Graphics Software Research Articles

Development of Website based Multiple Representation on Buffer Solution Topic in Chemistry Learning

Buffer solution is one of chemistry difficult topics. It contains theory, calculation, and experimentation, so it requires good analysis and understanding of concepts. The results of interviews with students in Bintan Regency showed that the sub material of determining buffer solution components and analyzing the working principles of buffer solutions was the most difficult part because it was abstract. Multiple representations on the website media will visualize abstract things from the topic of buffer solution so as to increase the understanding of concepts from students. The research aims to produce multiple representation website on buffer solution topics and to determine its feasibility, practicality, and readability. The research method used is research and development (RD) following the 4D development model by Thiagrajan (define, design, develop, and disseminate). The sample research used 21 students and five chemistry teachers in Bintan Regency to collect user responses related to practicality and readability. The data analysis calculates the average score of the validation and response values and classifies them into the available categories. The results of the validation show that the average score of material experts is 63.5 (learning, materials, multiple representations, and evaluation aspects), while the average score of media experts is 71.5 (graphic design, software engineering, and media selection criteria aspects), which are classified as very good. The results of practicality and readability responses are 119 (learning, materials, multiple representations, evaluation, graphic design, software engineering, and media selection criteria) and 70.5 (learning, graphic design, and software engineering), which are very good categories

DENNIS: a design and analysis tool for dynamic material x-ray diffraction experiments

We present DENNIS (Diffraction Experiment desigN and aNalysiS): a graphical software tool useful for the design and analysis of dynamic x-ray diffraction experiments, such as those performed on the Z Pulsed Power Facility, Thor Pulsed Power Generator, and Dynamic Compression Sector (DCS) of the Advanced Photon Source. DENNIS provides rapid powder and single-crystal diffraction pattern predictions and powder diffraction pattern image integration in three-dimensional geometries. Additional features include crystallographic information file reading, image processing, and synthetic diffraction pattern image generation. We overview the software's capabilities, detail the prediction and integration methodologies, and provide example implementations on Z and DCS experiments.

Relationship between Art and Design Students’ Technical and Managerial Skill Traits and Their Entrepreneurial Skill Traits

The unavailability of jobs for graduates has become a gross concern in developing countries such as Nigeria, which is not necessarily contingent on graduates from any specific course of study, including art and design education. It is thus evident that proficiency in artistic or creative talent alone is insufficient to guarantee a thriving art and design career and the need to develop the required entrepreneurial propensity. This study, therefore, aims to evaluate the entrepreneurial skills and traits of art and design students in Nigerian higher education institutions (HEIs) as a remedy for stimulating their entrepreneurial tendencies. The hypothesized model of art and design students’ entrepreneurial traits was developed based on the theoretical framework developed from the literature as a three-factor construct (Model 1.0) comprising technical/soft skills, managerial skills, and entrepreneurial skills. Data was obtained using a structured Likert scale questionnaire of 36 items adapted from Yilzman & Sunbul’s entrepreneurial scale from a sample of 186 art and design students. Data was analysed using descriptive statistics and thecovariance-based structural equation modelling (CB-SEM) via the IBM SPSS Statistics 26 and IBM SPSS Amos 26 Graphics software. The model fit results reveal that the goodness-of-fit statistics indexes fell within the acceptable range. The results of the hypotheses testing of the model show that no significant association exists between art and design students’ technical and entrepreneurial skill traits. However, there is a significant association betweentheir managerial and entrepreneurial skill traits. The outcome of this research has implications for TVET institutions in the arts and design field further to promote the development of students’ inherent entrepreneurial traits to boost their entrepreneurial tendencies.

From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.

The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.

SAAM II: A general mathematical modeling rapid prototyping environment.

Simulation Analysis and Modeling II (SAAM II) is a graphical modeling software used inlife sciences for compartmental model analysis, particularly, but not exclusively, appreciated in pharmacokinetics (PK) and pharmacodynamics (PD), metabolism, and tracer modeling. Its intuitive "circles and arrows" visuals allow users to easily build, solve, and fit compartmental models without the need for coding. It is suitable for rapid prototyping of models for complex kinetic analysis or PK/PD problems, and in educating students and non-modelers. Although it is straightforward in design, SAAM II incorporates sophisticated algorithms programmed in C to address ordinary differential equations, deal with complex systems via forcing functions, conduct multivariable regression featuring the Bayesian maximum a posteriori, perform identifiability and sensitivity analyses, and offer reporting functionalities, all within a single package. After 26 years from the last SAAM II tutorial paper, we demonstrate here SAAM II's updated applicability to current life sciences challenges. We review its features and present four contemporary case studies, including examples in target-mediated PK/PD, CAR-T-cell therapy, viral dynamics, and transmission models in epidemiology. Through such examples, we demonstrate that SAAM II provides a suitable interface for rapid model selection and prototyping. By enabling the fast creation of detailed mathematical models, SAAM II addresses a unique requirement within the mathematical modeling community.

3D Printed Hydrogel Sensor for Rapid Colorimetric Detection of Salivary pH.

Salivary pH is one of the crucial biomarkers used for non-invasive diagnosis of intraoral diseases, as well as general health conditions. However, standard pH sensors are usually too bulky, expensive, and impractical for routine use outside laboratory settings. Herein, a miniature hydrogel sensor, which enables quick and simple colorimetric detection of pH level, is shown. The sensor structure was manufactured from non-toxic hydrogel ink and patterned in the form of a matrix with 5 mm × 5 mm × 1 mm individual sensing pads using a 3D printing technique (bioplotting). The authors' ink composition, which contains sodium alginate, polyvinylpyrrolidone, and bromothymol blue indicator, enables repeatable and stable color response to different pH levels. The developed analysis software with an easy-to-use graphical user interface extracts the R(ed), G(reen), and B(lue) components of the color image of the hydrogel pads, and evaluates the pH value in a second. A calibration curve used for the analysis was obtained in a pH range of 3.5 to 9.0 using a laboratory pH meter as a reference. Validation of the sensor was performed on samples of artificial saliva for medical use and its mixtures with beverages of different pH values (lemon juice, coffee, black and green tea, bottled and tap water), and correct responses to acidic and alkaline solutions were observed. The matrix of square sensing pads used in this study provided multiple parallel responses for parametric tests, but the applied 3D printing method and ink composition enable easy adjustment of the shape of the sensing layer to other desired patterns and sizes. Additional mechanical tests of the hydrogel layers confirmed the relatively high quality and durability of the sensor structure. The solution presented here, comprising 3D printed hydrogel sensor pads, simple colorimetric detection, and graphical software for signal processing, opens the way to development of miniature and biocompatible diagnostic devices in the form of flexible, wearable, or intraoral sensors for prospective application in personalized medicine and point-of-care diagnosis.

MONET: The Minor Body Generator Tool at DART Lab.

Minor bodies exhibit considerable variability in shape and surface morphology, posing challenges for spacecraft operations, which are further compounded by highly non-linear dynamics and limited communication windows with Earth. Additionally, uncertainties persist in the shape and surface morphology of minor bodies due to errors in ground-based estimation techniques. The growing need for autonomy underscores the importance of robust image processing and visual-based navigation methods. To address this demand, it is essential to conduct tests on a variety of body shapes and with different surface morphological features. This work introduces the procedural Minor bOdy geNErator Tool (MONET), implemented using an open-source 3D computer graphics software. The starting point of MONET is the three-dimensional mesh of a generic minor body, which is procedurally modified by introducing craters, boulders, and surface roughness, resulting in a photorealistic model. MONET offers the flexibility to generate a diverse range of shapes and surface morphological features, aiding in the recreation of various minor bodies. Users can fine-tune relevant parameters to create the desired conditions based on the specific application requirements. The tool offers the capability to generate two default families of models: rubble-pile, characterized by numerous different-sized boulders, and comet-like, reflecting the typical morphology of comets. MONET serves as a valuable resource for researchers and engineers involved in minor body exploration missions and related projects, providing insights into the adaptability and effectiveness of guidance and navigation techniques across a wide range of morphological scenarios.

Development of deep learning based user-friendly interface for fruit quality detection

The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. The quality attributes of fruit such as total soluble solids, moisture content, pH, colour changes, and firmness at different varieties can be predicted according to different storage conditions with reliable classification accuracy. The advances in non-destructive techniques have led to the rapid utilisation of the imaging approach in order to monitor the fruit quality. These image datasets encompass diverse information which requires extensive data extraction. To overcome this issue, a deep learning approach using convolutional neural network was used to evaluate the fruit quality. A graphical user interface-based software (DLFRUIT-GUI) for data processing of fruit quality is developed. The toolbox allows the model training and selection based on the image datasets of the fruit. The software offers a push-button approach to establish deep learning models for monitoring fruit quality. The adoption of convolutional neural network model successfully improves the model performance which demonstrated efficient results in predicting the fruit quality at different varieties according to various storage conditions. The DLFRUIT-GUI toolbox provides rapid monitoring of fruit quality detection that can easily be accessible by users who have no programming skills and tedious data analysis.

Applications of forensic anthropology methodology: accuracy of virtual face reproductions performed on the Tenchini collection.

Facial reproduction validation uses the methodology typical of forensic anthropology to confirm the accuracy of three-dimensional reproductions of faces. Achieving high accuracy in virtual facial reproductions is still under study. In the present paper, the Tenchini collection, which contains wax reproductions of prisoners' faces and their skulls, was used. By creating facial reproductions on skulls from this collection, the result was compared with the real face of the person to whom the skull belongs. The three-dimensional volume of each examined skull of Tenchini collection was acquired via CT scan and photogrammetry. Subsequently, the virtual reproduction of each skull was processed using three-dimensional graphics software (ZBrush, Pixologic®). The morphological comparison parameters used in the field of personal identification by forensic anthropology were used. The blind procedure required the operator to see the mask subsequent to the facial reproduction phase, so that the facial reproduction cannot exploit the information that knowledge of the mask would have produced. The parameters used in the study of facial reproductions have shown discrepancies between the characteristics of the masks and the facial reproductions, partly expected because due to the lack of soft tissue on the skull. However, a high degree of accuracy in the facial reproductions performed due to the applied methodology was documented. The present study allowed us to observe how these parameters can be useful to study the accuracy of facial reproduction and identify what difficulties are encountered in producing a result close to the real appearance.

Synthetic Data for Deep Learning in Computer Vision & Medical Imaging: A Means to Reduce Data Bias

Deep-learning (DL) performs well in computer-vision and medical-imaging automated decision-making applications. A bottleneck of DL stems from the large amount of labelled data required to train accurate models that generalise well. Data scarcity and imbalance are common problems in imaging applications that can lead DL models towards biased decision making. A solution to this problem is synthetic data. Synthetic data is an inexpensive substitute to real data for improved accuracy and generalisability of DL models. This survey reviews the recent methods published in relation to the creation and use of synthetic data for computer-vision and medical-imaging DL applications. The focus will be on applications that utilised synthetic data to improve DL models by either incorporating an increased diversity of data that is difficult to obtain in real life, or by reducing a bias caused by class imbalance. Computer-graphics software and generative networks are the most popular data generation techniques encountered in the literature. We highlight their suitability for typical computer-vision and medical-imaging applications, and present promising avenues for research to overcome their computational and theoretical limitations.

The RoIe of Corporate SociaI ResponsibiIity and Perceived Risk on Brand LoyaIty Based on Cognitive MotivationaI ReIationaI Theory

This research was conducted to determine the reIationship between brand satisfaction, perceived risk, perceived quaIity, and brand IoyaIty to corporate sociaI responsibiIity in Generation Z in corporate sociaI responsibiIity activities. Cognitive MotivationaI ReIationaI Theory is used in research as the main main theory. The method in this uses a quantitative approach using a purposive sampIing technique which produces 180 sampIes. StructuraI Equation ModeIing (SEM) was used as an anaIysis technique proposed with AMOS 24 graphic software. The reIationship hypothesis of corporate sociaI responsibiIity has a significant positive effect on brand satisfaction and perceived quaIity. In other way, brand satisfaction has a positive effect on brand royaIty. The research resuIts of corporate sociaI responsibiIity on brand satisfaction aIso provide knowIedge that CSR activities wiII have an impact on pubIic satisfaction with the activities that have been provided by the company. This research aIso resuIts in CSR activities as weII as the attitude of consumers' assessments that they feeI towards the company. The research resuIts reIated to the practitioner impIications of CSR activities are that the increasing contribution of corporate sociaI responsibiIity to society wiII aIso improve the company's image and provide significant benefits to the company

PUFFIn – A user friendly fast interface for calculating and visualizing the dose distribution in materials

This article describes a new graphical user interface that uses the PENELOPE Monte Carlo code to calculate dose distributions in materials. It is named PUFFIn, for the Penelope User-Friendly Fast Interface and was developed as an educational and scoping analysis tool for non-experts in radiation modeling. PUFFIn enables the user to visualize and compare the dose distributions in objects (e.g., sterilized healthcare products) irradiated with cobalt-60 gamma-rays, electron beam (E-beam) or X-rays. From such comparisons, the user can determine the most efficient product and/or packaging designs for any given radiation field – whether for conceptual or existing products and packaging.PUFFIn is distributed in a complete, self-contained package of software, including the PENELOPE radiation transport code, a standard graphics package, and a set of simple exercises. The package is available to any user at no cost and requires a minimal amount of training compared to other similar software. PUFFIn's capabilities are described, as well as validation measurements performed at Texas A&M University E-beam facility and the Aerial E-beam Facility in France.

Research on Wireless Power Transfer Method for Intelligent Sensing Device of Non-Directly Buried Distribution Cables

This paper presents a study on the impact of circuit parameters on the transmission of electrical energy in wireless power transfer systems designed for intelligent sensing devices within the urban electric power Internet of Things (IoT). Relying on the essential principles of resonant mutual inductance models, the paper conducts an analytical investigation into the phenomena of power-frequency splitting characteristics, efficiency-frequency splitting characteristics, and efficacy synchronization characteristics within wireless energy transmission technologies. The investigation includes a detailed analysis of a wireless power transfer system model operating at 100 kHz, delineating how varying circuit parameters influence the system’s efficiency. Via the utilization of graphical software and computational programming for simulation modeling, this research delved into the dynamics between key parameters such as equivalent load and coupling coefficient and their influence on distinct splitting phenomena. This rigorous approach substantiated the validity of the proposed power-frequency and efficiency-frequency splitting characteristics outlined in the study. Based on the analytical results, it is shown that selecting an appropriate equivalent load or utilizing impedance matching networks to adjust the equivalent load to a suitable size is crucial in consideration of the system’s output power, voltage withstand level, and transmission efficiency. The research findings provide a theoretical basis for the design of wireless power supply systems for non-directly buried cable front-end sensing devices.

PELATIHAN DESAIN GRAFIS UNTUK MENINGKATKAN KREATIVITAS PADA SISWA SMK TARBIYATUL AULAD MENGGUNAKAN SOFTWARE COREL DRAW

At this time the computer has many applications that can help work and can increase creativity. Corel Draw is one of the graphic design software used in designing logos, posters, banners, invitations, and advertisements. This training aims to provide insight and knowledge, as well as new skills to students so that students can improve their abilities in the computer field, especially in graphic design and students are able to express their creative ideas in the form of graphic design in the form of posters. Graphic design training was held at SMK Tarbiyatul Aulad. SMK Tarbiyatul Aulad is a Vocational High School with accreditation A, registered with SK number: 08/YAY-TA/I/2012, NPSN number 69758144, located at Kp. Ngamplang Cibodas Village Cikajang District Garut Regency, West Java Province. SMK Tarbiyatul Aulad is under the auspices of Tarbiyatul Aulad Cikajang Foundation. The training activities were attended by 22 students of SMK Tarbiyatul Aulad. The graphic design training provided was in the form of poster making training. After the training, the students can make posters using Corel Draw software.

TECHNOLOGY OF THE DEVELOPMENT OF MACHINE-GRAPHICS PROFILE OF A PARTS AND ASSEMBLY UNITS IN TRAINING SKETCHES

The purpose of studying the discipline “Engineering Graphics” is to acquire skills in working with engineering and graphic information: mapping spatial objects to orthogonal planes in the form of a drawing (direct task), reading a drawing (inverse task), ultimately solving spatial and logical problems. The necessity to start performing graphic works with a pencil, paper, using drawing and graphic tools is shown and justified, and only then to involve modern computer technologies for these purposes. Not the ability to work with a pencil; it is not understood that the use of computer graphics hardware and software at the initial stage leads to the loss of graphic competence of the graduate, and ultimately to a decrease in the competitive ability of specialists.

Exploring the technological affordances of SimpleMind in supported academic writing: A mind-mapping software analysis

This research investigates EFL undergraduate students’ utilization of cross-platform mind-mapping software and the factors shaping their choice of devices and timing when employing SimpleMind to enhance their academic writing skills. Grounded in Mayer’s (2019) cognitive science principles of learning, this study posits that offering EFL learners dual channels for processing information, encompassing both visual and verbal modalities, enhances information retention and reduces cognitive load. SimpleMind, a digital graphic software, has the potential to support learners in this dual coding process of information, provided it is used thoughtfully. Through the framework of the affordance-actualization theory, this research advocates for empowering language learners to proactively discover and leverage SimpleMind’s affordances to craft a customized strategy aligned with their specific academic writing learning environment. This paper presents preliminary findings from a larger study involving 71 Japanese first-year students. They explored SimpleMind’s features to cater to their individualized academic writing learning preferences.

Using the golden ratio in detecting the aesthetics of Mosque facades: The case of contemporary Mosques in Erbil city

From ancient Greece till the present, the golden ratio has been considered one of the most significant criteria of beauty in art and architecture. Architectural forms are part of the visual language that is bound by the rules of geometry and proportion. This study aims to identify the extent to which contemporary mosques in the city of Erbil utilize the golden ratio in the aesthetics of their facades. The research attempts to answer the question: was the golden ratio implemented in designing the facade of contemporary mosques in Erbil? The study adopted a mixed quantitative and qualitative analysis method. To achieve the study's aim and answer its questions, six mosques built in the last decade in Erbil were selected. Qualitatively, survey and documentation followed. Quantitatively, Phi matrix software, AutoCAD, and graphic software were applied as a mathematical approach. The study concluded that only one case used the golden ratio in the design of its façade by 100%, while it did not exceed 75% in most other mosques. The study draws the attention of designers and architects in the field of mosque architecture to the adoption of the golden ratio in the designs of mosque facades because of its role in achieving the aesthetic aspect.

Reaching beyond GIS for comprehensive 3D visibility analysis

Visibility analyses are one of the fundamental geospatial processing tasks applied in various fields. Recent technological advancements have accelerated viewshed calculations and improved their accuracy thanks to the growing availability of high-resolution spatial data. However, limitations of standard GIS tools, primarily related to the inability to perform analyses in a fully three-dimensional environment and the restriction to only point-based object analyses, have hindered the development of visibility analyses methods that accurately replicate human perspectives. This article presents a novel approach that combines GIS with 3D graphic software and uses high resolution LIDAR data. The presented method not only addresses the limitations of traditional GIS methods but also opens up new possibilities for comprehensive 3D visibility analyses that can better represent real-world scenarios. The proposed methodology, which ensures compatibility of the results with GIS for further spatial analysis, has the potential to enhance decision-making processes in fields such as urban planning, landscape management and protection, environmental impact assessment, infrastructure planning and development. By presenting a case study involving a photovoltaic farm, this article demonstrates the practical applicability and benefits of the proposed method in real-world scenarios.

The Influence of Attitude and Perceived Risk to Optimize Intention to Adopt Based on Theory of Planned Behavior in Generation Z

This study aims to determine the effect of attitude and perceived risk on intention to adopt based on the theory of planned behavior (TPB) in Generation Z. This study employs a quantitative methodology, utilizing a purposive sampling technique. The data utilized in this study is primary data, which was collected through the distribution of questionnaires. The study has a sample size of 210 respondents. The data was evaluated using Structural Equation Modeling (SEM) analysis with the use of AMOS 24 Graphics software. The findings of this study indicate that attitude is significantly influenced by perceived utility, perceived trust, and subjective norm. Furthermore, attitude significantly impacts the intention to adopt. The study's recent discoveries indicate that perceived danger exerts a detrimental and noteworthy impact on attitude, while perceived ease of use exerts a detrimental but inconsequential impact on attitude. The findings of this study emphasize the significance of comprehending customer risk perceptions in relation to service utilization. Companies should take into account the factors that impact consumer opinions. This can be accomplished by implementing effective marketing techniques, enhancing customer service, or providing an optimal user experience. This study provides an update on the variables by including the perceived risk variable to assess the perceived risk experienced by consumers.

Historic British Royal Memes

Historic British Royal Memes