Whole System Research Articles

A generic hierarchical System of Systems Engineering (SOS) Approach for Model based System Engineering (MBSE) Projects

AbstractModel based systems engineering (MBSE) has been accepted worldwide by many industries, including the automotive industry, for several years. Hundreds of projects have already been developed and deployed using MBSE approaches. MBSE is gaining importance because it provides systems advantageous life cycle processes, such as returns of investments and meeting the demands of global marketplaces, as they become increasingly complex. Consequently, the number and pace of deployment using MBSE approaches will increase in the future.Our current work objective is to define a generic MBSE methodology compatible with Systems Engineering Body of Knowledge (SEBOK) functional decomposition principles, ‘Automotive open systems architecture’ (AUTOSAR) developments and compliant to ‘Automotive software performance improvement and capability determination’ (ASPICE) processes using the ‘systems modelling language’ (SysML). We have proposed a generic SysML process framework, a hierarchical system of systems (SOS) engineering approach and automation solutions. We have shown that the proposed solution helps meet the defined objectives. The work is targeted and relevant for automotive industry MBSE practitioners. In general, the research, apart from transportation and mobility industries, can also be used in other industries.

The Use of Knowledge Management Technology Among Selangor State Government Agencies

Knowledge management is one of the important things for the success of an organization. The state of Selangor, which is the first developed state in Malaysia since 2005, often being used as a benchmark by other states, including in terms of information technology implementation. This study has been conducted to identify the use of knowledge management technology among Selangor State government agencies. For this purpose, a quantitative study has been conducted by distributing questionnaire to the respondents from 10 Selangor State government agencies. Studies conducted show that knowledge management technology is part of the instruments used to assist governance in the government agencies of Selangor State. Besides, encouragement from management, related policies and even IT infrastructure are also available and support all information life cycle processes to run well in Selangor State government agencies.

Collaborative innovation: a technological perspective

Collaborative innovation: a technological perspective

The Barrier Factors to the Implementation of Building Information Modelling for Construction Industry in Sarawak

Building Information Modelling (BIM) Construction Lifecycle Process offers digital construction solutions throughout the whole project lifecycle by providing sustainable productivity and quality and increasing the work collaboration and efficiency of the design teams. BIM represents the development and application of computer-generated n-dimensional (n-D) models to simulate building construction planning, design, construction, and operation. In Sarawak, the BIM technology does not meet the construction stakeholder's expectations during the project lifecycles in different stages, which resulted in low BIM implementation. Therefore, this research study aims to identify the salient barrier factors to the implementation of BIM in the Sarawak construction industry, specifically in the design stage. To achieve the research study, the methodology is applied through literature review, followed by an online interview with BIM experts in Sarawak Construction Industry. Lastly, the findings of this study indicate the most salient factors faced by the Sarawak construction industry until the present, in terms of Technology, Cost, Management, Personal and Policy, such as (1) Lack of active participation from consultants in the project team, (2) Low enforcement from client, (3) Lack of senior management support, (4) Lack of desire to change of the older generation to implement BIM and (5) Lack of the knowledge regarding the cost benefits for implementing BIM.

Effects of agricultural pesticides on the susceptibility and fitness of malaria vectors in rural south-eastern Tanzania

BackgroundAgricultural pesticides may exert strong selection pressures on malaria vectors during the aquatic life stages and may contribute to resistance in adult mosquitoes. This could reduce the performance of key vector control interventions such as indoor-residual spraying and insecticide-treated nets. The aim of this study was to investigate effects of agrochemicals on susceptibility and fitness of the malaria vectors across farming areas in Tanzania.MethodsAn exploratory mixed-methods study was conducted to assess pesticide use in four villages (V1–V4) in south-eastern Tanzania. Anopheles gambiae (s.l.) larvae were collected from agricultural fields in the same villages and their emergent adults examined for insecticide susceptibility, egg-laying and wing lengths (as proxy for body size). These tests were repeated using two groups of laboratory-reared An. arabiensis, one of which was pre-exposed for 48 h to sub-lethal aquatic doses of agricultural pesticides found in the villages.ResultsFarmers lacked awareness about the linkages between the public health and agriculture sectors but were interested in being more informed. Agrochemical usage was reported as extensive in V1, V2 and V3 but minimal in V4. Similarly, mosquitoes from V1 to V3 but not V4 were resistant to pyrethroids and either pirimiphos-methyl or bendiocarb, or both. Adding the synergist piperonyl butoxide restored potency of the pyrethroids. Pre-exposure of laboratory-reared mosquitoes to pesticides during aquatic stages did not affect insecticide susceptibility in emergent adults of the same filial generation. There was also no effect on fecundity, except after pre-exposure to organophosphates, which were associated with fewer eggs and smaller mosquitoes. Wild mosquitoes were smaller than laboratory-reared ones, but fecundity was similar.ConclusionsSafeguarding the potential of insecticide-based interventions requires improved understanding of how agricultural pesticides influence important life cycle processes and transmission potential of mosquito vectors. In this study, susceptibility of mosquitoes to public health insecticides was lower in villages reporting frequent use of pesticides compared to villages with little or no pesticide use. Variations in the fitness parameters, fecundity and wing length marginally reflected the differences in exposure to agrochemicals and should be investigated further. Pesticide use may exert additional life cycle constraints on mosquito vectors, but this likely occurs after multi-generational exposures.Graphical

AI Futures Literacy

<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">When we are thinking</b> about the ethics of AI and the ramifications for selfhood and society brought about by technologically enabled modes of modern indentured servitude, we are thinking about the future. We are anticipating future risks, imagining potential disruptions and disruptors, considering the balance of harms and benefits, assessing their probability and their scale, and planning mitigation strategies to deal with them. This article proposes some new ways through which we might better understand the scope (and the limitations) of this mode of anticipatory thinking and so develop a stronger sociotechnical capability in what we might characterize as “ethical AI futures literacy.” It also suggests some first steps toward developing this new approach by highlighting some of the cognitive biases and deficiencies which particularly affect such futures thinking and which shape the anticipatory dynamics of both human and artificial intelligence <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> .

Cyber LOPA: An Integrated Approach for the Design of Dependable and Secure Cyber-Physical Systems

Safety risk assessment is an essential process to ensure a dependable cyber-physical system (CPS) design. Traditional risk assessment considers only physical failures. For modern CPSs, failures caused by cyber attacks are on the rise. The focus of latest research effort is on safety–security lifecycle integration and the expansion of modeling formalisms for risk assessment to incorporate security failures. The interaction between safety and security lifecycles and its impact on the overall system design, as well as the reliability loss resulting from ignoring security failures, are some of the overlooked research questions. This article addresses these research questions by presenting a new safety design method named cyber layer of protection analysis (CLOPA) that extends the existing layer of protection analysis (LOPA) framework to include failures caused by cyber attacks. The proposed method provides a rigorous mathematical formulation that expresses quantitatively the tradeoff between designing a highly reliable and a highly secure CPS. We further propose a co-design lifecycle process that integrates the safety and security risk assessment processes. We evaluate the proposed CLOPA approach and the integrated lifecycle on a practical case study of a process reactor controlled by an industrial control testbed and provide a comparison between the proposed CLOPA and current LOPA risk assessment practice.

BpEIN3.1 represses leaf senescence by inhibiting synthesis of ethylene and abscisic acid in Betula platyphylla

Leaf senescence and abscission play crucial role in annual plant adapting to seasonal alteration and climate changes by shortening life cycle and development process in response to abiotic and/or biotic stressors underlying phytohormones and environmental signals. Ethylene and abscisic acid are the major phytohormones that promotes leaf senescence, involving various transcription factors, such as EIN3 (ethylene-insensitive 3) and EIL (ethylene-insensitive 3-like) gene family, controlling leaf senescence through metabolite biosynthesis and signal transduction pathways. However, the roles of EIN3 regulating leaf senescence responding to environmental changes in perennial plant, especially forestry tree, remain unclear. In this study, we found that BpEIN3.1 from a subordinated to EIL3 subclade, is a transcription repressor and regulated light-dependent premature leaf senescence in birch (Betula platyphylla). BpEIN3.1 might inhibits the transcription of BpATPS1 by binding to its promoter. Shading suppressed premature leaf senescence in birch ein3.1 mutant line. Ethylene and abscisic acid biosynthesis were also reduced. In addition, abscisic acid positively regulated the expression of BpEIN3.1. This was demonstrated by the hormone-response element analysis of BpEIN3.1 promoter and its gene expression after the hormone treatments. Moreover, our results showed that abscisic acid is also involved in maintaining homeostasis. The molecular mechanism of leaf senescence provides a possibility to increasing wood production by delaying of leaf senescence.

Operational management as a basis for the formation of the enterprise's competitiveness

The relevance of practical issues of managing the company's operational activities, taking into account its impact on competitiveness, has been proven. The conditions of martial law in Ukraine are characterized by the decline of production at most industrial enterprises, the curtailment of scientific research, the loss of positive trends and the dynamics of the innovative activities development, the low competitiveness of products and the pace of economic development. The purpose of the study is to determine the features of operational management in modern conditions and to identify the nature of its influence on the formation of the company's competitiveness. For enterprises, efficiency is always related to meeting the needs of consumers and obtaining the maximum possible profit with acceptable risks. The nature of the influence of strategic and tactical operational management on the competitiveness of the enterprise is revealed. In practice, the life cycle of a competitive advantage, which is its indisputable specific difference, must be taken into account for a specific business entity. Such an approach is expedient, as it is able to ensure an early response to the dynamics of external and internal environmental factors. While characterizing the specifics of the enterprise's competitiveness, attention is focused on the following mandatory conditions for its evaluation of the enterprise: the presence of competitive products and ensuring effective operations. Based on the results of the analysis, it was concluded that in order to respond flexibly to changes and action plan within the framework of operational strategies, business analysis should be carried out in the following areas: value chain, business process map, product life cycle and business process cost. As practice shows, the operational activity of enterprises is characterized by a complex set of relations with various stakeholders. Representatives of the retail business in Ukraine and abroad, responding to requests for increased security and convenience, offer consumers various options for searching and paying for purchases: "Click and collect", "Without cashiers", "Scan and collect", "Smart carts", technological and biometric contactless payment systems, etc. The technology of logistics organization is also crucial for trade enterprises. Keywords: operational management, competitiveness management, operational strategy, competitive advantage, business process, costs.

Novel methodology for functional design chain analysis of a nuclear power plant: A new built Finnish power plant case study

Energized by the fact that nuclear power plants (NPP) have a multidisciplinary character as well as a high degree of coupling and interaction between their elements, regulatory bodies worldwide tend to induce a massive number of requirements to ensure the safety of the plants. Mainly, these requirements aim to apply the defence-in-depth (DiD) safety approach. In Fennovoima Hanhikivi 1 (FH1) NPP, the DiD approach is applied through formalizing functional entities that are responsible for defending various DiD levels and preventing them from failure. Each functional entity consists of safety functions that share common non-functional requirements such as safety classification, failure criterion, diversity, and separation requirements.When investigating the safety functions of any NPP, one concludes that they are significantly interconnected and their processing logics exchange a huge number of signals. Therefore, verifying each safety function independently is not effective because a function may seem to perform its function when it is considered alone, but challenges are found when also the interconnected functions are considered. Thus, it becomes essential to verify the whole functional chain. A functional chain can be defined as a set of safety functions that interact together to guarantee the success of plant systems in case of an initiating event. It should be noted that the functional chain term, defined in this study, is different from the safety group term defined in the IAEA safety glossary. The latter is an assembly of equipment, whereas a functional chain is a group of safety functions. In other words, considering the safety engineering process of the plant life cycle, a functional chain is constructed and defined based on plant-level design down to system-level design, while a safety group is constructed based on system-level design.In this study, a methodology for analysing the functional chain is developed. The methodology mainly targets verifying five aspects of the functional chain which are: measurements, actuators, decision-making processing logic, human–machine interface (HMI), and cabling between various components. The methodology utilizes system engineering approach integrated with a relational database that can be utilized to query the plant design data in order to verify the application of non-functional requirements to the plant design components. Additionally, the study also develops a tool that can assist its users to systematically apply the developed methodology and record its results.Finally, a case study for practically applying the methodology to a NPP design is presented. The application of the methodology succeeded in revealing issues that need to be further clarified with the plant supplier. The main usefulness of applying the developed “functional chain analysis” methodology to a NPP is that it provides an additional as-designed verification approach besides the existing verification methods.

Estimation and prediction of plastic losses to the environment in China from 1950 to 2050

The widespread use of plastics has resulted in serious environmental problems. Large amounts of plastic waste are released into the environment. A dynamic material flow analysis model was employed to estimate the plastic losses to the environment in China, distributed into different polymers, sources, environmental media, and lifecycle processes. Microplastic and macroplastic losses entering the environment were 352.1 kt/a and 12.7 Mt/a, of which polyethylene terephthalate (PET) (29.1% and 32.2%) accounted for the highest proportion, and the loss stocks in the ocean and soil were 4.0 and 173.7 Mt in 2020. The main microplastic and macroplastic losses were associated with the release during the use stage and mismanaged waste management. Considering the impacts from reducing plastic losses, the losses and loss stocks in 2050 would be approximately twice and four times those in 2020, respectively. The results of this study provide scientific support for reducing plastic pollution.

Addressing heterogeneity sources in manufacturing sustainability assessment using the system design view

Assessing manufacturing sustainability has become a task of paramount importance to date for the decisional impact over the whole product or process life cycle. The consistency of the sustainability assessment results derives from several practitioner’s choices and assumptions, depending on materials, the technological processes as well as the geographical context, that may be sources of heterogeneity. Addressing the sources of heterogeneity in sustainability assessment deriving from data contexts, procedural decision-making methods, measurement procedures is critical, provided that all existing methodologies, such as Life Cycle Assessment, Exergy Analysis and methods derived from their combinations, leave an important role to the subjective judgment of the practitioner. Heterogeneity is thus related to the possible different perspectives in drawing decisions, which may, for instance, reflect into the selection of dissimilar inventorying for the impact evaluation as well as in the selection of the most suitable impact category: the effect is the uncertainty in the final results. Heterogeneity issue can be attributed to multiple dimensions, such as data sources, indicators and subjective perspectives. In this paper, the problem of facing the sources of heterogeneity in sustainability assessment is discussed by endeavoring the system design view as a kind of guideline to implement the Exergy-based Analysis within the Life Cycle Thinking. The Life Cycle Assessment and Exergetic Analysis approach is carried out not to improve the methods themselves, but to revisit the entire design process, to improve it, with the aim of driving the decision of the practitioner, to make the results of the assessment more comparable, regardless of their subjective choices. An industrial case study is taken as a reference to prove the approach proposed and to highlight gaps that have not yet been filled.

The Stability Analysis of Coupled Differential Equations in Stellar Structure

Astrophysical and Mathematical Models usually describes the evolutionary processes of life cycle of stellar structure. The process of star formation undergoes various stages during its life cycle. In human time scale it is not possible to observe whole of the evolution of stellar structure. From the birth of star to the death of star, different complex cosmological phenomenon occurs in the galactic region. In general theory of astrophysics stars are assumed to be static and spherical in nature. This nature results from hydrostatic and thermostatic equilibrium. Self-gravitating forces makes the star to collapse gradually and intermittently. At the same time thermal nature of chemical composition inside the star develops the pressure and hinders the sudden collapse. As a result, there is change in physical quantities like temperature, density, mass, radius, luminosity opacity and many more structural behaviours of star. These quantities are taken as variable in differential equation which are evolved in due process of star evolution. During the evolution of star, hydrostatic equilibrium and thermal equilibrium remains the major areas of study, therefore emphasis is laid on the stability of stellar structure with main focus on the hydrostatic and thermal equilibrium.

Guest Editorial Introduction to the Special Section on Cybertwin-Driven 6G for V2X Applications

The papers in this special section focuses on cybertwin-driven 6G mobile communications for V2X applications. Digital twin is envisioned to enhance functionalities of future electric and autonomous vehicles. Serving as the digital representation of a vehicle on the application layer, digital twin models the entire lifecycle of processes and services of the vehicle. To provide fundamental support for digital twin from network and transport layers, an agent service, namely Cybertwin, acts as the communication, mobility, and security agent for each user entity (either human or thing) at the edge of the network. Specifically, Cybertwin, serving as a communication anchor, is the only entrance point of the user for the Internet and records all the user states and behaviors. In addition, Cybertwin can become the personal AI assistant and act as a security agent through customizing the visibility of recorded data. By enhancing edge intelligence and providing composite edge services, Cybertwin can support advanced vehicle-to-everything (V2X) applications in the future intelligent and secure vehicular 6G network.

SoftNER: Mining knowledge graphs from cloud incidents

The move from boxed products to services and the widespread adoption of cloud computing has had a huge impact on the software development life cycle and DevOps processes. Particularly, incident management has become critical for developing and operating large-scale services. Prior work on incident management has heavily focused on the challenges with incident triaging and de-duplication. In this work, we address the fundamental problem of structured knowledge extraction from service incidents. We have built SoftNER, a framework for mining Knowledge Graphs from incident reports. First, we build a novel multi-task learning based BiLSTM-CRF model which leverages not just the semantic context but also the data-types for extracting factual information in the form of named entities. Next, we present an approach to mine relations between the named entities for automatically constructing knowledge graphs. We have deployed SoftNER at Microsoft, a major cloud service provider and have evaluated it on more than 2 months of cloud incidents. We show that SoftNER’s unsupervised pipeline learns the software entity types from unstructured incident data with high precision of 0.96 (at rank 50) and 0.77 (at rank 100). We also evaluate and show that SoftNER’s unsupervised pipeline accurately labels data with a precision of 0.94. Further, our multi-task learning based deep learning model also outperforms the state-of-the-art NER models with an average F1 of 0.96. Lastly, using the knowledge extracted by SoftNER, we are able to build accurate models for tasks such as incident triaging and recommending entities based on their relevance to incident titles.

Software Enterprise Risk Detection Model Based on BP Neural Network

With the rapid development of software industry, software enterprises have many problems in risk management, and enterprises are facing a huge crisis. In order to detect the risk of software enterprise, a risk detection model based on BP neural network is proposed in this paper. Firstly, risk analysis and modeling are carried out for the software life cycle process of the enterprise. Then, BP neural network is combined with common software risk items to realize supervised deep learning based on label information in data set. Using the advantage of neural network in automatic selection of original data features, the relationship between these risk items is extracted. Meanwhile, the network model in this paper learns the complex relational rules of the input risk features, to classify the risks. Finally, the proposed combined prediction model is compared with other prediction models. The experimental results show that the risk prediction effect of the proposed algorithm is better, to avoid the loss caused by the risk of software enterprises.

How are indicators in Green Building Rating Systems addressing sustainability dimensions and life cycle frameworks in residential buildings?

The use of tools capable of evaluating the sustainability of buildings throughout their life cycle represents a key point enabling the transition towards a sustainable built environment. To this end, different Green Building Rating Systems (GBRS) have been developed over the last few decades. All of them are voluntary schemes and propose a set of indicators to evaluate the associated impacts of buildings throughout their life cycle. However, it is unclear how GBRS are addressing sustainability dimensions and the life cycle frameworks, and particularly in residential buildings, which are responsible for a great part of these impacts. The aim of this study is to explore, in detail, how indicators in GBRS are covering the three dimensions of sustainability (environmental, social and economic) and the information modules proposed by EN 15978, along the life cycle stages of the building construction process. To do so, eight GBRS were selected and the 387 sustainability indicators included in them were analysed and clustered according to three different classification criteria, namely, sustainability dimension, information modules and stage of the construction process life cycle. The analysis and clustering process of indicators was carried out by a panel of experts in the field of study, with multidisciplinary academic and professional background, throughout an iterative process of four rounds and meetings, which led to achieve a consensus in the findings. The results of the analysis revealed that the environmental dimension is the one that is considered most among the tools, and both the social and economic dimensions require more attention to achieve a good balance. GBRS are more focused on the evaluation of the embedded impacts of the building, since most of the indicators are related to the product and construction stages (A1-A5) and therefore need to acquire a more holistic approach throughout the whole life cycle; the indicators should be considered in the very early design stage (not when the building is in operation), when decisions are made and have more potential to improve the sustainability performance of the buildings throughout its lifespan. It was not possible to cluster one set of indicators as they referred to aspects beyond the EN 15978 system boundary (such as site, transport or domestic waste management), thus highlighting the need for more coherence between a building's life cycle and GBRS frameworks, on the one hand, and the inclusion of new information modules covering the above-mentioned additional aspects, on the other.

Создание и тестирование моделей неопределенных систем

Technological objects can be subject to various changes in the life cycle process, arising from the peculiarities of technological processes. Such changes include, for example, the formation of scale in the aggregates. As a result, the mathematical description of the object obtained at the previous stages of the life cycle may not correspond to the current state of the automation object. Such systems are called robust. The aim of the work is to define functions for the analysis and description of a high-pressure heater using the MATLAB system, using the Robust Toolbox library. Materials and methods. The initial data of the work was the transfer function of the heater through the flow channel, obtained experimentally. A controller was synthesized for this object and a description of the system and the transient process in MATLAB were presented. The next stage of work was the synthesis of uncertain parameters using the ureal function. As a result, the object received not specific parameter values, but an interval for each of the object's parameters. As a result, an object with uncertain parameters and graphs of its transients was obtained. At the next stage, the nominal parameters of the object were identified and the stability of the system was checked. A system with nominal parameters is stable, so it is possible to perform an analysis of a system with uncertain parameters. To do this, the calculation of robust stability was performed. Robust stability calculation was performed by means of MATLAB, using the robuststab function. As a result of the work, the function allows you to determine a number of values for estimating the system and a combination of system parameters at which the system under consideration becomes unstable. At the next stage of the study, the worst parameters of the system from the selected set were determined; the obtained values differ from the parameters of the robust instability of the system. As a result, the transfer functions of a system with nominal parameters, the worst parameters, and an unstable system are obtained, and the transfer functions are constructed. Results. With the help of the tool for analyzing robust systems, the study of the object was carried out, the ranges of parameters were determined, under which the system will remain stable.

Stakeholder Engagement: Bridging Research and Policy to Improve Measurement and Dental Care for Children in Medicaid.

Stakeholder Engagement: Bridging Research and Policy to Improve Measurement and Dental Care for Children in Medicaid.

Identifying Possible Improvements of Software Development Life Cycle (SDLC) Process of a Bank by Using Process Mining

Software development with its unique characteristics having knowledge-intensive and human-oriented aspects and complex domains, challenges organizations. The timely outcomes with high quality and desired cost that directly affect customer satisfaction have an important place in many organizations, including banks. In the last decade, as an emerging technique for business processes management, process mining has been applied in many domains, including manufacturing, supply chain, government, healthcare, and software engineering. There are limited number of studies on process mining techniques carried out for the software process, especially in the banking sector. A lack of tool infrastructure enabling to run the entire software development process and the challenges in integrating processed data from separated varying tools and assets complicate the use of process mining for software processes. This paper aims to identify the improvement points in the software development process of the Kuveyt Turk Participation Bank in Turkey through the surfacing actions. The findings and results are gathered by the application of process mining techniques of bupaR, and evaluation is provided by experts in the bank. After that, the relevant process improvements are identified. The results of this paper show that using process mining provides the organization with beneficial results, in particular, and a comprehensive view of the end-to-end Software Development Life Cycle (SDLC) processes.