Modern Technology Research Articles

Enhancing precision and safety in metallographic sample preparation: Reduce the stochasticity and workload with robotization

Abstract Despite advancements in metallography automation, sample preparation remains largely semi-automated with isolated subprocesses like sectioning, grinding, and polishing. Leveraging modern technologies such as collaborative robotics, AI-driven computer vision, and advanced sensors could enable fully integrated automation. However, the diversity of processes requires skilled human oversight. Integrating user-friendly cobot interfaces may promote a synergistic workspace that enhances safety, reduces monotony, and supports complex studies and documentation aligned with open science principles. Our study explores cost-effective mini robots in critical preparation stages, highlighting steps toward complex automation in metallography.

Risks and Opportunities of Digital Transformation in Social Systems amid Technological Modernization

Risks and Opportunities of Digital Transformation in Social Systems amid Technological Modernization

Utilisation of Machine Learning in Islamic Learning

Background. Machine learning is a branch of artificial intelligence that has become an important component in modern technology. This is due to its ability to develop computer programmes that can access and process data. In the context of Islamic learning, the application of machine learning can be a solution to improve the learning process and help in checking plagiarism. Purpose. This research aims to explore the utilisation of machine learning in Islamic learning. The specific objective is to understand the extent to which machine learning can facilitate Islamic religious education students in the learning process and assist in checking plagiarism. Method. This research uses a quantitative approach by collecting data through the Google Form application distributed to Islamic religious education students as research subjects. The data obtained is in the form of numbers which are then analysed to gain an understanding of the use of machine learning in Islamic learning. Results. The results showed that the use of machine learning can facilitate Islamic religious education students in learning and is effective in checking plagiarism. Students experience ease in understanding the material and the learning process becomes more efficient. Conclusion. Based on the research results, it can be concluded that machine learning has great potential in improving Islamic learning by solving various problems that may occur, such as difficulties in understanding the material and plagiarism problems. Nevertheless, this study has limitations in the scope of the subject which only focuses on Islamic religious education students. Therefore, the researcher recommends further research to expand the scope of subjects and deepen the understanding of the use of machine learning in various fields, as a reference for future research.

Advancing autism therapy: emotion analysis using rehabilitation robots and ai for children with ASD

Emotion analysis is a key component in understanding the unique communication patterns and emotional states of children with autism spectrum disorder (ASD). These children often struggle with traditional forms of expressing emotions, which presents a challenge for themselves and their therapists. Facial expression analysis techniques, supported by modern technologies such as machine learning and artificial intelligence, enable more accurate identification of subtle signals that may go unnoticed by human observers. The introduction of rehabilitation robots and emotion analysis software based on the analysis of facial expressions and gestures opens up new possibilities for individualizing therapy, adapting it to the child's specific reactions and needs. In this way, the use of these tools not only increases the effectiveness of treatment but also helps build more trusting therapeutic relationships, which is the basis for adequate support for the development of children with ASD. Regular monitoring of progress and modifying therapeutic approaches, supported by automation and data analysis, is essential to more effective and empathetic care for children with developmental disorders. However, the journey does not end here. Further research is necessary to develop and improve emotion analysis techniques for use in rehabilitation robots and their impact on the effectiveness of therapy for young patients

Advanced approaches for optimizing logistics and warehouse processes: from planning to delivery

The article discusses critical aspects of managing logistics and warehousing processes in today's business environment. The authors present modern approaches and strategies to help companies manage their supply chains efficiently and optimally. The first emphasis is on understanding logistics's role in a company's operations. The article presents an application developed to help analyze key elements of logistics management, such as transport, warehousing, and inventory management. Modern technology in logistics and warehouse management has been designed and used. The authors highlight the role of information systems, process automation, and data analytics in improving efficiency and reducing operating costs. The conclusions of the article point to the need for continuous improvement of logistics and warehouse management strategies so that companies can meet growing market demands and remain competitive in a dynamic business environment.

The Theory of Gradual Landing of Public Opinion During Crises

Public opinion is under consideration not only in the media but also in other fields, such as political science, social studies, and psychology, especially with the growing crises affecting institutions and countries during the 20th and 21st centuries. It is noticeable that there are few theories that explain many of the phenomena associated with public opinion, especially in the era of modern communication technologies and social media. This gap necessitated the development of a theory of gradual landing in public opinion during crises. This theory was developed by reviewing extensive literature on public opinion, crisis management, and media theory related to public opinion. The theory deals with four major variables: event, media, audience, and the parties involved in the conflict or crisis. These variables encompass the mechanisms that determine the paths on the rise and decline of public opinion issues. This theory integrates the degree of the significance of the topic and the media's interest. This theory helps identify various cases of rise and decline in the level of interest in public opinion within society.

Human movement monitoring system for classification of strength exercises and verification of their execution technique

Human movement analysis is critical to optimizing sports training and influencing exercise intensity and effectiveness. In the age of modern technology, more and more advanced systems are emerging to support coaches and expand the range of analysis performed. This article aims to verify that artificial intelligence, together with machine learning algorithms, can accurately classify exercises in a dynamic gym environment and effectively assess the correctness of their performance. For the initial analysis of movement, the Google MediaPipe Pose model was used, which was responsible for detecting the human silhouette and determining the coordinates of the position of critical joints. Based on these coordinates, the angles between each joint were calculated, and then their sequences were further analyzed. The sequences were analyzed using the following three algorithms: support vector machine (SVM), dense neural network, and LSTM recurrent network. As a result, the system based on recurrent LSTM networks achieved the best prediction efficiency of approximately 98%, enabling accurate exercise classification. Subsequently, verification of the activities' correctness was also carried out, and the system, based on recursive LSTM networks, again achieved the best efficiency, this time equal to 96% on average for all exercises. On this basis, it was concluded that the discussed approach enables practical analysis of human movement, which can significantly improve training methods and facilitate coaching work.

Modern technology of snaplage production in the Central region of Russia

Modern technology of snaplage production in the Central region of Russia

Integrating resilience and reliability in semiconductor supply chains during disruptions

The semiconductor industry, a cornerstone of modern technology, has been crucial in driving globalization and supporting various sectors, from consumer electronics to automotive industries. However, in recent years, the industry has faced substantial challenges threatening its ability to meet the surging demand for semiconductor chips. Disruptions at any point in the supply chain, from raw material sourcing to end-product delivery, can substantially influence the semiconductor ecosystem. The intricate nature of such SCs makes them highly vulnerable to various disruptions, emphasizing the critical need for building resilient and reliable supply chain strategies. This article presents comprehensive research aimed at addressing critical gaps in the understanding and management of resilience and reliability within the semiconductor supply chain (SSC). This study proposes a multi-objective mixed-integer non-linear programming (MO-MINLP) model to configure an SSC while considering reliability and resilience measures. It emphasizes and draws attention to the importance of resilience and reliability in managing SSC disruptions during a pandemic and potential future epidemic outbreak. Exploring the precise breakdown of batch transportation between two sites shows how disruption can affect product flow along the SC. The applicability of the proposed method is demonstrated through a numerical example of an SSC, solved using the LINGO solver. Finally, a sensitivity analysis is conducted on the model's parameters to assess the capability and effectiveness of the results from managerial viewpoints.

The Crisis of Technology and the Quest for Meaning: A Critical Conception of Media Philosophy

The crisis of modern technology has led to a series of issues such as the pervasive emptiness of meaning and the loss of subjectivity in human society. Under the influence of technological supremacy and instrumental rationality, philosophy, which abstractly refines the fundamental problems faced by humanity such as the meaning of existence, truth, and the dichotomy between rationality and irrationality, also finds itself in a crisis of legitimacy. In this context, the "media turn" in philosophy is an attempt to break free from its shackles. This paper proposes a media philosophy from the essential attributes of human communication and the inseparability of communication and media. By analyzing communication as a fundamental human essence, this paper outlines the basic concept of media philosophy, explores the path of media philosophy, and emphasizes the inherent significance of the collision of life's meanings and communicative exchanges. This paper asserts that in the era of "media as being" ontology, it is especially necessary to understand the essence of human existence and the face of the world constituted by communication from the perspective of media.

Use of non-conventional raw materials in the production of gluten-free pasta – a review

Currently, about 5% of the earth's population suffers from gluten-related disorders. Modern technologies for gluten-free diets and filling the protein deficit are aimed at manufacturing gluten-free (GF) pasta products using non-conventional plant raw materials with high biological value. GF grains and crops (rice, corn, buckwheat, amaranth, quinoa, etc.) are used to produce GF pasta products. However, there is a scarcity of studies that comprehensively understand GF flour addition on the nutritive, sensory and cooking properties. Therefore, the scope of this literature review covers the main types of non-conventional raw materials for GF pasta products and summarizes the research on pasta products made from them. Results indicate that the rheological and sensory attributes of pasta made from pure GF flours such as rice or corn still requires a deeper study of technological processes in producing GF pasta. Incorporating nutrient-dense ingredients such as amaranth, quinoa, sorghum, and chia flours not only enhances the nutritional profile of gluten-free pasta but also offers opportunities for diverse culinary applications. The improvement of sensory attributes in rice-, corn-, buckwheat-based pasta, coupled with the effective use of cooking enhancers like xanthan gum, transglutaminases, inulin, and alternative starches, paves the way for creating more palatable gluten-free options. As techniques such as high-temperature treatment, extrusion cooking, and starch pregelatinization become more refined, future developments may focus on optimizing these processes to further improve the texture, taste, and overall quality of gluten-free pasta. Continued research and innovation in ingredient selection and processing technologies will be crucial for meeting the growing demand for gluten-free products that do not compromise on culinary experience or nutritional value.

Ionic Covalent Organic Framework Solid-State Electrolytes.

Rechargeable secondary batteries, widely used in modern technology, are essential for mobile and consumer electronic devices and energy storage applications. Lithium (Li)-ion batteries are currently the most popular choice due to their decent energy density. However, the increasing demand for higher energy density has led to the development of Li metal batteries (LMBs). Despite their potential, the commonly used liquid electrolyte-based LMBs present serious safety concerns, such as dendrite growth and the risk of fire and explosion. To address these issues, using solid-state electrolytes in batteries has emerged as a promising solution. In this Perspective, recent advancements are discussed in ionic covalent organic framework (ICOFs)-based solid-state electrolytes, identify current challenges in the field, and propose future research directions. Highly crystalline ion conductors with polymeric versatility show promise as the next-generation solid-state electrolytes. Specifically, the use of anionic or cationic COFs is examined for Li-based batteries, highlight the high interfacial resistance caused by the intrinsic brittleness of crystalline ICOFs as the main limitation, and presents innovative ideas for developing all- and quasi-solid-state batteries using ICOF-based solid-state electrolytes. With these considerations and further developments, the potential for ICOFs is optimistic about enabling the realization of high-energy-density all-solid-state LMBs.

Error-Free Arduino Communication: Integrating Hamming Code for UART Serial Transmission

Serial communication is a fundamental method for data transfer in electronic devices, particularly in Arduino-based systems. However, existing protocols, such as Universal Asynchronous Receiver/Transmitter (UART), often lack robust error detection mechanisms, leading to potential data integrity issues. This study aims to address the knowledge gap regarding error detection in UART communication by implementing Hamming Code, a well-established method for detecting and correcting single-bit errors. The research employs a systematic approach, including data encoding before transmission and decoding with error correction at the receiver end. The results demonstrate that the integration of the Hamming Code significantly enhances the reliability of data transmission, reducing error rates and improving overall system performance. The implications of this research extend to various applications requiring high data integrity, such as industrial control systems and Internet of Things (IoT) devices. By providing a practical solution to the challenges of error detection in serial communication, this study contributes to the advancement of reliable communication systems in modern technology.

Valuable Contributions and Lessons Learned from Proteomics and Metabolomics Studies of COVID-19.

The COVID-19 pandemic caused by the SARS-CoV-2 virus infected more than 775,686,716 humans and was responsible for the death of more than 7,054,093 individuals. COVID-19 has taught us that the development of vaccines, repurposing of drugs, and understanding the mechanism of a disease can be done within a short time. The COVID-19 proteomics and metabolomics has contributed to its diagnosis, understanding of its progression, host-virus interaction, disease mechanism, and also in the search of suitable anti-COVID therapeutics. Mass spectrometry based proteomics was used to find the potential biomarkers of different stages of COVID-19 including severe and nonsevere cases in the blood serum. Notably, protein-protein interaction techniques to understand host-virus interactions were also significantly useful. The single-cell proteomics studies were carried out to ascertain the changes in immune cell composition and its activation in mild COVID-19 patients versus severe COVID-19 patients using whole-blood and peripheral-blood mononuclear cells. Modern technologies were helpful to deal with the pandemic; however, there is still scope for further development. Further, attempts were made to understand the protein-protein, metabolite-metabolite, and protein-metabolite interactomes, derived from proteins and metabolite fingerprints of COVID-19 patients by reanalysis of COVID-19 public mass spectrometry based proteomics and metabolomics studies. Further, some of these interactions were supported by the literature as validations in the COVID-19 studies.

Effectiveness of Information and Communication Programmes for Children with Special Educational Needs in the Context of Speech Development

The work aims to determine the effectiveness of information and communication programs for special educational needs (SENs) in the context of speech development. The aim was achieved through the use of general theoretical methods of analysis, observations, and calculations of the ranking factor, efficiency coefficient, and Phillips correlation coefficient. It was established that the most effective approaches for the development of children's speech are the use of information technologies (2.5), social interaction (2.37), and group approach (2.25). Results: The results provided grounds for developing a speech and general development program for children aged 4 to 7. The program provided for the creation of mind maps, provision of joint reading, performance of educational songs, and development of speech in accordance with the specified topic. Training became possible due to the use of modern technologies, namely the applications MindMeister, Digital Inclusion, and speech synthesis from Google and YouTube. It was established that the developed program had a positive effect on the improvement of children’s phonetic speech compared to the results at the beginning of the study. Conclusions: The practical significance of the work implies the possibility of using the developed program for speech correction among a larger number of children. Prospects: Research prospects are related to elaborating speech development mechanisms depending on the degree of speech impairment.

Modernization of administrative services in Ukraine based on the approval of new principles of their provision

The article is devoted to the topic of introducing new approaches to the provision of administrative services in Ukraine based on the approval of new principles of their provision. It is noted that administrative services are the leading means of realizing the rights of citizens in the field of public administration, because the absolute majority of cases decided by public administration bodies are initiated by citizens themselves and concern their subjective rights. The Ukrainian state quite successfully coped with the challenges in the field of administrative services after the beginning of the full-scale invasion of the Russian Federation on February 24, 2022. At the current stage, the format of “state-citizen” and “state-business” relations must be modernized taking into account modern technologies, optimization of procedures and improvement of service quality . Of great importance in the process of providing administrative services is the focus on modern, objective principles of their provision determined by socio-economic and technological development. After all, today a widespread phenomenon is the “digitalization” of the process of providing administrative services, which involves the introduction of electronic document management, the creation of online platforms for receiving services, and the automation of administrative procedures. The Center for Political and Legal Reforms developed the “Strategy for the reform of administrative services and their digitalization”. From the analysis of the document, it follows that the principles of providing administrative services today need a doctrinal update in their interpretation. In particular, the system of principles of administrative services should be supplemented with such things as decentralization of powers, simplification of procedures for the provision of administrative services, formality, integration of basic services in the Central Administrative Service, compensability for the provision of administrative services, unification of the procedure for resolving administrative cases, development of electronic public services, proactivity of public administration in in the field of provision of administrative services, protection of personal data.

Audio magnetotelluric view of the giant carbonatite-hosted Bayan Obo REE deposit, Inner Mongolia, northern China

As critical minerals in low-carbon economies, rare-earth elements (REEs) are crucial for modern industry, technology, and medicine. The largest known REE resource in the world is the Bayan Obo (BO) deposit in northern China. However, BO features as complicated mineral compositions and has experienced several geological events. As a reuslt, controversy remains about the BO REE genesis and enrichment mechanism, and debates are also ongoing about the controlling structure of this giant deposit. We carried out an multiscale electromagnetism study on BO mineral deposits. The multiscale study consists a microscale on samples, a small scale targeting mineral deposits and a mid scale concerning the mine field. The small and mid scale study were conducted using audio-magnetotelluric (AMT). This study revealed the controlling structure using geoelectrical characteristics. AMT data were acquired from more than 590 stations, and the petro-electromagnetism of several samples was analyzed to understand the geoelectrical features of the ore deposits and their surrounding rocks. The data were interpreted using Bostick transformation and generalized least-squares inversions. We obtained the geoelectrical structure of the BO complex down to a maximum depth of 3500 m, and we present two-dimensional imaging based on the AMT conversion results. The results show that the BO deposit developed at the transition of the high- and low-resistivity geoelectrical structure from south to north. Our AMT results indicate that the tectonic setting of the BO deposit is the transition zone between the rift edge and craton margin slope. The ore geology is presently controlled by the complex slope and the rift remnant, the ore-bearing dolostone in the profiles is Y-shaped. It goes downward from south to north and potentially features a great mineral prospect deep in the BO deposit.

Artificial intelligence in individualized retinal disease management.

Owing to the rapid development of modern computer technologies, artificial intelligence (AI) has emerged as an essential instrument for intelligent analysis across a range of fields. AI has been proven to be highly effective in ophthalmology, where it is frequently used for identifying, diagnosing, and typing retinal diseases. An increasing number of researchers have begun to comprehensively map patients' retinal diseases using AI, which has made individualized clinical prediction and treatment possible. These include prognostic improvement, risk prediction, progression assessment, and interventional therapies for retinal diseases. Researchers have used a range of input data methods to increase the accuracy and dependability of the results, including the use of tabular, textual, or image-based input data. They also combined the analyses of multiple types of input data. To give ophthalmologists access to precise, individualized, and high-quality treatment strategies that will further optimize treatment outcomes, this review summarizes the latest findings in AI research related to the prediction and guidance of clinical diagnosis and treatment of retinal diseases.

The Role of Superabsorbent Polymers and Polymer Composites in Water Resource Treatment and Management.

In the last century, the issue of "water reserves" has become a remarkably strategic topic in modern science and technology. In this context, water resource treatment and management systems are being developed in both agricultural and urban area scenarios. This can be achieved using superabsorbent polymers (SAPs), highly cross-linked hydrogels with three-dimensional, hydrophilic polymer structures capable of absorbing, swelling and retaining huge amounts of aqueous solutions. SAPs are able to respond to several external stimuli, such as temperature, pH, electric field, and solution composition and concentration. They can be used in many areas, from sensor technology to drug delivery, agriculture, firefighting applications, food, and the biomedical industry. In addition, new categories of functional SAP-based materials, mainly superabsorbent polymer composites, can also encapsulate fertilizers to efficiently provide the controlled release of both water and active compounds. Moreover, SAPs have great potential in wastewater treatment for the removal of harmful elements. In this respect, in the following review, the most promising and recent advances in the use of SAPs and composite SAPs as tools for the sustainable management and remediation of water resource are reviewed and discussed by identifying opportunities and drawbacks and highlighting new challenges and aims to inspire the research community.

Heidegger and Foucault on modern technology: does Gestell ‘correspond perfectly’ to dispositif?

ABSTRACT This article compares Heidegger and Foucault on modern technology, taking its clue from Agamben’s claim that Gestell and dispositif are ‘perfectly corresponding’ concepts. So far, however, the task of a detailed comparison of Gestell and dispositif remains unresolved. At first glance, the two terms appear compatible, designating how we moderns began objectifying nature as well as ourselves as manipulatable raw material. Significant for the discussion is Heidegger’s and Foucault’s contrasting readings of Nietzsche, i.e. as the ‘last metaphysician’ versus ‘the first genealogist’. Schematically, for Heidegger, modern technology figures as humanity’s nearly inescapable condition, whereas Foucault sees it is ‘functionally indeterminant’, evolving in multiple, intersecting, and unexpected ways.