Functional Requirements Research Articles

A decision support system to increase the compliance of diagnostic imaging examinations with imaging guidelines: focused on cerebrovascular diseases.

Diagnostic imaging decision support (DI-DS) system has emerged as an innovative evidence-based solution to decrease inappropriate diagnostic imaging. The aim of the present study was to design and evaluate a DI-DS system for cerebrovascular diseases. The present study was an applied piece of research. First, the conceptual model of the DI-DS system was designed based on its functional and non-functional requirements. Afterwards, to create the system's knowledge base, cerebrovascular diseases diagnostic imaging algorithms were extracted from the American College of Radiology Appropriateness Criteria (ACR-AC). Subsequently, the system was developed based on the obtained conceptual model and the extracted algorithms. The software was programmed by means of the C#. After debugging the system, it was evaluated regarding its performance and also the users' satisfaction with it. Assessing the users' satisfaction with the system demonstrated that all the evaluation criteria met the acceptable threshold (85 %). The retrospective evaluation of the system's performance indicated that from among 76 imaging examinations, which had previously been performed for 30 patients, 12 (15.78 %) were deemed inappropriate. And, the system accurately identified all the inappropriate physicians' decisions. The concurrent evaluation of the system's performance indicated that the system's recommendations helped the physicians remove 100 % (4 out of 4) of the inappropriate and 40 % (2 out of 5) of the inconclusive imaging examinations from their initial choices. A DI-DS system could increase the compliance of the physicians' decisions with diagnostic imaging guidelines, and also improve treatment outcomes through correct diagnosis and providing timely care.

Importance of CBCT diagnostics in dental implantology

ABSTRACT In today's world, the aesthetic demands of patients in dentistry are very high, followed by functional requirements. CBCT diagnostics facilitate the achievement of these goals. Modern dentistry involves replacing missing teeth with dental implants. In dental implantology, precise imaging techniques are essential to accurately capture the area where implants will be placed, in order to avoid damaging adjacent vital structures during surgery. Today, radiological analysis of CBCT scans is considered the best method of choice, or the gold standard, in the pre-implantation procedure. On CBCT scans, we can visualize the height, width, and density of the available bone for implant placement, the precise location of the maxillary sinus, mandibular canal, mental foramen, incisive canal, and diagnose certain present pathological changes.

Potential Influence of Interleukin-6 -174G/C Gene Polymorphism on Kidney Graft Function and Tacrolimus Dose Requirements: Five-Year Follow-up

1.Introduction: The study aimed to investigate the influence of interleukin (IL)-6 -174G/C gene polymorphism on graft function (defined as estimated glomerular filtration rate, eGFR), as well as on the tacrolimus (Tac) pharmacokinetics during the five years after kidney transplantation. 2.Methods: The study included 115 Caucasian kidney transplant recipients on Tac-based immunosuppression. The patients were followed between 6 and 60 post-transplantation months. Interleukin-6 and CYP3A5 genotyping were performed. 3.Results: Patients carrying the IL-6 -174GG genotype had lower eGFR values compared to the patients with the IL-6 -174GC and -174CC genotypes at the 12th, 48th and 60th post-transplantation months. The linear regression analysis indicated that eGFR at the 6th post-transplantation month and IL-6 -174G/C polymorphism are independent predictors of eGFR values in the late post-transplantation period. The IL-6 -174GG genotype carriers had lower dose-adjusted trough concentration (C0/D) of Tac compared to the IL-6 C allele carriers during the entire observation period (except at the 24th month), while this effect was independent of the CYP3A5 genotype within three years post-transplantation. 4.Conclusion: Interleukin-6 genotyping could be an additional tool to categorize patients toward the risk of graft deterioration in the long-term post-transplantation period. The IL-6 genotyping could be supportive in genotype-guided dosing of Tac.

Topology Optimization of the Bracket Structure in the Acquisition, Pointing, and Tracking System Considering Displacement and Key Point Stress Constraints

The lightweight and displacement-stable design of the mechanical support structure within the APTS (Acquisition, Pointing, and Tracking System) is crucial for enhancing the payload capacity of remote sensing, satellite communication, and laser systems, while still meeting specified functional requirements. This paper adopts the Solid Isotropic Material with Penalization (SIMP) method to investigate the structural topology optimization of the L-shaped bracket in the APTS, aiming to minimize structural compliance while using volume, key point displacement, and maximum stress as constraints. In the optimization model, differences in the topology of the L-shaped bracket structure are explored to minimize structural compliance, which was performed under volume, key point displacement, and stress constraints, and the results are compared with the initial reinforced structure. The innovative L-shaped bracket structure obtained through topology optimization uses significantly less material than the initial reinforced design, while still meeting the displacement and stress constraints. After smoothing, rounding, and finite element analysis, the displacement and stress performance of the optimized L-shaped bracket structure satisfies the set constraints. The method proposed in this paper offers an innovative solution for the lightweight design of mechanical support structures in APTS, with significant engineering application potential.

Redefining competency in fire safe design

The Grenfell Tower Inquiry reports paint a terrifying image of the construction industry, as an ensemble, and particularly, in all matters pertaining fire safe design. Carefully look at these reports will help define responsibilities and legal procedures will do this for many years to come. Nevertheless, it is also essential to address the future and how we evolve our practises and professionals in a manner that prevents a tragedy of this nature to happen again. For this purpose, a key message needs to be emphasized: a functional requirements system of regulation will not deliver what society expects unless a rigorous competency framework is created and implemented for all professionals involved in fire safety. The means to create and put in practise such a framework is at the core of the Grenfell Tower Inquiry Phase 2 recommendations.

Investigating Open Source LLMs to Retrofit Competency Questions in Ontology Engineering

Competency Questions (CQs) are essential in ontology engineering; they express an ontology's functional requirements as natural language questions, offer crucial insights into an ontology's scope and are pivotal for various tasks, e.g. ontology reuse, testing, requirement specification, and pattern definition. Despite their importance, the practice of publishing CQs alongside ontological artefacts is not commonly adopted. We propose an approach based on Generative AI, specifically Large Language Models (LLMs) for retrofitting CQs from existing ontologies and we investigate how open LLMs (i.e. Llama-2-70b, Mistral 7B and Flan-T5-xl) perform in generating CQs for existing ontologies. We compare these results with our previous efforts using closed-source LLMs and we reflect on the results.

Barriers, Facilitators, and Requirements for a Telerehabilitation Aftercare Program for Patients After Occupational Injuries: Semistructured Interviews With Key Stakeholders.

Patients with occupational injuries often receive multidisciplinary rehabilitation for a rapid return to work. Rehabilitation aftercare programs give patients the opportunity to help patients apply the progress they have made during the rehabilitation to their everyday activities. Telerehabilitation aftercare programs can help reduce barriers, such as lack of time due to other commitments, because they can be used regardless of time or location. Careful identification of barriers, facilitators, and design requirements with key stakeholders is a critical step in developing a telerehabilitation aftercare program. This study aims to identify barriers, facilitators, and design requirements for a future telerehabilitation aftercare program for patients with occupational injuries from the perspective of the key stakeholders. We used a literature review and expert recommendations to identify key stakeholders. We conducted semistructured interviews in person and via real-time video calls with 27 key stakeholders to collect data. Interviews were transcribed verbatim, and thematic analysis was applied. We selected key stakeholder statements about facilitators and barriers and categorized them as individual, technical, environmental, and organizational facilitators and barriers. We identified expressions that captured aspects that the telerehabilitation aftercare program should fulfill and clustered them into attributes and overarching values. We translated the attributes into one or more requirements and grouped them into content, functional, service, user experience, and work context requirements. The key stakeholders identified can be grouped into the following categories: patients, health care professionals, administrative personnel, and members of the telerehabilitation program design and development team. The most frequently reported facilitators of a future telerehabilitation aftercare program were time savings for patients, high motivation of the patients to participate in telerehabilitation aftercare program, high usability of the program, and regular in-person therapy meetings during the telerehabilitation aftercare program. The most frequently reported barriers were low digital affinity and skills of the patients and personnel, patients' lack of trust and acceptance of the telerehabilitation aftercare program, slow internet speed, program functionality problems (eg, application crashes or freezes), and inability of telerehabilitation to deliver certain elements of in-person rehabilitation aftercare such as monitoring exercise performance. In our study, the most common design requirements were reducing barriers and implementing facilitators. The 2 most frequently discussed overarching values were tailoring of telerehabilitation, such as a tailored exercise plan and tailored injury-related information, and social interaction, such as real-time psychotherapy and digital and in-person rehabilitation aftercare in a blended care approach. Key stakeholders reported on facilitators, barriers, and design requirements that should be considered throughout the development process. Tailoring telerehabilitation content was the key value for stakeholders to ensure the program could meet the needs of patients with different types of occupational injuries.

Autonomous Cargo Grabbing System for Drones Using Cameras and ROS

Abstract. With the rapid development of low-altitude economy, the functional requirements for logistics UAVs are constantly improving. In this paper, an unmanned aerial vehicle system (UAV) is proposed to realize autonomous grasping of goods. First of all, a new type of grasping device is proposed, which can be easily mounted on the UAV. The camera image stream mounted on the UAV was obtained through camera calibration and corrected. Subsequently, the object recognition algorithm was used to process the image frames, successfully identify the goods to be captured, and calculate the position and direction relationship between the UAV and the target cargo. Next, the speed of the drone is adjusted by the PID controller to achieve a stable landing above the target cargo. Then, the drone is equipped with a robotic claw innovatively designed by our team to complete the gripping of the goods. Subsequently, the drone lifted off and began to deliver cargo. Throughout the grabbing process, a laptop equipped with Ubuntu and ROS systems communicates with the drone via Wi-Fi. The feasibility of the whole system was proved by experiments.

Computer-Modeling System of Agronomist’s Labor Functions

The goal of the paper is to develop the computer-modeling system of an agronomist’s labor functions as the most optimal solution for teaching preschoolers and primary schoolchildren about trends and technologies in farming, aimed at increasing the attractiveness of professions in the field of agriculture. Among the main objectives of the research is the study of the essence of computer modeling as a teaching method in the works of domestic scientists, as well as the construction of models and their implementation using high-level programming languages in order to obtain an information system for the labor functions of an agronomist.Materials and methods. In the course of the analysis, a study was carried out of scientific and technical literature on the use of computer-modeling systems in the educational field. The analysis of the market for computer-modeling systems in the agricultural sector of crop production was carried out. When visualizing and describing system models, UML modeling notation was used. A diagram of use cases for this notation made it possible to describe the functional requirements and interactions between the system and its user. A UML notation sequence diagram was used to model the interaction of the main menu, game scene, and game character over time. The class diagram made it possible to define the structure of the system and the relationships between its objects, as well as an overview of the attributes and operations of the identified classes. The designed system models were implemented in the C# programming language in the Visual Studio development environment.Results. The study revealed the need to introduce new forms, methods and means of teaching into the content of the modern educational process, the implementation of which, largely, is carried out using information technology. The most optimal solution to the issue of teaching children about trends and technologies in agriculture, which has become relevant in the light of the rapid development of agriculture and its digital transformation, was the introduction of computer- modeling systems. The analysis of literature on the research problem has shown that in the works of L. Zhuk, M. Larionova, N. Rozova, etc. great attention is paid to the use of computer modeling as a teaching tool. According to the author, the use of this technology in the educational process makes it possible to implement such teaching principles as the principle of integrative learning, the principle of a practice-oriented approach, the principle of differentiation of learning and the principle of dialogical learning. There are no domestic developments in the subject area under consideration on the information systems market. The author of the study designed and implemented, using the object-oriented programming language C#, the computer-modeling system of agronomist’s labor functions as a technology for teaching professional tasks of an agronomist at various stages of agrarian evolution. The proposed solution allows you to be acquainted with four significant agrarian revolutions that played a decisive role in the transformation of agriculture: the Neolithic revolution, the Renaissance agricultural revolution, the green revolution and the digital revolution in agriculture. Conclusion. It is important to note that the computer-modeling system of the labor functions of agronomist is of interest for preschool and primary education institutions. This development can also be used in the system of additional education for children. Using a computer game in the educational process will expand children’s knowledge about agriculture: it will familiarize them with different agricultural processes, such as planting, growing and harvesting crops, as well as with various types of crop cultivation technologies. This will contribute to the development of interest in the study of agriculture and, as a result, the growth of students’ motivation to connect their professional activities with agriculture.

Generative Models for Source Code: Fine-Tuning Techniques for Structured Pattern Learning

This study addresses the problem of how to automatically generate source code that is not only functional, but also well-structured, readable, and maintainable. Existing generative models for source code often produce functional code, but they lack consistency in structure and adherence to coding standards, essential for integration into existing application development projects and long-term software maintenance. By training the model on specific code structures, including a dataset with Italian annotations, the proposed methodology ensures that the generated code is compliant with both the functional requirements and the pre-defined coding standards. The methodology proposed in this study applies transfer learning techniques on the DeepSeek Coder model, to refine pre-trained models to generate code that integrates additional structuring constraints. By training the model on specific code structures, including a dataset with Italian comments, the proposed methodology ensures that the generated code meets both functional requirements and coding structure. Experimental results, evaluated using the perplexity metric, demonstrate the effectiveness of the proposed approach, which impacts the goals of reducing errors, and ultimately improves software development quality.

A Study on Functional Requirements and Inspection Items for AI System Change Management and Model Improvement on the Web Platform

The rapid adoption of artificial intelligence (AI) on the web platform across multiple sectors has highlighted not only its inherent technical hurdles, such as unpredictability and lack of transparency, but also significant societal concerns. These include the misuse of AI technology, invasions of privacy, discrimination fueled by biased data, and infringements of copyright. Such challenges jeopardize the sustainable growth of AI and risk the erosion of societal trust, industry adoption and financial investment. This analysis explores the AI system’s lifecycle, emphasizing the essential continuous monitoring and the need for creating trustworthy AI technologies. It advocates for an ethically oriented development process to mitigate adverse effects and support sustainable progress. The dynamic and unpredictable nature of AI, compounded by variable data inputs and evolving distributions, requires consistent model updates and retraining to preserve the integrity of services. Addressing the ethical aspects, this paper outlines specific guidelines and evaluation criteria for AI development, proposing an adaptable feedback loop for model improvement. This method aims to detect and rectify performance declines through prompt retraining, thereby cultivating robust, ethically sound AI systems. Such systems are expected to maintain performance while ensuring user trust and adhering to data science and web technology standards. Ultimately, the study seeks to balance AI’s technological advancements with societal ethics and values, ensuring its role as a positive, reliable force across different industries. This balance is crucial for harmonizing innovation with the ethical use of data and science, thereby facilitating a future where AI contributes significantly and responsibly to societal well-being.

Classification of functional and nonfunctional requirements based on convolutional neural network with flower pollination optimizer

Classification of functional and nonfunctional requirements based on convolutional neural network with flower pollination optimizer

User-Centred Design to Inform Requirements for a Remotely Administered Hybrid Functional Test (RAHFT) Protocol.

Functional testing is important to inform return-to-work (RTW), but new paradigms are needed to increase access and availability of testing. Our purpose was to deploy a user centred design approach to collect, describe, and interpret end-user feedback (clinicians and patients) to inform functional requirements for a remotely administered hybrid functional test (RAHFT) protocol. Twenty participants (10 clinicians and 10 patients) were interviewed about existing in-person functional testing and about perceptions of prospective remotely administered functional testing protocols. Interview data were synthesized, where findings informed a focus group with functional testing clinician experts to identify functional design requirements for a RAHFT protocol. Patients agreed that access to equipment and technology, safety, and personal connections were important requirements for a functional testing protocol. Expert clinicians emphasized that a RAHFT should provide valid information to inform treatment planning and RTW outcome decisions, inclusive of opportunities to capture subjective and performance-based information. RAHFT protocols can play an important role towards early and safe RTW. RAHFT protocols will increase availability and improve access for workers that cannot easily attend a clinic for in-person testing. Findings from this study provide functional requirements that should be considered when designing RAHFT protocols.

Classification of Arabic User Requirements: A Semi-Automated Approach using NLP Tools

In this paper, we present a new Semi-Automated classification approach of Arabic user requirements into functional and non-functional requirements using natural language processing (NLP) tools, namely CAMeL Tools. We proposed a set of heuristics based on basic constructs of Arabic sentences in order to extract information from software requirements written in Arabic to classify the requirements into functional and non-functional requirements. CAMeL tools are used to generate tokens, PoS tags, and lemmas of the parsed user requirements, then a set of proposed heuristic rules are applied to CAMeL outputs to determine the closest tagging class for each statement. We implemented the proposed approach using Python code with using CAMeL Tools 1.3.1, under Ubuntu 20.04 LTS. The proposed approach is validated using a set of experiments involving a set of real cases evaluated by a group of experts, graduate, and undergraduate students who are familiar with software requirements. The results showed that the proposed approach achieved better results in the classification of Arabic software requirements than classifications by students with an accuracy of 90%.

Análisis de una plataforma para apoyar en el diagnóstico del síndrome de ovario poliquístico

Polycystic Ovary Syndrome (PCOS) is a common endocrine condition among women of reproductive age and its early diagnosis prevents long-term complications; however, this diagnosis presents difficulties due to the variability of symptoms, cultural taboos and the need for laboratory and imaging tests interpreted by specialists in Gynecology. On the other hand, Artificial Intelligence (AI) techniques have shown great potential to help in the early detection of different diseases. Currently, women in rural and semi-rural areas have little access to specialists and studies, so it is considered useful to have a health platform, which includes AI techniques, in mobile and web environments, that supports the detection of PCOS. This article shows the result of the systems analysis for the aforementioned platform, presenting the functional and non-functional requirements compiled with the help of health professionals in General Medicine and Gynecology.

Food packaging technology considerations for designers: Attending to food, consumer, manufacturer, and environmental issues.

Food packaging is essential for preserving food safety and quality while also addressing environmental concerns. Designers are at the forefront of developing packaging solutions that not only meet functional requirements but also align with evolving consumer preferences and sustainability concerns. To inform designers, this paper discusses fundamental principles of food packaging technology, encompassing aspects such as food preservation, distribution, marketing, usability, and disposal. It provides examples of innovations in active and smart packaging, nanotechnology, material biodegradability, and recyclability, as well as strategies to reduce packaging waste. By providing future food packaging designers with this essential knowledge and these insights, we hope to encourage them to contribute to future innovations that meet the needs of consumers and the environment.

Multisite Pt/H2Ti2O5-TiO2 catalyst for formaldehyde oxidation

The development of multisite catalysts that simultaneously satisfy compositional, spatial arrangement and functional requirements remains a significant challenge. Herein, we report a supported Pt catalyst on surface hydroxyl- and oxygen-vacancy-rich H2Ti2O5/TiO2 composite nanotubes for formaldehyde (HCHO) oxidation. Our study demonstrates that H2Ti2O5/TiO2 nanotubes can be prepared by a hydrothermal method and in particular, using Na2[Pt(OH)6] as a metal precursor yields ultrasmall and uniformly distributed Pt nanoparticles on the nanotube surface. In situ diffuse reflectance infrared Fourier transform spectroscopy analyses reveal that HCHO oxidation over the Pt/H2Ti2O5-TiO2 catalyst occurs via a cooperative catalysis mechanism: Pt facilitates the splitting of O2, surface hydroxyl group on H2Ti2O5 serves as HCHO adsorption site and oxygen vacancy on the TiO2 surface promotes the dissociation of H2O to generate active OH species. Consequently, the Pt/H2Ti2O5-TiO2 catalyst exhibits an impressively high mass-specific reaction rate of 118.0 μmol gPt−1 s−1 and excellent stability, outperforming previously reported HCHO oxidation catalysts.

The impact of nanomaterials on energy-centric form-finding of educational buildings in semi-arid climate

In the modern world, the use of novel technologies in architecture has become highly significant and transformative for human-environment interactions. One of the most critical concerns in architecture is achieving optimal forms and selecting suitable materials for effective design across diverse climatic zones. Also, adopting innovative climate design methods in public spaces, such as educational buildings, is essential due to their strategic urban locations and diverse user populations. Therefore, the research conducted in this study focuses on two main aspects: optimizing building form based on energy consumption and solar radiation received by vertical surfaces, and, selecting appropriate nanomaterials for building surface to reduce energy usage and maintenance costs. This study begins with theoretical foundations, defining the key terms through a comprehensive review of relevant literature. Then, four identical classroom modules with consistent height and floor levels are proposed, and Energy Plus software is used to evaluate the energy consumption based on a module simulation in initial forms of square and rectangle with varying proportions. The best module and orientation is determined using specified climatic data of the coldest and the hottest days of the year. Further, investigations involve combining these modules in various layouts, emphasizing those that align with the functional requirements of educational spaces. Finally, two parameters of energy consumption and solar radiation on vertical surfaces are measured during specified time interval between sunrise and sunset. The results indicate that among the four proposed modules, the 18 × 18 module with a north-south orientation is the most optimal in the semi-arid climate of Tehran, and therefore, Type 3 layout demonstrates the best performance for energy consumption. This is while by incorporating selected nanotechnology (self-cleaning nanomaterial paint), energy usage decreases in all layouts, regardless of the season.

A novel approach to control thermal induced buckling during laser welding of battery housing through a unilateral N-2-1 fixturing principle

Battery housing (BH) in modern electric vehicles must meet demanding functional requirements. The design and geometry of the BH become intricate to prevent damage during collisions and to ensure absolute impermeability to gases and water during operation. Moreover, in the pursuit of a lightweight BH, manufacturers rely on high-strength 6xxx aluminium alloys, posing significant challenges for the welding processes. It is estimated that up to 30 m of weld length is required during the construction of battery housings including joining the lid and under-shield to the main structural frame and joining the ribs to the frame for standard vehicles. Due to the increasing use of thin sheets for lightweighting the structure, thermal-induced buckling may occur and generate critical dimensional unconformities going beyond design tolerances. This underpins the need to optimise fixturing design to control thermal-induced buckling.This paper goes beyond the state-of-the-art “N-2-1” approaches for fixturing thin and deformable parts and proposes the new principle of “unilateral N-2-1 fixturing”. The driving idea is adding unilateral restraints to the direction of thermal contraction, which ultimately causes buckling; and, keeping the direction where the thermal expansion occurs in a free state. The methodology is based on three main steps: (1) physics-based modelling of parts and fixtures using a thermo-mechanical FEA simulation; (2) calibration of the weld heat source using metallographic data; (3) validation using optical scanning technology. The methodology was demonstrated during the laser beam welding of a high-strength aluminium 6xxx thin deformable lid to a rigid high-strength 6xxx aluminium extrusion frame. Results indicated that the thermal induced buckling deformation was reduced from 15 mm, when using the state-of-the-art fixturing approach, to approximately 2 mm with the proposed methodology.

Tailoring the structure of Al50Mo50 alloy films towards realizing the well match between mechanical and electrical performance by controlling the growth mode

Metal films that combine superior mechanical properties with good conductivity are crucial for fulfilling the structural and functional requirements for MEMS applications. To achieve this, single-phase supersaturated solid solution Al50Mo50 alloy films were synthesized using magnetron sputtering at room temperature. By varying the deposition rate, the growth mode of these films was systematically controlled. The results demonstrate that there is no segregation in any of the films, which maintain homogeneity in composition and exhibit unexpected thermal stability at 550℃. As the deposition rate increases, the growth mode of the films transitions from a nano-columnar crystal structure to a layered + island structure. The supersaturated solid solution Al50Mo50 alloy film featuring a layered + island structure exhibits notable properties: high hardness (11.86GPa), high elastic modulus (194.27GPa), excellent ductility with a critical strain of 1.5%, and exceptionally low resistivity (100.95 μΩ cm). This combination of mechanical and electrical properties ensures a well-balanced performance suitable for MEMS applications. Moreover, the controlled process of the growth model and the optimization mechanism for enhanced ductility are systematically elucidated. These findings identify Al50Mo50 alloy films as an ideal candidate material for the design and development of MEMS/NEMS devices.