Digital Method Research Articles

Programmable mechanical responses of a hybrid star-rhombus honeycomb based on digital design method

Hybrid honeycombs with programmable mechanical responses have received widespread attention due to their multifunctionality and superior mechanical properties. To improve the tunability of the hybrid honeycomb, a hybrid star-rhombus honeycomb (HSRH) is designed using a digital design method. Different coding strategies are obtained by programming the distribution position of the rhombic structure inside the star-shaped honeycomb. HSRH with different coding strategies are designed by coding “0″ (unreinforced structure) and “1″ (reinforced structure). The compressive stress, Poisson's ratio and energy absorption of HSRH are investigated by experiments and numerical simulations. The results show that HSRH produces ordered deformation in compression with multi-plateau characteristics. HSRH has superior energy absorption in the X direction than in the Y direction. The specific energy absorption can be regulated between 2.41 - 5.02 J/g and 1.57–4.29 J/g in the X and Y directions, respectively. HSRH with unidirectional and bidirectional filling strategies exhibit a double-plateau feature in the X and Y directions, while the HSRH with hierarchical filling strategies has a three-plateau feature in the X direction. The filling ratio plays a decisive role in the energy absorption of honeycomb and has a positive correlation with the energy absorption properties. Furthermore, diverse deformation modes can be customized by introducing pattern-coding strategies. The codable deformation mode and programmable energy absorption of the HSRH are achieved by controlling the filling ratio and coding strategy (i.e., coding the number and location of embedded rhombic structures). This study provides a digital method for the design of programmable hybrid honeycombs and facilitates their application in multi-tasking energy absorbers.

PELATIHAN METODE TEMATIK DIGITAL QUR`Ä€N BAGI TUTOR PAI UPI UNTUK MENANGKAL INTOLERANSI BERAGAMA PADA MAHASISWA

Various studies have found that around 50% of Indonesian students and university students are intolerant. Other research results show that students are more intolerant of fellow Muslims from different schools of thought. The roots of intolerance are twofold. First, they misunderstand the meaning of believer and disbeliever in the Qur’ān. Second, they misunderstood the basics of other religions and schools of thought. The training aims to provide digital thematic methods of the Qur’ān to build substantive religiosity and religious tolerance for PAI tutors. The training method uses lectures, questions and answers, discussions, demonstrations, implementation exercises, and small group guidance via zoom. The training participants were 50 prospective PAI tutor students. The training was successful because most of the participants: First, they were able to implement the Thematic digital Qur`ān method; second, looking at the meaning of believing-unbeliever refers to good and evil characters, not referring to religious identity; and third, to better understand the implications of religion directly from the Qur’ān in a substantive and tolerant manner.

Speckle reduction in digital holography with Non-local means filter based on the structural similarity

Speckle noise limits the application of digital holography across various fields. This paper proposes a Non-local means filter method to suppress speckle noise by determining the weight of each traversed pixel based on the structural similarity between image blocks centered on the target and traversed pixels. Experimental results show that, compared to other typical digital image processing methods, this method can significantly reduce the speckle noise and exhibits a clear advantage across various metrics. These results indicate that the proposed method holds significant development potential in the field of speckle noise reduction.

An enhanced digital twin-driven fault detection and isolation method based on sensor series imaging mechanism for gas turbine engine

Condition based maintenance plays a crucial role in ensuring the safety and reliability of gas turbine engine. Specifically, fault detection and isolation (FDI) can improve efficiency and reduce costs during maintenance. The traditional FDI methods, which developed only using physical engine data, lack a comprehensive consideration of high accuracy and strong applicability across different engine individuals. In this paper, an enhanced digital twin-driven FDI method is proposed, which combines a digital engine, sensor series imaging mechanism and a convolutional neural network. The digital engine is constructed to mirror the operational status of the physical engine. The output residuals between the physical and digital engines are transformed into multi-channel images to train a convolutional neural network for FDI of the physical engine. The network is then fine-tuned using fault-free data from the target engine to further strengthen diagnostic performance across different engine individuals. The effectiveness of the digital engine is verified using actual ground test data, and the performance of the proposed method is demonstrated through comparative simulations. The network, trained on operational data from Engine A and fine-tuned with fault-free data from other engines, exhibits the highest diagnostic accuracy and fault isolation rate. Compared with the physical engine data-based method, the accuracy is increased from 68.25% to 97.95%, the fault isolation rate is improved from 85.91% to 99.26%, and the false alarm rate is decreased from 4.41% to 0.34%. The results show that the proposed method has better FDI capabilities across different engine individuals.

A Cautionary Tale: Digital Clinical Trial Implementation of a Couples-Based HIV Prevention Study among Transgender Women and Their Partners in the United States.

This study investigates baseline differences in couples enrolled in the "It Takes Two" HIV prevention intervention for transgender women and their partners, comparing in-person participation pre-COVID-19 and digital participation during the pandemic. Among 52 couples (40% in-person, 60% digital), bivariate analyses revealed that in-person participants were more likely to be African American, have cisgender male partners, report higher unemployment, incarceration histories, greater relationship stigma, and lower relationship quality. The findings highlight the limitations of digital modalities in engaging transgender women of color and those with structural vulnerabilities. The study emphasizes that reliance on digital methods in HIV research jeopardizes the inclusion of those lacking technological access and literacy, especially communities disproportionately impacted by HIV. Researchers must incorporate hybrid or in-person options and engage communities to ensure equity and inclusion, thus overcoming barriers and ensuring comprehensive population reach in HIV prevention studies.

Role of reactive transport in the alteration of vitrified waste packages: the MOS model

The MOS model (acronym coming from the French MOdèle Simplifié) was born from the desire to have a simple tool that can quantify the contribution of the diffusive reactive environment to the alteration of a vitrified nuclear waste package in deep geological disposal conditions. In the model, this environmental contribution consists partly of the ability of iron, metallic casing corrosion products, and argillite to consume silicon, and partly of the brake on diffusive transport provided by silicon through the successive layers of environmental material. It is a modeling tool serving as an intermediary between operational modeling for the calculation of the source term from the glass, mathematically more simple and giving higher upper margins, and models that use geochemistry and transport, giving greater accuracy for the interactions between glass and its environment. The goal of the MOS model is to calculate the possible impact of silicon reactive diffusion on the alteration rate within the different layers of material surrounding nuclear glass. This article lists the simplifying hypotheses on which the MOS is based, presents the digital resolution method for an environment consisting of several successive layers with different reactivity and transport properties, and explains the model’s implementation.

COMPARISON OF FREEWAY SPACE DISTANCE OF WILLIS METHOD WITH DIGITAL PHOTO ANALYSIS METHOD IN BANJAR TRIBE

Background: The face's vertical dimension or vertical height is the distance between two anatomical points, namely the points on the maxilla and mandible. In measuring the vertical dimension, vertical dimensions of rest (DVR) and vertical dimensions of occlusion (DVO) must be measured. The difference between the vertical dimension of rest (DVR) and the vertical dimension of occlusion (DVO) is called the freeway space (FWS) or interocclusal distance. Freeway space is a key requirement for optimal comfort and function of a partial or complete denture. Each individual's freeway space distance is the movement of muscle function, which can be measured by direct methods such as the Willis method using calipers and the digital photo analysis method using computer software. Two measurement methods can be used to measure freeway space distance direct and indirect. Purpose: To analyze the difference between freeway space distance measured by the Willis method and by digital photo analysis of Adobe Photoshop and Corel Draw graphic design software in the Banjar tribe (a review of students at the Faculty of Dentistry, Universitas Lambung Mangkurat Banjarmasin). Methods: This study is a quantitative study with an analytic observational method and a cross-sectional approach. This study was conducted by collecting data simultaneously at one time by comparing three different methods on the same sample without being given any treatment. Results: One Way ANOVA test is 0.296 (P>0.05) which means there is no significant difference. Conclusion: There is no significant difference between the results of measuring freeway space distance using the Willis method with a digital caliper and digital photo analysis with Adobe Photoshop and Corel Draw software.

Analisis Efektivitas Penggunaan E-Wallet dalam Pembayaran Digital Bagi Mahasiswa Program Studi Manajemen Bisnis Syariah UMSU

This research aims to determine the motives, impacts and experiences of FAI UMSU Sharia Business Management students in using E-Wallets for Digital Payments. Based on the results of observations and interviews based on this title, researchers found that there are many factors that influence students to use E-Wallets for digital payments, including: promos, ease of use, service features, security of the e-wallet digital product. Almost all provinces in Indonesia have touched digital e-wallet applications (OVO, Gopay, Link Aja, Flip, DANA, Shopeepay and so on). E-wallet users are increasing rapidly and are widely used by various groups, including students. Although e-wallet service providers offer a variety of products, not all of them are used by students. E-wallet is a digital payment transaction method that includes features such as balance top-ups, bill payments, inter-bank transfers, money withdrawals, and so on. The use of digital e-wallets is still dominated by payments for online transportation transactions, purchases via e-commerce, and food and beverage delivery services. Security is also one of the factors that makes students interested and interested in using E-Wallet. Meanwhile, the existence of a security verification system makes consumers feel protected regarding the security of their personal data information when using E-Wallet. One of them is by launching fingerprint and facial verification features to validate every transaction.

Method of Digital Processing of Optical Spectra of Magnetron Discharge Plasma

To solve the actual problems associated with the development of the theory of magnetron discharge and the expansion of its practical application, a digital method of recording and processing the discharge plasma luminescence spectra is proposed in this work. To obtain the discharge plasma glow spectra, a photographic technique was used, which allowed simultaneous recording of the entire radiation spectrum in the 390.0-700.0 nm region. An additional advantage of this technique is the ability to track spatial changes in the composition and properties of the plasma in the discharge in the selected direction. A Canon EOS 80D digital camera with remote control was used to record the optical signal. A graphical application OSA was created to process digital images of the discharge plasma luminescence spectra. The paper describes the functionality of this application: determination of the wavelength of a spectral line and its belonging to a certain chemical element; measurement of the spatial distribution of the intensity of a spectral line along the selected direction of radiation registration. Determining the wavelength of a spectral line in the application is possible in two modes of operation - automatic and manual. In the first mode, the algorithm developed in this paper determines the wavelength for all spectral lines whose intensity exceeds the background value at a height of 10 % of the lower spectral limit. The second mode allows you to independently select a single spectral line or several to determine their wavelengths. The first mode is used for quick analysis, while the second mode allows you to determine the length of the spectral line with greater accuracy. To interpret the spectral lines, the methodology of reference lines from the databases of spectral line tables for various elements is used. The possibility of both full automatic verification, where all elements are sequentially searched, and selective verification, where one or more elements are selected, is provided. The paper shows that the spatial distribution of the intensity of tungsten spectral lines, and thus of excited atoms in a magnetron discharge, is a complex function of the distance from the cathode, which depends on the discharge parameters. The proposed digital methodology makes it possible to significantly speed up the process of obtaining physical information and increase the accuracy in determining the spectrum parameters.

Comparison of the Accuracy and Reliability of Instrumental Shade Selection Devices and Visual Shade Selection: An in Vitro Study.

New shade-matching devices are available for clinical use, but their accuracy and reliability have not been investigated. This in vitro study compared the accuracy and reliability of a shade-matching colorimeter (Optishade), a spectrophotometer (VITA Easyshade V), and visual shade matching in simulated clinical conditions. Shade matching was conducted with two digital devices; (Optishade and Vita Easyshade) and the visual shade selection method, with a new 16-tab Vita Classical shade guide. Shade tabs were placed within a gingival matrix and measurements were taken from the central area of each shade tab enclosed in a black box to simulate the oral cavity. Visual assessments were conducted independently by two examiners. For the reliability assessment, each shade tab was measured 20 times by each examiner. Accuracy was calculated as a percentage of the matching readings with the actual shade per each tab. Data were analyzed with the one-way ANOVA test (α = 0.05) and Pairwise Comparison (Bonferroni Post hoc Test) to assess accuracy. The reliability evaluation was conducted by comparison between both examiners using mean and standard deviation; by a two-tailed t-test for the independent samples for all the three groups included in the study. The shade matching accuracy of Optishade was 97.50%, Vita Easyshade 89.38%, and visual method 62.19%. Statistically, high significant difference in accuracy (p < 0.001) was found when comparing both Optishade and VITA Easyshade with the visual method. Additionally, there was statistically significant difference in accuracy (p < 0.05) when Optishade was compared to Vita Easyshade. The reliability of the Optishade was 99.6% and Vita Easy shade was 99.38%. Statistically, showed no statistically significant difference in the reliability of shade match obtained within the same group when comparing the readings of Examiner 1 and Examiner 2 (p > 0.05). The colorimeter demonstrated the highest accuracy, followed by the spectrophotometer, and the visual shade selection method. Both digital methods investigated in this study showed comparable reliability. The results of this study emphasize the clinical advantage of digital shade-matching devices over visual shade-matching. The colorimeter offers high accuracy for shade matching and should be considered to use for shade matching especially with restorations in the esthetic zone.

Urban traffic congestion and its association with gas station density: insights from Google Maps data

Analyzing air pollution caused by traffic conditions requires appropriate indicators. Currently, air pollution indicators are approximated by the number of vehicles and gas station density. However, this approach cannot provide information at a smaller level. This study aims to identify traffic congestion distribution from Google Maps data as an alternative air pollution indicator at smaller level using map digitization method. In addition, this study examines its relationship with the existing indicator called gas station density. The results show that the digitization method can map the traffic congestion distribution where most areas in West, North, and Central Jakarta are classified as high traffic. In addition, this study found that there is a strong and significant relationship of 0.58277 between traffic congestion distribution and gas station density. Thus, traffic congestion distribution and gas station density data from Google Maps can be used as an indicator of traffic-related air pollution, especially land transportation. Furthermore, this research is expected to serve as a basis for the government in determining mitigation strategies related to traffic congestion and the resulting emissions.

Phase unwrapping in digital holography based on SRDU-net

In digital holographic measurement, the hologram phase is extracted using an inverse tangent function, resulting in a wrapped phase that is constrained to be (-π,π]. However, the phase contains the height information of the object, which is crucial for accurate measurement of the object contour. Therefore, a digital holographic phase unwrapping method based on SRDU-Net (Separable-Residual-Dense-Inverted U-Net) is proposed in this paper. The SRDU-Net network is constructed by introducing depth-separable convolution, inverted residuals and dense blocks with U-Net as the network framework to achieve high-precision hologram phase recovery. This network adopts depth-separable convolution instead of traditional convolution, combines the inverse residual connection to construct a lightweight convolution structure, and defines dense blocks with this structure to form a lightweight grouped deep convolution network. Meanwhile, the Leaky ReLU activation function is used to introduce the learning rate mechanism to optimize the network parameters with Huber and MSE (mean square error) as the combined loss function. The simulated phase dataset is used to train the network, the trained network model is tested for speckle noise immunity, and phase unwrapping experiments are performed on the collected holograms of the test samples. The results show that SRDU-Net improves the SSIM by 0.1% and reduces the RMSE by 86% over Res-UNet (Residual-UNet). Therefore, the proposed method can realize high-precision recovery of digital holographic wrapped phases, and has a good robustness to phase unwrapping of holograms containing a high degree of speckle noise.

DIGITAL RESTORATIVE PROCEDURES IN DENTISTRY

ABSTRACT The integration of digital technologies in restorative dentistry has significantly transformed clinical workflows, enhancing precision, efficiency, and patient outcomes. This article explores the pivotal role of various digital procedures in modern dental practices. Digital imaging techniques have revolutionized diagnostic capabilities, providing high-resolution, detailed visualizations essential for accurate treatment planning. Digital cone beam computed tomography (CBCT) has further refined diagnostic accuracy, enabling three-dimensional assessment of dental structures, which is crucial for implantology and complex restorative cases. Digital caries detection methods offer enhanced early detection of carious lesions, improving preventative care and treatment outcomes. The advent of digital impression systems has streamlined the process of capturing accurate dental impressions, reducing patient discomfort and enhancing the precision of prosthetic restorations. Additionally, digital design-manufacturing (CAD/CAM) systems have facilitated the rapid production of high-quality dental restorations, allowing for same-day procedures and greater customization. Collectively, these digital advancements are reshaping the landscape of restorative dentistry, offering unprecedented opportunities for improving the accuracy, efficiency, and overall success of dental restorations. This review aims to provide an in-depth understanding of the current state of digital restorative procedures in dentistry, with a focus on the latest technological advancements and their clinical implications. Keywords: Dentistry, digital technology, CAD/CAM, CBCT.

디지털 콘텐츠 유통을 위한 OTT 비즈니스 모델 연구

The way cultural content is being distributed is rapidly changing in the digital age. This study focuses on the business model of Netflix, a dominant player in the global market for digital content distribution. The aim is to identify strategies and insights that can be useful for domestic OTT (Over-The-Top) companies seeking to distribute Korean content worldwide. Netflix is a global OTT company that provides a diverse range of content to consumers, including original productions. The STOF (Service, Technology, Organization, Finance) model is used to analyze Netflix's business model, which is suitable for Internet-based businesses. The study highlights the shift from traditional and physical methods of producing and distributing content, such as movies using the existing film method, to completely digital methods in the field of cultural content. The study is valuable for global and domestic OTT operators and policymakers, scholars, entertainment and media companies, and the general public who enjoy cultural content.

Digital twin method for intelligent lifting of cable structures under multi-collaborative mode

In order to ensure the high efficiency and quality consistency of cable structure in each construction stage, this study proposes a digital twin method for intelligent lifting of cable structure under multi-collaborative mode. Firstly, a construction and operation methods of the digital twin logic model are formed. In the logical model, a relationship between the transmission and iteration of construction information in the collaborative process is defined. In order to realize the adaptability of working conditions, the coupling relationship between construction step and structural elevation is established. A cable structure lifting analysis model driven by an improved long short-term memory neural network is proposed, which effectively solves the problem of poor convergence of the traditional finite element method. An automatic time window selection method is formed for the neural network. An adaptive moment estimation method is used for neural network parameter optimization, which improves the efficiency and accuracy of the analysis. Taking the lifting process of a cable truss structure test model as an example, a digital twin collaborative construction platform is established to verify the effectiveness and feasibility of the research method. The results show that the digital twin logic model realizes the process collaboration, scene collaboration and data collaboration, and significantly improves the stability of construction quality and the linkage of construction process. Through the improved long short-term memory neural network, the coupling relationship between the construction step and the structural elevation is established, which accurately guides the whole construction process.

In-situ CT scan-based analysis of damage evolution of coral reef limestone under cyclic loads

The subtropical hurricane, ocean circulation, and excavation disturbance by deep engineering of island reefs bring many challenges for the insight into the mechanical behaviors of coral reef limestone (CRL) under cyclic loads. This paper investigated the damage characteristics of coral gravel limestone (CGL) under triaxial cyclic loads based on the in-situ computed tomography (CT) technique and digital volume correlation method (DVC). The results suggested that the plastic strain of CGL still existed after unloading in the stage of linear elastic deformation. Crack initiation within the specimen occurred at the stress level of about 0.72, and accelerated damage occurred when the stress level exceeded 0.86. Subsequently, we utilized DVC technique to visualize the evolution process of 3-D strain field under cyclic loads. The strain field of the specimen generated strain release in the locality of crack initiation, and the heterogeneous degree of strain field firstly increase and then decrease with the increase of upper limit pressure. Moreover, the secant modulus exhibits a trend consistent with the heterogeneous degree of strain field. Therefore, we introduced the concept of self-information entropy to characterized the heterogeneous degree of strain field, attempting to describe the process of compression and damage of sample. The evolving relationship between secant modulus and axial strain of CGL under cyclic loads was established based on the heterogeneity of strain field. The proposed model provides promising way to predict secant modulus of porous rock materials based on-site CT testing and in-situ measurement in practical engineering.

Innovative financial strategies for achieving cost reduction and revenue growth in non-profit organizations

Non-profit organizations operate in a challenging financial environment, requiring innovative strategies to ensure sustainability and maximize their impact. This review paper explores essential financial strategies for non-profits, focusing on cost reduction, revenue growth, strategic financial planning, and leveraging technology. Cost reduction strategies, including operational efficiency, process streamlining, and technology implementation, enable non-profits to optimize resource allocation. Revenue growth is achieved through diversifying funding sources, expanding donor bases, and adopting social enterprises and digital fundraising methods. Strategic financial planning and management, encompassing robust financial plans, regular audits, and risk management, are foundational for financial health. Leveraging technology, such as financial management software, data analytics, and blockchain, further enhances financial efficiency and transparency. This comprehensive approach empowers non-profits to achieve financial stability, improve resource management, and enhance their mission-driven impact. Future directions recommend exploring new financial management practices and technologies to maintain competitiveness and sustainability in an evolving landscape.

Bespoke cultivation of seablite with digital agriculture and machine learning

Climate change has driven agriculture to alter farming methods for food production. This paper presents a new concept for monitoring, acquisition, management, analysis, and synthesis of ecological data, which captures the environmental determinants and direct gradients suited to a particular requirement for specific plant cultivation and sustainable agriculture. The purpose of this study is to investigate a smart seablite cultivation system. A novel digital agricultural method was developed and applied to digitised seablite cultivation. Machine learning was used to predict the future growth conditions of plants (seablites). The study identified the illustrative maps of seablite origins, a conceptual seablite smart farming model, essential factors for growing seablite, a digital circuit for cultivating seablite, and digital data of seablite growth phases comprised the digital data. The findings indicate that: (1) An indicator of soil salinity is a quantity of sodium chloride extracted from a seablite sample indicating its origin of environmental determinants. (2) Saline soil, saline water, pH, moisture, temperature, and sunlight are essential factors for seablite development. These factors are dependent on climate change and were measured using a smart seablite cultivation system. (3) Digital circuits of seablite cultivation provide a better understanding of the relationship between the essential factors for seablite growth and seablite growth phases. (4) Deep neural networks outperformed vector machines, with 86% accuracy at predicting future growth of seablites. Therefore, this finding showed that the essential seablite development factors can be manipulated as key controllers for agriculture in response to climate change and agriculture can be planned. Basic digitisation of specific plants aids plant migration. Digital agriculture is an important practice for agroecosystems.

1518: Flashing Automatic Contour Tracing (FACT) - A novel electron cutout digitization method

1518: Flashing Automatic Contour Tracing (FACT) - A novel electron cutout digitization method

Digital image correlation calculation method for RGB-D camera multi-view matching using variable template

Multi-view matching is an indispensable method for digital image correlation 3D reconstruction. However, as the camera viewing angle changes, traditional DIC methods can lead to the accumulation of matching errors and an increase in mismatches, thereby affecting the 3D reconstruction quality. This paper proposes a digital image correlation method for multi-view RGB-D images based on variable template matching. Initial positioning is achieved by dynamically adjusting the size and sampling direction of the variable template. Sub-pixel registration is then performed using the inverse compositional algorithm, followed by multi-view point cloud fusion using the Iterative Closest Point (ICP) registration method. Experimental results show that the iteration speed of point cloud registration is increased by 30%, and the cumulative error is reduced by 62.5%. These improvements demonstrate that the proposed method is suitable for multi-viewpoint matching scenarios, achieving excellent results in multi-view feature point matching and multi-view point cloud fusion, significantly enhancing 3D reconstruction accuracy and efficiency.