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The trend for an increasingly ubiquitous and cyber‐physical world has been leveraging the use and importance of microcontrollers (μC) to unprecedented levels. Therefore, microcontroller programming (μCP) becomes a paramount skill for electrical and computer engineering students. However, μCP poses significant challenges for undergraduate students, given the need to master low‐level programming languages and several algorithmic strategies that are not usual in "generic" programming. Moreover, μCP can be time‐consuming and complex even when using high‐level languages. This article samples the current state of μCP education in Portugal and unveils the potential support of natural language processing (NLP) tools (such as chatGPT). Our analysis of μCP curricular units from seven representative Portuguese engineering schools highlights a predominant use of AVR 8‐bit μC and project‐based learning. While NLP tools emerge as strong candidates as students' μC companion, their application and impact on the learning process and outcomes deserve to be understood. This study compares the most prominent NLP tools, analyzing their benefits and drawbacks for μCP education, building on both hands‐on tests and literature reviews. By providing automatic code generation and explanation of concepts, NLP tools can assist students in their learning process, allowing them to focus on software design and real‐world tasks that the μC is designed to handle, rather than on low‐level coding. We also analyzed the specific impact of chatGTP in the context of a μCP course at ISEP, confirming most of our expectations, but with a few curiosities. Overall, this work establishes the foundations for future research on the effective integration of NLP tools in μCP courses. [ABSTRACT FROM AUTHOR]

Purpose An investigational drug services (IDS) pharmacy plays a vital role in supporting clinical trial research by ensuring the safe and efficient management of investigational products. This article describes the implementation of an electronic project management software to improve an IDS pharmacy's study protocol work. The article describes the implementation of the software and how this approach addressed specific challenges, including project oversight, process standardization, documentation, reporting, accountability, and intrateam communication. Summary We describe an electronic project management software system used to streamline and standardize the work associated with study protocols. This software provides an organized and customizable workspace to manage tasks associated with each study protocol. The software automates task creation, tracks progress, and ensures comprehensive record keeping. Additionally, the software fosters effective communication within the team and offers real-time reporting to assess team productivity and progress. We have observed improved consistency, enhanced revenue, including approximately $18,000 in additional fee capture, and increased collaboration among pharmacy team members. Conclusion Implementing an electronic project management software has proven highly beneficial in the IDS pharmacy. The software has significantly improved workflow efficiency by addressing challenges in study protocol management. While initial setup and training required time and resources, the long-term benefits in project oversight, collaboration, and revenue capture justify the investment. An electronic project management software is a valuable tool in managing the complexity of study protocol activities and supports the pharmacy's crucial role in advancing clinical research. [ABSTRACT FROM AUTHOR]

As society's reliance on software systems escalates over time, so too does the cost of failure of these systems. Meanwhile, the complexity of software systems, as well as of their designs, is also ever‐increasing, influenced by the proliferation of new tools and technologies to address intended societal needs. The traditional response to this complexity in software engineering and software architecture has been to apply rationalistic approaches to software design through methods and tools for capturing design rationale and evaluating various design options against a set of criteria. However, research from other fields demonstrates that intuition may also hold benefits for making complex design decisions. All humans, including software designers, use intuition and rationality in varying combinations. The aim of this article is to provide a comprehensive overview of what is known and unknown from existing research regarding the use and performance consequences of using intuition and rationality in software design decision‐making. To this end, a systematic literature review has been conducted, with an initial sample of 3909 unique publications and a final sample of 26 primary studies. We present an overview of existing research, based on the literature concerning intuition and rationality use in software design decision‐making and propose a research agenda with 14 questions that should encourage researchers to fill identified research gaps. This research agenda emphasizes what should be investigated to be able to develop support for the application of the two cognitive processes in software design decision‐making. [ABSTRACT FROM AUTHOR]

Aim: To systemically identify and synthesize information on health professionals' and students' perceptions regarding the development needs of incident reporting software. Design: A systematic review of qualitative studies. Data Sources: A database search was conducted using Medline, CINAHL, Scopus, Web of Science and Medic without time or language limits in February 2023. Review methods: A total of 4359 studies were identified. Qualitative studies concerning the perceptions of health professionals and students regarding the development needs of incident reporting software were included, based on screening and critical appraisal by two independent reviewers. A thematic synthesis was conducted. Results: From 10 included studies, five analytical themes were analysed. Health professionals and students desired the following improvements or changes to incident reporting software: (1) the design of reporting software, (2) the anonymity of reporting, (3) the accessibility of reporting software, (4) the classification of fields and answer options and (5) feedback and tracking of reports. Wanted features included suitable reporting forms for various specialized fields that could be integrated into existing hospital information systems. Rapid, user‐friendly reporting software using multiple reporting platforms and with flexible fields and predefined answer options was preferred. While anonymous reporting was favoured, the idea of reporting serious incidents with both patient and reporter names was also suggested. Conclusion: Health professionals and students provided concrete insights into the development needs for reporting software. Considering the underreporting of healthcare cases, the perspectives of healthcare professionals must be considered while developing user‐friendly reporting tools. Reporting software that facilitates the reporting process could reduce underreporting. Reporting Method: The ENTREQ reporting guideline was used to support the reporting of this systematic review. Patient or Public Contribution: There was no patient or public contribution. Protocol Registration: The protocol is registered in the International Prospective Register of Systematic Reviews with register number CRD42023393804. [ABSTRACT FROM AUTHOR]

Over the past decade, a variety of digital platforms have emerged to deliver core correctional services. Understanding the challenges and drivers of correctional agencies' digitalisation helps us to understand the processes that shape these technologies and their impact on correctional environments and practices. To bridge this gap, we conducted interviews with 26 software developers and other stakeholders involved in the digitalisation of corrections, aiming to explore the challenges encountered in designing and implementing digital service delivery technologies for correctional services. Our findings shed light on some key challenges faced by software developers and other stakeholders involved in the design process, including institutional culture, justice system bureaucracy, and public perceptions. These challenges significantly influence design processes and the availability of digital products for end users. They shape the techno-social landscape of correctional agencies and contribute to the dominance or absence of certain digital platforms or artefacts. [ABSTRACT FROM AUTHOR]

The real-time judgment and screening of the dangerous parts of the whole structure is always one of the very difficult problems in the process of structural strength verification. As an important monitoring index in the static test of aircraft structure, the identification and judgment of the buckling position determines the degree of control of the field test personnel on the overall test. In the static strength test of aircraft structure, the test risk is more and more difficult to control, and unexpected structural failure occurs from time to time. In order to realize the identification of structural buckling parts accurately and efficiently, a buckling real-time detection system was designed and realized. The system realized real-time acquisition of collected data based on timer technology, and completes buckling position judgment based on nonlinearity, and finally visualized the buckling parts through two-dimensional and three-dimensional forms. The system has been applied in the test site, and the effect is remarkable. [ABSTRACT FROM AUTHOR]

Summary: This article presents the development of a new wind turbine simulation software to study wake flow physics. To this end, the design and development of waLBerla‐wind, a new simulator based on the lattice‐Boltzmann method that is known for its excellent performance and scaling properties, will be presented. Here it will be used for large eddy simulations (LES) coupled with actuator wind turbine models. Due to its modular software design, waLBerla‐wind is flexible and extensible with regard to turbine configurations. Additionally it is performance portable across different hardware architectures, another critical design goal. The new solver is validated by presenting force distributions and velocity profiles and comparing them with experimental data and a vortex solver. Furthermore, waLBerla‐wind's performance is compared to a theoretical peak performance, and analyzed with weak and strong scaling benchmarks on CPU and GPU systems. This analysis demonstrates the suitability for large‐scale applications and future cost‐effective full wind farm simulations. [ABSTRACT FROM AUTHOR]

AbstractIndexes are useful for summarizing multivariate information into single metrics for monitoring, communicating, and decision-making. While most work has focused on defining new indexes for specific purposes, more attention needs to be directed toward making it possible to understand index behavior in different data conditions, and to determine how their structure affects their values and the variability therein. Here we discuss a modular data pipeline recommendation to assemble indexes. It is universally applicable to index computation and allows investigation of index behavior as part of the development procedure. One can compute indexes with different parameter choices, adjust steps in the index definition by adding, removing, and swapping them to experiment with various index designs, calculate uncertainty measures, and assess indexes’ robustness. The article presents three examples to illustrate the usage of the pipeline framework: comparison of two different indexes designed to monitor the spatio-temporal distribution of drought in Queensland, Australia; the effect of dimension reduction choices on the Global Gender Gap Index (GGGI) on countries’ ranking; and how to calculate bootstrap confidence intervals for the Standardized Precipitation Index (SPI). The methods are supported by a new R package, called tidyindex. Supplemental materials for the article are available online. [ABSTRACT FROM AUTHOR]

Design patterns represent a means of communicating reusable solutions to common problems, provided they are implemented and maintained correctly. However, many design pattern instances erode as they age, sacrificing qualities they once provided. Identifying such instances of pattern decay is valuable because it allows for proactive attempts to extend the longevity and quality attributes of pattern components. Apart from structural decay, design patterns can exhibit symptoms of behavioral decay. We utilized a taxonomy that characterizes these negative behaviors and designed a case study wherein we measured structural and behavioral decay, hereafter referred to as pattern grime, as well as pattern quality and size, across pattern evolutions. We evaluated the relationships between structural and behavioral grime and found statistically significant cases of strong correlations between specific types of structural and behavioral grime. Furthermore, we extended the QATCH operational software quality model to incorporate design pattern evolution metrics and measured and correlated software quality to the presence of behavioral grime in software systems. Our results suggest a strong inverse relationship between software quality and behavioral grime. [ABSTRACT FROM AUTHOR]

Copyright of Rolling Stock (1002-7602) is the property of Rolling Stock Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper describes the design of a control unit for efficient battery charge management in battery electric vehicles (BEVs). The system design aims at controlling the performance of the charging process of dual lithium-ion battery blocks in electric vehicles, with a main battery that powers the vehicle and an auxiliary one for servicing the ancillary equipment. In this paper, we design and analyze the protocol of a control unit that operates and regulates the battery charge in electric vehicles to obtain optimum performance. The so-designed system enhances the battery charge process and protects the main battery from capacity reduction, thus enlarging the driving range of the electric vehicle. We design a specific protocol for an electric circuit that reproduces the structure of the battery charge system of an electric vehicle. The control system improves the efficiency of the auxiliary battery charge by 4.5%. The theoretical simulation matches experimental values in a simulation test by 98.4%. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the Internet of Things (IoT) application development falls more on libraries and tools, software developers design applications targeting power-constrained edge-computing devices. However, not only the quality-of-service (QoS) but also energy savings remain major challenges. This letter presents Cometes, a complete tool-flow that extends modern SDK tools, assisting developers in selecting resources toward the desired tradeoff between execution time and energy consumption, without exceeding the power limitations of the Edge clusters. Cometes runs at application design time, on top of Kubernetes, and exploits cross-device estimation methods as well as traditional multiobjective optimizers to enable efficient resource allocation. The presented solution achieves up to 66% energy savings, up to 50% speed-up, and an average improvement of 7%, compared to the placement policy of the lightweight Kubernetes (k3s). [ABSTRACT FROM AUTHOR]

To enhance the heat transfer inside the helically coiled tubes, a kind of internally finned helically coiled tubes is proposed. Compared to the smooth helically coiled tubes, the heat transfer and flow resistance characteristics of internally finned helically coiled tubes are investigated numerically. Influence of fin number, pitch and coil diameter on the performance is analyzed. Empirical correlations to calculate the Nusselt number and friction factor of internally finned helically coiled tubes are summarized. The helically coiled tubes heat exchangers are divided equally into several cells and the theoretical analysis of energy flow in each cell is carried out. According to the established equations of heat transfer, the calculation method for single-stream helically coiled tubes heat exchangers and multi-stream helically coiled tubes heat exchangers is proposed. The geometric model and thermohydraulic model are built up, and the design software for internally finned helically coiled tubes heat exchangers is developed based on Python. Take two cases of helically coiled tubes heat exchangers as examples, smooth helically coiled tubes and internally finned helically coiled tubes (fin number is six) are applied to validate the accuracy of calculations results obtained by design software. The results show that the deviation of outlet temperature and pressure drop is less than 7 % and 11 %, respectively. When applying internally finned helically coiled tubes, the heat transfer coefficient of the tube side is increased by approximately 30 %. The corresponding pressure drop and heat load is higher. The outlet temperature proves that the heat transfer is more insufficient in the case of internally finned helically coiled tubes (fin number is six).

This paper describes the design of a control unit for efficient battery charge management in battery electric vehicles (BEVs). The system design aims at controlling the performance of the charging process of dual lithium-ion battery blocks in electric vehicles, with a main battery that powers the vehicle and an auxiliary one for servicing the ancillary equipment. In this paper, we design and analyze the protocol of a control unit that operates and regulates the battery charge in electric vehicles to obtain optimum performance. The so-designed system enhances the battery charge process and protects the main battery from capacity reduction, thus enlarging the driving range of the electric vehicle. We design a specific protocol for an electric circuit that reproduces the structure of the battery charge system of an electric vehicle. The control system improves the efficiency of the auxiliary battery charge by 4.5%. The theoretical simulation matches experimental values in a simulation test by 98.4%.

Accurate estimation of software effort and time in the software development process is a key activity to achieve the necessary product quality. However, underestimation or overestimation of effort has become a key challenge for software development. One of the main problems is the estimation with metrics from late stages, because the product must already be finished to make estimates. In this paper, the use of statistical models and machine learning approaches for software estimation are used in early stages such as software design, and a data set is presented with metric values of design artifacts with 37 software projects. As results, models for the estimation of development time and effort are proposed and validated through leave-one-out cross-validation. Further, machine learning techniques were employed in order to compare software projects estimations. Through the statistical tests, it was proven that the errors were not statistically different with the regression models for effort estimation. However, with Random Forest the best statistical results were obtained for estimating development time. [ABSTRACT FROM AUTHOR]

We provide an overview of the INTERSECT project which delivers research software engineering training to intermediate and advanced developers of research software through week-long bootcamps. In addition to providing a project overview, we describe the first summer bootcamp, provide links to materials, and discuss observations from bootcamp participants. [ABSTRACT FROM AUTHOR]

Background and Aim: With increasing concerns over the stochastic effects of x-ray radiation in dental radiography, effective education of dental students in this field is important. According to studies, educational softwares enhance learning, therefore the aim of this study was to develop an educational software for dental radiation protection and to compare its effectiveness against classic lectures in Islamic Azad University, Tehran Dental branch. Material and Methods: The study was exploratory in the first stage and a clinical trial in the second. Software was developed based on ADA guideline, using ScreenRecorder and MultimediaBuilder. 46 dental students who have never received any education on dental radiation protection were divided into control (N=22) and test (N=24) groups which have been matched based on the GPA and VARK test results. The test group used the software, while the control group attended a lecture. Students’ learning rates were evaluated by using 2 identical 10-question multichoice tests taken immediately and after two weeks. The results were analyzed in SPSS25 using the Mann-U-Whitney test, independent samples t-test, and Pearson's chi-squared test. Results: Educational software was developed successfully. In both exams, the mean score in the test group was higher than that in the control group by a statistically significant difference (p<0.001). The mean scores of test group and control group were 8.91±1.31 and 6.13±1.67 in the first exam and 6.79±1.69 and 4.90±2.09 in the second one respectively. Conclusion: Multimedia educational software can improve learning of principles and methods of dental radiation protection in dental students. [ABSTRACT FROM AUTHOR]

The full potential for electronic health record systems in facilitating a positive transformation in care, with improvements in quality and safety, has yet to be realised. There remains a need to reconceptualise the structure, content and use of the nursing component of electronic health record systems. The aim of this study was to engage and involve a diverse group of stakeholders, including nurses and electronic health record system developers, in exploring together both issues and possible new approaches to documentation that better fit with practice, and that facilitate the optimal use of recorded data. Three focus groups were held in the UK and USA, using a semi-structured interview guide, and a common reflexive approach to analysis. The findings were synthesised into themes that were further developed into a set of development principles that might be used to inform a novel electronic health record system specification to support nursing practice. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rapid societal development and increased engineering construction have exacerbated the disturbance of the geological environment. The impact of extreme climatic factors has grown, leading to a surge in geological disasters, with landslides emerging as particularly significant. Consequently, fundamental research in geological disaster detection or monitoring necessitates an in-depth study of the physical phenomena accompanying landslides' development, evolution, and occurrence. Exploring the signal characteristics associated with landslides is crucial to indirectly understanding their development and change processes—a scientific question deserving thorough exploration. Despite this research's importance, there is a notable gap in the investigation of the key design and specific implementation of electromagnetic instruments tailored for landslide detection. This gap is particularly pronounced in designing and implementing data acquisition software for electromagnetic instruments. This interdisciplinary research draws on theoretical frameworks from embedded computer science, software engineering, digital signal processing technology, geophysics, and engineering geology. It focuses on developing specialized data acquisition application software for landslide detection or monitoring, contributing to the scientific understanding of landslide development and providing independent intellectual property in the electromagnetic wave signal detection field. [ABSTRACT FROM AUTHOR]

Copyright of Railway Investigation & Surveying is the property of Railway Investigation & Surveying Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Existing brain-computer interface (BCI) software platforms are typically designed for research purposes and offer limited usability for non-technical end-users. This paper presents the Mindset software application, which allows end-users to train and use a BCI through a graphical user interface. The four modules of Mindset (acquisition, visualization, training, and output) collectively provide functionality to connect to various EEG hardware, visualize incoming data streams, perform user training for mental imagery and visual P300 paradigms, and facilitate real-time control of a diverse range of applications. Online experiments were conducted to characterize system performance during motor imagery and visual P300 tasks with different EEG headsets and computing hardware. With both motor imagery and visual P300 paradigms, and two different headsets and two different computer configurations, output latency was no greater than 30 ms, latency jitter below 10 ms and system clock jitter less than 17 ms. Further, the prototypical event-related potential morphology was confirmed in the visual P300 paradigm, while the expected contralateral desynchronization was observed in the motor imagery paradigm. These results demonstrate that Mindset can satisfy the real-time requirements of a BCI system and reliably capture relevant neurophysiological signals with readily available computing hardware. Mindset facilitates the translation of BCI research into clinical and practical use by improving the accessibility and usability of BCI technology.

It is always difficult to analyze the law of ship movement, especially the behavior of ship. In this paper, a frequent pattern mining method based on a large number of historical track clustering of ships is proposed to estimate the future behavior of ships, and the software implementation is presented. In this paper, a comprehensive similarity measurement method of track is proposed and the meaning of frequent pattern mining based on track clustering is introduced. Secondly, the adaptive transformation of the classical density clustering algorithm is carried out and the implementation method of the clustering algorithm based on comprehensive similarity is given. Then, the most similar cluster of virtual trunk track calculation is extracted, and the estimation results of current ship behavior are obtained by statistics. Finally, the software design and test results based on C/S architecture are given. Experimental results show that this method can describe the behavior of track association, and the behavior estimation results obtained by the software can assist the research and judgment.

The ongoing digital transformation of industry is most clearly reflected in the increasing collection and analysis of data from various sources. Among these are sensor equipped machinery, telemetry in logistics or audiovisually monitored production floors. In order to utilize the data, e. g., to predict machinery malfunctions, its technically smooth consolidation is crucial. Therefore, numerous data interchange formats, protocols and middleware emerged over the past years. However, until today there is no gold standard technology stack for industrial data analysis, for multiple reasons, including the applications' heterogeneity. In this work, we present a software library which aims at decoupling messaging protocols and patterns from their implementation to overcome incompatibilities and, thus, facilitate data consolidation for software engineers. Moreover, we show how to use the library for rapidly modeling distributed cyber-physical systems using an integrated schema generation mechanism. Based on one real-world and one synthetic use case, we evaluate the library's applicability, discuss open issues and outline planned features. [ABSTRACT FROM AUTHOR]

Introduction: at present, when the use of information and technology is essential for decision making, the data has become a resource of a lot of value to boost the success of hospital entities and improve the quality of life of the people. Objective: describe the "Dynamic data set generator for intensive care service" software. Methods: technological development research in the Intensive Care Service of the "Arnaldo Milián Castro" Hospital in the 2017 to 2022 period. The defined population were all the specialists (12) of the intensive therapy room that used the system since January of January 2017 to December 2022. Results: it allows to collect clinical data of patients from the intensive therapy room and generate dynamic data sets for intensive care specialists and data analysis. Conclusions: system in exploitation since 2017, the data sets generated have been used for the application of automatic learning techniques, which has enhanced medical research and timely decision making. [ABSTRACT FROM AUTHOR]

Low Back Pain (LBP) is a prevalent health issue that affects many people's daily functioning and well-being. However, diagnosing LBP is challenging because it requires expert knowledge of the spine's structure and function. Therapists usually rely on asking patients questions to guide their tests, but this method is not very efficient. Moreover, existing systems for LBP diagnosis and information exchange are narrow in their coverage. To address these limitations, this paper proposes a design specification for a web-based decision support system that offers a preliminary diagnosis and suggests a comprehensive diagnosis that may have multiple components. The system design incorporates an intuitive and user-friendly framework that can handle the complex features of LBP diagnosis and uses verbal probability estimation to cope with the uncertainty involved. The design specification can facilitate communication among the relevant stakeholders. [ABSTRACT FROM AUTHOR]

The relevance of the research lies in the growing need of future teachers for effective and productive tools for teaching design, which can significantly reduce the time of learning new progressive software tools. With the development of technology and increasing competition in the market, speed and quality of design are becoming critical success factors. The purpose of the study is to study the effectiveness and productivity of using SolidWorks in the process of teaching design, as well as to determine its advantages over other CAD programs. The article analyzes the use of SolidWorks in the modern engineering and pedagogical process, highlights its advantages compared to other CAD programs, and emphasizes its importance for educators in the process of creating and learning new products and technologies. SolidWorks is positioned as an innovative design program that has numerous advantages due to the interface and a wide set of tools that allow you to significantly increase the efficiency and productivity of learning for the work of future educators. The program also provides the ability to perform various analyzes and simulations, which contributes to the improvement of product quality, allowing to identify potential problems in the early stages of design and reduce costs and risks in design. In general, the use of SolidWorks during the educational process provides ample opportunities for training future teachers. This software significantly increases the efficiency and quality of the educational process, making it an integral part of modern pedagogical education. Future innovations and developments in SolidWorks promise to further improve the competitiveness of design at various stages of the educational process. [ABSTRACT FROM AUTHOR]

It is always difficult to analyze the law of ship movement, especially the behavior of ship. In this paper, a frequent pattern mining method based on a large number of historical track clustering of ships is proposed to estimate the future behavior of ships, and the software implementation is presented. In this paper, a comprehensive similarity measurement method of track is proposed and the meaning of frequent pattern mining based on track clustering is introduced. Secondly, the adaptive transformation of the classical density clustering algorithm is carried out and the implementation method of the clustering algorithm based on comprehensive similarity is given. Then, the most similar cluster of virtual trunk track calculation is extracted, and the estimation results of current ship behavior are obtained by statistics. Finally, the software design and test results based on C/S architecture are given. Experimental results show that this method can describe the behavior of track association, and the behavior estimation results obtained by the software can assist the research and judgment. [ABSTRACT FROM AUTHOR]

Background and Aims: Systems existing in hospital or clinic settings offer services within the physical environment. Examples of such systems include picture archiving and communication systems, which provide remote services for patients. To develop a successful system, methods like software development life cycles (SDLCs) and design techniques, such as prototyping, are needed. This study aimed to specify requirements, design, and evaluation of dental image exchange and management system using a user‐centered approach. Methods: This cross‐sectional study was conducted in four phases, each corresponding to different stages of SDLCs. User‐needs data were used to gathered by interviews and observations. A prototype was developed using object‐oriented programming and presented to users for feedback. Finally, focus group was used to finalized the prototype into the desired system. Results: User needs were identified and prioritized from the outset, with ease of use, security, and mobile apps being their most essential requirements. The prototype underwent several iterations of design and evaluation in focus group sessions until users were satisfied, and their feedback was incorporated. Eventually, the prototype was refined into the final system with users' consent. Conclusion: The study revealed that instant access to information, voluntary participation, user interface (UI) design, and usefulness were critical variables for users and should be integral to any system. Successful implementation of such a system requires careful consideration of end‐users' needs and their application to the system. Moreover, integrating the system with electronic health records can further enhance the treatment process and the efficiency of medical staff. The voluntary perspective of users played a significant role in achieving an exemplary UI and overall satisfaction with the system. Developers and policymakers should consider these aspects in similar system development projects. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Computational Mechanics / Jisuan Lixue Xuebao is the property of Chinese Journal of Computational Mechanics Editorial Office, Dalian University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. We aimed to identify the key processes relevant to COVID-19 transmission dynamics and thereby develop a model that could quantify relevant epidemiological parameters.The pipeline's advantages include markedly increased speed, an expressive application programming interface, the transparency of open-source development, easy access to a broad range of calibration and optimisation tools and consideration of the full workflow from input manipulation through to algorithmic generation of the publication materials. Extending the base model to include mobility effects slightly improved model fit to data, with this approach selected as the model configuration for further epidemiological inference. Under our assumption of widespread immunity against severe outcomes from recent vaccination, incorporating an additional effect of the main vaccination programs rolled out during 2022 on transmission did not further improve model fit. Our simulations suggested that one in every two to six COVID-19 episodes were detected, subsequently emerging Omicron subvariants escaped 30–60% of recently acquired natural immunity and that natural immunity lasted only one to eight months on average. We documented our analyses algorithmically and present our methods in conjunction with interactive online code notebooks and plots.We demonstrate the feasibility of integrating a flexible domain-specific syntax library with state-of-the-art packages in high performance computing, calibration, optimisation and visualisation to create an end-to-end pipeline for infectious disease modelling. We used the resulting platform to demonstrate key epidemiological characteristics of the transition from the emergency to the endemic phase of the COVID-19 pandemic.

BackgroundInformation regarding response to past treatments may provide clues concerning the classes of drugs most or least likely to work for a particular metastatic or neoadjuvant early stage breast cancer patient. However, currently there is no systematized knowledge base that would support clinical treatment decision-making that takes response history into account.MethodsTo model history-dependent response data we leveraged a published in vitro breast cancer viability dataset (84 cell lines, 90 therapeutic compounds) to calculate the odds ratios (log (OR)) of responding to each drug given knowledge of (intrinsic/prior) response to all other agents. This OR matrix assumes (1) response is based on intrinsic rather than acquired characteristics, and (2) intrinsic sensitivity remains unchanged at the time of the next decision point. Fisher's exact test is used to identify predictive pairs and groups of agents (BH p  1). In vitro conditional response patterns clustered compounds into five predictive classes: (1) DNA damaging agents, (2) Aurora A kinase and cell cycle checkpoint inhibitors; (3) microtubule poisons; (4) HER2/EGFR inhibitors; and (5) PIK3C catalytic subunit inhibitors. The apriori algorithm implementation made further predictions including a directional association between resistance to HER2 inhibition and sensitivity to proteasome inhibitors.ConclusionsInvestigating drug sensitivity conditioned on observed sensitivity or resistance to prior drugs may be pivotal in informing clinicians deciding on the next line of breast cancer treatments for patients who have progressed on their current treatment. This study supports a strategy of treating patients with different agents in the same class where an associated sensitivity was observed, likely after one or more intervening treatments.