Digital Generation Research Articles

71‐1: CMOS Backplane Technology and Its Challenge for µLEDoS AR/XR Display

This paper introduces the latest CMOS (Complementary Metal‐Oxide‐Silicon) backplane technology for µLEDoS AR/XR display engines. The backplane supports a display resolution of 1,280RGB x 720 and has been implemented on a 28nm Fully Depleted Silicon on Insular (FD‐SOI) CMOS process in order to meet the requirements such as performance, power, and pixel size. The area of a single pixel is 4.95µm x 4.95µm achieving higher than 5,000 PPI in RGB‐color mode. Each pixel contains 3 independent sub‐pixel drivers and one dependent driver assigned for a red LED. Each sub‐pixel driver includes a 10‐bit video SRAM memory, PWM (Pulse Width Modulation) control logic block, a constant current generator, and LED driver stage to drive red, green, or blue LEDs. The backplane also integrates necessary image processing functions such as De‐mura compensation, dead‐pixel compensation, and digital gamma generation. The top surface of the backplane wafer is also prepared for a wafer‐to‐wafer hybridization bonding between the CMOS wafer and an LED wafer.

Digital Camouflage Generation Based on an Improved CycleGAN Network Model

Abstract This paper proposes a digital camouflage generation method based on an improved CycleGAN to produce camouflage patterns with a high degree of fusion with the background and realistic texture details. Firstly, a SE-ResNet network structure is constructed by combining the residual network ResNet with the channel attention mechanism SENet, enabling flexible adjustment of channel weights to effectively extract crucial channel features and enhance the network's perception capability of important information in images. Secondly, a color preservation loss is introduced to improve the adversarial loss function, thereby avoiding training instability and fluctuation in pattern quality. Experimental results demonstrate that the camouflage patterns generated using the proposed method achieve a Structural Similarity Index (SSIM) of 0.77 and a Peak Signal-to-Noise Ratio (PSNR) of 18.9, representing improvements of 0.27 and 3.3, respectively, compared to the original CycleGAN. This method can generate digital camouflage patterns with richer details, textures, and high fusion with the background.

Artificial Intelligence and Musicking

Artificial intelligence (AI) deployed for customer relationship management (CRM), digital rights management (DRM), content recommendation, and content generation challenge longstanding truths about listening to and making music. CRM uses music to surveil audiences, removes decision-making responsibilities from consumers, and alters relationships among listeners, artists, and music. DRM overprotects copyrighted content by subverting Fair Use Doctrine and privatizing the Public Domain thereby restricting human creativity. Generative AI, often trained on music misappropriated by developers, renders novel music that seemingly represents neither the artistry present in the training data nor the handiwork of the AI’s user. AI music, as such, appears to be produced through AI cognition, resulting in what some have called “machine folk” and contributing to a “culture in code.” A philosophical analysis of these relationships is required to fully understand how AI impacts music, artists, and audiences. Using metasynthesis and grounded theory, this study considers physical reductionism, metaphysical nihilism, existentialism, and modernity to describe the quiddity of AI’s role in the music ecosystem. Concluding thoughts call researchers and educators to act on philosophical and ethical discussions of AI and promote continued research, public education, and democratic/laymen intervention to ensure ethical outcomes in the AI music space.

Pathogenesis of Subjectivation in Post Digital Generation

Pathogenesis of Subjectivation in Post Digital Generation

Global Copyright Consortium: Empowering Decentralisation with Authority - Backed Blockchain

Abstract: Digital images are transferred with ease through the network. Many users are using the images without the knowledge of the owners. Zero watermarking does not alter the original information contained in vector map data and provides perfect imperceptibility. The use of zero watermarking for data copyright protection has become a significant trend in digital watermarking research. However, zero watermarking encounters tremendous obstacles to its development and application because of its requirement to store copyright information with a third party and its difficulty in confirming copyright ownership. However, traditional digital image generation methods have high operational requirements for designers due to difficulties in collecting data sets and simulating environmental scenes, which results in poor quality, lack of diversity, and long generation speed of generated images, making it difficult to meet the current needs of image generation.

Analysis of The Influence of Electronic Wallet Usage, Lifestyle, And Financial Literacy on The Consumptive Behaviour of Generation Z Workers in DKI Jakarta

This study investigates the influence of electronic wallet usage, lifestyle, and financial literacy on consumptive behavior among Generation Z workers in DKI Jakarta. With a population comprising about one-third of DKI Jakarta's total population, Generation Z is notably technologically adept, often referred to as the Internet or Digital Generation. Employing a quantitative approach, the research utilizes Partial Least Square Structure Equation Modeling (PLS-SEM) and collects data from 407 respondents through an online questionnaire. Findings reveal a positive and significant association between electronic wallet usage and consumptive behavior, as well as lifestyle and consumptive behavior. However, financial literacy exhibits an insignificant and negative impact on consumptive behavior. These insights contribute to understanding the financial behavior of Generation Z workers and may aid in fostering more prudent financial management practices among this demographic.

Uncovering Gen Z’s Styles: A Deep Dive into the Consumer Behavior in the Fashion Industry

As the first digital generation, Gen Z individuals exhibit unique characteristics and preferences that challenge traditional marketing strategies It appears that Gen Z has very different shopping habits from previous generations. This study seeks to fill this gap by conducting a thorough investigation into various aspects of Gen Z's relationship with fashion, including their shopping habits, brand preferences, influences, sustainability concerns, and how they express themselves through clothing and style choices. The study focuses only on Generation Z individuals aged 12 to 27 who actively shop for fashion items in the fashion industry and who are living around Noveleta, Cavite. The study covers three years to capture information about recent trends and changes. Due to time limitations, the study restricted data collection to interviews, excluding other methods. It will limit the investigation to specific fashion product categories, such as clothing and footwear. This study used qualitative research given that it aims to investigate how Gen Z consumers engage in the fashion industry. In this research, the researchers conduct a thematic analysis to interpret the collected data. The results of the study are, Gen Z expressed their individuality through different fashion style by creating unique outfits based on what they prefer. Social media is the most common factors influencing Gen Z’s decisions to purchase fashion products. Gen Z expressed a strong preference for sustainable and ethically produced fashion products that align with their values and beliefs. Lastly, affordability constraints are the most common experiences and challenges faced by Gen Z consumers.

Lead Generation Methodologies and Strategies

The research challenge is first articulated, along with the necessity for more investigation into lead generation techniques and methodologies across sectors. The project's focus on the vital role that lead generation plays in fostering corporate sustainability and growth. This study intends to provide insights and solutions applicable to a wide range of sectors by analyzing the complexities and difficulties related to lead generation. The research explores traditional and digital lead generation channels commonly utilized in the automotive sector, including but not limited to, dealership networks, online advertising, social media marketing, content marketing, search engine optimization (SEO), and email campaigns. It evaluates the effectiveness of each method in terms of lead quantity, lead quality, cost-effectiveness, and conversion rates, considering their applicability to Suzuki's marketing goals and budgetary constraints. The present study in automobile sector with lead generation strategy is essential for car businesses to thrive in a competitive market. It helps identify effective ways to attract and convert potential buyers, ensuring sustained sales growth. This research aims to uncover key strategies and insights to improve customer acquisition in the automotive industry. The study incorporates statistical tools like 5-point Likert scale, Anova and Regression techniques are used with necessary recommendations.

Parameter subset reduction for imaging-based digital twin generation of patients with left ventricular mechanical discoordination

BackgroundIntegration of a patient’s non-invasive imaging data in a digital twin (DT) of the heart can provide valuable insight into the myocardial disease substrates underlying left ventricular (LV) mechanical discoordination. However, when generating a DT, model parameters should be identifiable to obtain robust parameter estimations. In this study, we used the CircAdapt model of the human heart and circulation to find a subset of parameters which were identifiable from LV cavity volume and regional strain measurements of patients with different substrates of left bundle branch block (LBBB) and myocardial infarction (MI). To this end, we included seven patients with heart failure with reduced ejection fraction (HFrEF) and LBBB (study ID: 2018-0863, registration date: 2019–10–07), of which four were non-ischemic (LBBB-only) and three had previous MI (LBBB-MI), and six narrow QRS patients with MI (MI-only) (study ID: NL45241.041.13, registration date: 2013–11–12). Morris screening method (MSM) was applied first to find parameters which were important for LV volume, regional strain, and strain rate indices. Second, this parameter subset was iteratively reduced based on parameter identifiability and reproducibility. Parameter identifiability was based on the diaphony calculated from quasi-Monte Carlo simulations and reproducibility was based on the intraclass correlation coefficient (ICC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${ICC}$$\\end{document}) obtained from repeated parameter estimation using dynamic multi-swarm particle swarm optimization. Goodness-of-fit was defined as the mean squared error (χ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{{\\chi}}}^{{2}}$$\\end{document}) of LV myocardial strain, strain rate, and cavity volume.ResultsA subset of 270 parameters remained after MSM which produced high-quality DTs of all patients (χ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{{\\chi}}}^{{2}}$$\\end{document} < 1.6), but minimum parameter reproducibility was poor (ICCmin\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{ICC}}_{{min}}$$\\end{document} = 0.01). Iterative reduction yielded a reproducible (ICCmin\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{ICC}}_{{min}}$$\\end{document} = 0.83) subset of 75 parameters, including cardiac output, global LV activation duration, regional mechanical activation delay, and regional LV myocardial constitutive properties. This reduced subset produced patient-resembling DTs (χ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{{\\chi}}}^{{2}}$$\\end{document} < 2.2), while septal-to-lateral wall workload imbalance was higher for the LBBB-only DTs than for the MI-only DTs (p < 0.05).ConclusionsBy applying sensitivity and identifiability analysis, we successfully determined a parameter subset of the CircAdapt model which can be used to generate imaging-based DTs of patients with LV mechanical discoordination. Parameters were reproducibly estimated using particle swarm optimization, and derived LV myocardial work distribution was representative for the patient’s underlying disease substrate. This DT technology enables patient-specific substrate characterization and can potentially be used to support clinical decision making.

A trust management solution for 5G-based future generation Internet of Vehicles

In recent years, 5G Internet-of-Vehicles (IoV) related standards have drawn attention in both academia and industry for supporting an efficient and reliable communication among vehicles in the network. However, notice that 5G-IoV related issues are defined as critical in both real and cyber space environments, as malfunctioning in such systems could cause traffic paralysis, serious accidents, and privacy leaks. Therefore, in order to overcome these challenges, a trusted and ideal framework is proposed using Dempster–Shafer Theory (DST), which is combined with a recommender mechanism in order to identify several DDoS threats. The major trust elements in order to identify the legitimacy of a node include frequency statistics, trust factor, residual energy, and trust policy. The proposed trusted mechanism is designed to provide an improved and efficient security solution by avoiding intruders which attempt to disrupt a 5G-IoV network. The proposed mechanism is further analyzed against several security measures, and validated using traditional security schemes in IoV environments.

The Digital Competences Necessary for the Successful Pedagogical Practice of Teachers in the Digital Age

The digital transformation of society is a reality. Technology is becoming integral to people’s daily lives and children are growing up in the digital age. The education systems have to reflect and adapt to the new digital reality to effectively engage and prepare students for the future. Teachers have to possess digital competences at a high level, meaning that they are successfully able to use digital tools and technologies in their teaching practices. Digital competences include digital literacy, experience using educational software and platforms, and the ability to seamlessly integrate information and communication technologies (ICT) into the organization of educational activities. The current paper aims to study the opinion of teachers in Bulgarian schools regarding the possibilities of using digital technologies to achieve educational goals and the extent to which teachers integrate digital tools in their teaching activities. Teachers’ opinions about the need for specific digital competences are important. The results of the survey show that teachers in Bulgaria actively use digital technologies in their daily teaching activities (84.8%) in order to create and provide learning content to students and to provoke their active participation, and is a convenient tool for evaluating their students’ knowledge and skills and for providing effective feedback. The conducted research also identifies the necessary competences that teachers of the digital generation of learners need—skills and competences for developing authored electronic resources in various formats for students with different learning styles, as well as for working in online environments—individually and collaboratively with other teachers.

FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonization and smart modeling of the data to foster advanced AI analytical processes, which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the satellite imagery data and the flood risk assessment processes. The utilization of those models reinforces the fusion and homogenization of diverse information and data, facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework is developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customized and applicable easily to support the water data management processes effectively.

Artistic Virtual Reality Scene Analysis Taking into Account the Interactive Digital Media Pattern Generation Technology

With the development of science and technology and the continuous strength of Chinese spiritual civilization, digital media patterns have penetrated into various fields and played a central role in them. This article studies the endless emergence of various new media, and the channels of information dissemination are becoming more and more abundant. With the development of science and technology, new media are gradually derived, such as: IPTV, electronic magazines, etc., which have developed on the basis of traditional media. But there is a qualitative difference from traditional media. Digital media has a profound impact on mass society.This article proposes that digital media has become the most important means of communication in the information society. The digital media creative industry and the country's economic development have formed a close relationship of interdependence and mutual promotion. Based on the interactive digital media model generation technology, the research of artistic virtual and real scene analysis is the main issue today. The experimental results of this paper show that through the experimental investigation and analysis in 2019 and 2020, it is found that the application trend of company A and B in the virtual reality situation has increased significantly. The application rate of company A and B in 2019 reached about 43%, but the trend is not unstable. However, in 2020, it can be clearly seen that the application rate of companies A and B in applying digital media patterns to virtual and real scenarios has stabilized, exceeding 35% every month. It can be seen in the text below that when the four models are in different periods, the value of the optimal solution is different, and when the model is at 0.1 and 31, the optimal solution appears.Experiments show that digital media is widely used in the analysis of virtual and real scenarios. Based on the new research field formed by the fusion and intersection of digital media patterns, starting with the changes in the main body, objects, tools and forms of virtual and real scene communication in the context of digital media, it conducts in-depth research on the creation of artistic virtual and real scenes from many aspects.

A Digital Animation Generation Model Based on Cycle Adversarial Neural Network

This paper proposes a digital animation generation model based on Cycle Adversarial Neural Network (CycleGAN). Compared with the classical CycleGAN, this research presents a multi-attention approach to enhance the network’s generalization. Specifically, a style enhancement module and a style cross-attention mechanism are introduced into the generator network structure, which enables the model to better parse the structural information of the content image and realize the accurate matching of content features and style features. Furthermore, the introduction of a multi-scale discriminator with a fused attention mechanism enhances the preservation of content information from the source image in the output animated image. The experiments conducted in this study demonstrate that the model proposed in this paper exhibits superior performance in generating digital animation. This model not only enhances the realism and variety of the generated effects, but also achieves significant improvements in the coherence and stability of long time-series animation. The contribution of this paper lies in the introduction of the multi-attention mechanism, which enhances the generalization of the network and is of great theoretical and practical significance for the development of the field of digital animation generation.

Association of Childhood Attention Deficit/Hyperactivity Disorder With Adolescent Traditional and Cyberbullying Victimization in the Digital Generation: A Population-Based Cohort Study

PurposeThis population-based cohort study aimed to examine the association with childhood attention deficit/hyperactivity disorder (ADHD) and bullying experiences during adolescence among Digital Generation individuals, exploring both traditional and cyberbullying. MethodsThis study included data from 15,240 participants, collected from the Taiwan Adolescent to Adult Longitudinal Study project. Participants, initially in seventh and 10th grade in 2015, were selected through a multistage stratified sampling approach. Self-report questionnaires assessed traditional and cyberbullying victimization experiences during adolescence, with 5-year longitudinal follow-up. Childhood ADHD diagnoses were identified by linking data to Taiwan's National Health Insurance Research Database from 2000 to 2015. Logistic regression models were employed to examine the relationship between childhood ADHD and bullying victimization while controlling for relevant covariates. ResultsIndividuals diagnosed with childhood ADHD exhibited a significantly higher likelihood of experiencing bullying during adolescence (adjusted odds ratio (aOR) = 1.52, 95% confidence interval (CI): 1.28–1.80). This association extended to various forms of bullying, including physical (aOR = 1.42, 95% CI: 1.20–1.68), verbal (aOR = 1.42, 95% CI: 1.20–1.67), relational (aOR = 1.45, 95% CI: 1.22–1.71), and cyber (aOR = 1.35, 95% CI: 1.14–1.61). Additional factors positively associated with bullying victimization included male, binge drinking, and depression, while a positive campus atmosphere was protective against bullying. However, there is no evidence for interactions between these factors and ADHD in their associations with bullying. DiscussionChildhood ADHD increases the risk of both traditional and cyberbullying during adolescence. Recognizing this risk is essential for targeted interventions and further research on underlying mechanisms.

Design and Implementation of a Digital Function Signals Generator using FPGA

Design and Implementation of a Digital Function Signals Generator using FPGA

Blockchain Targets Integrated IoT for Smart Healthcare Systems - A Bibliometric Analysis

Blockchain technology and the Internet of Things (IoT) for smart healthcare systems has emerged as a promising area of research, as evidenced by a bibliometric analysis. This analysis explores the scholarly literature on the integration of blockchain and IoT in healthcare, identifying key trends, influential publications, and research directions. By leveraging blockchain's decentralized and immutable nature alongside the IoT's ability to collect and transmit real-time health data from various devices, smart healthcare systems aim to enhance data security, interoperability, and patient privacy. Bibliometric analysis provides valuable insights into the evolution of research in this field, highlighting emerging topics, interdisciplinary collaborations, and potential applications that can revolutionize healthcare delivery and management in the future. This paper introduces the Weighted Key Signature for Smart Healthcare Systems (WKSS), a framework designed to optimize healthcare operations within smart environments. With advanced technologies such as blockchain, Internet of Things (IoT), and integration technologies, WKSS aims to improve patient care, resource utilization, and overall healthcare system efficiency. The framework encompasses key components including digital signature generation, computational efficiency, and bibliometric analysis to provide insights into emerging trends and key contributors within smart healthcare systems. Through a comprehensive analysis, including simulations and bibliometric studies, this paper demonstrates the effectiveness of WKSS in reducing patient waiting times, enhancing resource utilization rates, and improving healthcare provider efficiency. Through simulations and bibliometric analysis, significant improvements were observed in key metrics. The average patient waiting time decreased from 45 to 34 minutes, resource utilization rates increased from 70% to 85%, and examination room occupancy rose from 60% to 75%. Additionally, physician and nurse utilization rates improved from 80% to 90% and from 75% to 85%, respectively.

Peculiarities of online communication of trade union organizations with a youth audience

In a rapidly changing system of labor relations, trade union organizations increasingly recognize the importance of involving a young generation to maintain the stability of their functioning and effectiveness. At the same time, this social group is one of the most unprepared in terms of socio-legal and economic understanding of the essence of professional activity. Hence, it is obvious that both sides need each other. However, traditional means of mass information and mobilization no longer resonate with the digital media generation. Social networks come to the fore, specifically the Chinese platform TikTok. It has a high potential for dissemination of information and popularization of trade union organizations. The main purpose of this research paper is to explore the agenda for the relevant subject matter in this application. The main method is content analysis. Search requests were made using the following keywords: trade union (English language), związek zawodowy (Polish language) and profspilka (Ukrainian language). This way let us to expand the meaning and strengthen the weight of the results. Among other things, thematic content, content producers and means for its formation are determined. In conclusion, trade union organizations have already noticed the potential of the platform for communication with young people. Nonetheless, they have just begun to introduce this audience to their activities.

Development of digital literacy of a future educational psychologist in the process of professional training

Relevance. The relevance of the study is determined by the rapid digitalisation of society, which puts forward the need to revise educational programmes to train multifunctional specialists in the educational field who are able to use digital tools in their professional activities, and productively interact with the �digital generation� of students. Purpose. The purpose of the research is to find effective pedagogical strategies for the development of digital literacy among future specialists. Methodology. The study employed a qualitative combination of causal analysis, induction, and synthesis to examine modern approaches to digital literacy development. A pedagogical experiment was conducted, utilizing survey methods and control groups to assess students' digital literacy levels. This experiment also aimed to evaluate the effectiveness of pedagogical strategies in cultivating digital skills among future specialists. Results. Consideration of the theoretical basis for the research problem showed that the digital literacy of an educational psychologist is based on the ability to implement their knowledge of digital technologies and resources in professional activities. In the course of the study, the importance of an innovative approach in the development of digital literacy of students during their studies at the university was argued. In addition, the analysed modern research on digital literacy in the educational sphere helped to identify current problems affecting the quality of development of students� digital competencies. In this regard, an elective special course was developed and introduced into the educational programme. Conclusions. The study showed that integrating innovative methods and digital technologies in educational psychologists' training significantly improves their digital literacy and professional competencies, as demonstrated by experimental group outcomes. Keywords: innovation; educational strategy; information competencies; differentiated approach; communication skills

Simulation study of digital waveform-driven quadrupole mass filter operated in higher stability regions for high-resolution inductively coupled plasma mass spectrometry.

The use of a frequency-scanned digital quadrupole mass filter (QMF) with varying duty cycles shows promise for application as a high-resolution mass analyzer design for inductively coupled plasma mass spectrometry (ICP-MS). High resolution in ICP-MS is important to overcome isobaric polyatomic interferences. Here, we explore the possibility and the characteristics of using a digital quadrupole operating in higher stability regions for ICP-MS. We perform computational simulations in SIMION of a digital QMF that is operated by scanning the frequency of the digital waveform at a fixed driving voltage and various duty cycles. For ions in the atomic mass range (7-238 m/z), we investigate the expected resolution, transmission, fringe field effects, and ion trajectories. We compare different characteristics between sine and digital waveform QMF. Within the capability of current digital waveform generation technology, a digital QMF can produce variable mass resolution, from several hundred to more than 10 000. This mass resolution covers the low, medium, and high resolutions that are typical for sector-field ICP-MS. Additionally, simulations suggest that transmission of the QMF remains high at high resolution. For example, with 87.50/12.50 duty cycle (zone 4,1), resolution at 10% peak width is 10420 for m/z 80. The transmission through the quadrupole, which is constant for all isoenergetic ions, is ~2.5%, and most ion loss is due to the defocusing effects of the fringe field. Compared to sinusoidal QMFs, ions need many fewer cycles in the digital QMF to obtain high resolution. The results demonstrate that the use of a frequency-scanned, duty-cycle-modulated digital QMF as the mass analyzer for ICP-MS has the potential to produce high resolution while maintaining considerable transmission, thus overcoming most spectral interferences in elemental MS.