyin (known as TikTok overseas) could provide additional mental health information services to Chinese women. However, the factors that influence women to seek mental health information services in Douyin are still understudied. The study applied the Comprehensive Model of Information Seeking (CMIS) to Chinese women's mental health information seeking behaviors on Douyin to examine this. The study used a questionnaire (N=505), and the data analysis was conducted using partial least squares structural equation modeling (PLS-SEM). SmartPLS 4.0 was the primary data analysis technology. Results showed that direct experience, beliefs, salience, and characteristics of mental health information could significantly affect the utility of mental health information on Douyin. In addition, utility, social support, and characteristics directly affect Chinese women's mental health information seeking. Moreover, utility partially mediates the relationship between direct experience, beliefs, salience, characteristics, and mental health information seeking. Rather than targeting specific diseases or pan-health information, this study demonstrates the possibility of applying CMIS to mental health information seeking. This insight could contribute to Douyin and government health interventions to better meet the mental health information needs of Chinese women.
Data-Driven Defenses Against Adversarial Attacks for Autonomous Vehicles

Deep Learning (DL) is a growing technological frontier supporting many autonomous driving applications. Past decade with the growth in deep learning concepts and models, we also witnessed a growth in cyber-security concerns related to these models. Adversarial attacks are well-known attacks on these models where slight noise/ perturbations are introduced with the input image, forcing the DL models to misclassify with high confidence. These are significant threats and concerns when using DL models for real-world autonomous vehicle applications. However, various defensive mechanisms have been suggested to improve the resiliency of these models. In this study, we worked on the LISA dataset and tested with four transfer learning models, EfficientNet, SqueezeNet, ResNet-18 and Inception-V3, with accuracies of 95%, 95%, 94% and 97%, respectively. Based on the severity of adversarial attacks, we selected three attacks, Fast Gradient Sign Method (FGSM), Basic Iterative Method (BIM) and Project Gradient Descent (PGD) attacks ranging from less intensive to highly intensive adversarial attacks. When subjected to FGSM, BIM, and PGD attacks, we discovered that the model performance for EfficientNet decreased to 92%, 38%, and 50%, that for SqueezeNet decreased to 87%, 53%, and 59%, that for ResNet-18 decreased to 95%, 53%, and 49%, and that for Inception-V3decreased to 93%, 45%, and 56%. respectively. The combination of Total Variance Minimization and Spatial Smoothing was determined to be the most effective defensive method combination to increase performance during adversarial attacks. Despite only slight improvements in the performance of FGSM attacks, all models significantly outperformed during BIM and PGD attacks, with performance accuracy of 83% and higher.
A continuous state transition algorithm with guaranteed optimality

As a constructivism-based intelligent optimization method, the state transition algorithm (STA) has exhibited powerful search ability in optimization. However, in basic STA, it usually sets the maximum number of iterations or function evaluations as the termination condition by experience. If the termination condition is not set well, it may stop at an unpredictable point. In this study, a continuous STA with guaranteed optimality is proposed by altering the termination conditions of the basic STA, without using the maximum number of iterations or function evaluations. It is proved that the modified STA can find a final solution with guaranteed optimality. Experimental results have testified the findings.
A Field Study on Polish Customers’ Attitude Towards a Service Robot in a Cafe

More and more stores in Poland are adopting robots as customer assistants or promotional tools. However, customer attitudes to such novelty remain unexplored. This study focused on the role of social robots in self-service cafes. This domain has not been explored in Poland before, and there is not much research in other countries as well. We conducted a field study in two cafes with a teleoperated robot Nao, which sat next to the counter serving as an assistant to a human barista. We observed customer behavior, conducted semi-structured interviews and questionnaires with the customers. The results show that Polish customers are neutral and insecure about robots. However, they do not exhibit a total dislike of these technologies. We considered three stages of the interaction and identified features of each stage that need to be designed carefully to yield user satisfaction.
PI NETWORK : A REVOLUTION

Pi Network is a cryptocurrency project that stands out for its innovative approach to mining and accessibility. Launched in 2019, the platform allows users to mine its native digital currency, Pi, directly from their mobile devices, aiming to democratize the mining process and make cryptocurrency participation more inclusive. Notably, Pi Network utilizes the Stellar Consensus Protocol for its blockchain, emphasizing a balance between security, decentralization, and transaction speed. Positioned in its early development stages, Pi Network places a strong emphasis on community engagement, encouraging users to actively participate and contribute to the project. It is essential for users and enthusiasts to stay informed about updates and changes in the Pi Network ecosystem, as the cryptocurrency space is dynamic and subject to evolution. Additionally, users should consider the regulatory landscape and associated risks inherent in participating in a cryptocurrency project during its early stages.
Advanced Metering Infrastructure Data Aggregation Scheme Based on Blockchain

Smart grid stands as both the cornerstone of the modern energy system and the pivotal technology for addressing energy-related challenges. Advanced Metering Infrastructure constitute a critical component within the smart grid ecosystem, providing real-time energy consumption data to power utility companies. Advanced Metering Infrastructure enables these companies to make timely and accurate decisions. Hence, the issue of data security pertaining to Advanced Metering Infrastructure assumes profound significance. Presently, Advanced Metering Infrastructure data confronts challenges associated with centralized data storage, rendering it susceptible to potential cyberattacks. Moreover, with the burgeoning number of electricity consumers, the resultant data volumes have swelled considerably. Consequently, the transmission of this data becomes intricate and its efficiency is compromised. To address these issues, this paper presents a lightweight blockchain data aggregation scheme. By integrating fog computing and cloud computing, a three-tier blockchain-based architecture is devised. Initially, digital signatures are employed to ensure the validity and integrity of user data. The innate attributes of blockchain technology are harnessed to safeguard the security of electricity energy data. Through secondary data aggregation, the privacy-sensitive user data is efficiently compressed and subsequently integrated into the blockchain, thereby mitigating the storage pressure on the blockchain and enhancing data transmission efficiency. Ultimately, through rigorous theoretical analysis and simulated experimentation, the paper demonstrates that, in comparison to existing methodologies, lightweight blockchain data aggregation scheme exhibits heightened security. Additionally, lightweight blockchain data aggregation scheme holds a competitive advantage in terms of computational and communication costs.
Unsupervised Deep-Learning Approach for Underwater Image Enhancement

Underwater images often contain color casting and blurriness which reduce the quality. State-of-the-art shows different deep-learning models to handle these degradations. However, they required ground truth to train, which is impossible to acquire when studying underwater images. We present an unsupervised deep-learning approach for underwater image enhancement based on the mathematical model of a hazy image. This allows us to train networks without the need for a reference image. We use three networks to estimate the transmission map, the atmospheric light, and the enhanced image and propose a compound loss function to train our approach accurately. We achieve state-of-the-art results in the structural similarity index (SSIM) while performing optimally nearly real-time inference speeds.