Digital Method Research Articles

Evaluating the Influence of Viral Marketing and Brand Awareness on Purchase Decisions a Study Tiktok Shop

This study examines the impact of Viral Marketing and Brand Awareness on Purchasing Decisions, individually and collectively. The quantitative study approach examines 90 consumers using the Tik Tok Shop in Tebing Tinggi. The sample was selected using a purposive sampling approach grounded in particular criteria. Data collection was conducted using an online questionnaire, and Data analysis was conducted via SPSS version 25. The findings indicated that Viral Marketing significantly influences Purchasing Decisions and Brand Awareness. Both Viral Marketing and Brand Awareness have a substantial and beneficial influence on Purchasing Decisions. This research enhances comprehension of The impact of digital marketing methods on consumer behavior in the era of social media.

Three-dimensional digital imaging analysis of the palatal bone thickness for orthodontic mini-implant insertion – determination of the safe zone and angulation

BackgroundIn order to successfully perform orthodontic mini-implant procedures successfully for the subsequent anchoring of orthodontic appliances, it is crucial to know the palatal bone thickness. This is usually assessed using two-dimensional radiographs. The purpose of this study was to use a three-dimensional digital imaging measurement method to provide information on palatal bone volume and bone thickness and to make recommendations on the optimal and safe insertion site and angle for palatal mini-implants.MethodsFor this observational, cross-section study, pre-existing cone beam computed tomography scans of 184 patients were converted into 3D Standard Tessellation Language (STL) models of the maxilla. The area between the canine and the first molar was divided into 6 regions of interest (ROIs), three on the left side of the palate and three on the right side. The bone thickness of the palate was analyzed volumetrically and linearly while simulating different mini-implant insertion angles of 0°, 10°, 20° and 30° degrees relative to the palatal surface.ResultsAmong the ROIs, the greatest mean bone thickness was observed in the region of the first premolars with a mean distance (MD) of 10.44 ± 2.53 mm and decreased from anterior to posterior (MD: 3.44 ± 1.16 mm). The highest volume (Vol) values were also measured in the anterior palatal region (Vol: 1127.26 ± 483.91 mm3), while there was also a decrease in the posterior region (Vol: 394.36 ± 180.22 mm3). Regarding the simulated palatal mini-implant insertion sites, the greatest bone thickness was found in the anterior region, at the level of the canines with an angle of 0° (MD: 12.25 ± 3.75 mm). In the more posterior region, at the level between the first and second premolars, the greatest bone thickness was observed at an angle of 30° (MD: 7.93 ± 3.81 mm). Gender differences were found.ConclusionThis clinical study showed that the paramedian region at the level of the first premolar is the safest site for orthodontic mini-implant placement as evaluated by three-dimensional measurements. The results showed that implant insertion angle, gender and age are important aspects to consider when planning and inserting orthodontic palatal mini-implants.Trial registrationN.a.

Evaluation of the accuracy of a simplified hybrid method versus the traditional digital method for measuring palatal volume

ObjectiveThis study aimed to compare a direct conventional 3D digital technique vis a vis a hybrid method in measuring palatal volume. Materials and methodsThirty maxillary casts were obtained from the records of patients undergoing orthodontic treatment and pre-conceived boundaries of the palatal vault were marked. Sample was categorised into Group I (Volume estimation using CBCT scan) and Group II (Volume estimation using hybrid method). Estimation of the palatal volume in this study involved filling the volume of interest in the palate with gypsum (Type IV) stone material and carefully carving according to the boundaries and anatomy. This positive reproduction of the palatal space was safely retrieved and then scanned in the NewTom GiANO HR Cone Beam Imaging setup. The obtained scan was analysed in NNT Software Version 3.10 and the volume of the palate was calculated. Two experienced orthodontists carried out the measurements to evaluate the inter and intra-observer reliability. This was compared with the palatal volume calculated by the conventional digital method using CBCT in the NNT Software. ResultThis study showed a consistent and narrow range of the confidence interval for palatal volume. Hence, the sample size was sufficient and had good precision. Considering a 95 % confidence interval, the intra-class correlation coefficient was robust (>0.9) for all measurements calculated by the hybrid method suggesting a high reliability. The mean difference in measurement of palatal volume (Group I vs, Group II) was 1.37 + 0.64 mm3 and the difference was statistically insignificant. Statistical t-test conducted between the two methods showed a p-value of 0.34, implying no statistically significant difference between the two methods. ConclusionThe hybrid method for evaluating the palatal volume is simple, accurate and comparable to the conventional digital method. A major advantage of this simplified method is that the patient is not exposed to any radiation of CBCT. Also, need for a specific skillset for digitally measuring the palatal volume is not a must.

An accurate semi-empirical model for PMT pulse signal analysis.

The energy information of pulse signals is significantly important for applications such as computed tomography (CT), positron emission tomography (PET), and research on defects in condensed matter. Time-over-threshold (TOT) and multi-voltage threshold (MVT) are commonly used digitization methods in sampling pulse signal. However, both approaches rely on a mathematical model of the pulse signal to derive energy information. This study proposes a semi-empirical mathematical model for pulse signals formation process in scintillation crystal-coupled photomultiplier tube(PMT) probes, by utilizing the CR-RC shaping method. This mathematical model accurately describes output of the PMT pulse signals. This study analyzes a substantial dataset of pulse signals, comparing the performance of the newly designed mathematical model with that of the double exponential function in terms of their ability to fit pulse signals. The results indicate that the mathematical model developed herein achieves an average R2 of 0.9255, significantly surpassing the 0.9155 of the double exponential function, thereby demonstrating its superior fitting efficacy.

Embracing pluralism: assessing the perceptions of different stakeholders on the effectiveness of advisory methods in Ontario

ABSTRACT Purpose Extension and advisory services (EAS) are crucial for farm success and rural well-being in Canada. Like elsewhere, Ontario’s EAS has transformed, embracing diverse providers and methods. While research on pluralistic EAS grows, little examines how stakeholders perceive the effectiveness of different methods. This study fills the gap, evaluating Ontario’s pluralistic EAS methods through key stakeholder perspectives. Methodology Using the Q-methodology, we conducted an online survey on Qualtrics with 49 purposively selected producers, advisors, and researchers and used PQMethod software to analyze their viewpoints. Findings The findings revealed three factors representing the respondents’ views about the usefulness of different advisory methods. The first factor focuses on personalized methods, while the second highlights digitally engaged methods. The third factor stresses traditional extension methods that include group and training-based activities. Researchers’ perspectives leaned towards digital methods, while producers emphasized personalized extension methods, and most advisors were loaded under traditional advisory methods. Practical implications Stakeholders value traditional and personalized extension methods for their interactivity and on-farm presence. The study suggests a personalized advice strategy integrating online, face-to-face, and group methods. Policy implications The findings provide insight for policymakers and practitioners to improve the effectiveness of pluralistic agricultural advisory service delivery by integrating various advisory methods. Theoretical implication This study enriches the discourse on pluralistic advisory systems by presenting stakeholder perspectives on method efficacy. Originality/value This unique study unveils multi-stakeholder views on advisory methods, aiding Ontario farmers to receive relevant, accurate information and meet their needs.

Digital Analysis Methods in Business-Processes and Projects in Digital Twins at Investment-Construction Companies

The article analyzes modeling of investment-construction company work from graph models to digital analogues. Such analysis is necessary in order to build economically grounded twin of the investment-construction company. The need to use advanced digital methods of business-analysis in conditions of real time was substantiated. It was demonstrated that elaboration of digital methods of business-analysis in projects and business-processes in investment-construction work is acute and leans against numerous factors. They are as follows: positive overseas experience in projecting and controlling processes; adjustment of this experience to specific features of project and business-process organization in Russia; use of digital imitation models of investment-construction enterprise in conditions of real time; introduction of digital methods of strategic and operative business-analysis of projects and business-processes into imitation model and digital twins at investment-construction enterprises; use of promising digital technologies in digital methods of business-analysis in projects and business-processes, for instance, analysis of big data, artificial neuron nets, cloud technologies, internet of things, virtual reality, augmented reality, technologies of register distribution, automation and robotics of business-processes, etc. Typical features of digital analysis built in digital twin for effective decision-making in management were identified. The article provided results of modeling visualization and digital analysis of business-processes.

Turning the Page on Hardcopy Risk Management Plan Educational Materials: Digitalization Made Possible.

'Risk Management Plan Educational Materials' (RMP EMs) are additional risk minimization measures (aRMMs) intended to prevent or reduce the occurrence of adverse reactions associated with the exposure to a medicine, or to reduce their severity or impact on the patient. While the healthcare sector is embracing various digital tools and platforms for educational and/or awareness building purposes, paper-based materials have remained the mainstay approach for implementation of aRMMs by pharmaceutical companies. Novartis in Singapore conducted a pilot on the feasibility of distributing electronic copies of RMP EMs (e-RMP). Post-pilot, e-RMP was officially implemented in Novartis Singapore. A year following the launch of e-RMP, a survey was performed with healthcare professionals (HCPs) to understand end-users' experience. The survey responses revealed a general preference by both HCPs and patients towards e-RMP. Digital methods of delivering educational aRMMs offer great benefits over traditional paper-based programs. e-RMP significantly reduces the time needed for updated RMP EMs to reach HCPs and their patients/caregivers. This is important to ensure that HCPs and patients/caregivers are made aware of any updates in key safety messages of the products in a timely manner to ultimately ensure patient safety. The successful transition to digital solutions requires purposeful collaborations between key stakeholders of the healthcare ecosystem including regulatory authorities, pharmaceutical companies, HCPs, patients and caregivers. This article aims to provide insights on the digitalization journey of e-RMP, a case study in Singapore, outlining the value but also some of the challenges faced during this transformation.

The use of artificial intelligence and digital technologies as a method of political influence on young people

The article describes the basic principles of using artificial intelligence and digital technologies in the context of identifying and countering foreign means of influencing young people in their own environment. The basic principles of the influence of digital technologies, digitalization in politics and its impact on youth and modern politics in general are revealed. The relevance of the article is determined by the fact that in the context of modern globalization and the development of information and communication technologies, foreign countries are increasingly using digital methods of influence aimed at influencing the youth of other countries, including the Russian one. This manifests itself as the spread of disinformation and propaganda, the organization of protest actions and the recruitment of young people into terrorist and extremist organizations, etc. Artificial intelligence and digital technologies can help Russia in countering foreign influence on young people. They can be used to analyze large amounts of data, create a monitoring system, and develop information campaigns.

Digital Public Consultation and the Opportunities for Participatory Democracy: An Exploratory Study

The decision-making process involves different stages in which the authorities should ensure that citizens’ views and concerns are voiced by encouraging citizens to become directly involved in policy areas and issues so that they can actively engage in collective public choices. Public consultation therefore plays a crucial role in promoting democratic values and strengthening the legitimacy of decision-making processes in governments and organizations. This study aims to analyze young people’s reaction to the general trend towards digitalization and the extent to which young people are willing to adopt new digital methods of public consultation. The results show that the digitalization trend is sparking enthusiasm for innovation and efficiency among our respondents, but they also highlight concerns about data security and the impact on jobs. Our study finds a generally positive attitude towards the use of online platforms for public consultations, highlighting the role of online platforms in increasing the trust of European citizens in the European legislature, but at the same time questioning the importance the European Union would attach to opinions expressed through digital platforms and the representativeness of the group of participants. The results of this study have strong administrative and managerial implications and can provide important insights into the search for solutions regarding the implementation of digitalization and online consultation in EU legislation.

Mesh Smoothing of 3D Prosthesis and Orthosis Models

Introduction. Formation of a contact surface in prosthetics and orthotics is crucial for the restoration of human musculoskeletal functions. This paper considers specific features of methods currently used for denoising of a 3D model surface obtained by optical scanning. An algorithm for manufacturing an individual prosthetic and orthopedic product is developed. The current literature reports no similar methods, which may be explained by the widespread use of gypsum technology for the manufacture of prostheses and orthoses.Aim. Research and development of digital filtration methods for 3D meshes obtained by optical scanning for further modeling of individual prosthesis and orthosis modules.Materials and methods. It is proposed to optimize the pre-processing stage of 3D scanned models by applying denoising and smoothing processes. In total, 50 optical 3D scans were selected for testing via the following denoising algorithms: bilateral filtering, vertex-based anisotropic smoothing, mean and median filtering applied to face normals.Results. The study was conducted using 3D scans of lower limb stumps and Chenault brace orthoses and corsets provided by the Institute of Prosthetics and Orthotics, Albrecht Federal Scientific and Educational Centre of Medical and Social Expertise and Rehabilitation. А method for denoising and smoothing of the 3D model surfaces for the manufacture of prosthetic and orthopedic products is proposed. The SNR metric difference SNR – δ-SNR (with averaging by scans and SNR values) and average execution time were calculated. The bilateral filtration method with δ-SNR = 11.3362 dB and a runtime of 8.8900 s showed the highest efficiency.Conclusion. The proposed methods for the pre-processing stage of 3D optical scans showed high efficiency in the formation of 3D models of prosthesis and orthosis modules. The results obtained can be used for automating the process of manufacturing various prosthetic and orthopedic products, which is particularly relevant in the context of the modern geopolitical situation.

Revolutionizing Dental Restorations: The Impact of Digital Impressions on Conventional Techniques and Modern Implant Dentistry

Impression techniques in dentistry are fundamental for creating precise molds of a patient’s oral structures and crucial for fabricating dental restorations such as crowns, bridges, and dentures. This review explores both conventional and digital techniques, highlighting the growing prominence of digital impressions. Digital methods, which utilize intraoral scanners and CAD/CAM systems, offer enhanced precision, patient comfort, and efficiency compared to traditional methods. They are particularly beneficial for implant procedures and complex restorations. While conventional techniques remain widely used due to their cost-effectiveness and versatility, digital impressions are revolutionizing modern dentistry by streamlining workflows, improving accuracy, and facilitating better clinical outcomes. In summary, digital impressions simplify the process, and accuracy, increase patient comfort, and result in improved clinical outcomes in implant dentistry. They play a vital role in contemporary implant procedures, covering everything from initial planning to the final restoration.

Evaluation of the stress-strain state of the RC beam with the use of DIC

Abstract The article presents the results of adapting the digital image correlation method for the possibility of diagnosing reinforced concrete structures. Reinforced concrete (RC) bending elements are the most widely used in construction practice, which determines the importance of reliable estimation of their stress-strain state. The purpose of this study includes reliable theoretical and experimental investigation of the strength and deformability parameters of the RC beam. The experimental study was conducted using digital image correlation and sub-micron contactless gauges. Experimental data was verified with the calculation of the stress-strain state of the RC beam according to DBN V.2.6-98:2009 and Eurocode 2 and the finite-element modelling (FEM). As a result, the values of deflections, concrete and rebar strains were obtained and presented as corresponding diagrams. The results of all the methods are within the same ranges. Also, the form and character of corresponding diagrams are very similar. The indicated deviations were within acceptable limits. It was noted that the theoretical calculation generally provides lower strain values, which is a satisfactory result, as it indicates the bearing capacity reserves provided by the current regulations. The propagation of cracks was monitored during the experiment and the measured cracks opening was compared with theoretical assumptions. Theoretical values are higher than experimental, which shows certain conservativity of valid normative regulations. The experimental and theoretical results were in good correspondence, which confirms their reliability. It was concluded, that the proposed in the study complex theoretic-experimental approach provides essential information about the strength and deformability of the structure.

Development of Digital Prediction Methods for Viscoelastic Processes of Polymer Textile Materials

Development of Digital Prediction Methods for Viscoelastic Processes of Polymer Textile Materials

Level of knowledge and use of digital payment methods in Paraguay

La sociedad está inmersa en lo digital y el empleo de medios digitales de pagos permitió dinamizar el comercio electrónico. En Paraguay, fuera de las grandes urbes, pagar en efectivo sigue siendo el más utilizado, esto por falta de una educación digital en los habitantes; aunque, se espera que esta situación vaya revirtiéndose y se impongan los medios digitales de pagos. La metodología tuvo enfoque cuantitativo de tipo descriptivo, no experimental y de corte transversal, se utilizó una encuesta estructurada; y, los datos obtenidos fueron procesados en planilla electrónica y SPSS. La muestra por conveniencia la conforman 724 ciudadanos paraguayos de todos los departamentos del país. A través del estudio se pudo identificar lo siguiente: Existe una percepción heterogénea sobre los medios digitales de pago; 46,5% utiliza los medios digitales de pagos; 60,2% de los que utilizan medios digitales de pagos, cuentan con banca digital; 70,8% de los medios digitales de pagos se utilizan para pagar los servicios de agua, luz y telefonía; 83,6% de los medios digitales de pagos son utilizados para realizar pagos o transferencias; 23,5% de los encuestados realizó compras por internet. Además, se confirmó que no existe una relación significativa entre sexo, edad, nivel de ingreso, estudios realizados ni lugar de residencia y el uso de los medios digitales de pagos. Pero, si existe una relación significativa entre el nivel de ingreso, lugar de residencia y estudios realizados con el grado de confianza en los medios digitales de pago.

Digital Image Processing to Detect Adaptive Evolution.

In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data are limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multiscale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.

Comparative Effectiveness of Health Communication Strategies in Nursing: A Mixed Methods Study of Internet, mHealth, and Social Media Versus Traditional Methods

Abstract Background Effective communication is vital in health care, especially for nursing students who are the future of health care delivery. In Iraq’s nursing education landscape, characterized by challenges such as resource constraints and infrastructural limitations, understanding communication modalities is crucial. Objective This mixed methods study conducted in 2 nursing colleges aims to explore and compare the effectiveness of health communication on the web, through mobile health (mHealth) applications, and via social media among nursing students in Iraq. The research addresses a gap in understanding communication modalities specific to Iraq and explores the perspectives, experiences, and challenges faced by nursing students. Methods Qualitative interviews were conducted with a purposive sample (n=30), and a structured survey was distributed to a larger sample (n=300) representing diverse educational programs. The study used a nuanced approach to gather insights into the preferences and usage patterns of nursing students regarding communication modalities. The study was conducted between January 12, 2023, and May 5, 2023. Results Qualitative findings highlighted nursing students’ reliance on the web for educational materials, the significant role of mHealth applications in clinical skill development, and the emergence of social media platforms as community-building tools. Quantitative results revealed high-frequency web use (276/300, 92%) for educational purposes, regular mHealth application usage (204/300, 68%) in clinical settings, and active engagement on social media platforms (240/300, 80%). Traditional methods such as face-to-face interactions (216/300, 72%) and practical experiences (255/300, 85%) were preferred for developing essential skills. Conclusions The study underscores nursing students’ preference for an integrated approach, recognizing the complementary strengths of traditional and digital methods. Challenges include concerns about information accuracy and ethical considerations in digital spaces. The findings emphasize the need for curriculum adjustments that seamlessly integrate diverse communication modalities to create a dynamic learning environment. Educators play a crucial role in shaping this integration, emphasizing the enduring value of face-to-face interactions and practical experiences while harnessing the benefits of digital resources. Clear guidelines on professional behavior online are essential. Overall, the study expands the understanding of communication modalities among nursing students in Iraq and provides valuable insights for health care education stakeholders globally.

The Impact of Advertising on the Popularity of Music Works

Not only is advertising a powerful tool for businesses and marketing, it also shapes consumers’ behavior in the music industry as well. This article deals with the influence of traditional and digital advertising methods on the popularity of musical productions. This research seeks to navigate the relationship between the intensity of advertising and the popularity of the music work through the examination of several case studies and data from different genres of music. It highlights the roles of several media channels and platforms including streaming services and social media in making songs go viral as well as the economic impacts on the musicians and record companies. The study provides insight into the problem of excessive commercialization in a digital sphere as a consequence of modern overexposure of the music industry. This article concludes with recommendations for maximizing the effects of advertising on musical productions’ popularity while maintaining artistic integrity.

Optimization of energy acquisition system in smart grid based on artificial intelligence and digital twin technology

In response to the low operating speed and poor stability of energy harvesting systems in smart grids, an energy harvesting optimization method based on improved convolutional neural networks and digital twin technology is proposed in the experiment. Firstly, a smart grid data transmission framework integrating digital twin technology is proposed. A digital twin mapping method based on time, data, and topology structure is used to realize the digital twin mapping at the device level of power grid. Through data synchronization and interaction between the physical power grid and the digital twin model, the operational efficiency and reliability of the power grid are improved. Then, the classical convolutional neural network and attention mechanism are used to comprehensively analyze the physical topology data in the smart grid energy acquisition system. The improved lightweight target detection model is combined to monitor the equipment status of the smart grid and extract key features. Simultaneously utilizing convolutional attention mechanism to dynamically adjust the feature weights of channels or spaces, completing the preprocessing of energy harvesting data. Finally, combined with energy harvesting and power grid switching system, the process of energy harvesting and power grid operation are optimized together. On the training and validation sets, when the channels exceeded 60, the proposed method achieved a system energy efficiency of 55% during operation. The system energy efficiency of the other three comparative algorithms was all less than 40%. In practical applications, as the energy transfer loss increased to 1.0, the system throughput increased to 50 bits. The electricity needs of different users were met, and the difference between power allocation and optimal power allocation was small, which was very reasonable. This proves that the research has effectively optimized the energy harvesting system in the smart grid, improving the efficiency and reliability of the system in practical applications of the smart grid. At the same time, in the increasingly severe energy problem, this system can further provide technical references for the utilization of renewable energy and help achieve the goal of sustainable energy.

A digital twin modeling method of production lines based on flexible manufacturing

A digital twin modeling method of production lines based on flexible manufacturing

Digital twin modeling method for environmental governance of abandoned landfills based on multi-agent systems

Background It is currently observed that some landfills are experiencing severe overloading, with some having ceased operations. However, they continue to threaten the environment and public health. There is an urgent need for governance, although the process is complex and requires more intelligent and efficient governance approaches. Methods This study explored the application of digital twin technology based on multi-agent systems in the environmental governance of abandoned landfills. This paper addresses the demands of landfill governance by integrating modules, including twin models, mechanisms, and big data, and integrating each module with corresponding intelligent agents, forming a thoughtful, collaborative, and adaptive digital twin agent system. Results This method can collect and analyze on-site data more systematically and provide feedback to management personnel to guide the adjustment of on-site plans and improve the on-site management efficiency by 30%. Conclusions Through application cases, the operation process of this system in specific landfill environmental governance scenarios was demonstrated, confirming its superiority in environmental governance. This system can facilitate environmental monitoring, intelligent analysis, and decision control during the governance of abandoned landfills.