Computer Technology Research Articles

Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review.

Diet-related diseases, such as type 2 diabetes, require strict dietary management to slow down disease progression and call for innovative management strategies. Conventional diet monitoring places a significant memory burden on patients, who may not accurately remember details of their meals and thus frequently falls short in preventing disease progression. Recent advances in sensor and computational technologies have sparked interest in developing eating detection platforms. This review investigates central hemodynamic and thermoregulatory responses as potential biomarkers for eating detection. We searched peer-reviewed literature indexed in PubMed, Web of Science, and Scopus on June 20, 2022, with no date limits. We also conducted manual searches in the same databases until April 21, 2024. We included English-language papers demonstrating the impact of eating on central hemodynamics and thermoregulation in healthy individuals. To evaluate the overall study quality and assess the risk of bias, we designed a customized tool inspired by the Cochrane assessment framework. This tool has 4 categories: high, medium, low, and very low. A total of 2 independent reviewers conducted title and abstract screening, full-text review, and study quality and risk of bias analysis. In instances of disagreement between the 2 reviewers, a third reviewer served as an adjudicator. Our search retrieved 11,450 studies, and 25 met our inclusion criteria. Among the 25 included studies, 32% (8/25) were classified as high quality, 52% (13/25) as medium quality, and 16% (4/25) as low quality. Furthermore, we found no evidence of publication bias in any of the included studies. A consistent postprandial increase in heart rate, cardiac output, and stroke volume was observed in at least 95% (heart rate: 19/19, cardiac output: 18/19, stroke volume: 11/11) of the studies that investigated these variables' responses to eating. Specifically, cardiac output increased by 9%-100%, stroke volume by 18%-41%, and heart rate by 6%-21% across these studies. These changes were statistically significant (P<.05). In contrast, the 8 studies that investigated postprandial thermoregulatory effects displayed grossly inconsistent results, showing wide variations in response with no clear patterns of change, indicating a high degree of variability among these studies. Our findings demonstrate that central hemodynamic responses, particularly heart rate, hold promise for wearable-based eating detection, as cardiac output and stroke volume cannot be measured by any currently available noninvasive medical or consumer-grade wearables. PROSPERO CRD42022360600; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=360600.

Role of Telemedicine and Telehealth in Public Healthcare Sector: A Narrative Review.

Clinicians, researchers in health services, and other experts have been investigating how to improve healthcare using advanced computer and telecommunication technology for more than 30 years. Adequate medical facilities are still lacking in many places of the world. In these kinds of situations, technology can be quite helpful in expanding healthcare access to rural locations and offering better care at a lower cost. The delivery of healthcare is changing dramatically because of telemedicine and telehealth, particularly in terms of improving access to care. This paper aims to provide an update on the history, background, applications, benefits, barriers, and challenges of these recent technologies. This review article also covers the healthcare conditions of rural as well as urban communities. Furthermore, the implications of technologies used and improvement in the health status of an individual are also discussed. During the COVID-19 epidemic, telehealth quickly gained popularity, bringing to light a number of issues. Effective primary medical networks are crucial, as the COVID-19 pandemichighlighted the need for improving public health responses during crises and revealed the existing fragmentation in healthcare delivery systems.

Exploration and Practice of Course Ideology and Politics Construction in Engineering Course of Application-oriented Universities

This paper analyzes the problems in the construction of course ideology and politics, uses information technology to enable the change of thinking mode, and explores the innovation research on the new carrier and new model. The concept of tree in computer science and technology is applied to the construction of course ideology and politics, based on that a standardized ideological and political case base is built and a closed-loop model is proposed. Through the integration design of the core value system and the entire process of education and teaching, the integrated development of professional construction and ideological and political education is realized.

Automatic Segmentation of Hemorrhages in the Ultra-wide Field Retina: Multi-scale Attention Subtraction Networks and An Ultra-wide Field Retinal Hemorrhage Dataset.

Ultra-wide field (UWF) retinal imaging can improve the detection rate of retinal hemorrhage as compared with conventional fundus images. However, hemorrhages in UWF retinal images can also become smaller and more widely distributed, which can be time consuming and labor intensive. With the development of computer technology, automatic segmentation techniques can assist physicians in diagnosis. However, the lack of publicly available UWF retinal hemorrhage segmentation datasets has limited the development of automatic hemorrhage segmentation techniques in UWF retinal images. We present a large-scale high-quality UWF retinal hemorrhage segmentation dataset, named UWF-RHS Dataset, for public use. To the best of our knowledge, we are the first team to make the UWF retinal hemorrhage segmentation dataset publicly available. In addition, we propose a multi-scale attention subtraction network (MASNet) for UWF retinal hemorrhage segmentation. Specifically, highly focused lesion features are extracted by using the proposed multi-scale attention subtraction (MAS) module at the progress of the skip-connection. Several comparative experiments and ablation experiments were performed at the UWF-RHS Dataset, and all experiments state that our proposed method is effective in diagnosing retinal hemorrhages with state-of-the-art results. The proposed UWF-RHS dataset and MASNet will greatly facilitate the development of automated segmentation techniques for UWF retinal hemorrhages. Links to the UWF-RHS dataset and the MASNet model code are available fromhttps://github.com/wurenkai/UWF-RHS-Dataset-and-MASNet.

GIS-technologies and algorithm for developing regional systems for handling medical waste on the example of three regions

Introduction. GIS is a modern computer technology designed for collecting, storing, analyzing and visualizing spatial data – mapping. GIS is also actively used in healthcare to solve many regional problems, including optimization and management of healthcare resources. Over last decade, many researchers have used mathematical software models for healthcare waste management. A review of the literature shows facility location, risk to the public, and economic feasibility to be among the issues that have been extensively covered in the literature. Designing a reverse logistics network using mathematical software tools is an efficient and effective way to manage healthcare waste. The objective of the study. To determine the optimal approach to creating a functional model of a system for managing medical waste of class B and C using GIS-technologies for each of the three regions, based on the characteristics of each. Materials and methods. Medical institutions in three regions (St. Petersburg, Leningrad Region and Krasnoyarsk Territory) as sources of medical waste generation were considered taking into account their capacity and specialization. The composition and volumes of waste by class were determined using a calculation method based on indicative waste generation standards. The identification of local technologies for the neutralization of medical waste existing in medical institutions was carried out. The obtained data was processed statistically and displayed on electronic maps for subsequent use in GIS technologies, as well as for the development and justification of a waste management system for medical institutions, taking into account the prospects for the development of healthcare. Results. Based on the analysis of data on medical waste of classes B and C in individual medical institutions, as well as an analysis of the power of existing technologies for neutralizing this waste using GIS technologies, proposals were developed to improve the medical waste management system in three regions. The proposals are aimed at improving the sanitary and epidemiological situation in the regions over a five-year period and take into account the features of the existing transport infrastructure and the requirements of sanitary legislation. Limitations. The model of a medical waste management system using GIS technologies was used only for managing waste of classes B and C. Conclusion. To ensure the safe and environmentally sustainable functioning of the waste management system of classes B and C in the regions, it is necessary to apply an integrated approach based on GIS technologies. This approach should take into account the regional characteristics of the management of the medical waste disposal system and its economic feasibility and take into account the regional characteristics of transport logistics and the prospects for the development of healthcare.

The impact of technostress on caregivers of primary and secondary school children during distance-learning throughout the COVID-19 pandemic

ABSTRACT The shift to online learning due to the COVID-19 pandemic has led to numerous complaints from caregivers unaccustomed to new technologies, resulting in technostress, defined as “stress or psychosomatic illness caused by working with computer technology on a daily basis.” This study investigates the prevalence and impact of technostress on caregivers of primary and middle school children attending online school from home in the United Arab Emirates (UAE). A cross-sectional study was conducted among caregivers with children in primary and middle school residing in the UAE (n = 727; males = 86, females = 641). Data was collected using an online questionnaire examining technostress and its impact on caregiver-child relationships and health, including sleep, anxiety, and appetite. Data analysis was performed using SPSS (version 26). Caregivers aged 30–39 years and females had the highest technostress scores (p < 0.05), while occupation and education levels had no effect. Technostress was significantly correlated with mental health (r2 = 0.291; p < 0.001) and caregiver-child relationships (r2 = 0.429; p < 0.001). Caregivers with two or more children in primary and middle school had higher technostress scores (p < 0.05). In conclusion, female caregivers aged 30–39 experienced higher technostress, negatively impacting their mental health and relationships with their children. We recommend targeted anti-technostress courses and enhanced communication.

No Drone’s Sky: Full Spectrum Drone Surveillance and Neutralisation Concept for Enhanced Counter-UAS Framework

Unmanned Aircraft Systems (UAS), commonly known as drones, have witnessed substantial global proliferation in the past decade. Their constructive applications hold the promise of being a useful, yet critical component in creating a more efficient society with the enhancement of safety, efficiency, and facilitating advancements in various domains, ultimately contributing to our modern daily lives. However, the escalating dependence on computer and communication technologies renders, especially small, UAS susceptible to various threats, posing risks to public safety, national security, and individual privacy. Addressing these concerns necessitates the development of innovative technologies designed to detect, track, identify, and eliminate UAS in a manner that upholds safety, security, and privacy. A Counter-Unmanned Aircraft System (C-UAS) is defined as a system or apparatus capable of legally and securely incapacitating, disrupting, or assuming control over an UAS. Recent years have witnessed significant research endeavours aimed at detecting and eliminate drone threats. Detection methodologies encompass acoustic, visual, passive radio frequency, radar, and data fusion techniques, while neutralisation strategies encompass physical capture and jamming approaches. This paper, delving into the realm of small drone surveillance, is the opening segment of a three-part series aims to envision a C-UAS framework; it provides an exhaustive review of existing literature in the domain of UAS surveillance, delineating the challenges associated with countering unauthorised or unsafe drone operations, and evaluating the trajectory of detection to prepare against UAS-induced threats. Therefore, the fundamental objective of this paper is to offer a comprehensive surveillance baseline for a structured vision to a C-UAS framework, thus fostering a research community dedicated to the secure integration of drones into the airspace system.

METHODOLOGY FOR QUANTITATIVE ASSESSMENT OF THE FILAMENTOUS INDEX IN TECHNOLOGIES OF BIOLOGICAL WASTEWATER TREATMENT

For the quantitative control of the filamentous index in biological treatment facilities, a computerized methodology has been developed within the presented study. Its use enhances the reliability and techno-genic safety of operating biological treatment facilities. Problems related to filamentous microorganisms, which can hinder effective wastewater treatment, are considered. Sludge bulking occurs when the intensive growth of these microorganisms complicates the separation of activated sludge from treated wastewater, leading to various operational issues. The study emphasizes the importance of microscopic analysis in identifying and addressing problems associated with filamentous organisms. The use of microscopic analysis as a crucial tool for managing activated sludge issues is discussed. The classification system developed by D. Eikelboom, which identifies 21 types of filamentous organisms based on visual characteristics, is described in detail. The filamentous index, a key parameter for monitoring the quality of activated sludge, is examined in detail, along with methods to minimize subjective evaluation factors using computer technologies. The primary goal of the study is to develop a computerized methodology for the rapid quantitative determination of the filamentous index, and area of filamentous microorganisms in activated sludge. The ImageJ software was used for processing microphotographs of sludge, enabling precise measurements of geometric characteristics. The analysis includes processing images from Eikelboom's work to establish reference values for the filamentous index. Microsoft Excel software was used for theoretical calculations and statistical analysis of experimental data. The results of the research, which confirm the effectiveness of the proposed methodologies, are presented. Keywords: activated sludge, sludge bulking, filamentous index, quantitative analysis, treatment efficiency.

Enhancing rural healthcare through internet-based remote collaborative outpatient services: A comprehensive evaluation in Changzhi, Shanxi Province.

The advancement of digital technology, particularly telemedicine, has become crucial in improving healthcare access in rural areas. By integrating cloud computing and mHealth technologies, Internet-based Collaborative Outpatient Clinics offer a promising solution to overcome the limitations of traditional healthcare delivery in underserved communities. A trial was conducted in 4 counties of Changzhi City in Shanxi Province, China. The system extended to 495 rural communities and served over 5000 rural residents. Deep learning algorithms were employed to analyze medical data patterns to increase the accuracy of diagnoses and the quality of personalized treatment recommendations. After the implementation of the system, there was a significant improvement in the satisfaction levels of rural residents regarding medical services; the accuracy of medical consultations increased by 30%, and the convenience of medical access improved by 50%. There was also a notable enhancement in overall health management. Satisfaction rates among healthcare professionals and rural inhabitants were over 90% and 85%, respectively, indicating that the system has had a significant positive impact on the quality of health-care services. The study confirms the feasibility of implementing telemedicine services in rural areas and offers evidence and an operational framework for promoting innovative healthcare models on a large scale.

Mapping the Path of Digital Transformation: The Role of Leadership in Building Adaptive Organizational Culture

The development movement continues towards the digital transformation era, marked by rapid advances in information and computer technology (ICT) and the emergence of social media platforms that change the order of life to be more practical and accessible and deny the geographical distance between people. These changes require universities to adapt to the demands of rapid development. This study aims to explore the strategies carried out by university leaders in facing the challenges of the digital era and map the extent to which the transformation of university organizational culture is operated in the face of digital technology pressure. The research used a qualitative approach with a multi-site format in three private universities. Data analysis applies constant comparative analysis, which ends with a simultaneous analysis step. The results showed that university leaders are ready to implement an open strategy in facing the challenges of the digital era by utilizing these technological advances. However, there are differences in the utilization of network assets owned by institutions and the knowledge and experience of leaders. Organizational culture transformation is operated to the extent that institutions can master digital technology to optimize the performance of institutional services. Universities' engagement with digital technology does not disrupt the resilience of their organizational culture because it only leads to an adaptive surface layer.

Optimization of machine learning model training procedure on multi-gpu systems to enhance cyber security in telecommunication networks

This paper analyzes the optimization features of machine learning (ML) model training procedures using multi-GPU systems to enhance cyber security in telecommunication networks. A key aspect of the study is the use of data parallelism, which allows the distribution of the training load across multiple GPUs, significantly reducing training time and improving model accuracy-critical factors for rapid threat detection in cyberspace. A novel approach for optimizing data batch size using Mutual Information (MI) is proposed, which harmonizes the utilization of computational resources with the information content of the training data. MI helps to determine the optimal data batch size that minimizes training errors and improves model accuracy without a significant increase in training time. Experimental results demonstrate the substantial advantages of multi-GPU configurations compared to single-GPU setups, providing faster training and improved model accuracy. It was particularly emphasized that MI-guided batch size tuning significantly outperforms traditional manual tuning methods, ensuring higher validation accuracy and reducing training time. The study showed that the MI-based approach is an effective tool for addressing the problem of optimizing ML model training processes in real-world scenarios where cyber security is critical. The proposed methods allow ML models to train faster and more accurately identify potential threats, making them particularly relevant for telecommunication networks where a rapid response to new threats in real time is required. The implementation of modern computational technologies such as multi-GPU systems and MI-optimized training enhances the efficiency and accuracy of machine learning models. This, in turn, improves cyber security measures and ensures a more reliable defence of telecommunication networks against malicious attacks. It is noted that the proposed approaches can be adapted not only for cyber security but also for other areas where high model accuracy and fast training are important. Future research prospects include the development of new machine learning methods, particularly deep neural networks, the exploration of alternative computational architectures such as quantum computing or distributed systems, and their integration into real-time systems. Special attention should be paid to the ethical aspects of implementing automated cyber security systems, particularly in preventing bias in algorithms and ensuring fairness in their application.

La cultura informática en la enseñanza-aprendizaje del inglés

This review article aims to analyze the impact of computer culture on the teaching and learning process of the English language. The methodology used included the systematic review of previous studies that explored the integration of computer technology in the English classroom, as well as the analysis of pedagogical approaches and technological tools used. The results revealed that incorporating computer culture in English teaching can improve variables like motivation, active participation, and the development of communication skills. Furthermore, it was observed that digital technologies offer opportunities for the individualization of learning and the creation of more interactive and dynamic educational environments. In conclusion, the importance of continuing to investigate and promote the strategic use of computer culture in the teaching of English is highlighted, with the aim of enhancing the quality and effectiveness of education in an increasingly digitalized world.

Maintaining Security of Patient Data by Employing Private Blockchain and Fog Computing Technologies based on Internet of Medical Things

Maintaining Security of Patient Data by Employing Private Blockchain and Fog Computing Technologies based on Internet of Medical Things

Preface

Abstract During June 21-22, 2024, the 2nd International Conference on Computer Technology and Information Science (CTIS2024) was successfully held online. This conference included keynote speeches, invited speeches, oral and poster presentations. Prof. Yong Yue from Xi’an Jiaotong-Liverpool University (XJTLU), China; Assoc. Prof. Lei Chen from Shandong University, China and Dr. Binqiang Wang from Inspur (Beijing) Electronic Information Industry Co. Ltd attended the conference and delivered keynote speeches. In addition, experts and scholars from the Guizhou Normal University, Guiyang, China; Harbin Institute of Technology; IEIT SYSTEMS Co., Ltd.; Kansai University, Osaka, Japan and other universities and institutes shared wonderful speeches. This conference proceedings included 7 accepted articles selected from 39 submissions, all the papers have been through rigorous review and process to meet the requirements of international publication standard. We would like to express our gratitude to the reviewers of these manuscripts, who provided constructive criticism and stimulated comments and suggestions to the authors. We are extremely grateful as organizers, technical program committee and editors and extend our most sincere thanks to all the authors for their excellent contribution and work. Our sincere gratitude also goes to the IOP Publishing editors and managers for their helpful cooperation during the preparation of the proceedings. On behalf of the Organizing Committee of CTIS2024. List of Technical Program Committee is available in this Pdf.

Intelligent joint communication and computation scheme of UAV-assisted Offloading in high speed rail scenarios

With the continuous development of communication and computation technologies, large bandwidth services place higher demands on computing capacity and throughput in High-Speed Rail (HSR) scenarios. On the one hand, Millimetre-Wave enables high data transmission rates, but leads to high Doppler frequency deviation as well as large path loss. On the other hand, the development of Mobile Edge Computing greatly alleviates user computing congestion. In this paper, we propose the Adaptive Joint Communication and Computation Resource Allocation scheme to solve the energy optimization problem of a dual-band UAV and Mobile Relay relay-assisted HSR offloading system. This scheme works well to optimize the performance of the system through resource allocation. In addition, since the optimization problem is modeled as a Mixed-Integer Nonlinear Program, we propose the Pre- and Post-state connected Parameterized Deep Q-Network algorithm, which is based on Deep Reinforcement Learning approach, for offloading decision and bandwidth resource allocation. Simulation results show that the proposed algorithms result in lower system energy consumption, while ensuring a high task completion rate as well.

Combining Multistaged Filters and Modified Segmentation Network for Improving Lung Nodules Classification.

Advancements in computational technology have led to a shift towards automated detection processes in lung cancer screening, particularly through nodule segmentation techniques. These techniques employ thresholding to distinguish between soft and firm tissues, including cancerous nodules. The challenge of accurately detecting nodules close to critical lung structures such as blood vessels, bronchi, and the pleura highlights the necessity for more sophisticated methods to enhance diagnostic accuracy. This paper proposed combined processing filters for data preparation before using one of the modified Convolutional Neural Networks (CNNs) as the classifier. With refined filters, the nodule targets are solid, semi-solid, and ground glass, ranging from low-stage cancer (cancer screening data) to high-stage cancer. Furthermore, two additional works were added to address juxta-pleural nodules while the pre-processing end and classification are done in a 3-dimensional domain in opposition to the usual image classification. The accuracy output indicates that even using a simple Segmentation Network if modified correctly, can improve the classification result compared to the other eight models. The proposed sequence total accuracy reached 99.7%, with 99.71% cancer class accuracy and 99.82% non-cancer accuracy, much higher than any previous research, which can improve the detection efforts of the radiologist.

Do Generative Artificial Intelligence Company Strategies of ‘Moving Fast and Breaking Things’ in Civil Society Cancel Their Social Licence to Operate? A Nurse’s Evaluation of Chatbot Impacts

A rapid expansion of the computer technology industry, particularly in the field of artificial intelligence, has ignited a global concern that warrants our immediate action. As nurses, our professional values frameworks compel us to protect public health and address national and global health issues. When industry activities adversely affect the social wellbeing of civil society and social institutions, it is important to evaluate them against their industry’s ‘social license to operate, which is a measure of public trust, credibility, and the legitimacy of their industrial and corporate citizenship status. The central question is, do computer technology companies continue to have a social license to operate in civil society? Nurses are encouraged to evaluate the computer technology industry’s recent ‘generative artificial intelligence’ chatbot activities against its tacit undertaking to be good corporate citizens in return for social acceptance of their operations and behaviour. An evidence-based overview of chatbot impacts on societies, environmental sustainability and human rights provide a basis for evaluation. Basic computer technology terminology and relevant concepts are explained. This article is a direct call to action for clinical nurses and those involved in research, education, management, and policy. We have a duty to critically assess the claims made by chatbot technology vendors in both practice and social contexts. If these vendors integrate chatbot technologies with existing machine learning used in nursing and healthcare technologies it could result in detrimental effects beyond user control. By influencing decisions on technology adoption, we can ensure the implementation of safeguards, protect patient safety and social well-being, and uphold the integrity of nursing values. A closing discussion of impacts of computer industry trust deficits on healthcare and research reflects the author’s concerns and conclusions about the central question. Readers may draw other conclusions and perhaps use the issues and evidence presented here to stimulate further investigations.

Complex Pythagorean neutrosophic normal interval-valued set with an aggregation operators using score values

The complex Pythagorean neutrosophic normal interval-valued set approach solves the multiple-attribute decision-making problem. We introduce the new concepts such as complex Pythagorean neutrosophic normal interval-valued weighted averaging, complex Pythagorean neutrosophic normal interval-valued weighted geometric, complex generalized Pythagorean neutrosophic normal interval-valued weighted averaging and complex generalized Pythagorean neutrosophic normal interval-valued weighted geometric operator. We demonstrate that complex Pythagorean neutrosophic normal interval-valued set satisfy algebraic structures such as associative, idempotent, bounded, commutative and monotonic properties. Additionally, we develop algorithm and flowchart that solve problems using these operators. Examples of using enhanced score values and accuracy values in real-world environments are provided in this paper. Artificial intelligence refers to the simulation or approximation of human intelligence in machines. Its goals include computer enhanced learning, reasoning and perception. Artificial intelligence is being used today across different industries, from finance to healthcare. Agricultural robots have been described as being highly dependent on computer and machine tool technology. Four factors can be used to evaluate the quality of a robotics system: the controller’s sophistication, the software efficiency, the maximum moment of inertia, and the manufacturer’s reliability. The best alternative can be determined by comparing expert opinions to the criteria. Therefore, the parameter ∇ has a very significant impact on the results of the model. This comparison aims to prove that the models under consideration are valid and valuable by comparing them with the available and proposed models. In conclusion, the value of ∇ significantly impacts the model performance. Based on the comparison and sensitivity analysis, we conclude that the proposed aggregation operation is superior and more reliable than the existing one. The criteria were compared to the most appropriate options based on expert assessments.

THE IMPORTANCE OF MILITARY-PATRIOTIC UPBRINGING OF SCHOOLCHILDREN IN MODERN CONDITIONS

The article discusses the process of organizing military-patriotic upbringing for schoolchildren and emphasizes the significance of patriotism. Patriotism, being an integral part of military-patriotic upbringing, serves as a fundamental principle and the primary aspect of socializing an individual. The article aims to underscore the importance of military-patriotic education for schoolchildren in contemporary society. It outlines various extracurricular activities that can be implemented in schools to deepen students’ love for their homeland and national as well as universal values. Through these activities, students will come to appreciate the heroes among them and understand that protecting the motherland requires military patriotism. Additionally, the article briefly touches upon integrating information technologies into the educational system, acknowledging the 21st century as the era of computer technologies. Through various computer programs, teachers can introduce students to the golden pages of our history, the lives of heroes, the everyday life of today’s border guards, and the heroic stories of brave soldiers guarding the borders of the motherland and drawing those same borders. In the article, we also discuss the role and significance of the family because it is a powerful force and a primary focus of the educational system. Together with schools, families fulfill the sacred duty of educating literate and patriotic citizens who will become defenders of the homeland in the future. They are envisioned as the future Armenian soldiers and strong supporters of the motherland.

CONCEPTUAL METAPHORS OF ARTIFICIAL INTELLIGENCE AND AI DEVELOPMENT IN THE GUARDIAN NEWSPAPER

The whirlwind advent of ChatGPT in 2022 has marked a new age of artificial intelligence (AI), the general name for the technology that combines computer technology, big data bases and machines. This AI technology quickly makes its presence felt with hundreds of popular programs and chatbots such as the portrait-making AI diffusion art and the thesis-writing ChatGPT. This paper investigates the conceptual metaphors representing AI and AI development in The Guardian, a UK-based newspaper, to figure out how this technology and its growth have been introduced to ordinary people via mass media. Employing the Conceptual Metaphor Theory proposed by Lakoff &amp; Johnson (1980), this study found three AI-related conceptual metaphors, namely, AI IS A HUMAN BEING, AI IS AN ANIMAL and AI IS A NATURAL FORCE, which are realized by more than 100 linguistic expressions across 33 news articles. Also, this research found five conceptual metaphors related to AI development, namely AI DEVELOPMENT IS WAR, AI DEVELOPMENT IS A RACE, AI DEVELOPMENT IS A CONVERSATION, AI DEVELOPMENT IS A DANCE, AI DEVELOPMENT IS A GAME and these metaphors are manifested by approximately 40 linguistic expressions. This paper discusses the way that these metaphors could influence the way people and technology companies think about AI and AI development.