Non-functional Characteristics Research Articles

The machine system as a factor of scientific and technological progress in agro-industrial complex

The article proposes a principle for forming a machine system using the object-process approach to modeling technical systems as a methodology of systems engineering. It has been shown that the central concept of a machine system is scientific and technological progress (STP): a machine system should simultaneously promote progress in the agro-industrial complex (AIC) and reflect it. The article presents a definition of a machine system, its functions, main goal, architecture, stakeholders, and external environment. A machine system is positioned as a mixed system that combines conceptual, substantive, and physical components. The conceptual part is an information product – the machine system itself, presented in the form of a computer program, website, standards, databases, on paper, etc. The physical component is a group of experts in developing a machine system. It has been shown that in a market economy, a machine system should be built not on the basis of specific brands and models of technical means, but on the basis of their types. A definition of the type was proposed based on the division of technical means characteristics into functional and non-functional. To substantiate the machine types, an approximate list of types of non-functional characteristics of agricultural machinery was formed. Diagrams of the architecture of the machine system and the development of types of agricultural machines were constructed. The architecture of the machine system is a combination of the structure of the machine system and the activities of experts in the development of the machine system, which ensures the performance of the machine system of its functions, the main ones being the systematization of agricultural machines and technologies and the formation of ideas among interested parties about the state and directions of scientific and technological progress in the agro-industrial complex.

Study of web application development methodology for a medical clinic using React

The article explores in detail the methodologies for developing web applications for medical clinics using the popular React library. The main goal of this study is the analysis of modern approaches to the creation of web applications that meet the specific requirements of medical institutions. Particular attention is paid to the functional and non-functional characteristics that are critical to such systems, including data security, user experience, integration with existing systems, and compliance with regulatory standards. First of all, a comprehensive analysis of the requirements of medical clinics for web applications was carried out. Data security is one of the most important aspects as healthcare institutions work with sensitive information. The study examines methods for ensuring the confidentiality and integrity of medical data, including compliance with HIPAA and GDPR standards. React makes it easy to integrate modern security tools such as JWT (JSON Web Tokens) for authentication and authorization, and use secure HTTP connections for data transfer. In addition, special attention is paid to the user experience (UX/UI), which should ensure the convenience and efficiency of using the web application by both medical personnel and patients. React allows you to create dynamic and interactive interfaces that can adapt to different devices and screens, thus providing a high-quality user experience. This is especially important for medical applications, where the accuracy and speed of interaction can affect the quality of healthcare delivery. A detailed description of best practices and approaches to web application development using React is provided. A component architecture is considered, which provides modularity and code reuse, which is a key factor in creating scalable and easily maintainable applications. Different methods of state management in the application, such as the use of Context API and Redux, have been explored, which allows for efficient data management and stable operation of the application. Guidelines for configuring routing using the React Router library are described, allowing you to create dynamic and multi-page applications while providing smooth navigation and a good user experience. In addition, ways to ensure application security are considered, including protection against XSS attacks, CSRF and other types of vulnerabilities, which is critical in medical applications. The article provides specific recommendations for implementing a web application for a medical clinic. They include practical code examples that demonstrate the implementation of key functionalities such as user registration and authentication, medical record processing, and database interaction. The process of setting up the infrastructure for development, testing and deployment of the application is described, including the use of CI/CD tools to automate these processes, which contributes to increasing the efficiency of development and the quality of the final product. The article provides valuable information for developers who seek to create effective and secure web applications for medical clinics using modern technologies. The conclusions and recommendations presented in the study will help ensure high quality and compliance of the developed solutions with modern industry standards and requirements, which will contribute to increasing the efficiency of the work of medical institutions and the quality of medical services provided to patients

Smartwatch-Based Interventions for People With Dementia: User-Centered Design Approach.

Assistive technologies can help people living with dementia maintain their everyday activities. Nevertheless, there is a gap between the potential and use of these materials. Involving future users may help close this gap, but the impact on people with dementia is unclear. We aimed to determine if user-centered development of smartwatch-based interventions together with people with dementia is feasible. In addition, we evaluated the extent to which user feedback is plausible and therefore helpful for technological improvements. We examined the interactions between smartwatches and people with dementia or people with mild cognitive impairment. All participants were prompted to complete 2 tasks (drinking water and a specific cognitive task). Prompts were triggered using a smartphone as a remote control and were repeated up to 3 times if participants failed to complete a task. Overall, 50% (20/40) of the participants received regular prompts, and 50% (20/40) received intensive audiovisual prompts to perform everyday tasks. Participants' reactions were observed remotely via cameras. User feedback was captured via questionnaires, which included topics like usability, design, usefulness, and concerns. The internal consistency of the subscales was calculated. Plausibility was also checked using qualitative approaches. Participants noted their preferences for particular functions and improvements. Patients struggled with rating using the Likert scale; therefore, we assisted them with completing the questionnaire. Usability (mean 78 out of 100, SD 15.22) and usefulness (mean 9 out of 12) were rated high. The smartwatch design was appealing to most participants (31/40, 76%). Only a few participants (6/40, 15%) were concerned about using the watch. Better usability was associated with better cognition. The observed success and self-rated task comprehension were in agreement for most participants (32/40, 80%). In different qualitative analyses, participants' responses were, in most cases, plausible. Only 8% (3/40) of the participants were completely unaware of their irregular task performance. People with dementia can have positive experiences with smartwatches. Most people with dementia provided valuable information. Developing assistive technologies together with people with dementia can help to prioritize the future development of functional and nonfunctional features.

Pairing New Approach of Tree Soft with MCDM Techniques: Toward Advisory an Outstanding Web Service Provider Based on QoS Levels


 Web services (WSs) have become dynamic because of technological advancements and internet usage. Hence, selecting a WS provider among a variety of WS providers that perform the same function is a critical process. However, the crucial point is that various consumers may have varied needs when it comes to the quality attributes of services, such as cost, response time, throughput, security, availability, etc. These aspects of Web services are known as quality of service (QoS), or non-functional characteristics. Hence, this issue is the robust motivator for conducting this study. The objective of this study is to evaluate a set of WSs that provide various services for various consumers and organizations. This evaluation is conducted based on a set of QoS attributes. Hence, we are applying a new approach to describe this problem in the form of leaves or branches of a tree or hierarchy. This approach is represented in a soft tree set. Also, we leveraged Multi-Criteria Decision Making (MCDM) techniques such as entropy and weighted sum methods under the authority of the Single Value Neutrosophic (SVN) Scale. The entropy technique analyzes attributes or leaves in each level contained in the tree's soft approach, obtaining attributes’ weights. These weights are used to rank and recommend optimal WS providers through the application of these weights in WSM. The results of implementing entropy-WSM in a tree-soft approach indicated that WS2 is the optimal provider. In contrast, WS3 is the worst provider.

Unified Graphical Co-modelling, Analysis and Verification of Cyber-physical Systems by Combining AADL and Simulink/Stateflow

The design of safety-critical cyber-physical systems (CPSs) involve several dimensions, including physics, hardware rchitecture and software functionality. It is desirable to design CPSs by taking these issues into account uniformly and yet, few existing design workflows support this aim. For instance, AADL is an architecturecentric modelling formalism for CPSs, which focuses on modelling architecture and prototyping real-time hardware platforms, but it delegates physical and software behavioral models to so-called annexes. By contrast, Simulink/Stateflow (S/S) focuses on modelling interacting physical and software behaviors, but does not render the non-functional characteristics of their hardware platforms. To address this issue, in [1], we proposed the combination of AADL and S/S, called AADL S/S, to comodel CPSs and presented a method to uniformly analyse and verify them. AADL S/S provides a unified graphical co-modelling environment for CPS design and supports simulation through C code generation. Also, [1] presented a formal semantics of AADL S/S by translation to Hybrid Communicating Sequential Processes (HCSP), yielding a deductive verification framework of the combined models using Hybrid Hoare Logic (HHL). Additionally, [1] proved the correctness of the translation of AADL S/S to HCSP.

An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

Today, various stakeholders provide a large number of functionally similarWeb Services (WS) to meet increasingly complex business needs. Therefore, to distinguish similar WS, some researchers have proposed using the non-functional characteristics, named Quality of Service (QoS), and user’s needs, expressed through Quality of Experience (QoE). Thus, all those QoS and QoE attributes should be taken into account in predicting WS quality jointly, called WS QoSE (Quality of Service and Experience). However, these attributes are different in nature, i.e., QoS is data-driven and numerical, while QoE is expert-based and linguistic. Consequently, to predict WS QoSE, in this paper, we propose a hybrid fuzzy inference approach, composing both quantitative and qualitative data inputs into WS QoSE output by applying the adaptive neuro-fuzzy inference system (ANFIS). The developed prototype allows us to implement the proposed approach, investigate its performance, and study the effect of QoE attributes on WS QoSE. The results of the two experiments show good performance and suitability of the proposed hybrid fuzzy inference approach for predicting WS QoSE based on combining QoS and QoE attributes. We expect that those results inspire researchers and practitioners to understand the WS QoSE better and develop user needs matching WS.

Why are consumers dissatisfied? A text mining approach on Sri Lankan mobile banking apps

PurposeThe motivation of this study is to identify whether the overall rating of a banking app actually reflects the customer opinion and to find the causes for reduced ratings. Thus, these causes lead to the dissatisfaction of customers. Additionally, these insights reflect the overall rating of the app and it is a source of information to the executive management to contemplate on their services and take timely and effective decisions to improve their mobile app.Design/methodology/approachThis research was conducted on ten reputed Sri Lankan mobile banking apps to analyze the textual opinions of the customers. Data were collected from the Google Play Store considering the higher Android consumers in Sri Lanka. Each review was automatically classified into a relevant sentiment (positive, negative or neutral). These classified reviews were examined along with its rating to identify any discrepancies. The trends of the positive and negative reviews of each app were observed separately along with time. Topic modeling techniques were used to identify the causes of such behavior.FindingsAlthough banks expect to perpetuate good customer reviews all the time, there were aberrant negative trends observed during certain time ranges. The results revealed that unstable versions after recent updates, bad customer service, erroneous functional and nonfunctional features are the root causes toward the dissatisfaction of the customers.Originality/valueNo previous study has been done on the textual reviews of Sri Lankan mobile banking apps. Most studies had considered analyzing the reviews of the app on the entire period of its usage, whereas this research finds the trends where negative reviews surpass the positive reviews and analyze the causes of such behavior.

Fintech companies: taxonomy of services and development of innovations (on the example of Kaspi bank JSC)

The financial sector of the Republic of Kazakhstan is facing a radical transformation. Using digital technologies to offer innovative services, new innovative developments are emerging in areas such as asset management, lending or insurance. Despite the growth in investment, there are very few theoretical ideas in the phenomenon of fintech companies. Until now, the proposals of fintech companies have been mainly studied from a functional point of view. Since the functional point of view is not enough to fully understand the proposals of fintech companies, a classification of non-functional characteristics is proposed. Therefore, the analysis of FinTech companies in the consumer-oriented sector is limited. The taxonomy proposed in this study includes 11 dimensions structured by common interactions with prospects, data, and revenue generation. On this basis, this taxonomy contributes to descriptive knowledge about fintech companies, allowing researchers and practitioners to analyze the service offerings of fintech startups and organizations in Kazakhstan in a structured way. At the same time, the impact of innovative products on the activities of Kaspi Bank JSC and its financial results is shown.

Copying fideliy of functional and non-functional features in ni-Vanuatu children: A transmission chain study.

Observational learning plays a key role in cultural transmission. Previous transmission chain experiments have shown that children are able to maintain information across multiple generations through observational learning. It still remains unclear how the transmission of functional vs. non-functional information and the effect of being observed unfold across age in different communities. Here, we examine children's copying fidelity in observational learning of 5- to 13-year-olds from five different communities in Vanuatu, both individually (n = 263, 144 boys) and throughout a transmission chain of five to six children (n = 324, 178 boys). We additionally varied the functionality of the feature being copied (shape vs. color) and the copying context (observed vs. unobserved). Further, we also study developmental and cultural variation in the interaction of features and conditions. We find that children transmit the functional feature shape more faithfully than the non-functional feature color, both in the dyadic transitions as well as the transmission chains with an increasing tendency to do so as they get older. The age patterns show greater variation between communities for color than for shape. Overall, we find that being observed shows no uniform effects but influences transmission differently across communities. Our study shows that children are prone to passing on a functional feature across multiple generations of peers. Children copy non-functional features as well, but with lower fidelity. In sum, our results show children's high propensity and developing abilities for observational learning, ultimately allowing for effective cultural transmission.

Expanding the Frontiers of Industrial Robots beyond Factories: Design and in the Wild Validation

Robots able to coexist and interact with humans are key elements for Society 5.0. To produce the right expectations towards robots, it will be necessary to expose the true current capabilities of robots to the general public. In this context, Human–Robot Interaction (HRI) in the wild emerges as a relevant paradigm. In this article, we affront the challenge of bringing an industrial robot (NEXTAGE Open) outside factories and laboratories to be used in a public setting. We designed a multi-modal interactive scenario that integrates state-of-the-art sensory devices, deep learning methods for perception, and a human–machine graphical interface that monitors the system and provides useful information to participants. The main objective of the presented work is to build a robust and fully autonomous robotic system able to: (1) share the same space as humans, (2) work in a public and crowded space, and (3) provide an intuitive and engaging experience for a robotic exposition. In addition, we measured the attitudes, perceptions, expectations, and emotional reactions of volunteers. Results suggest that participants considered our proposed scenario as enjoyable, safe, interesting, and clear. Those points are also the main concerns of participants about sharing workspaces of daily environments with robots. However, we can point out some limitations with a biased population mainly composed of Japanese and males. In future work, we will improve our scenario with non-functional features or emotional expressions from the robot.

Semantic Interoperability Methods for Smart Service Systems: A Survey

Functional and nonfunctional characteristics of software systems are defined by their architecture. Therefore, research streams such as Internet-of-Things (IoT) or component-based software engineering provide researchers and practitioners with construction guidelines for selected architectural characteristics. Current systems can be categorized in delivering services to the user and being engineered in a smart way. For example, services being provided by IoT-Systems must fulfill users’ goals in a highly dynamic and ad-hoc way. Consequently, this survey aims at answering various research questions regarding the methodical composition of system components and services. Furthermore, new research opportunities are sketched that should be tackled to make the scientific progress available to practitioners. Based on a systematic literature review from a software architecture point of view, in this paper we identify 75 primary studies for domain-specific IoT component composition approaches and architectures. Initial results show that current integration approaches mainly focus on performance evaluation of their integration solutions, which may be too narrow for fulfilling user goals by utilizing of IoT architectures.

A data-driven approach for constructing multilayer network-based service ecosystem models

Services are flourishing drastically both on the Internet and in the real world. In addition, services have become much more interconnected to facilitate transboundary business collaboration to create and deliver distinct new values to customers. Various service ecosystems come into being and are increasingly becoming a focus in both research and practice. However, due to the lack of widely recognized service ecosystem models and sufficient real data for constructing such models, existing studies on service ecosystems are limited to a very narrow scope and cannot effectively guide the design, optimization, and evolution of service ecosystems. In this paper, we first propose a multilayer network-based service ecosystem model (MSEM), which covers a variety of service-related elements, including stakeholders, channels, functional and nonfunctional features, and domains, and more importantly, structural and evolutionary relations between them. “Events” are introduced to describe the triggers of service ecosystem evolution. Then, we propose a data-driven approach for constructing MSEM from public media news and external data sources. Experiments conducted on real news corpora show that compared with other approaches, our approach can construct large-scale models for real-world service ecosystems with lower cost and higher efficiency.

Comparative Study of Data Visualization Tools in Big Data Analysis for Business Intelligence

Abstract: In this era of information, the development of figures has radically expanded, where a colossal amount of data is being delivered from various sources. Because of this huge collection, the worth of information turns into a significant component in each perspective. Data communication is very important to any business - be it small, midsize orBrobdingnagian. Businesses need Data Visualizations to identify data trends at a rapid pace, which would otherwise be tedious. Data Visualization is a robust technology capable of presenting a large dataset in a graphical format. Its centrality goes far beyond merely introducing information to clients. It also assists customers in comprehending information and making decisions. It involves the use of charts, graphs, diagrams, and other info-graphics to communicate data. Surprisingly, a plethora of Data Visualization tools and methodologies have evolved in recent years. This paper conducts an assessment of the mostwidely used and distributed visualization tools for massive data sets, presenting a synoptic of the main functional and non-functional characteristics of the surveyed tools

Development of an electronic system for remote assessment of students' knowledge in cloud-based learning environment

The system for remote assessment of knowledge automates formation of task (tickets) with questions and tasks for conducting intermediate and final monitoring of knowledge of students is offered. In the process of developing an electronic system for knowledge assessment, the basic requirements for a web application and the modules that the system consists of were determined, the main roles of users in the system and their functionality were identified, access rights were established. The technical, functional, and non-functional features of the software product are described, web technologies for creating an application for knowledge assessment are considered. The diagram of system sequences, the use-case diagram, which schematically describing roles and functions of agents in an information system, the diagram of classes of a database structure are presented with UML description. Based on the defined requirements for the resource in cloud-based learning environment, the following technologies for its development were chosen: the server programming language PHP, JavaScript programming language and its libraries were used, as well as the MySQL database with PhpMyAdmin tool for administration of chosen database management system. OpenServer software complex system was used to develop and test the application functionality. The usage of the proposed electronic assessment system of knowledge contributes to the formation of an open information and cloud-based learning environment of a modern educational institution, enhances the efficiency and more rational distribution of teacher time in preparing tests or exams, activates repetition of educational material and knowledge assimilation, indirectly motivates students to more honest learning.

A Comparative and Analytical Study for Choosing the Best Suited SDN Network Operating System for Cloud Data Center

The growing deployment of Software Defined Network (SDN) paradigm in the academic and commercial sectors resulted in many different Network Operating Systems (NOS). As a result, adopting the right NOS requires an analytical study of the available alternatives according to the target use case. This study aims to determine the best NOS according to the requirements of Cloud Data Center (CDC). This paper evaluates the specifications of the most common open-source NOSs. The studied features have been classified into two groups, i.e., non-functional features such as availability, scalability, ease of use, maturity, security and interoperability, and functional features, such as virtualization, fault verification and troubleshooting, packet forwarding techniques and traffic protection solutions. A Decision support system, Analytical Hierarchy Process (AHP) has been applied for assessing specifications of the inspected NOSs, namely, ONOS, Opendaylight (ODL), Floodlight, Ryu, POX and Tungsten. Our investigation revealed that ODL is the most suitable NOS for CDC compared to the rest studied NOSs. However, ODL and ONOS have almost similar scores compared to the rest NOSs.

Non-Functional Testing Framework for Container-Based Applications

Objectives: To propose a generic framework that would help in defining a process and an eco-system which could be used to thoroughly test the non-functional behavior of any container-based applications. Methods: A comprehensive study was conducted to investigate the available frameworks for testing non-functional characteristics. This was followed up by quantitative analysis to know containers, non-functional aspects, generic framework, and its usage requirement. The step-by-step method was used to design the framework, where first the sub-parts were designed and implemented. It was followed up by defining the integration points of all the sub-parts. Finally, a fully matured, functional, and integrated framework came into effect. Findings: There are no frameworks available to focus on the non-functional aspect of container-based applications. The proposed framework can be utilized by various entities, viz developers, testers, integrators, and system or application certification authorities. It can be used to determine the nature and behavior of containerized applications under the known and unknown factors of non-functional characteristics, which transcends the mere realm of application behavior but primarily delves into the surrounding actors for the proper functioning of the application. Novelty: A unique testing framework for container applications focusing on non-functional characteristics. Keywords: Framework, Capacity, Scalability, High Availability, Non­Functional Testing

A Hybrid Hyper-Heuristic Flower Pollination Algorithm for Service Composition Problem in IoT

Objectives: The modern science applications have non-continuous and multivariate nature due to which the traditional optimization methods suffer a lack of efficiency. Flower pollination is a natural interesting procedure in the real world. The novel optimization algorithms can be designed by employing the evolutionary capability of the flower pollination to optimize resources. Methods: This paper introduces the hybrid algorithm named Hybrid Hyper-Heuristic Flower Pollination Algorithm, HHFPA. It uses a combination of Flower Pollination Algorithm (FPA) and Hyper- Heuristic Evolutionary Algorithm (HypEA). This paper compares the basic FPA with the proposed algorithm named HHFPA. FPA is inspired by the pollination process of flowers whereas the hyper-heuristic evolutionary algorithm operates on the heuristics search space that contains all the heuristics to find a solution for a given problem. The proposed algorithm is implemented to solve the Quality of Service (QoS) based Service Composition Problem (SCoP) in Internet of Things (IoT). With increasing services with same functionality on the web, selecting a suitable candidate service based on non-functional characteristics such as QoS has become an inspiration for optimization. Results: This paper includes experimental results showing better outcomes to find the best solution using the proposed algorithm as compared to Basic FPA. Conclusion: The empirical analysis also reveals that HHFPA outperformed basic FPA in solving the SCoP with more convergence rates.

Game the Oretic Approach for Cloud Service Negotiation

Cloud computing is a booming technology in the area of digital markets. Tackling the nonfunctional characteristics is a big challenge between service consumers (SC) and service providers (SP). Without proper negotiation between the participants specifying their quality of service (QoS) requirements, service level agreement (SLA) cannot be achieved. Two strategies that are commonly prevalent in the negotiation process are concession model and trade off model. The concession model assures the service consumer (SC) receiving the services on time without any deferment. But service consumer has only limited utility. To balance the utility and achievement rates, the authors propose a mixed negotiation approach for cloud service negotiation, which is based on “Game of Chicken.” Extensive results show that a mixed negotiation approach brings equal amount of satisfaction to both service consumer and service provider in terms of achieving higher utility and outperforms the concession approach, while taking fewer time delays than that of a tradeoff approach.

A model-based systems engineering approach for developing modular system architectures

Modular system architectures are increasingly important to manufacturers as they seek to decrease system development lead time and as customers have come to expect systems that allow for frequent modular upgrades. There has been considerable research into how to design modules within a system architecture and how to assess the modularity of systems. However, with these established approaches, the modularity assessment is a stand-alone, post-architecting analysis. This research demonstrates how, using model-based systems engineering (MBSE), the assessment of the modularity of a system architecture can be incorporated into the architecting process. To facilitate this, a modularity ontology is developed to guide the semantics and syntax of extensions to the Systems Modeling Language (SysML). Model metadata from behavioural, structural, and state-based system elements is directly assessed using Design Structure Matrix (DSM) based analysis. Elements in the architecture are automatically assigned to modules and the system’s modularity is assessed. The approach allows for the system architect to also consider non-functional characteristics in the formation of modules. The architecting and the modularity analysis of the system are completed in a single environment, using SysML parametric diagrams as the catalyst, allowing for a more holistic and complete understanding of the system and its modularity.

A Location-Based Factorization Machine Model for Web Service QoS Prediction

With the prevalence of web services, a large number of similar web services are provided by different providers. To select the optimal service among these service candidates, Quality of Service (QoS), representing the non-functional characteristics, plays an important role. To obtain the QoS values of web services, a number of web service QoS prediction methods have been proposed. Collaborative web service QoS prediction is one of the most popular approaches. Based on the historical QoS data, collaborative QoS prediction methods employ memory-based collaborative filtering (CF), model-based CF, or their hybrids to predict QoS values. However, these methods usually only consider the QoS information of similar users and services, neglecting the correlation between them. To enhance the prediction accuracy, we propose a novel method to predict QoS values based on factorization machine, which leverages not only QoS information of users and services but also the user and service neighbor’s information. To evaluate our approach, we conduct experiments on a large-scale real-world dataset with 1,974,675 web service invocations. The experiment results show that our approach achieves higher prediction accuracy than other QoS prediction methods.