Reviewerly/exHarmony huggingface dataset:
The integration between the Internet of Things and Artificial Intelligence

The digitalization of the world today is advancing. In this time period, people started to get interested in emerging developments like AI, ML, IoT, and data analytics.Individuals are attempting to use machines and other methods to make their work easier. Another idea that was founded on the aforementioned developments is the autonomous concept. IoT and AI were widely used in the business, agricultural, and health care sectors. Therefore, Applications that link AI and IoT are becoming increasingly popular these days. Many sectors also switch from non-automated to IoT-driven solutions that are additional accurate and Controllable than previously.Due to AIs inclusion in those systems, their level of dependability is likewise very high. As a result, humans do not need to focus on numerous jobs because the system is taken care of by IoT platforms driven by AI.IoT will continue to face several severe problems, such as security risks and ethical dilemmas. IoT with AI may seem exciting, but what matters most is how the general public views it—whether they see it as a benefit, a burden, or a threat.
CHRONOS Project: The Transformation of Time-dependent Clinical Trajectories into Intelligent Ones Using an Innovative Technological Solution

Introduction: The health system faces many challenges including the lack of personnel or resources and the overcrowding of emergency rooms. In this context, Real Time Locating Systems (RTLS) offer the possibility of improving the efficiency, safety and quality of care management. Clinical trajectories are currently very dependent on manual processes. We believe that real-time management systems that use geolocation can optimize time-dependent clinical trajectories, improve critical care and transform the health network for patients, caregivers and managers. Typically, RTLS tools require a significant investment in terms of installation, configuration, and integration. Method: The Nano Data Center (NDC) system developed by Humanitas Solutions is equipped with an advanced and low-cost IT infrastructure. It is self-deploying, self-configurable and allows geolocation and autonomous telecommunication with multiple interfaces (WIFI, Bluetooth, electrical). It requires a power source and operates without requiring access to technological infrastructures, which is the major difference with similar products based mainly on cloud computing and dependent on internet connectivity. We tested, as a pilot project, the deployment of the NDC system in a complex hospital environment ( Centre intégré de la santé et des services sociaux de la Montérégie-Centre, Quebec, Canada ) in order to demonstrate its potential use. Results: Using the NDC system, we were successful in establishing an autonomous communication network over several hospital floors. This innovation made it possible to support the real-time geolocalization of fictive patients and the creation of a real-time dashboard for monitoring clinical trajectories, analyzing data, and evaluating performance. Conclusion: The next development phases of the CHRONOS project include real-time notification and transformation of clinical trajectories into smart trajectories. The independence of the NDC system in terms of infrastructures would allow its deployment in low-resource environments, such as temporary installations or remote areas. Thus, its potential benefit in creating connected environments in disaster situations.
METHODICAL USE OF PROVERBS IN THE RUSSIAN LANGUAGE BY FUTURE SCIENCE TEACHERS

Improving the content of the processes of increasing the level of methodological training of future informatics teachers, realizing innovative methods of information search, processing and use, their adaptation and interpretation for the recipient of information, the development of science and changing social practice to revise one's point of view, to choose innovative forms and methods of work.
Lowering Cost of Photovoltaic Systems Using Forecast Dependent Design, Monitoring and Management Methodology

The target of current work is to cut off the cost of solar energy systems by using weather forecasting to predict energy production and implementing energy management measures to optimize the use of energy and reduce the need for energy storage.For standalone systems, this can include reducing the number of PV panels and battery banks, while still ensuring that there is enough energy to meet user needs.The energy management system you describe monitors the power level of the storage elements and adaptively controls switching to minimize the number of panels and battery banks needed.For grid-connected systems, the goal is to calculate the energy produced by the system and use that information to arrive at a zero-balance bill, considering the user's daily and nighttime energy consumption.The proposed energy management procedures are designed to reduce costs by optimizing the use of energy.the percentage of cost reduction has been determined for both types of systems.
Enterprise Architecture Modelling for PBO: A Case Study

The project management (PM) practices that characterize Project-Based Organizations (PBOs) are part of their core business processes.Moreover, some PBOs obtain their incomings by developing and delivering projects, such as construction companies.PBO's design and analysis have been developed from an organizational design perspective applying several frameworks such as Galbraiths' Star Model or McKinseys' 7S.For the same purpose, the systems thinking approach is also a suitable alternative for managing organizational complexity and computer-assisted business design and analysis.Within this perspective, the Enterprise Architecture (EA) managing tool has been widely applied in the information systems industry and, over time, has extended to other industries.EA is a group of principles, methods and models for designing and analyzing the enterprises' organizational structure, business processes, information systems and infrastructure.The use of EA as a management tool has the advantage of graphically showing the interrelationships between different components of an organization.Systems thinking has positioned itself as a suitable perspective for organizing PM knowledge, as shown in the last version of PMBOK (seventh).Following this trend, this research develops an EA model of a PBO and shows how the EA components can represent the specific PM artefacts displayed in a PBO.The obtained model and its completeness is evaluated using the Star Model framework.This work is expected to encourage analysts and project managers to opt for EA as a management and governance tool for their projects and the organizations that host them.
Deep Learning with OBH for Real-Time Rotation-Invariant Signs Detection

Numerous studies are being undertaken to provide answers for sign language recognition and classification. Deep learning-based models have higher accuracy (90%-98%); however, require more runtime memory and processing in terms of both computational power and execution time (1 hour 20 minutes) for feature extraction and training images. Besides, deep learning models are not entirely insensitive to translation, rotation, and scaling; unless the training data includes rotated, translated, or scaled signs. However, Orientation-Based Hashcode (OBH) completes gesture recognition in a significantly shorter length of time (5 minutes) and with reasonable accuracy (80%-85%). In addition, OBH is not affected by translation, rotation, scaling, or occlusion. As a result, a new intermediary model is developed to detect sign language and perform classification with a reasonable processing time (6 minutes) like OBH while providing attractive accuracy (90%-96%) and invariance qualities. This paper presents a coupled and completely networked autonomous system comprised of OBH and Gabor features with machine learning models. The proposed model is evaluated with 576 sign alphabet images (RGB and Depth) from 24 distinct categories, and the results are compared to those obtained using traditional machine learning methodologies. The proposed methodology is 95.8% accurate against a randomly selected test dataset and 93.85% accurate after 9-fold validation.
THE USE OF PSRA AND QAR STRATEGIES TO IMPROVE TENTH GRADE STUDENTS' READING COMPREHENSION

The study's objectives were to determine whether or not there was any significant achievement on students' reading comprehension between students taught by PSRA Strategy, (2) whether or not there was any significant achievement on students' reading comprehension taught by QAR Strategy, and (3) whether or not there was any significant difference in students' reading comprehension achievement between students taught by PSRA Strategy and QA Strategy. The study's population consisted of all tenth grade students at SMAN 4 Kota Jambi during the academic year 2021/2022. The samples were collected by two classes, each with 32 students. This study used a quasi-experimental design with two groups of students. Cluster Sampling was used as a sampling technique. For In order to collect data, the test was given twice, once before and once after. The findings revealed that both the PSRA strategy and the QAR strategy had a significant impact on students' reading achievement in each class. Based on the data, it was discovered that the students' mean post-test score in the experimental group who were taught using the PSRA Strategy was 84.63 and the students' mean post-test score in the control group who were taught using the QAR Strategy was 79.70. However, based on the independent sample t-test analysis, the t-obtained (3.216) was found to be greater than the t-table (1.671), indicating that the null Hypothesis (Ho) was rejected and the alternative Hypothesis (Ha) was accepted. It indicates that there was a significant difference in students' reading comprehension achievement between those taught using the PSRA Strategy and those taught using the QAR Strategy. Furthermore, the students' score achievement when using the PSRA strategy is greater than the students' score achievement when using the QAR strategy. Finally, the PSRA strategy is more significant than the QAR strategy.
TEACHERSâ€™ STRATEGIES IN TEACHING ENGLISH FOR YOUNG LEARNERS

In this globalization era, people have to communicate globally. English plays a very important role especially in international communication. It is used in various activities like education, business, politics and technology. Consequently, it is taught in Indonesia to provide supplementary knowledge for communication. The importance of learning English cannot be ignored, it is the greatest common language spoken all over the world. In addition, learning English is very important to increase knowledge and language ability. In Indonesia, English has been introduced at kindergarten school, as the development of the world globalization that demand English skill for all people from different nation in the world. Every school has learned English, there is no need to fear but urgent need for wise adaptation and negotiation so that English becomes a powerful tool for gaining tremendous and unlimited knowledge for all kinds of subjects learned at school. Teaching English to young learners is not as easy as imagined, the teachers is not only help the students to get knowledge, competences and morality, but also have to prepare everythingâ€™s need. The teachers have to use many strategies in teaching such as applying various strategies, media and game in order to keep studentsâ€™ interest in learning English. In this research, quantitative research was used that aim to find out teachersâ€™ strategies in teaching English to young learners. The population was all of the teachers at one of kindergartens in Palembang, and the sample was selected through simple random sampling technique. In collecting the data, interview and questionnaire were used, and then the data was analyzed through descriptive method in this research. Based on the result of the research, it was found that there were three teaching and learning strategies used by the teachers in teaching English for young learners
Understanding the Challenges of Tackling Cybercrime Activities in the Era of 5G Technology

Context: Deployment of 5G wireless technology has taken place in some developed and developing countries. The technology is expected to provide faster speed, greater reliability, low latency, in addition to opening up a new sphere of possibilities such as connected vehicles and devices. However, despite the expectation of improvements promised in the 5G era when compared to previous mobile wireless technologies such as 4G and 3G, there is a growing concern within the ICT industry that there are a number of security issues, particularly cybercrime attacks that may likely become rampant due to the power of the 5G technology. ICT experts agrees that 5G technology will result in massive data transactions due to the ultra-high speed, low latency and extra capacity provided by these networks. Therefore, there is the need to ensure that data and transactions are secured in such a way that personal information is not hacked, data privacy is preserved, and systems do not crash. Objective: The objective of this study is to analyze the critical challenges in combating cybercrime activities in the era of 5G technology. The paper will look at the security issues in the 4G networks and then compare it with the upcoming technologies expected in the 5G era. Method: The paper uses secondary data that was obtained by reviewing relevant articles written by various scholars on the topics of 5G technology, 4G technology, cybercrime activities in the era of 4G, how cybercrime will be tackled in the era of 5G technology, as well as evolution of mobile generation technologies from 1G to 5G. Results: The study highlighted a better understanding of cyber security threats, attacks, vulnerability in the 4G technology era and suggested a number of ways to deal with them and help to implement a secure information platform in the era of the technology.
PHILOSOPHICAL ANALYSIS OF INNOVATIVE AND CREATIVE FACTORS OF HUMAN CONSCIOUSNESS

Objective. The objective of the article is to identify the problems of innovative and creative human activity in the field of consciousness as structural elements of transformative activity in order to improve and deepen the understanding of the creative process as such. Methods. The following methods are used to study the innovative and creative factors of human consciousness: natural-ontological and socio-ontological to analyze the peculiarities of the formation and development of consciousness, axiological — while assessing the importance of creativity and innovation as characteristics for the individual, moral and ethical methods in studying the consequences of creative and innovative process for humanity in general, as well as a constructive and destructive approaches to the interpretation of the welfare state. The scientific principles of the research are the principle of objectivity (in analyzing the results of the creative process and physiological features of consciousness), determinism (used to study the forms of manifestation of activity of consciousness), systematicity (general presentation of the material is based on a holistic perception of creativity in the system of individual, physiological, social and cultural norms). Results. The studied consciousness and spheres of social consciousness show that creativity is a necessary component of human consciousness. It appears in the mythological, religious and spiritual components. The innovative is a source of understanding the creative, it reveals the essential components of creation as such. Consciousness is a litmus test of various questions that do not have an unambiguous answer, manifesting itself as both the source and the result of solving these questions. The creative component of consciousness generates different types of reality, due to modern advances in science. Innovative and creative factors of human consciousness are due to psychological, anatomical and social factors. Creativity is understood as a characteristic creative activity of consciousness, a transformative force.
NON-CONVEX HYBRID TOTAL VARIATION FOR RESTORING MEDICAL IMAGE CORRUPTED BY POISSON NOISE

Abstract. In this work, we proposed the hybrid non-convex regularizers for Poisson noise removal on medical images. The model is built by a combination of non-convex total variation and non-convex fractional total variation. The proposed model allows for avoiding the annoying staircase artifacts and obtaining the reconstruction results with sharp and neat edges during the noise removal process. For handling the minimization problem, we employ the alternating minimization method associated with the iteratively reweighted l1 algorithm. Numerical experiments illustrate the efficiency of the proposed model and corresponding algorithm.
ВИКОРИСТАННЯ АРТТЕРАПЕВТИЧНИХ ЗАСОБІВ У ПІДГОТОВЦІ МАЙБУТНІХ ФАХІВЦІВ

Abstract: the article is devoted to the consideration of the problem of using art therapy tools in the training of future teachers of higher education institutions. The study theoretically substantiated and tested the introduction of ar therapeutic means in the process of professional training of future teachers of a higher school. The experimental verification confirmed the expediency of introducing such tools into the real educational process of training future teachers.
Computer Forensics and Advanced Methodology

The field of computer forensics emerged in response to the substantial increase in computer-related crimes occurring annually. This rise in criminal activity can be attributed to the rapid expansion of the internet, which has provided perpetrators with increased opportunities for illicit actions. When a computer system is compromised and an intrusion is detected, it becomes crucial for a specialized forensics team to investigate the incident with the objective of identifying and tracing the responsible party. The outcome of such forensic efforts often leads to legal action being taken against those accountable for the wrongdoing. The methodology employed in computer forensics continually evolves alongside advancements in crime approaches, particularly as attackers leverage emerging technologies. To ensure the accuracy of forensic investigations, it is imperative that the scientific knowledge underlying the forensic process be complemented by the integration of technological tools. A plethora of hardware and software options are available to facilitate the analysis and interpretation of forensic data, thereby enhancing the efficiency and effectiveness of investigations. While the fundamental objectives of computer forensics primarily involve the seamless preservation, identification, extraction, documentation, and analysis of data, the widespread adoption of this discipline is contingent upon the law enforcement community's ability to keep pace with advancements in computing technology. Furthermore, the prevalence of diverse computer devices resulting from the emergence of microcomputer technology also plays a crucial role in shaping the field of computer forensics. This research paper aims to provide a comprehensive overview of computer forensics, encompassing advanced methodologies and detailing various technology tools that facilitate the forensic process. Specific areas of focus include the analysis of encrypted drives, disk analysis techniques, analysis toolkits, investigations involving volatile memory, and the examination of captured network packets. By exploring these aspects, this paper aims to contribute to the existing body of knowledge in the field of computer forensics and support practitioners in their pursuit of effective investigative techniques.
An Economic Appraisal of Blockchain’s Impact on Finance and Market Competition

This paper provides an economic appraisal of blockchain technology's impact on the two representative pillars of an economic system: finance and market competition. It is argued that although cryptocurrencies designed upon blockchain technology are perceived as alternative currencies and speculative financial assets today, their roles are limited in the economic sense. However, blockchain technology can promote market competition in the internet sector by the virtue of decentralization. In comparison to the highly concentrated market power of current internet companies, new dynamics of market competition based on Web3 are discussed.
VIRTUAL LEARNING AMIDST COVID-19 OUTBREAK: THE CHALLENGES IN LANGUAGE LEARNING

The outbreak of COVID-19 has put the universe into a big changes. Most sectors of life including education has to be adjusted for the sake of everybodyâ€™s safety. Language learning, which ideally needs a lot of interactions, should be held virtually. This sudden shift may cause several intervening factors which influence the success of it. This study was aimed at discussing the factors that may challenge the language learning during the virtual learning mode amidst the COVID-19. After studying some research about this issue, several factors namely lack of internet access, poor comprehension, poor interaction, overload tasks, insufficient infrastructure support, environmental distraction, and lack of motivation are found to be the challenges in implementing a successful virtual language learning amidst the outbreak.
Diverse classifiers with label dependencies for long-tail relation extraction in big data

Relation extraction is a critical step in knowledge recommendation for big data, but long-tailed distribution in real-world relations presents a significant challenge. Most relations fail to gather enough training instances, which forms a long tail in data distribution and leads to poor performance on these relations. Previous studies have made efforts to improve models for long-tailed relations by sharing knowledge from head classes to the long-tail. Despite proven effectiveness on long tail relations, this line of work lacks control over the knowledge transfer process, which can harm performance on head classes. To address this issue, we propose an approach that enhances the label hierarchical dependencies of a classifier through label-to-sentence attention with multi-granular constraints across different levels of relation. Moreover, We introduce an ensemble mechanism that uses a router module to balance performance between head and tail classes, thereby fixing the long-tail problem on relation extraction data set. Our approach achieves excellent performance on long-tail and all relations on the large-scale benchmark data set New York Times, without sacrificing performance on head relations. The experiment results demonstrate that our approach effectively alleviates long-tail problems and boosts performance on long-tail classes in relation extraction without harming the performance on head classes.
New Learning Technologies in Design Education

This article is dedicated to the development of highly qualified design students. Innovative technology methods proposed for use in educational practice by design students are being studied. All methods are aimed at future professionals, their activities, interests and desire. The introduction of innovative technologies is associated with competently oriented education and projects. Particular attention should be paid to the educational process of preparing future designers for practical activity, but the theoretical basis is also important in the learning process. An example of current innovations is the idea of game methods that open up the possibility of developing students' professional skills in design and development of competent training components. The importance of the psychological component is determined in the pedagogical process.