Graphical Tool Research Articles

Evaluation of a Graphic Narrative Patient Education Tool to Reduce Pre-treatment Anxiety for Patients Receiving Radiotherapy in a Latin American Hospital

Evaluation of a Graphic Narrative Patient Education Tool to Reduce Pre-treatment Anxiety for Patients Receiving Radiotherapy in a Latin American Hospital

Multicriteria decision support under uncertainty: combining outranking methods with Bayesian networks

AbstractAssessing alternative solutions that have uncertain evaluations in conflicting multiple criteria is not straightforward. Probabilistic models such as Bayesian networks (BNs) can effectively model and represent the uncertainty in such problems, but they do not include built-in mechanisms to guide different decision makers (DMs) with varying preferences toward the final decision. We propose a systematic approach to combine outranking methods with BNs to provide decision support for solutions with multiple and conflicting criteria under uncertainty. The proposed approach is based on Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), and it offers different levels of precision and flexibility to the DMs in assessing the solutions. Our approach includes graphical tools and summary metrics to enhance the presentation of its results to the DMs. We test our approach with a case study on supplier selection where the uncertainty in supplier performances is modeled with a BN. We demonstrate that the proposed approach can enable the joint use of multiple criteria techniques with probabilistic modeling techniques like BNs to provide decision support in complex environments including uncertainty.

The expanding scope of ship design practice

As the former International Chair of IMDC, the initiator of the continuing series of IMDC State of Art (SoA) Reports and the lead author of most IMDC SoA Reports on design methodology from 1997 to 2018, the author has both pioneered and observed an increasingly broader scope in the practice of the design of particularly complex vessels. The paper commences with reviewing some key publications, not just to recent IMDCs, that have tracked the manner in which “ship design” (in the broadest sense) has become more sophisticated – especially in the crucial early stages of design. The diversity of ship design practice, not just due to computer-based methods, is readily observable. Moreover, the impact of computer aided design in ship design has not just been to better analyse ship performance (e. g. in hydrodynamics, strength and ship infrastructure systems behaviour) but also in the increasing use of graphical tools and design methods to enable “better ship design”. In a growing number of, mainly, academic centres, but also in some government agencies and design consultancies, there is a clear desire to better understand how to design “ships” and to manage the ship design process, especially for the most complex and novel classes of vessels. In particular, the objectives being sought when conceptualising and synthesising a range of ship options (as part of the requirement elucidation approach) in an ever-increasing scoping of the relevant issues, amounts to developing a more holistic approach. This is not just due to an increasingly complex ship acquisition and ownership environment, but also due to environmental and socio-economic (especially system safety) concerns. Overlaying all this are the opportunities or the spectre of Artificial Intelligence (or perhaps more immediately those of Machine Learning) and its likely impact on engineering practice as well as those other professions in the “marine design enterprise”. The paper concludes by emphasising that while ship design has distinct differences, when compared with most other large scale engineering design practice, the lead ship design profession of the naval architect has somehow to deal with this expanding scope in the practice of “ship design”. This means the education and on the job development thrust must broaden if the ship design profession is not to be side-lined into acting as mere hull engineers. It is argued, such a specific role will be more vulnerable in an increasingly Machine Learning dominated future, than the holistic ship creating and systems architectural alternative. Finally an ambitious vision for future ship designers is given alongside a summary of the specific main contributions by the author to ship design methodology.

Development and application of EpitopeScan, a Python3 toolset for mutation tracking in SARS-CoV-2 immunogenic epitopes.

Outbreaks of coronaviruses and especially the recent COVID-19 pandemic emphasize the importance of immunological research in this area to mitigate the effect of future incidents. Bioinformatics approaches are capable of providing multisided insights from virus sequencing data, although currently available software options are not entirely suitable for a specific task of mutation surveillance within immunogenic epitopes of SARS-CoV-2. Here, we describe the development of a mutation tracker, EpitopeScan, a Python3 package with command line and graphical user interface tools facilitating the investigation of the mutation dynamics in SARS-CoV-2 epitopes via analysis of multiple-sequence alignments of genomes over time. We provide an application case by examining three Spike protein-derived immunodominant CD4+ T-cell epitopes restricted by HLA-DRB1*04:01, an allele strongly associated with susceptibility to rheumatoid arthritis (RA). Mutations in these peptides are relevant for immune monitoring of CD4+ T-cell responses against SARS-CoV-2 spike protein in patients with RA. The analysis focused on 2.3 million SARS-CoV-2 genomes sampled in England. We detail cases of epitope conservation over time, partial loss of conservation, and complete divergence from the wild type following the emergence of the N969K Omicron-specific mutation in November 2021. The wild type and the mutated peptide represent potential candidates to monitor variant-specific CD4+ T-cell responses. EpitopeScan is available via GitHub repository https://github.com/Aleksandr-biochem/EpitopeScan.

An efficient computational scheme for solving coupled time-fractional Schrödinger equation via cubic B-spline functions.

The time fractional Schrödinger equation contributes to our understanding of complex quantum systems, anomalous diffusion processes, and the application of fractional calculus in physics and cubic B-spline is a versatile tool in numerical analysis and computer graphics. This paper introduces a numerical method for solving the time fractional Schrödinger equation using B-spline functions and the Atangana-Baleanu fractional derivative. The proposed method employs a finite difference scheme to discretize the fractional derivative in time, while a θ-weighted scheme is used to discretize the space directions. The efficiency of the method is demonstrated through numerical results, and error norms are examined at various values of the non-integer parameter, temporal directions, and spatial directions.

Graphics based business process harnessing tools, advancing digital maturity of business

PurposeThe advancement of digital maturity at a business level has proven to be challenging, with limited time, resources and skills in extracting and mapping business processes. In order to advance digitalization, the mapping of all business activities is essential. To close this gap, this research is aimed at enabling the operational level extraction and classification of business activities using a graphical methodology. This objective is accomplished through the development of a digital tool that leverages Software Development Life Cycle (SDLC) principles.Design/methodology/approachThis research is focused on facilitating rapid extraction of business activities with the adoption of a graphical methodology. Business activities are captured through a digital tool in a structured, interlinked and hierarchical manner.FindingsNotably, this work is novel as it introduces a new graphical tool to replace traditional tools in the domain of Business Process Mapping (BPM). This graphical tool is distinguished by a unique feature; that is a self-configuring database with the flexibility to capture all process options, providing innovative solutions to the challenges faced in digitalizing business processes.Originality/valueThis work is original in that a new graphical interface is developed to replace traditional tools in the space of BP data gathering. The unique challenge of an auto configuring database with flexibility to capture all process options is presented.

Application of hierarchical cluster analysis and principal component analysis to identify compositional trends of brine in crystalline basements and sedimentary basins

The present study identifies distinct geochemical signatures of deep brines originating from crystalline basements and sedimentary basins. A corresponding conceptual hydrogeochemical model is developed outlining the evolution of crystalline and sedimentary brines. The combined application of Hierarchical Cluster Analysis and Principal Component Analysis allowed the identification of evolutionary trends of groundwater towards crystalline and sedimentary brines. Using 308 brine samples from the existing literature, eight chemical species were considered in the analysis: sodium, magnesium, potassium, calcium, strontium, chlorine, sulfate, and bromine, from which two salinity evolution pathways towards common Ca–Cl brines were derived: (1) the evolution of crystalline brines, which evolved from recharge water to brine through hydration of silicates, is described by the linear equation Ca = −1610 + 0.4*Cl; and (2) the evolution of sedimentary brines, which evolved from recharge water to brine through dissolution and precipitation of halite, is described by the linear equation Cl/Br = 103 + Na/Br. We also discuss differences in water isotopes, and in lithium and boron concentrations which directly reflect various temperature-dependent processes that control the evolution of sedimentary and crystalline brines. This leads to development of a discriminatory graphical tool using B/Br and Li/Br ratios, with crystalline brines having B/Br and Li/Br ratios below 0.01 and sedimentary brines above 0.01. Our results improve our understanding of deep crustal brine evolution through brine-rock interaction.

Behavioural determinants of the healthcare providers in Ukraine: Focus on competition context

The development of the healthcare system is an important task for every country, given that long-term economic and social development is absolutely impossible without a healthy nation. Therefore, improving public health and ensuring that the maximum number of people have access to quality healthcare services is one of the state's strategic priorities. In this regard, the authors of the paper set a goal to establish how the reform of the healthcare system in Ukraine has led to changes in the behavioural determinants of healthcare providers and recipients in the domestic healthcare market. The paper uses such research methods as comparison, visualization, graphical data visualization tools, and statistical methods of data analysis. The study revealed that Ukrainian citizens got a chance to freely choose their physicians by signing declarations with them, which led to increased competition among physicians and other doctors and healthcare facilities; at the same time, the number of declarations signed with private healthcare facilities increased significantly. Furthermore, the developed econometric model allows us to identify statistically significant relationships between the amount of state funding and lifestyle and environmental indicators, which will allow us to improve the mechanisms and amount of funding in the sector, improving the health of the nation in the new competitive environment.

Utilization of CANVA as a Learning Media for Social Studies

The aim of this study is to explain the utilization of Canva which can be used as a learning media in Social Studies (IPS) subjects along with the stages of its creation. The research method used is a literature study. Library or library research can be interpreted as a series of activities relating to methods of collecting library data, reading and taking notes and processing research materials. Canva is a web-based graphic design tool that allows users to create digital and print images by customizing social media pages, enhancing blog posts, and creating printable materials. With the various templates provided by Canva or by designing your own, Canva can be used as a learning medium and make teaching and learning activities in class more interesting.

Causal chain event graphs for remedial maintenance.

The analysis of system reliability has often benefited from graphical tools such as fault trees and Bayesian networks. In this article, instead of conventional graphical tools, we apply a probabilistic graphical model called the chain event graph (CEG) to represent the failures and processes of deterioration of a system. The CEG is derived from an event tree and can flexibly represent the unfolding of asymmetric processes. For this application, we need to define a new class of formal intervention we call remedial to model the causal effects of remedial maintenance. This fixes the root causes of a failure and returns the status of the system to as good as new. We demonstrate that the semantics of the CEG are rich enough to express this novel type of intervention. Furthermore, through the bespoke causal algebras, the CEG provides a transparent framework with which to guide and express the rationale behind predictive inferences about the effects of various types of remedial intervention. A backdoor theorem is adapted to apply to these interventions to help discover when a system is only partiallyobserved.

Predicting the web crippling capacity of cold-formed steel lipped channels using hybrid machine learning techniques

Cold-Formed Steel Lipped (CFSL) channels are susceptible to a localized failure mechanism known as web crippling, triggered by concentrated loads or reactions applied to the web of the section. These loads induce buckling and distortion in the web, ultimately leading to the member's collapse. It is a challenging task to accurately determine the web crippling capacity of a CFSL channel due to its complexity and various influencing factors. This paper presents hybrid soft computing techniques for accurately predicting the web crippling capacity of CFSL channels subjected to two flange load cases. The developed soft computing techniques combine Artificial Neural Networks (ANN) with either Genetic Algorithms (GA) or Particle Swarm Optimization (PSO) to improve computational efficiency and accuracy. The finite element models of CFSL channels are developed and validated by experimental results and then employed to generate a database, which is used to train machine learning models, including ANN, GA-ANN, and PSO-ANN. Analysis is undertaken on the reliability of existing design formulas for determining the web crippling capacity of CFSL channels. It is shown that the PSO-ANN model outperforms the other models in terms of prediction accuracy. The existing design codes and formulas are not reliable in estimating the web crippling capacity of CFSL channels. However, the proposed model yields good correlation with finite element analysis results. A user- friendly graphical interface tool is developed for the practical design of cold-formed steel lipped channels.

Enhancing Data Trustworthiness in Explorative Analysis: An Interactive Approach for Data Quality Monitoring

The volume of data to be analyzed has increased tremendously in recent years. In order to extract knowledge from this data, domain experts gain new insights with the help of graphical analysis tools for explorative analyses. Here, the reliability and trustworthiness of an exploratory analysis is determined by the quality of the underlying data. Existing approaches require manual testing to ensure data quality which is often neglected. This research aims to introduce a novel interactive approach for seamlessly integrating data quality considerations into the process of explorative data analysis conducted by domain experts. We derive requirements, conduct an extensive literature review, and develop an approach that efficiently combines stakeholders’ strengths, allowing unobtrusive data quality integration in interactive analysis. Our approach enhances trustworthiness due to unobtrusive monitoring of data quality within the context of explorative data analysis. Domain experts gain insights more reliably, bridging the gap between technical requirements and domain expertise. In conclusion, our research presents a promising solution for improving the reliability and trustworthiness of explorative data analysis, especially for domain experts who may lack technical knowledge. By seamlessly integrating data quality into the analytical process, we empower domain experts to extract valuable insights from the ever-increasing volume of data, thereby advancing the field of data-driven decision-making.

Group-wise monitoring of multivariate data with missing values

In this article, we aim to detect the changes in the process that generates multivariate data by monitoring their mean shift. To do this, we utilize a graphical tool known as a multivariate control chart. However, monitoring the mean of multivariate data poses two challenges: the grouped structure of individual observations and the presence of missing values. In this research, we introduce a novel method called HTC for monitoring group-wise multivariate data that includes missing values. HTC offers several advantages over existing methods. First, it is applicable to various types of dependence among individual observations within a group. Second, it provides a unique upper control limit (UCL) regardless of the missing data pattern. Lastly, HTC is computationally more efficient compared to resampling-based techniques. We conduct comprehensive numerical studies to evaluate the performance of the HTC method and compare it with the existing group-wise monitoring method, referred to as HTM. Compared to HTM, HTC achieves a higher true positive rate (TPR) while effectively controlling the in-control false alarm rate ( FAR 0 ) at a pre-determined level across various settings considered in our study. To illustrate its effectiveness, we applied HTC to monitoring multivariate environmental data collected from the manufacturing process of a semiconductor company in Korea.

Causal diagrams for civil and structural engineers

Causal diagrams are logic and graphical tools that depict assumptions about presumed causal relations. Such diagrams have proven effective in tackling a variety of problems in social sciences and epidemiology research yet remain foreign to civil engineers. Unlike the traditional means of examining relationships via multivariable regression, causal diagrams can identify the presence of confounders, colliders, and mediators. Thus, this paper hopes to introduce the big ideas behind causal diagrams (specifically, directed acyclic graphs (DAGs)) and how to create and apply such diagrams to several civil engineering problems. Findings from the presented case studies indicate that civil engineers can successfully use causal diagrams to improve their understanding of complex causation relations, thereby accelerating research and practical efforts.

Efficient 32-nm CNTFET-Based 1-Bit Adder: A Fast and Energy-Optimized Design

CNTFETs are a shows potential choice for traditional CMOS technology due to their potential for lesser power consumption and superior performance. In the present paper, a new 1-bit hybrid full adder has been deliberated and proposed using both pass transistor (PT) and transmission gate logics (TGL), which utilizes a total of 16 transistors. The combination of PT and TGL can lead to improved power efficiency, reduced delay, and enhanced circuit performance in various VLSI applications. For 0.9 V supply voltage at 32-nm CNTFET technology, the power consumption is 0.0748 μW, which is to be an exceptionally low value with a lesser delay of 7.586 Ps and the power-delay-product (PDP) of 0.5674 aJ. The results obtained from this analysis demonstrate the power efficiency, speed, and overall performance of the proposed full adder design. The combination of 32-nm CNTFET technology, deliberate circuit design choices, and the use of specific logic elements (CMOS inverters and strong transmission gates) contributes to the reported characteristics. Using a 0.9 V supply voltage and 32-nm Stanford CNTFET Model technology, the suggested 1-bit adder circuit's concert was investigated using the Mentor Graphics Tool. Finally, using the proposed 1-bit full adder circuit, an N-bit ripple carry adder (N=8, 16 & 32) is implemented and demonstrated. The Simulation results of the 8-bit RCA with a power consumption of 0.373 μW, the delay is 16.852 Ps and the PDP is 6.2857 aJ. These results show that proposed RCA’s have better performance compared to the already reported designs in terms of performance, speed, and power economy.

Evaluating the quality and nutritional content of bottled waters in Algeria

ABSTRACT The present study offers a quality assessment of the mineral and spring waters marketed in Algeria within the national and international legislations, examine the potential contribution of bottled waters to essential elements intake and effects on public health based on empirical, graphical tools, multivariate statistical techniques and (DRI) system. The study covered a dataset of 30 mineral and 33 spring brands. The parameters included, from bottle labels, were of physicochemical nature. All brands comply with national and WHO norms for the bottled waters, except for (Brand#63) in which NO2− exceeded the maximum permissible limit for mineral water and (Brands#4 and #21) where TH and TDS exceeded the Algerian recommended guidelines for spring water. Nearly 5% of the total brands were of bicarbonate nature belonging to mineral water, while 25% of all brands were suitable for low-sodium-diet. PCA and HCA showed that bottled waters could be classified into two distinct groups, according to degree of mineralization. The DRI-system revealed that Algerian bottled waters contributed substantially to the daily intake for Mg2+ with up to (63%), Na+ (40.36%) and Ca2+ (36%) for spring water for different ages and genders, whereas mineral water exceeded the maximum recommended daily intake for Ca2+ (128%) and Na+ (148.36%) for adults.

PPP project price mode typologies: a China-based comparative case study

PurposePublic–Private Partnerships (PPPs) are crucial to the procurement of global infrastructure projects. Moreover, a price mode based on a cluster of core concessionary items is key to the delivery of value-for-money and successful project outcomes. However, existing research has yet to fully identify PPP concessionary items, nor yet described the range of practical price modes. This study provides taxonomy of core concessionary items impacting PPP projects, systematically classifies price modes, and assesses the applicability and risk impacts of those price modes on PPP projects.Design/methodology/approachThis study adopts a comparative case study method in analyzing core concessionary items and alternative price modes. China is taken as the context, as it is one of the world’s largest PPP markets. In ensuring research validity and reliability, diverse data sources are utilized, with a graphic content analysis tool developed to capture the structure of price modes.FindingsEight PPP price modes are identified. These are: (1) UP (Unit Price) mode, (2) ALS (Annual Lump Sum) mode, (3) IRR (Internal Rate of Return) mode, (4) RP (Return for Investing Capital (RIC) - Profit Rate of O&M (PROM)) mode, (5) RFP (RIC - Financing Interest Rate (FR) - PROM) mode, (6) RFPL (RIC - FR - PROM - Lower Limit of User Charge (LLoUC)) mode, (7) RFL (RIC - FR - Lump Sum/Fixed Unit Price O&M Contract (LSOM/FUP)) mode, and (8) RFLL (RIC - FR - LSOM/FUP - LLoUC) mode. Other main findings are as follows: (1) Five risk allocation configurations can be achieved via these price modes. Yet while different price modes enable the allocation of specific risks, these do not always align with contracting parties’ original intentions. (2) IRR and RP modes may be less applicable in general because of their vulnerability in allocating critical risks and capacity for spurring opportunistic behavior.Originality/valueBy depicting the paths by which concessionary items in price modes affect cash flow, a systematic analysis of price modes was conducted exposing structural characteristics, along with risk allocation choice implications. The study is unique in: (1) Providing a systematic classification of PPP price modes used in PPP projects, (2) Presenting a comprehensive identification and streamlining of concessionary items in PPP practice, and (3) Analyzing the risk effects of different price modes. Together, these outcomes offer a hitherto unavailable perspective on PPP project risk management. The value of the study lies in the following: (1) Existing studies employ diverse concessionary items, but their applicability varies. This study offers an overarching framework facilitating decision-making in selecting appropriate PPP price modes and in determining concessionary items. (2) This study adds to the understanding of PPP price modes in significant ways that will aid local governments and potential sponsors in crafting and administrating more workable contract designs.

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.

Generalized overview infographic: a customizable library instructional material on the NIH Data Management and Sharing Policy.

The Generalized Overview of the NIH Data Management and Sharing Policy Effective 2023.01.15 (Generalized Overview) is an instructional material that provides a basic, clear, and linear understanding of the NIH policy and its requirements. While not developing or utilizing new technology, the Generalized Overview is innovative and notable for creatively using a freely available graphic design tool to translate government policy language into an accessible and understandable infographic that can disseminate important information about the NIH DMS Policy needed by researchers and by those who support them. Shared via a Creative Commons license, others may fully adapt the infographic or may simply add their own institutional contact information. The Generalized Overview can be used by any who find themselves responsible for publicizing and/or teaching the NIH Data Management and Sharing Policy at their respective libraries and institutions. It is intended for educational purposes only and should not be used as a substitute for official guidance from the NIH.

Rational preference knowledge influence on the evolutionary equilibrium of carbon reduction negotiation: An exploration based on timed petri net

In the digital economy age, carbon emission reduction is perhaps the most crucial contribution affecting national activities and international negotiations. In a potential carbon reduction conflict, a rational participant expects to select a suitable strategic opinion to reach another state with improved benefit. Participants’ preferences reflect their priority ranking on multiple possible conflict solutions, directly determining the evolutionary direction and equilibrium solutions. Referring to the potential carbon reduction conflicts, Timed Petri Net for Conflict Analysis (TPNCA) is proposed as a graphical tool to explore participants’ rational preferences, state transformation, and conflict evolutionary equilibrium. The generation rule of TPNCA is designed according to carbon reduction co-operators’ rational preference knowledge. From the long-term perspective, dynamic unilateral improvement is proposed to reflect decision-makers’ strategic initiative willingness to reach end nodes. Dynamic equilibrium conditions are conducted to determine the final stability state for a conflict. This study reveals how participants’ preference knowledge and time constraints influence conflict evolutionary and dynamic equilibria. Climate group should positively engage in carbon reduction negotiations and flexibly adjust national tasks, according to real-time carbon reduction contributions. This study (1) reveals the influence of preference knowledge on conflict evolution, (2) explores the role of time constraints in determining a terminated node, (3) proposes dynamic equilibrium from the long-term perspective, and (4) helps guide participants’ strategic decision-making for mutually solving carbon reduction.