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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]

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]

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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]

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]

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.

Abstract Background Developmental disorders are a prevalent problem in the health sector of low- and middle-income countries (LMICs), and children in these countries are at greater risk. A registry system is helpful and vital to monitoring and managing this disease. Objective The present study aims to develop an electronic registry system for children's developmental motor disorders. Methods The study was conducted between 2019 and 2020 in three phases. First, the requirements of the system were identified. Second, UML diagrams were first drawn using Microsoft Visio software. Then, the system was designed using the ASP.NET framework in Visual Studio 2018, and the C# programming language was used in the NET 4.5 technology platform. In the third phase, system usability was evaluated from the users' viewpoint. Results The findings of this research included system requirements, a conceptual model, and a web-based system. The client and system server connection was established through the IP/TCP communication protocol in a university physical network. End users approved the system with an agreement rate of 87.14%. Conclusion The study's results can be used as a model for designing and developing systems related to children's developmental movement disorders in other countries. It is also suggested as a valuable platform for research and improving the management of this disease.

In order to adapt to the management mode of the products pipeline network under the new system, set up a service-oriented pipeline system and make for the universality of batch tracking technology, a discussion was made about the products pipeline batch interface tracking technology under the PipeChina system. First of all, the oil batch coding rules and operation terms were standardized from the perspective of information level, which is favorable to the popularization and application. In terms of the development environment, it was considered an effective way to apply online real-time tracking to the accuracy improvement of products pipeline batch interface tracking software(hereinafter referred to as the tracking software), as well as the best way to develop the tracking software on the domestic SCADA system. In respect of technical scheme design, an interface tracking method with 50% concentration point(vol%) was determined and a design was made to the function and flow of tracking software. In response to the key challenges, the accuracy, calibration and error correction of batch tracking were analyzed and verified by the field application results. The customization and universality of the tracking software were discussed from three aspects: data system, oil transportation technology and model coefficient. As a result, an idea was proposed to design the tracking software interface from the software function level. Generally, the research results lay a foundation for the research on accurate products pipeline batch interface tracking technology and the opening of a new control mode of products pipeline network.

Multiphysics processes in fractured porous media is a research field of importance for several subsurface applications and has received considerable attention over the last decade. The dynamics are characterized by strong couplings between processes as well as interaction between the processes and the structure of the fractured medium itself. The rich range of behaviour calls for explorative mathematical modelling, such as experimentation with constitutive laws and novel coupling concepts between physical processes. Moreover, efficient simulations of the strong couplings between multiphysics processes and geological structures require the development of tailored numerical methods.We present a modelling framework and its implementation in the open-source simulation toolbox PorePy, which is designed for rapid prototyping of multiphysics processes in fractured porous media. PorePy uses a mixed-dimensional representation of the fracture geometry and generally applies fully implicit couplings between processes. The code design follows the paradigms of modularity and differentiable programming, which together allow for extreme flexibility in experimentation with governing equations with minimal changes to the code base. The code integrity is supported by a multilevel testing framework ensuring the reliability of the code.We present our modelling framework within a context of thermo-poroelasticity in deformable fractured porous media, illustrating the close relation between the governing equations and the source code. We furthermore discuss the design of the testing framework and present simulations showcasing the extendibility of PorePy, as well as the type of results that can be produced by mixed-dimensional simulation tools.

Abstract 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.

This paper presents the design, development, and testing of an interactive planning tool for urban-wetland systems. The tool targets initial architectural and urban design stages, enabling a broader understanding of natural-urban synergies, ecosystem services, and sustainable systemic design strategies for water management, energy efficiency, on-site food production, community, coastal protection, and security. Targeting a test study site in Queensland, Australia, this paper aims to establish proof of concept for the tool algorithm used to calculate quantitative values for each sub-system and two novel system assessment criteria: 'fair share' (FS) and benefit cost (BC) ratio. The FS criterion is based on the permaculture FS ethical principle and tracks system diversity, resilience, and self-sustenance. The BC criterion builds on cost-benefit valuation methods but includes non-market values, providing a holistic assessment of system costs and benefits, including ecosystem services. Good practise (GP) and best practise (BP) design scenarios are developed for this study site and compared against a business-as-usual (BAU) case. Results demonstrate the relevance of FS and BC as assessment criteria to aid in the development of sustainable designs. Compared to the BAU scenario, the GP and BP scenario BC ratios increased 12 and 14 times, respectively. Yearly cost of living reductions for GP were equivalent to 26,990 AUD per site inhabitant, with BP resulting in a negative yearly cost of living (a yearly benefit equivalent to 6420 AUD per site inhabitant). The use of the FS and BC assessment criteria and tool highlights a potential new approach to planning and development processes, integrating aspects currently omitted within planning requirements and assessments. [ABSTRACT FROM AUTHOR]

Agricultural vehicles, such as tractors, combines, and harvesters, are following the trend of commercial vehicles with a transition from diesel to electric propulsion. Seen as an integrated system, a full-electric tractor is a complex machine with many systems that have to be interconnected for efficient functionality; thus, the need for a central control unit arises. The purpose of this article is to present an electronic control unit that interconnects the powertrain, the hydraulic systems, and the auxiliary systems of a full-electric tractor, with an emphasis on optimization through software design. The article describes the hardware of the electronic control unit and the software state diagrams necessary to implement the functions required by the electric tractor. The results of this article show how, through software optimization, the performances of the tractor can be improved, with parameters such as the response time of the various equipment being a useful indicator of such an improvement. Furthermore, the implementation of trip memory and an easy-to-use human–machine interface allows for easy diagnostic of the electric tractor. [ABSTRACT FROM AUTHOR]

Music education, whether professional or amateur, includes learning musical instruments. Intonation is a critical factor in their training. The main objective of this research work is the design and validation of online educational software for the real-time training and evaluation of intonation in non-fixed pitch musical instruments, such as fretted string instruments (violin, viola, and cello) and brass instruments (trumpet, horn, and trombone). This software is intended to create a practice artefact for novice music students. A design sciences research methodology is adopted to achieve a product tested for functionality and usability. Novice students carry out the validation phase through a study consisting of previous practice with the software and the administration of a questionnaire with open-ended items grouped in technical-didactic, emotional, and overall dimensions, plus two additional questions. The results show evidence that the software was well received, confirming previous studies on the design and validation of educational music education software. [ABSTRACT FROM AUTHOR]

The performance analysis and evaluation of satellite navigation systems under ionospheric scintillation have been a focal point in the field of modern aviation. With the development and upgrading of satellite navigation systems, the performance indicators and evaluation techniques of these systems also require continuous iteration and optimization. In this study, based on the ionospheric scintillation model and satellite navigation algorithm, we designed a software tool to evaluate the performance of GNSS aviation services under various ionospheric scintillation intensities. The software is implemented in the C/C++ programming language and provides assessment capabilities for different ionospheric scintillation environments and flight phases. By encapsulating the software task modules using technologies such as dynamic link libraries and thread pools, the software can flexibly adjust the ionospheric scintillation intensity and control the flight trajectory. This ensures the strong scalability and reusability of the software. The software supports the performance evaluation of aviation services during all flight phases of global flights and is compatible with GPS, BDS, GALILEO, and GLONASS systems. Through verification of the accuracy, integrity, continuity, and availability of the GNSS system under different flight phases and ionospheric scintillation effects, the effectiveness of the software design has been validated. [ABSTRACT FROM AUTHOR]

Paediatric burns are a major public health issue because of long‐term physical, psychological and social consequences and the high cost of treatment. The aim of this study was to design and evaluate a mobile‐based self‐management application for caregivers of children with severe burns. A participatory design technique was employed to develop the Burn application, which included three main phases: the determination of application requirements, the design and evaluation of the low‐fidelity prototype, and the design and evaluation of the high‐fidelity prototypes. In the first phase, application requirements were determined via validated paper questionnaires using the Delphi technique. In the second step, a low‐fidelity prototype was prepared using conceptual models and evaluated through a focus group with specialists. Seven specialists reviewed the application and evaluated how this prototype meets functional requirements and objectives. The third phase was performed in three stages. First, the high‐fidelity prototype was designed and developed by the JAVA programming language. Second, a cognitive walk‐through was carried out to show how users can interact with the mobile application and how it works. Third, this program was installed on the mobile phones of 28 caregivers of burned children, eight IT experts, and two general surgeries, and the prototype's usability was evaluated. In the present study, most caregivers of children with burns stated that after discharge, they face problems regarding infection control and wound care (4.07) and how to perform physical activity (4.12). User registration, educational materials, caregiver‐clinician communication, chat box, and appointment booking, safe login were the most important characteristic of the Burn application. Mean usability evaluation scores were in the range of 7.92 ± 0.238 to 8.10 ± 0.103, which is considered at a "good" level. From the Burn program design experience, it can be concluded that co‐design with health care specialists can significantly support and meet the specialists' and patients' needs and ensure the program's usefulness. In addition, application evaluation by users involved and not involved in the application design process can help enhance usability. [ABSTRACT FROM AUTHOR]

Background: An oral examination might reveal important diagnostic information regarding a patient’s general health. There are several natural changes in the soft tissue structures of the mouth that may resemble a pathological condition. The aim of this research was to develop an educational web- based application for diagnosis in oral medicine and evaluation of the students’ attitudes towards it. Methods: This educational intervention involved one sample group and was conducted from September to December 2019. In the first step, the educational software was designed based on the ADDIE instructional design model. In the second step, 30 dental students were selected by census sampling, and their attitudes towards the designed educational web application were assessed. The web-based educational application was developed using the asp.net web form framework and the #c programming language. The standard kaplan educational product questionnaire was used to assess dental students’ attitudes. Descriptive statistics including the mean, standard deviation, percentage, and frequency were used. Statistical significance was calculated for the components of the questionnaire using the one sample t-test and the cutoff point of 3. SPSS V26 was used to analyze the tests. Results: The majority of students had positive attitudes in all 12 domains of the questionnaire including objectives (P=0.0001), assessment (P=0.0001), practice (P=0.0001), examples (P=0.0001), information (P=0.001), multimedia (P=0.028), overviews (P=0.011), integration (P=0.144), motivation (P=0.0001); organization (P=0.003), usability (P=0.0001), and personalization (P=0.144) which were significantly greater than average and were acceptable. Despite the difference between the two domains (integration and personalization) with the average score, no statistically significant difference was seen. Conclusion: The innovative educational software was successfully developed. The results revealed that students were extremely satisfied with the quality of the educational software. As a result, it can be effectively employed as a teaching aid when combined with conventional education.

As Artificial Intelligence (AI) and Digital Transformation (DT) technologies become increasingly ubiquitous in modern society, the flaws in their designs are starting to attract attention. AI models have been shown to be susceptible to biases in the training data, especially against underrepresented groups. Although an increasing call for AI solution designers to take fairness into account, the field lacks a design methodology to help AI design teams of members from different backgrounds brainstorm and surface potential fairness issues during the design stage. To address this problem, we propose the Fairness in Design (FID) framework to help AI software designers surface and explore complex fairness-related issues, that otherwise can be overlooked. We explore literature in the field of fairness in AI to narrow down the field into ten major fairness principles, which assist designers in brainstorming around metrics and guide thinking processes about fairness. FID facilitates discussions among design team members, through a game-like approach that is based on a set of prompt cards, to identify and discuss potential concerns from the perspective of various stakeholders. Extensive user studies show that FID is effective at assisting participants in making better decisions about fairness, especially complex issues that involve algorithmic decisions. It has also been found to decrease the barrier of entry for software teams, in terms of the pre-requisite knowledge about fairness, to address fairness issues so that they can make more appropriate related design decisions. The FID methodological framework contributes a novel toolkit to aid in the design and conception process of AI systems, decrease barriers to entry, and assist critical thinking around complex issues surrounding algorithmic systems. The framework is integrated into a step-by-step card game for AI system designers to employ during the design and conception stage of the life-cycle process. FID is a unique decision support framework for software teams interested to create fairness-aware AI solutions.

Functional, usable, and maintainable open-source software is increasingly essential to scientific research, but there is a large variation in formal training for software development and maintainability. Here, we propose 10 "rules" centered on 2 best practice components: clean code and testing. These 2 areas are relatively straightforward and provide substantial utility relative to the learning investment. Adopting clean code practices helps to standardize and organize software code in order to enhance readability and reduce cognitive load for both the initial developer and subsequent contributors; this allows developers to concentrate on core functionality and reduce errors. Clean coding styles make software code more amenable to testing, including unit tests that work best with modular and consistent software code. Unit tests interrogate specific and isolated coding behavior to reduce coding errors and ensure intended functionality, especially as code increases in complexity; unit tests also implicitly provide example usages of code. Other forms of testing are geared to discover erroneous behavior arising from unexpected inputs or emerging from the interaction of complex codebases. Although conforming to coding styles and designing tests can add time to the software development project in the short term, these foundational tools can help to improve the correctness, quality, usability, and maintainability of open-source scientific software code. They also advance the principal point of scientific research: producing accurate results in a reproducible way. In addition to suggesting several tips for getting started with clean code and testing practices, we recommend numerous tools for the popular open-source scientific software languages Python, R, and Julia.

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 Objectives: to develop a responsive website focused on treatment adherence for adult users living with HIV. Methods: technological study conducted between August and October 2020, in the light of Pierre Lévy’s theoretical-philosophical framework, using the Double Diamond Process methodology associated with the five stages of The Elements of User Experience framework. Results: it was developed the responsive website Positive Care (Positive o Cuidado), composed of an initial presentation screen and 13 other screens named: Family Health and You; Undetectable = Untransmissible; Antiretroviral Drugs; Routine Tests; Vaccination; Antiretroviral Delivery; Drug Interactions; Combined Prevention; Support Services; Healthy Life; Family and Reproductive Planning; Covid 19; and Questions, Curiosities, and Myths. Final Considerations: the responsive website was developed based on the software design and programming process and has requirements/functionalities with the potential to strengthen the collective intelligence about HIV and, consequently, to promote treatment adherence by its users.

Understanding disease prevention and control is developing due to global pandemics such as severe new coronavirus illness (COVID-19). In addition, the transmission of viruses in residential structures, particularly multi-story apartment complexes, is growing. This study examined the factors which characterise the reach in common interior spaces of social distance post-COVID-19. Secondly, the relationship between types of apartments and which are best after-COVID-19 can be observed. A questionnaire and data gathering for five apartment buildings selected in Erbil were used to the design technique. SPSS and space syntax (software design) and the correlation, regression, and descriptive statistics were then used to examine the data. This research investigates the essential link of social distancing factors in the living areas with independent variables, including physical, psychological, communication, and environmental aspects, in apartment spaces. This research also looks at social distancing factors in apartment spaces. In addition, multiple regression analyses revealed an equation that represents the best prediction of social distance in multi-story living areas with various independent factors of indoor communities. The study shows a favorable association between the components in common interior spaces and social distancing between units with many floors based on a hypothesis test. It also analyses five typical plan typologies of a building with several levels, based on the study and questionnaire evaluations of the inhabitants' space syntax. As a consequence, the advantages and defects of each building type were evaluated. The mixed-method employed in this research has contributed significantly to the acceptability and readability of the design of multi-story apartments as a control tool. Furthermore, the analyses led to a clear preference for the single-loaded (gallery) corridor layout for social distancing. [ABSTRACT FROM AUTHOR]

Often most software development doesn't start from scratch but applies previously developed artifacts. These reusable artifacts are involved in various phases of the software life cycle, ranging from requirements to maintenance. Software design as the high level of software development process has an important impact on the following stages, so its reuse is gaining more and more attention. Unified modeling language (UML) class diagram as a modeling tool has become a de facto standard of software design, and thus its reuse also becomes a concern accordingly. So far, the related research on the reuse of UML class diagrams has focused on matching and retrieval. As a large number of class diagrams enter the repository for reuse, classification has become an essential task. The classification is divided into unsupervised classification (also known as clustering) and supervised classification. In our previous work, we discussed the clustering of UML class diagrams. In this paper, we focus on only the supervised classification of UML class diagrams and propose a supervised classification method. A novel ensemble classifier F-KNB combining both dependent and independent construction ideas is built. The similarity of class diagrams is described, in which the semantic, structural and hybrid matching is defined, respectively. The extracted feature elements are used in base classifiers F-KNN and F-NBs that are constructed based on improved K-nearest neighbors (KNNs) and Naive Bayes (NB), respectively. A series of experimental results show that the proposed ensemble classifier F-KNB shows a good classification quality and efficiency under the condition of variable size and distribution of training samples. [ABSTRACT FROM AUTHOR]

Background: Developmental disorders are a prevalent problem in the health sector of low- and middle-income countries (LMICs), and children in these countries are at greater risk. A registry system is helpful and vital to monitoring and managing this disease. Objective: The present study aims to develop an electronic registry system for children's developmental motor disorders. Methods: The study was conducted between 2019 and 2020 in three phases. First, the requirements of the system were identified. Second, UML diagrams were first drawn using Microsoft Visio software. Then, the system was designed using the ASP.NET framework in Visual Studio 2018, and the C# programming language was used in the NET 4.5 technology platform. In the third phase, system usability was evaluated from the users' viewpoint. Results: The findings of this research included system requirements, a conceptual model, and a web-based system. The client and system server connection was established through the IP/TCP communication protocol in a university physical network. End users approved the system with an agreement rate of 87.14%. Conclusion: The study's results can be used as a model for designing and developing systems related to children's developmental movement disorders in other countries. It is also suggested as a valuable platform for research and improving the management of this disease. [ABSTRACT FROM AUTHOR]

Objective:As computer programming becomes increasingly important in the biomedical sciences and more libraries offer programming classes, it is crucial for librarians to understand how researchers use programming in their work. The goal of this study was to understand why biomedical researchers who enrolled in a library-sponsored workshop wanted to learn to program in R and Python. Methods:Semi-structured in-depth interviews were performed with fourteen researchers registered for beginning R and Python programming workshops at the University of California, San Francisco Library. A thematic analysis approach was used to extract the top reasons that researchers learned to program. Results:Four major themes emerged from the interviews. Researchers wanted to learn R and Python programming in order to perform their data analysis independently, to be an informed collaborator, to engage with new forms of big data research, and to have more flexibility in the tools that they used for their research. Conclusions:Librarians designing programming workshops should remember that most researchers are hoping to apply their new skills to a specific research task such as data cleaning, data analysis, and statistics and that language preferences can vary based on research community as well as personal preferences. Understanding the programming goals of researchers will make it easier for librarians to partner effectively and offer services that are critically needed in the biomedical community.

This article presents a software platform (SP) that helps generate convolutional and feed-forward neural networks and a parametric identification algorithm is proposed for a Cartesian robot using convolutional neural networks (CNN) generated and trained with the proposed SP. The user interface is friendly and aids in developing convolutional and feed-forward neural networks. The SP is made in LAB VIEW®. The user does not need the complete knowledge of mathematics used to perform the training or execution of the network or the programming skills to perform the code that performs such tasks. The SP is designed to reduce the deployment time of neural networks, providing the user with a graphical interface that guides the user through the formation and development of the neural network, this is one of the main contributions. The SP interface is described in this article, showing all the options offered. Five neural networks are presented to prove and demonstrate the software platform’s use. The dynamic models of the Cartesian robot are used; one has six parameters and the other ten parameters. The maximum similarity achieved by the identification algorithm with the six-parameter dynamic model was 99.15% and 99.92% for the ten-parameter model; both are numerical torque analyses. A real Cartesian robot was identified, and five experimental torques were reconstructed for each axis; the maximum similarity was 97.87%. The proposed algorithm is compared with least squares, which obtain 95.81%. Therefore, the results show that the proposed method generates better parametric identification.

The need to support complex human and machine collaboration has increased because of recent advances in the use of software and artificial intelligence approaches across various application domains. Building applications with more autonomy has grown dramatically as modern system development capability has significantly improved. However, understanding how to assign duties between humans and machines still needs improvement, and there is a need for better approaches to apportion these tasks. Current methods do not make adaptive automation easy, as task assignments during system operation need to take knowledge about the optimal level of automation (LOA) into account during the collaboration. There is currently a lack of explicit knowledge regarding the factors that influence the variability of human-system interaction and the correct LOA. Additionally, models have not been provided to represent the adaptive LOA variation based on these parameters and their interactions and interdependencies. The study, presented in this paper, based on an extensive literature review, identifies and classifies the factors that affect the degree of automation in autonomous systems. It also proposes a model based on feature diagrams representing the factors and their relationships with LOAs. With the support of two illustrative examples, we demonstrate how to apply these factors and how they relate to one another. This work advances research in the design of autonomous systems by offering an adaptive automation approach that can suggest levels of automation to facilitate human-computer interactions.

The importance of software security has increased along with the number and severity of incidents in recent years. Security is a multidisciplinary aspect of the software development lifecycle, operation, and user utilization. Being a complex and specialized area of software engineering, it is often sidestepped in software development methodologies and processes. We address software security at the design level by adopting design patterns that encapsulate reusable solutions for recurring security problems. Design patterns can help development teams implement the best-proven solutions for a specialized problem domain. However, from the analysis of three secure pattern implementations by 70 junior programmers, we detected several structural errors resulting from their interpretation. We propose reusable unit testing test cases based on annotations to avoid secure pattern interpretation errors and provide an example for one popular secure pattern. Providing these test cases to the same group of programmers, they implemented the pattern without errors. The reason is annotations build a framework that disciplines programmers to incorporate secure patterns in their applications and ensure automatic testing.

Abstract The evolution of Cloud Computing into a service utility, along with the pervasive adoption of the IoT paradigm, has promoted a significant growth in the need of computational and storage services. The traditional use of cloud services, focused on the consumption of one provider, is not valid anymore due to different shortcomings being the risk of vendor lock-in a critical. We are assisting to a change of paradigm, from the usage of a single cloud provider to the combination of multiple cloud service types, affecting the way in which applications are designed, developed, deployed and operated over such heterogeneous ecosystems. The result is an effective heterogeneity of architectures, methods, tools, and frameworks, copying with the multi-cloud application concept. The goal of this study is manifold. Firstly, it aims to characterize the multi-cloud concept from the application development perspective by reviewing existing definitions of multi-cloud native applications in the literature. Secondly, we set up the basis for the architectural characterization of these kind of applications. Finally, we highlight several open research issues drawn up from the analysis carried out. To achieve that, we have conducted a systematic literature review (SLR), where, a large set of primary studies published between 2011 and 2021 have been studied and classified. The in-depth analysis has revealed five main research trends for the improvement of the development and operation DevOps lifecycle of “multi-cloud native applications”. The paper finishes with directions for future work and research challenges to be addressed by the software community.

Mobile phones can produce detailed and personalized data to help diagnose, treat, prevent or rehabilitate women who are victims of gender violence. We sent automatic text messages, based on cognitive-behavioural therapy, to female victims of gender violence to assess the feasibility of the medium for mental health intervention. During the 28-day intervention period, each woman received four automatic text messages every day on a pre-established schedule. We evaluated symptoms of depression using the Personal Health Questionnaire-9. The Personal Health Questionnaire-9 decreased from an average of 14.8 at the beginning of the intervention, to 6.1 at the end of the text messaging period. All of the women reported that they liked receiving the messages, they found them useful and they felt that the messages had improved their health. Text messages are acceptable to women users who are recipients of public health and social services. Future research should focus more on the evaluation of the results and on how the specific content and aspects of text messaging improve health outcomes.

The rapid development of technology in today’s times make business’ survival a rather complex task. It is therefore necessary for the specialized organization and administration of each company to differentiate and strengthen its competitive advantages. Gamification is an established practice in many business domains and can enforce employees to engage in business processes and change aspects of their behavior. Even though numerous gamification patterns that are described in literature have been used so far by businesses to various working environments, the outcomes were not the best possible that we would expect in terms of their right utilization to business non-game contexts. Thus, there is need for concise gamification patterns that can offer right guidance to game designers in business. Gamification design patterns can provide a distilled knowledge of techniques of how to design object-oriented software. This paper aims to address this gap in existing literature by describing new gamification design patterns, classifying them according to specific criteria and providing new information to this research domain. Our study is a descriptive literature review and is based on review of previous works. This descriptive literature review tries to give a better understanding by proposing new gamification design patterns in the continuously evolving research domain of gamification design patterns.

The following work presents a software solution capable of designing general meal plans which approach an optimal match of nutritional characteristics submitted by the user. A thorough review of existing literature indicates the absence of a software solution to this problem in its most general form. Existing solutions tend to address particular forms of the problem in specific contexts, for example, optimising culturally typical diets in response to specific medical conditions. Conversely, this work focuses on developing a nutritional software model with sufficient flexibility to be described as general, paired with a simple, specifically designed optimisation algorithm for working with the proposed prototype system. The resulting software tool can express the following characteristics: arbitrary nutritional content; economic characteristics; binary food-type classifications (e.g. vegetarian); and, because of the optimisation framework, can capture goals for any number of meals; meal composition (combinations of recipes for a given meal at a particular time); a maximum economic cost per meal; and nutritional content within each meal. The work outlines a prototype user interface to enable nutritional data and user goals to be entered and validated. Finally, based on ten specific test problems containing varied dietary goals, a basic algorithm tuning approach is described. The results suggest that the proposed prototype system can address the general meal optimisation problem. There is a discussion of several future developments to improve system capabilities and usability further. [ABSTRACT FROM AUTHOR]

Background: An oral examination might reveal important diagnostic information regarding a patient's general health. There are several natural changes in the soft tissue structures of the mouth that may resemble a pathological condition. The aim of this research was to develop an educational web- based application for diagnosis in oral medicine and evaluation of the students' attitudes towards it. Methods: This educational intervention involved one sample group and was conducted from September to December 2019. In the first step, the educational software was designed based on the ADDIE instructional design model. In the second step, 30 dental students were selected by census sampling, and their attitudes towards the designed educational web application were assessed. The web-based educational application was developed using the asp.net web form framework and the #c programming language. The standard kaplan educational product questionnaire was used to assess dental students' attitudes. Descriptive statistics including the mean, standard deviation, percentage, and frequency were used. Statistical significance was calculated for the components of the questionnaire using the one sample t-test and the cutoff point of 3. SPSS V26 was used to analyze the tests. Results: The majority of students had positive attitudes in all 12 domains of the questionnaire including objectives (P=0.0001), assessment (P=0.0001), practice (P=0.0001), examples (P=0.0001), information (P=0.001), multimedia (P=0.028), overviews (P=0.011), integration (P=0.144), motivation (P=0.0001); organization (P=0.003), usability (P=0.0001), and personalization (P=0.144) which were significantly greater than average and were acceptable. Despite the difference between the two domains (integration and personalization) with the average score, no statistically significant difference was seen. Conclusion: The innovative educational software was successfully developed. The results revealed that students were extremely satisfied with the quality of the educational software. As a result, it can be effectively employed as a teaching aid when combined with conventional education. [ABSTRACT FROM AUTHOR]

The article is devoted to methods and models of designing systems for the digital transformation of industrial enterprises within the framework of the Industry 4.0 concept. The purpose of this work is to formalize a new notation for graphical modeling of the architecture of complex large-scale systems with data-centric microservice architectures and to present a variant of the reference model of such an architecture for creating an autonomously functioning industrial enterprise. The paper provides a list and justification for the use of functional components of a data-centric microservice architecture based on the analysis of modern approaches to building systems and the authors' own results obtained during the implementation of a number of projects. The problems of using traditional graphical modeling notations to represent a data-centric microservice architecture are considered. Examples of designing a model of such an architecture for a mining enterprise are given. [ABSTRACT FROM AUTHOR]

Developing complex software may be difficult for students or those with less technical expertise in software design due to the large number of diagrams and the complexity of their relationships. Unified modeling language (UML) provides conceptual software design as a system's blueprints, including programming statements, software processes, software components, deployment, design, and development, whereas database schemas use UML for an object-oriented database and entity relation model (ERD) for a relational database. An information flow diagram (IFD) is a technical tool for designing software that includes Infrastructure, data and information, and processing flow. IFD can benefit from examining a new paradigm that facilitates a more practical and rapid understanding of information designs. This data set contains the results of an investigation into the factors affecting the acceptance of IFD for software design by college students. Google forms are used to collect information from undergraduate and graduate computer science, IT, and software engineering students. The extended technology acceptance model (TAM) will focus on studying factors affecting acceptance or decision to use IFD, which includes the ability to create information flow diagrams, satisfaction with software design, and business requirement expectations. This study was carried out at four Thai universities. Research data collection for software design and development courses spanned the academic year 2021. Concerning the use of IFD in software design, 537 respondents were questioned regarding their perceptions, behavioral intentions, information flow diagram capability, software design satisfaction, and business requirement expectations. All students completed the survey. To ensure that participation was voluntary, each participant gave informed consent. Any collected information was rendered anonymous. The participants were given the information solely for research purposes. Ethical values, respect, autonomy, compassion, and confidentiality were guaranteed. The survey's primary questions correspond to the acceptance model's independent variables. Online distribution of the questionnaire yielded 537 valid responses. The dataset consists of 1) student demographics and 2) student perspectives on the factors influencing their intent to learn and apply IFD to software design. Partial Least Squares - Structural Equation Modelling was utilized to analyze the data (PLS-SEM). With the help of these data, researchers, software developers, and educators in various settings can use and analyze alternative software designs and validate models used to study and predict the acceptance of behaviors and factors.

Business 4.0 emphasizes mass personalization and customisation. Even though additive manufacturing (AM) technologies are capable of producing single items, they are not suitable for 3D printing in large quantities. They are at a disadvantage because they can’t finish the industrial process in big volumes. As a result, all activity utilizing additive manufacturing techniques in industrial manufacturing is cautious. Thus, that is the basis of this study. In order to increase the dependability of additive manufacturing procedures and large-scale 3D printing of smart products for global businesses, the research attempts to identify and take advantage of Industry 4.0 technologies. Our study focuses on the requirements of Industry 4.0 technology in data science and additive manufacturing applications. Technologies (ITs) are used in additive manufacturing. Business 4.0 emphasizes mass personalization and customisation. Even though additive manufacturing (AM) technologies are capable of producing single items, they are not suitable for 3D printing in large quantities. They are at a disadvantage because they can’t finish the industrial process in big volumes. As a result, all activity utilizing additive manufacturing techniques in industrial manufacturing is cautious. Thus, that is the basis of this study. In order to increase the dependability of additive manufacturing procedures and large-scale 3D printing of smart products for global businesses, the research attempts to identify and take advantage of Industry 4.0 technologies. Our study focuses on the requirements of Industry 4.0 technology in data science and additive manufacturing applications. Technologies (ITs) are used in additive manufacturing.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

Digitalization could provide efficient and cost-effective health and well-being services to the rapidly aging population. However, digital services do not always meet their needs. We investigated the experiences and service needs of older employees by collecting quantitative and qualitative data through a survey (n = 497). The results suggested a negative association between user satisfaction and age during retirement transition. Peak experiences were meaningful, explaining a 26% variation in the overall evaluation of the portal. The negative peak experiences concerned poorly functioning features, and the positive ones the ability to take care of one’s health smoothly and easily. The respondents had high expectations for functionality, efficiency, and ease of use. They wanted more support for self-managing health: controlling weight, sleeping, recovery, and exercising.

Avatar actions can be captured using certain gesture sensors or can be predefined by game designers through desktop applications. In other words, developing an online avatar editor could be necessary to specify the detailed actions for use by people who are not game creators. Our research team proposed a web-based toolset, myKLA, to construct and design avatar actions with editor and player features. The goal of myKLA is to help users define the required behaviors of avatars within a set time frame without codes. We used cyber–physical system theory in a software reconstruction initiative. Additionally, an exchangeable JSON file format for predefining the avatar actions was opened and shared here. Furthermore, the cyclomatic complexity of the main code blocks in our toolset was measured and changed using the McCabe approach to fine-tune the performance. An algorithm was proposed for quickly calculating an integrated activity diagram from several sub-activity diagrams. Our research showed that it is easy to create an avatar head and embed it in other web-based applications for additional interaction utilization. Therefore, our findings will be useful in creating and designing new educational tools. [ABSTRACT FROM AUTHOR]

The evolution of Cloud Computing into a service utility, along with the pervasive adoption of the IoT paradigm, has promoted a significant growth in the need of computational and storage services. The traditional use of cloud services, focused on the consumption of one provider, is not valid anymore due to different shortcomings being the risk of vendor lock-in a critical. We are assisting to a change of paradigm, from the usage of a single cloud provider to the combination of multiple cloud service types, affecting the way in which applications are designed, developed, deployed and operated over such heterogeneous ecosystems. The result is an effective heterogeneity of architectures, methods, tools, and frameworks, copying with the multi-cloud application concept. The goal of this study is manifold. Firstly, it aims to characterize the multi-cloud concept from the application development perspective by reviewing existing definitions of multi-cloud native applications in the literature. Secondly, we set up the basis for the architectural characterization of these kind of applications. Finally, we highlight several open research issues drawn up from the analysis carried out. To achieve that, we have conducted a systematic literature review (SLR), where, a large set of primary studies published between 2011 and 2021 have been studied and classified. The in-depth analysis has revealed five main research trends for the improvement of the development and operation DevOps lifecycle of "multi-cloud native applications". The paper finishes with directions for future work and research challenges to be addressed by the software community. [ABSTRACT FROM AUTHOR]

Background and Objectives: The increasing speed of environmental changes and the intensification of competition among organizations have caused organizations to seek solutions for greater flexibility in responding to environmental needs and changes. In fact, moving towards creating organizations that have a high degree of flexibility in adapting to a changing environment is a vital and effective solution. One of the effective factors in keeping pace with changes in the environment is the improvement of organizational performance. In this regard, the importance and attention to the development, and improvement of human resources leads to the improvement of organizational performance. There are various strategies and methods for the development and improvement of human resources. One of the ways to develop and improve human resources is coaching. In fact, coaching has created a new approach to staff learning and development. Since information technology is a link among all modern sciences and determines the development of human resources, it has created a new concept in coaching. This research focuses on coaching and information technology. In fact, the purpose of this study is to design a prototype of coaching software as one of the tools to optimize the performance of human resources and ultimately improve organizational performance . Methods: The information of this study was obtained using a mixed approach. The mixed approach benefits from two parts, namely qualitative and quantitative, to achieve the research result. Therefore, the present study used the phenomenological method in the qualitative part and the survey method in the quantitative part. The research instruments in the qualitative part was the focus group method. In the quantitative part of the research, a researcher-made questionnaire was used to collect the information. The statistical population of the study in the qualitative section were specialists in the field of education and human resources, from among them 10 people were selected using the method of snowball sampling. The statistical population of the study in the quantitative part were the top managers of Mashhad Power Distribution Company. From this statistical population, the top managers of the western part of the company, which included 20 people, were selected to perform a usability test . Findings: The data obtained from the qualitative part of the research included 4 components for designing the coaching software, which was based on the prototype model of software development. The data obtained from the research were quantitatively analyzed by SPSS software. Quantitative data analyzed by the software showed that the aforementioned software has the required usability to be implemented in organizations and used by individuals . Conclusion: The present study with laying emphasis on reducing the generation gap between managers and current employees and the individuals who will be employed in the organization and also; and with laying emphasis on technology design by education and human resources experts and examining the existing human resources software, sought to design a prototype of coaching software with features such as communication, cognition, problem facilitation process and problem coping, belief in the ability of individuals and motivational dimensions, and implementation of the selected solution and 360-degree evaluation. The aforementioned features were not seen in the Iranian software examined in the study. In addition to the above features, the distinguishing feature of the aforementioned software is attention to the Cohen and Bradford coaching model, and being process-oriented and feedback-oriented. [ABSTRACT FROM AUTHOR]

The rapid development of technology in today's times make business' survival a rather complex task. It is therefore necessary for the specialized organization and administration of each company to differentiate and strengthen its competitive advantages. Gamification is an established practice in many business domains and can enforce employees to engage in business processes and change aspects of their behavior. Even though numerous gamification patterns that are described in literature have been used so far by businesses to various working environments, the outcomes were not the best possible that we would expect in terms of their right utilization to business non-game contexts. Thus, there is need for concise gamification patterns that can offer right guidance to game designers in business. Gamification design patterns can provide a distilled knowledge of techniques of how to design object-oriented software. This paper aims to address this gap in existing literature by describing new gamification design patterns, classifying them according to specific criteria and providing new information to this research domain. Our study is a descriptive literature review and is based on review of previous works. This descriptive literature review tries to give a better understanding by proposing new gamification design patterns in the continuously evolving research domain of gamification design patterns [ABSTRACT FROM AUTHOR]

Intelligent technology parameter choosing software is the future development trend of realizing precisely control and efficient production. However, the technology parameter choosing software has not been reported probably due to the lack of in-depth understanding of quantitative relationship between technology parameter and magnetic properties for soft ferromagnetic composites. This paper describes a novel strategy to construct quantitative relationship model and develop technology parameter choosing software. Using gas precursor concentration parameter during fluidized bed chemical vapor deposition as an example, the microstructure and performances of Fe(Si)–SiO2 soft ferromagnetic composites obtained were systematically studied. The quantitative relationships between gas precursor concentration and magnetic performances were built based on the gas precursor concentration dependence of SiO2 insulating layer thickness and other classical theoretical models. The findings suggest that the saturation magnetization increase with the gas precursor concentration; however, the impacts of the gas precursor concentration on electrical resistivity and eddy current loss are relatively complex. Informed by these quantitative relationship models, the supporting software has been designed, which can configure the technology parameter automaticity according to the target performance of soft ferromagnetic composites. The results may deepen the understanding on the quantitative relationship and provide ideas for developing efficient production control software.