The importance and necessity to keep an archive of important records at universities is highly needed to maintain reasonable efficiency, transparency, and accuracy. This study used the life cycle and records continuum models to examine the records and archives management methods utilized at a selected Lebanese private university. The study capitalized on and explored records and archives management at the university and assessed practices considering recommendations from “The World Bank Group Records Management Guide”. The main objective was to assess current practices and procedures concerning the abovementioned guide. This work recommended a plan based on the evaluation results to control documents and archives at the university. A mixed-method research approach was used and primary data were collected using a structured questionnaire, a focus group, semi-structured interviews, and personal observations. Purposive sampling was used where 38 respondents were chosen to answer the questionnaire including staff who interacted with records daily; five members of the Information Technology (IT) team were involved in the focus group, and 11 interviewees (chosen from the 38 questionnaire respondents) were interviewed. Key findings support that the university lacked sufficient records management practices, and documents were managed informally. There was also a paucity of skilled records management professionals, which created problems with the development, circulation, utilization, preservation, and destruction of records, putting the university at risk of losing valuable information. The study recommended a procedural plan for records management system integration, reviewing the practices, and implementing new policies and procedures based on the universal and legal requirements to ensure that important records are kept and archived consistently.
Kasra Khaghanizadeh, Mohammad Ghasemi, Abdolali Keshtegar
et al.
AbstractThe aim of the present study is to design and develop an innovative ecosystem model for small and medium-sized enterprises in Iran. The design of this innovation ecosystem model can act as a driving factor for involving various actors in the production, design, development and commercialization of innovative products and services in small and medium-sized enterprises. To achieve this goal, the meta-synthesis method was used and, according to previous studies, 1469 articles were selected and interpreted from among various articles. In fact, an interpretation beyond previous studies was obtained and in this method, the findings were combined and a comprehensive view of the phenomenon in question was obtained. Finally, 69 articles were selected using the screening method. The findings show that, according to the combination of studies conducted, the dimensions of the innovation ecosystem model in small and medium-sized enterprises include innovation in inputs, innovation in processes, innovation in outcomes and outputs, social innovations, strategy innovations, and environmental sustainability innovations. In fact, in addition to these dimensions, their indicators and components have also been extracted, which actually play a facilitating role in implementing the desired model. The results show that the innovation ecosystem model, which is the result of extracting indicators and components, can be applied in small and medium-sized enterprises.IntroductionToday, creativity and innovation and the ability to discover new opportunities are among the most essential characteristics of entrepreneurs. Competition in technology and ensuring and continuing life and survival in companies and industries require finding new solutions and methods of dealing with problems that depend greatly on innovation, creation of new products, processes, and approaches. In today's business world, some factors such as continuous and sometimes fundamental changes in technologies, emergence of new demands from customers, short product and service life cycles, disappearance of the boundary between industries and the constant presence of new entrants from different industries and many other factors have created a special space and as a result of these changes, companies are dependent on other companies and institutions to create value for their customers. Considering value creation from an ecosystem perspective is different from the traditional view, which is based on value creation by a specific company and is static. Therefore, to use ecosystems, companies need to change their perspective from a traditional and company-based and static view to an ecosystem view (Fuller et al., 2019). In the innovation ecosystem, key people are connected to many other factors in valuable interactions. One of the reasons for the increasing importance of innovation at the international level is the globalization of markets and the competitive pressure on companies to keep on seeking innovation. Innovation ecosystems connect the way actors, producers, service providers, end users, regulators, and civil society organizations to achieve a collective outcome (Zakobedes & Calleagues, 2017). Ecosystems similar to innovation ecosystems increase the sustainability of organizations and industries and can support their sustainable activities towards sustainable development (Reezner & Calleagues, 2019), because it is likely to have implications for both researchers and policymakers and practitioners (Dedhayer & Calleagues, 2018).Regarding the theoretical gap in the research, it can be said that by reviewing the research, it was found that limited studies have been presented in the field of designing and developing a coherent framework for the innovation ecosystem in small and medium-sized enterprises in the country, although many of these studies were very general or only analyzed the innovation ecosystem from one aspect (Holm & Ankarkrona, 2016). Also, regarding the necessity of conducting this research, it can be said that previous studies have mainly focused on the technological dimension of the ecosystem, which limits the possibility of examining and evaluating complex ecosystems (Chen et al., 2016). On the other hand, a large part of the studies have only examined a few ecosystem actors and the interactions between them, and have not comprehensively examined all stakeholders and the relationships between them (Motoyama & Knowlton, 2017). Today, designing an innovation ecosystem model can be considered as a stimulus to increase the performance of these small and medium-sized industries. In this regard, the present study attempts to, through the study of previous research, address the question of how the innovation ecosystem model in small and medium-sized enterprises is designed and developed using the meta-synthesis model.Theoretical frameworkIn the present era, innovation emerges when the organization seeks to respond to an environment in which it is operating under environmental disturbances, and this has caused managers to focus on organizational transformation in order to adapt and respond to changes in a timely manner and maintain the organization's competitive advantages, and they consider themselves in need of an appropriate leadership style and human capital management to deal with such changes (Veghry and Fileshver, 2024).Small companies may not grow with proper innovation management, but they can still survive. Companies that have planned innovation management well will be able to survive (Zoares Eskoober and Goozman, 2017). On the other hand, businesses also face obstacles, including restrictions and laws on content production and advertising, audience limitations, the impact of political and social crises, the presence of competition, references, government restrictions, unethical behavior of audiences and competitors, and systemic problems such as messaging bugs and lack of financial support, lack of sufficient facilities, and ideological limitations (Kafshdar Toosi, 2024). As Shompiter emphasizes, innovation is a powerful tool for new companies to successfully enter the market and challenge established companies. Also, established organizations need innovation to maintain their competitive position in the face of new and emerging or “disruptive” technologies (Cresstenson, 2010). Radical innovations are those that are developed by a company and are also innovations that are new to an industry (Reechesten and Salter, 2006). SMEs, known for their centralized management and informal structures, are therefore more prone to innovation. Companies that propose product innovation should focus on new product development or technological improvements, while companies that introduce new organizational methods such as process innovation should focus on knowledge and management culture (Ikermorat and Bardoogan, 2011). However, the most difficult task for SMEs is to realize this idea to meet demand. SMEs must follow several stages until the newly created product becomes marketable. New product development is a process in which new ideas are used in the final product and service. This process consists of six stages. Research and development stage, product design, concept testing, prototype, test marketing, and commercialization or launch. All these processes require resources and budget. Studies show that in Iran, not much research has been done so far on the topic of innovation ecosystem model in small and medium-sized companies and key players, and even practical models and patterns in this field. Considering that today advanced economies have placed innovation as their main factor and driver, developing countries need innovation in services and products to accelerate their growth and development. Considering the economic conditions of the country, many small and medium-sized companies cannot continue their production cycle.MethodologyThis research is applicable in terms of purpose, qualitative in terms of data collection, and with a meta-synthesis approach in terms of research implementation method. This research is based on the seven-step method of Sandelowski and Barroso (2007) in meta-synthesis.Research findingsIn this research, based on articles discovered from reputable journals and databases, 68 articles were fully reviewed and by combining the findings, six dimensions along with their indicators and components were identified for the innovation ecosystem, described below. Based on the results of the meta-synthesis, the dimensions of the innovation ecosystem can be categorized into six main areas, including input innovation, process innovation, strategy innovation, output and outcome innovation, social innovation, and environmental innovation.Conclusion The first dimension is the input innovation dimension, consistent with the research of Liang & Wang (2023) and Block et al., (2023), and based on the research conducted, it is suggested that in order to have an effective input in the field of innovation, its indicators and components need to be calculated in a real sense and in accordance with the environment in which it operates. These indicators and components include crowdfunding, launching a venture capital fund, hiring startup-minded employees, innovation in financing methods, etc. The second dimension is the process innovation dimension, which acts as a strategic role in converting inputs into outputs and, in a way, extracts accurate and correct outputs and actions after a targeted and effective analysis of inputs. The results of this dimension are consistent with the research of Piñera-Salmerón et al., (2023). In this dimension, indicators and components such as the production of artificial intelligence-based services, updating machinery and equipment, setting up a research and development unit, using artificial intelligence capabilities, smartening business processes, continuous product improvement, application of quality tools, redesigning parts and components, etc. are mentioned. The third dimension is innovation in outputs and outcomes, which are actually indicators such as obtaining an electronic trust mark, developing new product versions, setting up spin-off companies, using online sales platforms, developing the export of innovative products, obtaining a knowledge-based mark for products, commercializing innovative products, etc., and is consistent with the research of Jin & Li (2023). The fourth dimension is social innovation, the results of which are consistent with the research of Sampaio & Sebastião (2024), and these studies showed that this dimension facilitates the cooperation of non-governmental sectors and civil society to promote innovation and also influence the innovation process. In fact, social innovation is an environmental factor that plays a decisive role in the adoption of innovation and the production of innovation. The indicators of this dimension include the development of corporate citizenship behavior, the allocation of budget lines to the field of social responsibility, the creation of local networks for the exchange of knowledge and benefits, etc. The fifth dimension is innovation strategies, which is consistent with the research of Agazu & Kero (2024). The components of this dimension include the development of entrepreneurial culture, the development of digital entrepreneurship, co-creation in the production of new products, and the development of gradual innovation, and therefore it is suggested that strategy be considered as a facilitator of the role of the innovation path and the purposefulness of the innovation development process. The sixth dimension is environmental innovation, which includes indicators and components such as green innovation development, green management development, green product development, green marketing development, reduction of environmental pollutants, use of less polluting materials, etc., which is consistent with the research of Kirikkaleli et al., (2023). The three dimensions of social innovation, environmental innovation, and strategic innovation are considered as external environmental dimensions of innovation that affect the internal environment of innovation and in a way stimulate innovation. Any research or management action in the field of innovation ecosystems requires a precise understanding of the six dimensions.
Azadeh Amoozegar, Basma Mohamed Hassan Elsiddig, Mohammad Falahat
et al.
IntroductionSudanese higher education institutions must recognize the influence of Big Five personality traits on employee creativity to foster a workforce that is both innovative and adaptable. These traits play a key role in shaping how employees approach their work and generate new ideas. While studies have explored the link between each of the Big Five personality traits and creativity, the findings have been varied.MethodsThis research employed a cross-sectional correlational approach to examine how the Big Five personality traits influence employee creativity in public universities in Sudan. Participants in the study were randomly selected from five public universities in South Sudan. Data analysis was carried out using SmartPLS 4.ResultsThe findings of this research showed that Openness, Agreeableness, and Consciousness significantly influenced creativity, whereas Extraversion and Neuroticism did not. Additionally, the relationship between the Big Five personality traits and creativity was not moderated by gender.DiscussionIdentifying employee personality types and how they influence creativity is crucial for university management when hiring academic staff, especially in developing countries, since it can help them select individuals more likely to excel at research, teaching, and innovation. This knowledge can also inform employment policy to foster an environment conducive to creativity and growth.
Absenteeism at work, possibly leading to productivity loss in business, is related to various psychological, social, and economic factors. Since predicting absenteeism is involved with complex associations of such factors, appropriately utilizing machine learning algorithms is required in the analysis. Statistical pre-processing and applications of machine learning methods have developed the comprehensive analysis of massive social data for absenteeism. The aim of this study is to develop a quantitative approach to identify the associations of factors and classify the absenteeism by including the effect of factors in the high-dimensional data. This approach implements association analysis including odds ratio test and network analysis, and supervised learning with imbalanced classification with random forest, application of principal component analysis and penalized regression methods. The dataset in this study includes records of various types of absenteeism at workplace from July 2007 to July 2010 in Brazil. Our study shows that there exist strongly interacting factors and that specific factors are strongly associated with absenteeism. The proposed method is validated on publicly available data sets using random forest and penalized regression with k-fold cross validation in order to strengthen better generalizability. One of major findings in this study is to elucidate the associations of factors affecting absenteeism. Application to similarly structured social data improves the understanding of the complex interplay between social factors and absenteeism that are important for people analytics which can help organizations resolve management difficulties.
History of scholarship and learning. The humanities, Social Sciences
Aurora Eleonora TWAROWSKI, Diana SALA, Nicolae BIBU
The paper investigates the impact of the COVID-19 pandemic on the management
of opera houses in Romania, from the perspective of the opera consumer. It focuses on two
important aspects related to the management of opera houses during the COVID-19
pandemic: the replacement of live performance with digital opera and the response of
cultural institutions to the needs of the opera consumer community. These aspects were
measured by consumer satisfaction regarding the replacement of live performance with
digital opera and by the way in which opera houses responded to the needs of the community,
during the lockdown period. The study analyzed how variables such as age and education
level of consumers are associated, on the one hand, with consumer satisfaction regarding the
replacement of live performance with digital opera (ÎC1), and on the other hand, with the
assessment of the way in which cultural institutions responded, during the lockdown period,
to the needs of the community (ÎC2). The results highlight significant differences between
various audience groups, outlining distinct profiles of perception and cultural adaptation.
The article highlights the role of demographic factors in shaping attitudes towards the
digitalization of the lyrical theater experience and the importance of a flexible managerial
strategy, oriented towards the diversified needs of post-pandemic opera consumers.
Economics as a science, Business records management
Anna Kasperczuk, Michał Ćwiąkała, Ernest Górka
et al.
This study examines the role of work-life balance (WLB) as a strategic component of effective business management and its influence on employee motivation, job satisfaction, and organizational performance. Drawing on a quantitative survey of 102 economically active individuals, the research investigates the effectiveness of various WLB initiatives, including flexible working hours, private medical care, and additional employee benefits. The results reveal that flexible working arrangements are the most impactful tool for enhancing work-life balance and significantly contribute to higher levels of employee motivation. A statistically significant positive correlation was observed between perceived work-life balance and motivation, indicating that improving WLB directly strengthens commitment, reduces burnout, and increases job satisfaction. Moreover, the findings highlight differences in WLB perceptions across demographic groups, suggesting the need for tailored policies. The study emphasizes that organizations actively supporting WLB achieve greater employee loyalty, improved productivity, and enhanced employer branding. These results have practical implications for human resource strategies, showing that integrating WLB initiatives can improve overall organizational performance and societal well-being. The paper also identifies research gaps and recommends exploring cultural, occupational, and remote work contexts in future studies to better understand how WLB strategies shape workforce engagement in dynamic labor markets.
Although the goal of achieving semantic interoperability of electronic health records (EHRs) is pursued by many researchers, it has not been accomplished yet. In this paper, we present a proposal that smoothes out the way toward the achievement of that goal. In particular, our study focuses on medical diagnoses statements. In summary, the main contributions of our ontology-based proposal are the following: first, it includes a canonical ontology whose EHR-related terms focus on semantic aspects. As a result, their descriptions are independent of languages and technology aspects used in different organizations to represent EHRs. Moreover, those terms are related to their corresponding codes in well-known medical terminologies. Second, it deals with modules that allow obtaining rich ontological representations of EHR information managed by proprietary models of health information systems. The features of one specific module are shown as reference. Third, it considers the necessary mapping axioms between ontological terms enhanced with so-called path mappings. This feature smoothes out structural differences between heterogeneous EHR representations, allowing proper alignment of information.
This paper offers an overview of collaborative consumption (CC), the related business models (BM), the value added (VA) from the consumer's perspective and the role of trust. CC is expanding but it is unclear what opportunities it offers and what the challenges will be. This research evaluates the current CC BMs and identifies 13 ways they add value from the consumer's perspective. This research further explores whether CC BMs fall into two categories in terms of what the consumer values. In the first category, the CC BMs require a low level of trust while in the second category of CC BMs a higher level of trust is necessary. It was found that 13 VA by CC BMs could be grouped into personal interest, communal interest and trust building. It is important for organisations to acknowledge how their CC BM relates to these dimensions.
Проаналізовано програмні документи зменшення антропотехногенного впливу на гідросферу, сформовано їх узагальнене бачення. Запропоновано методологічний інструментарій формування змісту, принципів та елементів Концепції зменшення антропотехногенного впливу на водні ресурси. Розроблено комплекс критеріїв формування моделі антропотехногенного впливу на гідросферу. Деталізовано економічні, соціальні та екологічні аспекти формування та реалізації Концепції. Розроблено комплекс критеріїв формування моделі антропотехногенного впливу на гідросферу. Деталізовано економічні важелі впливу на безпеку водокористування, соціальні та екологічні наслідки реалізації Концепції. Визначено напрями використання економічного потенціалу раціонального водокористування. Систематизовано рекомендації щодо раціонального використання водних ресурсів. Зроблено висновок, що концептуалізація антропотехногенного впливу на стан водних ресурсів сприятиме соціально-екологічному, економічному обґрунтуванню та практичному вирішення проблем забруднення водних ресурсів.
Economics as a science, Business records management
Reinforcement learning (RL) based investment strategies have been widely adopted in portfolio management (PM) in recent years. Nevertheless, most RL-based approaches may often emphasize on pursuing returns while ignoring the risks of the underlying trading strategies that may potentially lead to great losses especially under high market volatility. Therefore, a risk-manageable PM investment framework integrating both RL and barrier functions (BF) is proposed to carefully balance the needs for high returns and acceptable risk exposure in PM applications. Up to our understanding, this work represents the first attempt to combine BF and RL for financial applications. While the involved RL approach may aggressively search for more profitable trading strategies, the BF-based risk controller will continuously monitor the market states to dynamically adjust the investment portfolio as a controllable measure for avoiding potential losses particularly in downtrend markets. Additionally, two adaptive mechanisms are provided to dynamically adjust the impact of risk controllers such that the proposed framework can be flexibly adapted to uptrend and downtrend markets. The empirical results of our proposed framework clearly reveal such advantages against most well-known RL-based approaches on real-world data sets. More importantly, our proposed framework shed lights on many possible directions for future investigation.
Security and privacy are primary concerns in IoT management. Security breaches in IoT resources, such as smart sensors, can leak sensitive data and compromise the privacy of individuals. Effective IoT management requires a comprehensive approach to prioritize access security and data privacy protection. Digital twins create virtual representations of IoT resources. Blockchain adds decentralization, transparency, and reliability to IoT systems. This research integrates digital twins and blockchain to manage access to IoT data streaming. Digital twins are used to encapsulate data access and view configurations. Access is enabled on digital twins, not on IoT resources directly. Trust structures programmed as smart contracts are the ones that manage access to digital twins. Consequently, IoT resources are not exposed to third parties, and access security breaches can be prevented. Blockchain has been used to validate digital twins and store their configuration. The research presented in this paper enables multitenant access and customization of data streaming views and abstracts the complexity of data access management. This approach provides access and configuration security and data privacy protection.
Timotheus Kampik, Christian Warmuth, Adrian Rebmann
et al.
The continued success of Large Language Models (LLMs) and other generative artificial intelligence approaches highlights the advantages that large information corpora can have over rigidly defined symbolic models, but also serves as a proof-point of the challenges that purely statistics-based approaches have in terms of safety and trustworthiness. As a framework for contextualizing the potential, as well as the limitations of LLMs and other foundation model-based technologies, we propose the concept of a Large Process Model (LPM) that combines the correlation power of LLMs with the analytical precision and reliability of knowledge-based systems and automated reasoning approaches. LPMs are envisioned to directly utilize the wealth of process management experience that experts have accumulated, as well as process performance data of organizations with diverse characteristics, e.g.,\ regarding size, region, or industry. In this vision, the proposed LPM would allow organizations to receive context-specific (tailored) process and other business models, analytical deep-dives, and improvement recommendations. As such, they would allow to substantially decrease the time and effort required for business transformation, while also allowing for deeper, more impactful, and more actionable insights than previously possible. We argue that implementing an LPM is feasible, but also highlight limitations and research challenges that need to be solved to implement particular aspects of the LPM vision.
Extremely large-scale arrays (XL-arrays) have emerged as a promising technology to achieve super-high spectral efficiency and spatial resolution in future wireless systems. The large aperture of XL-arrays means that spherical rather than planar wavefronts must be considered, and a paradigm shift from far-field to near-field communications is necessary. Unlike existing works that have mainly considered far-field beam management, we study the new near-field beam management for XL-arrays. We first provide an overview of near-field communications and introduce various applications of XL-arrays in both outdoor and indoor scenarios. Then, three typical near-field beam management methods for XL-arrays are discussed: near-field beam training, beam tracking, and beam scheduling. We point out their main design issues and propose promising solutions to address them. Moreover, other important directions in near-field communications are also highlighted to motivate future research.
Traditional business models involve cost, market development, distribution channels, business partnerships, and supply chain management. The development of the digital economy and digital network technology has engendered a shift away from the traditional model of operation. Intermediaries have long played an essential role in promoting the benefits of economic activities, but new technology is increasingly replacing intermediaries in their roles of connecting players, such as, involving, committing, and mobilizing players. Potential conflicts of interest must therefore be further resolved, avoided, or mitigated. Blockchain technology, as a tool for keeping immutable and digital records, can address increasingly complex issues in global value chains to pursue sustainable development. It attempts to realize the trust mechanism and has been redefining the function of intermediaries. This study used a multiple-case study approach to examine how blockchain technology affects intermediate functionality. We evaluated the industry’s use of blockchains to assess how the processes were reshaped and how the intermediary roles were refined. On the basis of the findings, we propose three potential changes for the roles of intermediaries to improve operational efficiency.
Mohsen Barzegari Ardekani, Abolfazl Kazazi, Jahanyar Bamdad Soufi
et al.
Over the past few decades, great advances have been made in many industries, including the food industry, from which the development of useful products can be noted. Given the undeniable necessity of innovation in the food industry and its role in the economy, it has been attempted to present a qualitative model of the factors influencing innovation in the development of high-value food products with the aim of export boom using fuzzy cognitive mapping methodology. For this purpose, after expressing the subject, theoretical bases and background analysis, using an interpretive paradigm and a qualitative research design, an initial conceptual framework of the research with content analysis approach has been prepared and the innovation model has been presented. Then, cognitive mapping technique tools are used to examine different policies on the model and analyze it. The findings from the innovation mapping showed that the product system, the production of useful products, the interaction and partnership with customers to create value are key components to the success of the sweet and chocolate industry. In addition, the formulation of innovation promotion policies should take a composite approach to the components, and investing in the factors individually cannot achieve much improvement.
Ishwar Venugopal, Jessica Töllich, Michael Fairbank
et al.
Deep-learning models such as Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) have been successfully used for process-mining tasks. They have achieved better performance for different predictive tasks than traditional approaches. We extend the existing body of research by testing four different variants of Graph Neural Networks (GNN) and a fully connected Multi-layer Perceptron (MLP) with dropout for the tasks of predicting the nature and timestamp of the next process activity. In contrast to existing studies, we evaluate our models' performance at different stages of a process, determined by quartiles of the number of events and normalized quarters of the case duration. This provides new insights into the performance of a prediction model, as they behave differently at different stages of a business-process. Interestingly, our experiments show that the simple MLP often outperforms more sophisticated deep-learning models in both prediction tasks. We argue that care needs to be taken when applying automated process-prediction techniques at different stages of a process. We further argue that researchers should reflect their results with strong baselines methods like simple MLPs.
Archives are very important for an organization because as a source of organizational information relating to the development and operational activities of a business or government organization. More and more organizational work will also increase the number of records produced. From time to time the number of records will increase, requiring management. Records management is an important aspect in an organization, both business organizations and good government so that the information to be sought can be found quickly and accurately. Managing archives manually that has been done so far, has several weaknesses, including: requiring large space and storage, the risk of damage to the archive due to disaster, requires a lot of employees and a long search time. This study aims to determine the records management procedure which includes receiving incoming and outgoing mail, archiving, rediscovering records, and maintaining records. This research is a qualitative descriptive study. The subjects of this study were 3 administrative staff from Ponorogo Regency Social Service. Data analysis refers to the Miles and Huberman model using source triangulation and research instruments in the form of interviews and documentation. Based on the results of a study entitled "Management of Archives in Supporting Information Services in the Administration Section at the Social Service Agency of Ponorogo" that records management in supporting information services has been running well because the management system is in accordance with the filing procedures.
Hakan Gencturk, Elcin Erdogan, Mustafa Karaca
et al.
Nowadays, prognostics-aware systems are increasingly used in many systems and it is critical for sustaining autonomy. All engineering systems, especially robots, are not perfect. Absence of failures in a certain time is the perfect system and it is impossible practically. In all engineering works, we must try to predict or minimize/prevent failures in the system. Failures in the systems are generally unknown, so prediction of these failures and reliability of the system is made by prediction process. Reliability analysis is important for the improving the system performance, extending system lifetime, etc. Prognostic and Health Management (PHM) includes reliability, safety, predictive fault detection / isolation, advanced diagnostics / prognostics, component lifecycle tracking, health reporting and information management, etc. This study proposes an open source robot prognostic and health management tool using model-based methodology namely "Prognostics and Health Management tool for ROS". This tool is a generic tool for using with any kind of robot (mobile robot, robot arm, drone etc.) with compatible with ROS. Some features of this tool are managing / monitoring robots' health, RUL, probability of task completion (PoTC) etc. User is able to enter the necessary equations and components information (hazard rates, robot configuration etc.) to the PHM tool and the other sensory data like temperature, humidity, pressure, load etc. In addition to these, a case study is conducted for the mobile robots (OTA) using this tool.
Blockchain has attracted broad interests to build decentralised applications. Blockchain has attracted broad interests to build decentralised applications. However, developing such applications without introducing vulnerabilities is hard for developers, not the least because the deployed code is immutable and can be called by anyone with access to the network. Model-driven engineering (MDE) helps to reduce those risks, by combining proven code snippets as per the model specification, which is easier to understand than source code. Therefore, in this paper, we present an approach for integrated MDE across business processes and asset management (e.g. for settlement). Our approach includes methods for fungible/non-fungible asset registration, escrow for conditional payment, and asset swap. The proposed MDE approach is implemented in a smart contract generation tool called Lorikeet, and evaluated in terms of feasibility, functional correctness, and cost effectiveness.
This article proposes a self-organizing collaborative computing network with an approach to enhance the expectation of a collaborating node for joining the self-organizing network. The proposed approach relies on Ethereum cryptocurrency and Smart Contract to enhance the expectation of collaborating nodes by monetizing the services provided to the self-organizing network. Furthermore, an escrow based smart contract is formalized in the proposed framework to sustains the monetary trust issue between collaborating nodes. The proposed scheme can enforce an autonomic incentive management mechanism to any type of self-organizing networks such as self-organizing clouds, ad-hoc networks, self-organizing federated cloud networks, self-organizing federated learning networks, and self-organizing D2D networks to name a few. Considering the distributed nature of these self-organizing networks and the Ethereum blockchain network, a distributed agent-based methodology is materialized in the proposed framework. Following this, a proof of concept implementation for the general case of a self-organizing cloud is presented. Lastly, the article provides some insights into possible future directions using the proposed framework.