Reviewerly/exHarmony huggingface dataset:
Exploring The Potential of Microlearning for Toefl Ibt Preparation Among High School Students

The aim of this needs analysis is to investigate the potential of microlearning as a learning approach to prepare high school students for the TOEFL iBT. Microlearning is an instructional method that involves brief participation in an activity that is intended to yield a specific result. While prior research has shown its benefits in encouraging independent learning, reducing mental fatigue, and preventing demotivation and cognitive impairments, most studies have focused on adult learners, with only a small fraction conducted in high school settings. In Indonesia, certificates of English aptitude tests, such as TOEFL iBT, are necessary for higher education and job applications. However, the topic and skills are rarely discussed in schools, resulting in many high school graduates being unprepared for the exam. Typically, students resort to private institutions or tutors to acquire the necessary skills, but the associated costs and time commitment can be discouraging. Therefore, it is essential to examine the perceived importance of TOEFL iBT, learning difficulties, and learning preferences. The findings will inform recommendations on integrating microlearning into the existing educational framework. Future studies should explore microlearning themes further, expand research to high school context, and explore mobile-based microlearning.
Securing smart cities in the quantum era: challenges, solutions, and regulatory considerations

This study investigates the growing threat of quantum computing to classical encryption, with a specific focus on the vulnerabilities of RSA. Examining how Shor's algorithm compromises RSA security, the research proposes mitigation strategies. Through a comprehensive analysis of quantum algorithms and a review of recent literature, the study evaluates the efficacy of quantum attacks on RSA keys. Emphasizing the urgency of transitioning to quantum-resistant cryptographic solutions, the research identifies key challenges and provides recommendations for enhancing cybersecurity in the quantum era. The research methodology involves extensive literature reviews on quantum computing, RSA encryption, and related methodologies. Practical implications and the feasibility of quantumresistant alternatives are explored, shedding light on the potential impacts of quantum attacks on RSA encryption. The study emphasizes the need for swift adaptation to quantum-resistant cryptographic solutions, offering insights into key challenges associated with this transition and recommending strategies for enhanced cybersecurity in the era of quantum computing. The successful execution of this research hinges on access to computational resources for quantum simulations and cryptography analyses. Additionally, collaboration with experts in quantum computing and cryptography is crucial for validation and guidance throughout the research process. Access to relevant literature, datasets, cryptography software libraries, and surveys is essential for a comprehensive study that addresses the evolving quantum security landscape.
ChatGPT security risks and solutions

As artificial intelligence (AI) technologies become more popular in enterprise environments, special chatbot technologies such as ChatGPT are gaining popularity due to their abilities, services, and benefits. However, these chatbots suffer from significant security risks and vulnerabilities that need to be addressed, such as confidentiality weaknesses, authentication issues, chatbot breaches, data poisoning, and others. This article identifies the potential ChatGPT risks and threats and proposes solutions and remedies to address the security issues of the chatbots risks, such as calling for policy changes, proposing training, equipping the teams with AI technology and tools, implementing strong access controls, using secure servers and storage systems, limiting access to systems, supporting a well-defined incident response process, and calling for government oversight to ensure AI usage doesn't become detrimental to cybersecurity efforts. Ending with future directions and recommendations to protect the use of this technology and guide future research and practice in this field.
Use of large language models for medical synthetic data generation in mental illness

Data quantity and quality are very important for the development of medical artificial intelligence research. Nowadays, thanks to easier access to data, studies in this field produce very successful results. However, many factors such as protection of patient rights in medical data and confidentiality of personal data prevent researchers from directly accessing the data. For this reason, synthetic data creation studies are often needed both to expand the training and test sets and to create sample cases to be used in the relevant field. In this study, various synthetic patient data are created to be presented to a language model that enables the detection of psychological disorders through patient text. Synthetic data sets were produced with 200 artificial patient data created with popular LLM examples ChatGPT and Google Bard. The quality of synthetic data was measured with the help of a pre-trained BERT model using these datasets. In the experiments, it was observed that chatbots that generate instant data, such as ChatGPT and Google Bard, produced successful results at rates of 89% and 86% with the language representation model. With the experimental results, it appears that LLM studies can provide more successful results than advanced language models in various medical text production tasks.
A survey on quantum cryptography for ecommerce applications

Cryptography which involves mathematical notations and algorithms to transform plaintext into cipher text for secure communication of data protection, data confidentiality though benefit from Machine Learning techniques with enhance security. Machine Learning models used in cryptography may be susceptible to confrontational attacks. There is a need to develop robust and resistant computing techniques to overcome attacks especially in ecommerce applications where the expected growth rate is by 10.75% on annual basis which will reach $107.3 billion by the end of 2023.Quantum computing is going to play a key role in near future through which quantum cryptography techniques can be applied on different Machine Learning models to enhance secure transactions in ensuring the privacy, integrity, efficiency in data-driven application and authenticity of sensitive information. In associated learning environments, where models are trained across numerous devices or servers, quantum cryptography can be utilized to provide secure communication and parameter updates while keeping the data decentralized and private. This paper focus on open issues and challenges of Machine Learning cryptography with quantum computing cryptography through Machine Learning Models in ecommerce.
Designing and evaluating the performance of a solar tracker system in hot-arid regions

Solar energy is a clean energy that is produced by transmitting the sun's rays to solar panels, which causes an interaction and allows electrons in the circuit to flow to obtain energy. Countries are currently using solar energy instead of fossil fuels, which cause global warming and destroy the ecosystem. A smart solar tracking system is proposed in this paper to track the most energy from the sun all times A dual-axis solar system prototype has been developed to monitor the sun and gather the most power. Hardware design and implementation, as well as software programming for the solar tracker's controller unit, are among the suggested system development tasks. The action of two servo motors, which rotated the solar panel in two axes, was controlled by an Arduino controller. The amount of rotation has been calculated by the Arduino controller using data from four light-dependent resistor (LDR) sensors situated close to the solar panel. The dual-axis solar system outperforms the single axis and stationary solar systems, according to the project results.
Detection and classification of malicious URLs based on machine learning models

There has been a shift in the last few years that saw a rapid increase in eservices that need the transmission of sensitive and private information over the internet. Along with the number of people utilizing the internet, crime-attacks are expanding quickly. Malicious attacks using malicious URLs are becoming the simplest way to compromise the security chain's weakest link. Machine learning is an extremely well-liked method for identifying malicious or fake URLs. Tree based classification ML models may be utilized to detect non-benign URLs by training them by utilizing a dataset that contains common malicious URLs. This paper explains the lexical features in a URL that may be utilized to train the machine learning models. It also calculates the accuracy rate of different models and selects one for prediction based on the calculated accuracies.
Breast abnormalities classification using pre-processing and deep transfer learning techniques

Heart disease is no longer the second leading cause of mortality for women; instead, breast cancer has replaced it. Mammography examinations must accurately determine the precise type and subtype of breast cancer to effectively diagnose earlystage breast cancer, thereby enhancing the probability of the patient's survival. However, given the range of breast kinds and subtypes, as well as the complexity of their microenvironment, it continues to be a severe issue. To solve these issues, we provide a two-stage classification technique. The pre-processing step, which comprised multiple noise reduction filters, was where it all began. Then, using transfer learning approaches, we suggested a CNN architecture with feature extractors based on pre-trained models from Resnet50 V2 and Xception. As a consequence, we proved that the suggested method worked effectively for breast Mass instances by developing such a model and training it using our pre-processed dataset. Using the CBIS-DDSM we reached the highest accuracy of 99.99% for classifying breast Nasses and Calcs.
On a Problem of Calculating the Solvability Set for a Linear System with Uncertainty

We consider a linear-convex control system defined by a set of differential equations with continuous matrix coefficients. The system may have control parameters, as well as uncertainties (interference) the possible values of which are subject to strict pointwise constraints. For this system, over a finite period of time, taking into account the constraints, we study the problem of guaranteed hitting the target set from a given initial position despite the effect of uncertainty. The main stage of solving the problem is the construction of an alternating integral and a solvability set. To construct the latter, the greatest computational complexity is the calculation of the geometric difference between the target set and the set determined by the uncertainty. A two-dimensional example of this problem is considered for which a method is proposed for finding the solvability set without the need to calculate the convex hull of the difference of the support functions of the sets.
A Study on the improvement of Environmental Product Declaration of Ready-mixed concrete

Since the revision of the Green Standard for Energy and Environmental Design (G-SEED), Environmental Product Declaration (EPD) of building materials has increased rapidly as additional points have been given to use building materials that have obtained EPD based on Life Cycle Assessment (LCA). In particular, the cumulative number of (Environmental Product Declaration–EPD) of ready-mixed concrete (RMC) is increasing every year from 18 in 2018, 109 in 2019, 501 in 2020, and 809 in 2021. In order to increase the reliability of the current EPD results, this study aims to present an improvement plan for the certification of EPD of RMC by analyzing the RMC Product Category Rules (PCR) as stipulated by the EPD. As a result of PCR analysis, there was a need to subdivide the method of allocating the number of processes, and there was a need to indicate the calculation of emissions of individual factories. Through this RMC PCR analysis, it is expected to be used as a review data for revising EPD's general product preparation guidelines, building material preparation guidelines, and remicon preparation guidelines in the future.
Individualization of independent work in the professional training of future teachers: An experimental study

The individualisation of independent work in the professional training of future teachers contributes to the stable achievement of results in professional and pedagogical training, as it takes into account the needs, motivation, and capabilities of the student. One of the leading technologies of innovative education is tutoring, which ensures an open educational environment in a higher education institution. The article outlines the results of an experimental study of the state of individualisation of independent work in the professional training of future university teachers on the basis of comprehensive, competence-based, systemic and activity-based approaches. The experiment was conducted in the form of a questionnaire among 54 respondents – master students majoring in “011 – Educational, Pedagogical Sciences” of the Mykhailo Drahomanov Ukrainian State University in order to find out their attitude to the current individualisation of independent work and the introduction of tutoring technology. The respondents were offered a Google Forms questionnaire “The current state of individualisation of students' independent work in higher education institutions”, which consisted of 10 questions with possible answers. The results of the experiment showed that modern higher education institutions do not provide adequate conditions for the development of important skills and qualities in students, such as independence, the ability for self-education, self-development, and self-knowledge. It is established that the majority of master's students express their dissatisfaction with the organisation of individualised independent work in higher education institutions, which is due to insufficient attention to their interests, needs, and motives. It is proposed to introduce an integrated form of professional and pedagogical training of future teachers – tutoring technology as an important mechanism for innovating education, which can ensure the openness of the educational and scientific environment. The essence of the educational process under the guidance of a tutor, when a student acts as a tutor on the basis of subject-subject partnership interaction, is revealed. The results of the confirmatory experiment make it possible to further study the conceptual foundations of tutoring as a leading technology for individualising the educational and scientific process. The developed experimental study on the current state of individualisation of independent work in higher education institutions can be implemented at all levels of training of future pedagogical specialists
A Citation Network Analysis on Diffusion of Technologies to Other Fields: a Case Study About FWI

Summary In recent years, the rapid changes in social trends and technologies, such as digital transformation and energy transition, have had a large impact on many industries. Future forecasts and exploration of potential values become indispensable for dealing with such changes and achieving the success of novel research and/or business. In this paper, we discuss an approach to evaluate the diffusion of innovative technologies to other fields using the network data in academic articles citing a review paper. This study provides a case study of full waveform inversion as an example in exploration geophysics to demonstrate the effectiveness of the approach by using the Web of Science database. This analysis enables us to forecast the trend of technologies by analyzing the diffusion of the other technologies as well as full waveform inversion.
High-Efficient Cloud Seismic Data Solution for Real-Time Geosteering Optimization

Summary The high cost and complexity of lateral wells require advanced technological equipment, state-of-the-art IT solutions, and data interpretation practices to keep the well within the target zone. Nevertheless, data integration and communication within the operations team are one of the most common challenges during the drilling activities. Modern geosteering software allows users to integrate all types of geoscience data, Log While Drilling, and 3D seismic surveys within one cloud-based platform. This IT solution can compress 3D seismic surveys using VDS technology that helps to optimize the storage and accelerate the visualization and interpretation processes. Streaming seismic data from the cloud simplifies the geosteering workflow and aids the geosteerer to make more confident decisions. Access to the free VDS APIs enables data liberation and innovative, cloud-native workflows for geosteering.
Delivering business value through OSDUTM – accelerating adoption with Transitional Architecture

Summary This paper presents a blueprint for OSDU implementations that introduces 'Transitional Architecture' as an approach that harnesses new and existing technology to accelerate delivery of value of the platform to the business community in operators. This paper explores what OSDU, the value proposition and some of the commonly raised concerns of the platform, before presenting a solution which is built around business requirements of subsurface departments
APPLICATION OF DIGITTAL TECHNOLOGIES IN RECRUITMENT PROCESS

The recruitment process is one of the essential parts of human resource management. Through successful recruitment, the organization ensures the selection of suitable applicants, which is paramount for the effectiveness of the enterprise. Successful recruitment will exert a positive effect on the organization as well as motivate the selected applicant to show high performance. How do modern digital technologies apply to the process of recruitment? The purpose of our report is to answer this question. The structure of the paper is as follows: Introduction, Chapter I – Recruitment process, Chapter II - Application of Modern Digital Technologies in Recruitment Process, Conclusion.
Application of AI and ML for sensor data analysis

Wireless sensor networks (WSNs) have made significant progress in recent years and are now regarded as reliable study fields. The source field and sink of a wireless network are provided by a large number of wireless sensor nodes that make up a wireless sensor network (WSN). Wireless sensor networks (WSNs) offer the capacity to sense the nearby nodes, do computations, and wirelessly connect to other nodes. WSN is used in various fields, including the military, tracking, monitoring remote environments, surveillance, the healthcare industry, and more. The challenges for more advanced technology and development have grown as a result of widespread application. This Review paper offers a comprehensive analysis of the recent trends and advancements in sensor technology in wireless communication in the context of Machine learning (ML) and Artificial intelligence (AI) applied to sensor data.
Speech subscribers using Python

This project leverages Python to develop a robust and efficient speech recognition system. The system's versatility extends to multiple applications, such as voice assistants, transcription services, and accessibility aids. By harnessing Python's extensive libraries and frameworks, we ensure scalability and adaptability. Our project addresses the growing demand for natural language interfaces and enhances human-computer interaction across various platforms. With a focus on accuracy, speed, and usability, this speech recognition solution paves the way for seamless communication between humans and machines.
State regulation of the position of the Muslim clergy in the Yenisei province in the second half 19th – early 20th centuries

The article is devoted to the problem of the influence of state authorities on the Muslim clergy of the Russian Empire in the second half of the 19th - early 20th centuries. The authors pay special attention to the relationship of the mullahs of the Yenisei province with the Muslim communities of the region. However, with the increase in the number of registered mullahs in the region, there was a tendency for them to be rejected by representatives of the Muslim faith. Based on the analysis of archival materials, it is concluded that the provincial authorities played a huge role in solving many issues concerning the Muslim clergy in the province. The Orenburg Mohammedan Spiritual Assembly, which was essentially a state body, was of great importance for the life of communities.
DESAIN CLOUD KITCHEN BERORIENTASI KENYAMANAN

The Cloud Kitchens generally use buildings that are not designed to be used as intended. This has an impact on the occurrence of obstacles in use. Even though the kitchen plays an important role, it is necessary to design a good construction, equipment and supporting equipment.Cloud Kitchen is designed with the concept of Multi-Sensory Collective Kitchen which aims to make a kitchen that can support business owners in producing and developing their business. This design is oriented towards environmental comfort and can support users to use their five senses to produce good products.
Turning a Puck.js into an open source one-button tracker

&lt;strong&gt; tl;dr: You can turn your Puck.js into a &lt;em&gt; one-button tracker &lt;/em&gt; with this open source website I made &lt;/strong&gt; &lt;em&gt; Open Humans &lt;/em&gt; community member James Littlejohn highlighted the &lt;em&gt; Espruino &lt;/em&gt; family of open source hardware boards and devices during one of our community calls some weeks ago.
PROTECTING AND UNDERSTANDING DIGITAL DESIGNS – THE SHAPE OF THINGS TO COME

This study looks into aspects of the new EU design legislation that relate to the subject-matter of digital designs and the extent to which Polish law should adapt for full harmonization. The first part examines the new open-ended definitions of a ‘design’ and ‘product’ with a focus on dematerialized items that exist solely through appearance. The second part touches upon several legal parameters serving the identification of the object of design protection. It discusses the visibility requirement embedded by the filing requirements, the eye-perception of design features, and the disconnection of the scope of protection from the designated product category. The last part takes an interdisciplinary approach based on the rules of psychology and design engineering in order to explain the issues that underline human vision, with a focus on the appearance of user interfaces. The understanding of sensory and cognitive determinants of human perception is a useful guide for a judge or examiner in the assessment of the overall impression of two designs. Because of the challenges resulting from the specificity of digital designs, this article argues that Polish law should comprehensively implement the new EU design provisions in order to prevent further difficulties in enforcement.