Pellet is widely used in blast furnace ironmaking. Pellet quality affects the effect of ironmaking, the existing control system of grating-rotary kiln mainly adopts manual control mode, and the quality of pellet production largely depends on the experience, fatigue, and sense of responsibility of the site operators. The use of the Internet of things technology in the integration and improvement of enterprise information level, to achieve fine, intelligent production management, at the same time, is conducive to promoting (...) steel enterprises to reduce costs and increase efficiency, energy conservation and emission reduction, transformation and upgrading, and taking a new road to industrialization. According to the working principle and technological characteristics of the grate-rotary kiln at all stages, this paper designs the management system of firing pellets based on convolutional neural network and IoT technology, so as to realize automatic recognition of image data obtained by the perceptual layer and make an intelligent analysis of it. The system can classify the working conditions of the current equipment, so as to judge whether the production process parameters of the grate-rotary kiln are up to the standard, thus achieving the goal of controlling the quality of the finished pellet. (shrink)

Electric-mechanical equipment manufacturing industries focus on the implementation of intelligent manufacturing systems in order to enhance customer services for highly customized machines with high-profit margins such as electric power transformers. Intelligent manufacturing consists in using supply chain data that are integrated for smart decision making during the production life cycle. This research, in cooperation with a large electric power transformer manufacturer, provides an overview of critical intelligent manufacturing technologies. An ontology schema forms the terminology relationships needed (...) to build two intelligent supply chain management modules for the IM system demonstration. The two core modules proposed in this research are the intelligent supplier selection and component ordering module and the product quality prediction module. The intelligent supplier selection and component ordering module dispatches orders that match the best options of suppliers based on combined analytic hierarchy process analysis and multiobjective integer optimization. In the case study, the intelligent supplier selection and component ordering module demonstrates several acceptable Pareto solutions based on strict constraints, which is a very challenging task for decision makers without assistance. The second module is the product quality prediction module which uses multivariate regression and ARIMA to predict the quality of the finished products. Results show that the R square values are very close to 1. The module shortens the time for the company to accurately judge whether the two semifinished iron cores for the product meet the quality requirements. The component supplier selection module and the finished product quality prediction module developed in this research can be extended to other IM systems for general high-end equipment manufacturers using mass customization. (shrink)

Financial risks are among the most important risks in the construction industry projects, which significantly impact project objectives, including project cost. Besides, financial risks have many interactions with each other and project parameters, which must be taken into account to analyze risks correctly. In addition, a source of financial risks in a project is the contract, which is the most important project document. Identifying terms related to financial risks in a contract and considering their effects on the risk management (...) process is an essential issue that has been neglected. Hence, an integrated model for evaluating financial risks and their related contractual clauses were presented. To this end, the effect of financial risks on the project cost was simulated using a system dynamics model. Moreover, terms related to financial risks in a contract text were identified and extracted using text mining, and their effect was included in the system dynamics model. The model was implemented in a hospital construction project in Tehran as a case study, and its results were analyzed. The innovation of the research is integrating text mining and the system dynamics model to investigate the effect of financial risks and related contractual clauses on the project cost. (shrink)

In order to solve the problems of poor physical fitness of college students and low efficiency of college sport venues' management, an intelligent sports management system based on deep learning technology is designed by using information technology and human-computer interaction under artificial intelligence. Based on the Browser/Server structure, the intelligent sports management system is constructed. The basic framework of Spring Cloud is used to integrate the framework and components of each part, and a (...) distributed microservice system is built. The artificial intelligence recommendation algorithm is used to analyze the user's age, body mass index, and physical health status, and recommend sports programs suitable for students, thus realizing the intelligent sports program recommendation function. At the same time, the recommendation algorithm is used to complete the course recommendation according to the students' preferences, teaching distance, opening time, course evaluation, and other indexes, and the course registration system is constructed; after the analysis of the entity and the relationship between the entities of the intelligent sports system, the database relational model of the system is designed with the entity relationship diagram. The results of the functional test show that the system can run well. In conclusion, the sports training environment instructional system based on artificial intelligence and deep learning technology can meet the teaching needs of colleges, improve the sports' quality for college students, and promote psychological education. (shrink)

The economical/environmental scheduling problem of the ship integrated energy system has high computational complexity, which includes more than one optimization objective, various types of constraints, and frequently fluctuated load demand. Therefore, the intelligent scheduling strategies cannot be applied to the ship energy management system online, which has limited computing power and storage space. Aiming at realizing green computing on SEMS, in this paper a typical SIES-EESP optimization model is built, considering the form of decision vectors, (...) the economical/environmental optimization objectives, and various types of real-world constraints of the SIES. Based on the complexity of SIES-EESPs, a two-stage offline-to-online multiobjective optimization strategy for SIES-EESP is proposed, which transfers part of the energy dispatch online computing task to the offline high-performance computer systems. The specific constraints handling methods are designed to reduce both continuous and discrete constraints violations of SIES-EESPs. Then, an establishment method of energy scheduling scheme-base is proposed. By using the big data offline, the economical/environmental scheduling solutions of a typical year can be obtained and stored with more computing resources and operation time on land. Thereafter, a short-term multiobjective offline-to-online optimization approach by SEMS is considered, with the application of multiobjective evolutionary algorithm and typical schemes corresponding to the actual SIES-EESPs. Simulation results show that the proposed strategy can obtain enough feasible Pareto solutions in a shorter time and get well-distributed Pareto sets with better convergence performance, which can well adapt to the features of real-world SIES-EESPs and save plenty of operation time and storage space for the SEMS. (shrink)

Tennis players have more physical training content, and the training items are complex. For athletes, training programs that adapt to their individual characteristics should be formulated according to their physical characteristics. The current development of big data has brought about changes in thinking, management, and business models. The combination of complex systems and big data can also make breakthroughs in the sports field. Based on this, this article proposes a tennis player training schedule intelligent formulation system based (...) on complex system big data. First of all, this article adopts the literature data method, comparative analysis method, experimental analysis method, etc., in-depth study of the concepts of big data, complex system, and the physical structure characteristics of tennis sports. This paper designs an intelligent system for making tennis players’ training schedule, which collects, transforms, and integrates tennis training data through the characteristics of big data. Then, the dynamic time regulation of tennis is performed through a complex system, and finally, the experimental system is analyzed. This article mainly analyzes the comparison of physical indicators between the experimental group and the control group before and after the experiment, the evaluation indicators of sports events, the strength training effects of tennis events, and the analysis of shoulder joint tests. There is no significant difference between the experimental group and the control group in the items before the experiment, P > 0.05, which suggests that the physical fitness of the two groups of athletes is similar; in the posttest data, the experimental group and the control group have significant differences, P < 0.05, indicating an effect from the experiment. In particular, in fan running, forward and backward strokes, and the serve, the scores of the experimental group were higher than those of the control group, indicating that the use of the formulated training system demonstrated significant results. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several (...) class='Hi'>system components, the requirements of the different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

The likely near future creation of artificial superintelligence carries significant risks to humanity. These risks are difficult to conceptualise and quantify, but malicious use of existing artificial intelligence by criminals and state actors is already occurring and poses risks to digital security, physical security and integrity of political systems. These risks will increase as artificial intelligence moves closer to superintelligence. While there is little research on risk management tools used in artificial intelligence development, the current global standard for risk (...) management, ISO 31000:2018, is likely used extensively by developers of artificial intelligence technologies. This paper argues that risk management has a common set of vulnerabilities when applied to artificial superintelligence which cannot be resolved within the existing framework and alternative approaches must be developed. Some vulnerabilities are similar to issues posed by malicious threat actors such as professional criminals and terrorists. Like these malicious actors, artificial superintelligence will be capable of rendering mitigation ineffective by working against countermeasures or attacking in ways not anticipated by the risk management process. Criminal threat management recognises this vulnerability and seeks to guide and block the intent of malicious threat actors as an alternative to risk management. An artificial intelligence treachery threat model that acknowledges the failings of risk management and leverages the concepts of criminal threat management and artificial stupidity is proposed. This model identifies emergent malicious behaviour and allows intervention against negative outcomes at the moment of artificial intelligence’s greatest vulnerability. (shrink)

The Intelligent Nation proposes a systemic and radical transformation of the organisation, management, ownership and performance of the services of the state by capitalising on the potential offered by contemporary information capability and fulfilling the rights and obligations both to and of citizens. In this book, John Beckford shows how, by adopting the principles of an intelligent organisation, the state can thrive and meet the needs of its citizens. He proposes a complete rethink of the state as (...) the enabler or provider of public services. In particular, he points to the failure of the public sector to significantly emulate the massive gains in productivity and customer focus experienced in both manufacturing and services (e.g. finance, retailing, insurance). Governance and all public services must be redesigned to align to the contemporary needs of the citizen and exploit the power of information to enable a transformation of their effectiveness, redefine efficiency, and support human-based services in crucial areas. Each chapter provides the key learning points, a discussion of the problem in theory and practice, integrated case studies, and discussion points. Written in an accessible style, the book provides thought-provoking supplemental reading for masters and undergraduate students reading organization theory, organization development, political science, public administration, healthcare, information systems, and business and management science. (shrink)

This article develops a conceptual framework for regulating Artificial Intelligence (AI) that encompasses all stages of modern public policy-making, from the basics to a sustainable governance. Based on a vast systematic review of the literature on Artificial Intelligence Regulation (AIR) published between 2010 and 2020, a dispersed body of knowledge loosely centred around the “framework” concept was organised, described, and pictured for better understanding. The resulting integrative framework encapsulates 21 prior depictions of the policy-making process, aiming to achieve gold-standard societal (...) values, such as fairness, freedom and long-term sustainability. This challenge of integrating the AIR literature was matched by the identification of a structural common ground among different approaches. The AIR framework results from an effort to identify and later analytically deduce synthetic, and generic tool for a country-specific, stakeholder-aware analysis of AIR matters. Theories and principles as diverse as Agile and Ethics were combined in the “AIR framework”, which provides a conceptual lens for societies to think collectively and make informed policy decisions related to what, when, and how the uses and applications of AI should be regulated. Moreover, the AIR framework serves as a theoretically sound starting point for endeavours related to AI regulation, from legislation to research and development. As we know, the (potential) impacts of AI on society are immense, and therefore the discourses, social negotiations, and applications of this technology should be guided by common grounds based on contemporary governance techniques, and social values legitimated via dialogue and scientific research. (shrink)

This groundbreaking proceedings volume explores the integration of Artificial Intelligence (AI) across key domains—healthcare, finance, education, robotics, industrial and other engineering applications —unveiling its transformative potential and practical implications. With a multidisciplinary lens, it transcends technical aspects, fostering a comprehensive understanding while bridging theory and practice. Approaching the subject matter with depth, the book combines theoretical foundations with real-world case studies, empowering researchers, professionals, and enthusiasts with the knowledge and tools to effectively harness AI. Encompassing diverse AI topics—machine learning, natural (...) language processing, computer vision, data analytics and supervisory control — the volume showcases state-of-the-art techniques propelling AI advancements. Structured into four parts: Part 1: Artificial Intelligence (AI), explores evolving deep neural networks, reinforcement learning, and explainable AI, providing a deep dive into the technical foundations of AI advancements. Part 2: Robotics and Control Systems, delves into the integration of AI in robotics and automatic control, addressing supervisory control, automated robotic movement coordination, anomaly detection, dynamic programming, and fault tolerance, offering insights into the evolving landscape of intelligent automation. Part 3: AI and Society, examines the societal impact of AI through chapters on ethical considerations, economic growth, environmental engagements, and hazard management, providing a holistic perspective on AI's role in shaping society. Part 4: PhD Symposium, presents the future of AI through cutting-edge research, covering legal and ethical dimensions, privacy considerations, and computationally efficient solutions, offering a glimpse into the next generation of AI advancements. Catering to a diverse audience—from industry leaders to students—the volume consolidates the expertise of renowned professionals, serving as a comprehensive resource for navigating the ever-evolving AI landscape. An essential reference for those staying at the forefront of AI developments. (shrink)

IntroductionThis case study describes the process faculty at a large research university undertook to build a stand-alone online academic integrity course for first-year and transfer students. Because academic integrity is decentralized at the institution, building a more systematic program had to come from the bottom-up (faculty developed) rather than from the top down (institutionally mandated).Case descriptionUsing the learning management system, faculty and e-learning designers collaborated to build the course. Incorporating nuanced scenarios for six different types of misconduct (consistent (...) with the University’s Code of Student Rights, Responsibilities & Conduct), a pre- and post-test, and assessments for each scenario, the course provides experience in recognizing and avoiding academic misconduct.Discussion and evaluationAs a stand-alone course, the faculty who created it maintain control over content and are able to analyze student performance across the institution. In the ten months since its launch, the course has been eagerly adopted by faculty (n = 1853 students have completed the course) and post-test scores indicate students are learning from the course.ConclusionsAfter the successful launch of the student course, the next step, already underway, is the launch of learning modules for faculty and teaching assistants. (shrink)

In this book, the author examines the ethical implications of Artificial Intelligence systems as they integrate and replace traditional social structures in new sociocognitive-technological environments. She discusses issues related to the integrity of researchers, technologists, and manufacturers as they design, construct, use, and manage artificially intelligent systems; formalisms for reasoning about moral decisions as part of the behavior of artificial autonomous systems such as agents and robots; and design methodologies for social agents based on societal, moral, and legal values. (...) Throughout the book the author discusses related work, conscious of both classical, philosophical treatments of ethical issues and the implications in modern, algorithmic systems, and she combines regular references and footnotes with suggestions for further reading. This short overview is suitable for undergraduate students, in both technical and non-technical courses, and for interested and concerned researchers, practitioners, and citizens. (shrink)

As one of the basic manufacturing industries in China, injection molding industry is faced with the problems of low degree of informatization and intelligence, resulting in low production efficiency and high costs. It is urgent to integrate deeply with new generation of information technology to achieve transformation and upgrade. In this paper, an integrative industrial Internet architecture of “integration of intelligent equipment, intelligent production lines, intelligent workshops, intelligent factories, and intelligent formats” was described. The injection (...) molding intelligent control system, the production management, control platform based on the MES system, and other key technologies were researched. Also, the smart factory architecture based on digital twin was established, and the implementation method of the smart factory digital twin system was elaborated. The feasibility and effectiveness of the method had been verified through the industrial application, which provided the technical supports for the injection molding industrial Internet system. Finally, the intelligent manufacturing industrial Internet cloud platform for injection molding industry was prospected. (shrink)

The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. At the conditions of pandemic, the success of health care system depends significantly on the regular implementation of effective research tools and population monitoring. The earlier the risks (...) of disease can be identified, the more effective process of preventive measures or treatments can be. This publication is about the creation of a prototype for such a tool within the project «Development of methods, algorithms and intelligent analytical system for processing and analysis of heterogeneous clinical and biomedical data to improve the diagnosis of complex diseases», implementted by the V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, together with the United Institute of Informatics Problems, National Academy of Sciences of Belarus. The insurers, entering the market, can insure mostly low risks by facilitating more frequent changes of insurers by consumers and mixing the overall health insurance market. Socio-demographic variables can be risk adjusters. Since age and gender have a relatively small explanatory power, other socio-demographic variables were studied – marital status, retirement status, disability status, educational level, income level. Because insurers have an interest in beneficial diagnoses for their policyholders, they are also interested in the ability to interpret relevant information – upcoding: insurers can encourage their policyholders to consult with doctors more often to select as many diagnoses as possible. Many countries and health care systems use diagnostic information to determine the reimbursement to a service provider, revealing the necessary data. For processing and analysis of these data, software implementations of construction for classifiers, allocation of informative features, processing of heterogeneous medical and biological variables for carrying out scientific research in the field of clinical medicine are developed. The experience of the use of applied containerized biomedical software tools in cloud environment is summarized. The reproducibility of scientific computing in relation with modern technologies of scientific calculations is discussed. Particularly, attention is paid to containerization of biomedical applications, this permits to get reproducibility of the conditions in which the calculations took place, technologies of software pipelining of calculations, that allows to organize flow calculations, and technologies for parameterization of software environment, that allows to reproduce, if necessary, an identical computing environment. The main approaches to biomedical data preprocessing and integration in the framework of the intelligent analytical system are described. The experience of using the developed linear classifier, gained during its testing on artificial and real data, allows us to conclude about several advantages provided by the containerized form of the created application: it permits to provide access to real data located in cloud environment; it is possible to perform calculations to solve research problems on cloud resources both with the help of developed tools and with the help of cloud services; such a form of research organization makes numerical experiments reproducible, i.e. any other researcher can compare the results of their developments on specific data that have already been studied by others, in order to verify the conclusions and technical feasibility of new results; there exists a universal opportunity to use the developed tools on technical devices of various classes from a personal computer to powerful cluster. (shrink)

Abstract: Networking is one of the most important areas currently used for data transfer and enterprise management. It also includes the security aspect that enables us to protect our network to prevent hackers from accessing the organization's data. In this paper, we would like to learn what the network is and how it works. And what are the basics of the network since its emergence and know the mechanism of action components. After reading this paper - even if you (...) do not have a general background on networking - you will be able to manage your own network and be able to distribute and control your ip. (shrink)

It is primordial to insist on a continuous education that is open, flexible, and personalized, allowing the individual to update and make his or her knowledge adequate throughout life. The creation of distributed environments for constructivist learning is a challenge. Research in this field is needed for the development of cooperative learning tools able to facilitate and motivate learning. The development of intelligent didactic systems is complex, demanding the support of knowledge coming from different fields. That is why to (...) develop this class of systems a multidisciplinary team is needed, including pedagogues; educational psychologists; specialists in the knowledge domain; and technicians in computer graphics, programming, multimedia, virtual reality, project management, and so forth. Virtual immersion introduces new resources for interindividual communications that deal with reality interpretation. The authors outline the beginning of a long journey on how imagination power can be used for the collective creation of worlds able to improve learning. (shrink)

With the development and application of information technology, the digitization of information management and the virtualization of physical models have become very important technical application fields in the world. The establishment of the 3D landscape model and the realization of the 3D geographic information system are based on this, and there is not only a wide range of development prospects in many aspects such as urban planning and management, planning and design, local government construction, housing industry development, (...) land monitoring and management, and environmental monitoring and evaluation. There are not only research studies and formulations but also a practical significance in other analysis, evaluation, decision making, and other departments. In recent years, the research of 3D city modeling has been developed rapidly, and most of the existing 2D-GIS can be transformed into 3D visual landscape. Based on the three-dimensional geographic information system and desktop drawing software AutoCAD, this paper takes the two-dimensional line drawing of a residential district as the base map, expounds the design process of the three-dimensional simulation model of the urban community from the aspects of map preprocessing, building simulation model construction, texture mapping, and virtual visualization, and discusses the problems encountered in it. The main contributions of this paper are that this technology puts forward a new solution for the integrated corridor operation and maintenance management, greatly improves the intelligent management level of the integrated corridor operation and maintenance work, and simplifies the complex integrated corridor operation and maintenance management. It is helpful to improve the work efficiency of operation and maintenance, reduce the dependence of personnel, and respond to the long-term construction needs of the smart city at the same time. (shrink)

The broad range of capabilities exhibited by humans and animals is achieved through a large set of heterogeneous, tightly integrated cognitive mechanisms. To move artificial systems closer to such general-purpose intelligence we cannot avoid replicating some subset—quite possibly a substantial portion—of this large set. Progress in this direction requires that systems integration be taken more seriously as a fundamental research problem. In this paper I make the argument that intelligence must be studied holistically. I present key issues that must (...) be addressed in the area of integration and propose solutions for speeding up rate of progress towards more powerful, integrated A.I. systems, including (a) tools for building large, complex architectures, (b) a design methodology for building realtime A.I. systems and (c) methods for facilitating code sharing at the community level. (shrink)

This paper outlines an original interactivist-constructivist approach to modelling intelligence and learning as a dynamical embodied form of adaptiveness and explores some applications of I-C to understanding the way cognitive learning is realized in the brain. Two key ideas for conceptualizing intelligence within this framework are developed. These are: intelligence is centrally concerned with the capacity for coherent, context-sensitive, self-directed management of interaction; and the primary model for cognitive learning is anticipative skill construction. Self-directedness is a capacity for integrative (...) process modulation which allows a system to "steer" itself through its world by anticipatively matching its own viability requirements to interaction with its environment. Because the adaptive interaction processes required of intelligent systems are too complex for effective action to be prespecified learning is an important component of intelligence. A model of self-directed anticipative learning is formulated based on interactive skill construction, and argued to constitute a central constructivist process involved in cognitive development. SDAL illuminates the capacity of intelligent learners to start with the vague, poorly defined problems typically posed in realistic learning situations and progressively refine them, transforming them into problems with sufficient structure to guide the construction of a solution. Finally, some of the implications of I-C for modelling of the neuronal basis of intelligence and learning are explored; in particular, Quartz and Sejnowski's recent neural constructivism paradigm, enriched by Montague and Sejnowski's dopaminergic model of anticipative-predictive neural learning, is assessed as a promising, but incomplete, contribution to this approach. The paper concludes with a fourfold reflection on the divergence in cognitive modelling philosophy between the I-C and the traditional computational information processing approaches. (shrink)

GIS is important equipment in the substation system in a complex microgrid network. Due to the long-term service in harsh operation environments, the electrical performance of GIS equipment will be seriously affected. Therefore, the regular maintenance of GIS equipment in the substation system is a routine task so as to ensure the normal operation of the microgrid networks. The traditional method relies on manual labor, where not only with the low operation efficiency but also regarding some maintenance, labors (...) cannot reach the inside of the GIS equipment, which seriously restricted the completion of GIS equipment maintenance operation. Based on the above analysis, a basic configuration of a GIS equipment maintenance robot with smart structure, convenient control, and stable motion characteristic has been proposed in this paper. Through the optimization design of the chassis adsorption system, the GIS inspection robot can achieve hanging and vertical adsorption inside the GIS equipment and some special motion status. In this way, the entire GIS equipment can be inspected without blind spots. Through establishing the mechanical model of the GIS inspection robot under the hanging and vertical motion state, the robustness and stability of the GIS inspection robot in the special status have been analyzed, and the corresponding GIS inspection robot robust stability motion control method has also been proposed. Finally, through the integrated design of mechanical system and hardware and software control system, the GIS inspection robot physical prototype system has been developed and the maintenance operation experiment has been carried out in Hunan Electric Power Company Maintenance Company through simulating the internal GIS equipment. The physical prototype can realize the basic movement and special movement in internal GIS equipment without any blind spots and complete the inspection task of GIS equipment operation; the movement of GIS robot is dexterous and stable in the whole operation process, which has strong robust stability. The research of GIS inspection robot in the complex microgrid networks has important theoretical significance and practical application value for the intelligent operation and maintenance management of substation system in complex microgrid networks. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial (deep learning, robotics), natural sciences (neuroscience, cognitive science, biology), and philosophy (philosophy of computing, philosophy of mind, natural philosophy). The question is, what at (...) this stage of the development the inspiration from nature, specifically its computational models such as info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach human-level intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

This article analyzes emerging artificial intelligence (AI)-enhanced lie detection systems from ethical and human resource (HR) management perspectives. I show how these AI enhancements transform lie detection, followed with analyses as to how the changes can lead to moral problems. Specifically, I examine how these applications of AI introduce human rights issues of fairness, mental privacy, and bias and outline the implications of these changes for HR management. The changes that AI is making to lie detection are altering (...) the roles of human test administrators and human subjects, adding machine learning-based AI agents to the situation and establishing invasive data collection processes as well as introducing certain biases in results. I project that the potentials for pervasive and continuous lie detection initiatives (“truth machines”) are substantial, displacing human-centered efforts to establish trust and foster integrity in organizations. I argue that if it is possible for HR managers to do so, they should cease using technologically-based lie detection systems entirely and work to foster trust and accountability on a human scale. However, if these AI-enhanced technologies are put into place by organizations by law, agency mandate, or other compulsory measures, care should be taken that the impacts of the technologies on human rights and wellbeing are considered. The article explores how AI can displace the human agent in some aspects of lie detection and credibility assessment scenarios, expanding the prospects for inscrutable, “black box” processes and novel physiological constructs (such as “biomarkers of deceit”) that may increase the potential for such human rights concerns as fairness, mental privacy, and bias. Employee interactions with autonomous lie detection systems rather with than human beings who administer specific tests can reframe organizational processes and rules concerning the assessment of personal honesty and integrity. The dystopian projection of organizational life in which analyses and judgments of the honesty of one’s utterances are made automatically and in conjunction with one’s personal profile provides unsettling prospects for the autonomy of self-representation. (shrink)

This article makes a strong case in favour of linking spirituality to management education. The author has used his experiences as a teacher of management studies, as well as the knowledge that he has gathered as a seeker in search of self–revelation to locate the role and signifi cance of spirituality in the managerial context. The analytic–driven search for information and knowledge, the intellect–driven explanations of context and an exposure to lifeskills linked to emotional intelligence are traditional, albeit (...) insuffi cient, inputs to management education. Such an education is incapable of developing well–rounded individuals capable of handling paradoxes, confl icts and something that managers traditionally have very low tolerance for—ambiguity. This necessitates the inclusion of spiritual intelligence described by the author as a search for inner unfoldment, making the transition from self–consciousness to consciousness of the Self. The article draws heavily on the Advaita–Vedanta tradition of Sanatana Dharma to delineate the tools and processes that are integral to the craft of a practicing manager. The act of managing is perceived as a battle where the three armours of analytical, emotional and spiritual intelligence are to be simultaneously deployed by global managers to negotiate the grey and ambiguous waters of global business. It is spiritual intelligence that enables the manager to awaken the fi rm to its true potential, address questions of philosophy and awaken the fi rm to its larger role in terms of corporate social responsibility. (shrink)

Biodiversity initiatives have traditionally operated within a 'science-first' model of environmental decision - making. The model assumes a hierarchical relationship in which scientific knowledge is elevated above other knowledge systems. Consequently, other types of knowledge held by the public, such as traditional or lay knowledges, are undervalued and under -represented in biodiversity projects. Drawing upon two case studies of biodiversity initiatives in Canada, this paper looks at the role that constructivist conceptions of education play in the integration of alternative knowledge (...) systems in environmental decision - making. In so doing, it argues that the conservation, sustainable use and equitable sharing goals outlined by the Convention on Biological Diversity demand new models of governance which embrace the adaptive management qualities of learning organisations. (shrink)

Smart city is a brand-new city form, in which information and communication technologies are utilized to sense, analyze, and integrate the key information of city operation core system, so that intelligent responses can be immediately and effectively taken to various demands including people’s livelihood, environmental protection, public safety, city services, and industrial and commercial activities. Digital economy is a mixed economy with the coexistence of multiple business models and diversified value creation models based on the information and communication (...) technologies and in the digital economy, many things are undergoing huge changes, and their corresponding economic rules also need to be adjusted. On the basis of analyzing previous research works, this paper expounded the research status and significance of smart city’s resource scheduling and strategic management, elaborated the development background, current status, and future challenges of digital economy, introduced the methods and principles of city-level spatiotemporal data model and spatial full factor coding, formulated resource scheduling strategies for smart city based on digital economy, explored the dynamic fusion, storage, and update of smart city’s multisource heterogeneous data, conducted the information display and analysis of multilevel smart city, proposed strategic management approaches for smart city based on digital economy, analyzed the integrated implementation model of shared resource scheduling and people-oriented social management, and discussed the economic growth factors and standardization mechanism of smart city under the background of digital economy. The results of this study provide a reference for further research studies on the resource scheduling and strategic management of smart city under the background of digital economy. (shrink)

The present issue is the beginning of a new journal from various sub-disciplines and paradigms in order – Cognitive Systems Research – which we have to construct a coherent picture of how the various developed in response to what we perceive to be an pieces fit together overall. Such a synthesis is unfilled niche in the current literature in the areas of essential to the discovery of designs for general Cognitive Science and Artificial Intelligence.

This paper describes the Eunomos software, an advanced legal document and knowledge management system, based on legislative XML and ontologies. We describe the challenges of legal research in an increasingly complex, multi-level and multi-lingual world and how the Eunomos software helps users cut through the information overload to get the legal information they need in an organized and structured way and keep track of the state of the relevant law on any given topic. Using NLP tools to semi-automate (...) the lower-skill tasks makes this ambitious project a realistic commercial prospect as it helps keep costs down while at the same time allowing greater coverage. We describe the core system from workflow and technical perspectives, and discuss applications of the system for various user groups. (shrink)

Actuality of the usage of the food safety knowledge-based technologies is shown. The food safety stakeholders and information objects are presented. The set of ontologies and context areas which are described decision –making tasks and processes are shown. The basic ontology is presented as a means of conceptual representation of the field of food safety. The usage of decision-making is considered. Modern food processing technologies, food safety requirements, food safety requirements etc. are characterized by the need for complex and rational (...) solutions. It is necessary to consider different aspects of decision-making in food safety, which can be based not only on the knowledge of a particular subject area. The use of information and knowledge is a key task in any problem area related to the production and dissemination of knowledge, especially new types of unique content that are useful and accessible. The paper aim is to conceptually present an ontological system based on the use of context and ontologies and aimed at supporting decision making in the food safety management system. Food safety knowledge, which used in decision-making processes, is considered as the context knowledge and the knowledge that describes the content. The paper presents food safety stakeholders and provides information objects. The information and knowledge includes various aspects such as knowledge and information on the production and processing industry; and the food safety aspects. For this purpose, an interconnected set of ontologies is used, which is a multilevel associative structure: meta-ontology; basic ontology; context ontology; set of domain ontologies; realization ontology; user presentation and interaction ontology; model of inference machine. Implementation of food safety processes and integration of the components of decision-making is based on the presentation of the multi-level system of management and decision-making in it through a model of a context. The context framework takes into account different context domains, such as: purpose/result, actor, process/action, object, environment, facility, tools, presentation, location, and time. The ontology implementation builds an inter connected system of preparation and choice of solutions, both for the given problem and for interaction with other complexes of problems and tasks, allows to make decisions taking into account the consequences of their implementation. (shrink)

A concept of co-evolution is argued to complement Integrated Water Resource Management's gap in administrative integration. Co-evolution's complement to Integrated Water Resource Management is explored through issues surrounding joint water management arrangements between the Israelis and Palestinians in the late 1990s and early 21st century. How co-evolution contributes to such a water management approach highlights how we might think about what it means to encourage innovation. Conclusions of the article suggest co-evolution provides the language (...) and description for the changing interactions and political environment and therefore provides a sharper conceptualization for administrative integration. (shrink)

The emerging contemporary natural philosophy provides a common ground for the integrative view of the natural, the artificial, and the human-social knowledge and practices. Learning process is central for acquiring, maintaining, and managing knowledge, both theoretical and practical. This paper explores the relationships between the present advances in understanding of learning in the sciences of the artificial, natural sciences, and philosophy. The question is, what at this stage of the development the inspiration from nature, specifically its computational models such as (...) info-computation through morphological computing, can contribute to machine learning and artificial intelligence, and how much on the other hand models and experiments in machine learning and robotics can motivate, justify, and inform research in computational cognitive science, neurosciences, and computing nature. We propose that one contribution can be understanding of the mechanisms of ‘learning to learn’, as a step towards deep learning with symbolic layer of computation/information processing in a framework linking connectionism with symbolism. As all natural systems possessing intelligence are cognitive systems, we describe the evolutionary arguments for the necessity of learning to learn for a system to reach humanlevel intelligence through evolution and development. The paper thus presents a contribution to the epistemology of the contemporary philosophy of nature. (shrink)

Although the management and planning of water resources are extremely significant to human development, the complexity of implementation is unimaginable. To achieve this, the high-precision water consumption prediction is actually the key component of urban water optimization management system. Water consumption is usually affected by many factors, such as weather, economy, and water prices. If these impact factors are directly combined to predict water consumption, the weight of each perspective on the water consumption will be ignored, which (...) will be greatly detrimental to the prediction accuracy. Therefore, this paper proposes a deep neural network-based complex system for urban water management. The essence of it is to formulate a water consumption prediction model with the aid of principal component analysis and the integrated deep neural network, which is abbreviated as UWM-Id. The PCA classifies the factors affecting water consumption in the original data into three categories according to their correlation and inputs them into the neural network model. The results in the previous step are assigned weights and integrated into the form of fully connected layer. Finally, analyzing the sensitivity of the proposed UWM-Id and comparing its performance with a series of commonly used baseline methods for data mining, a large number of experiments have proved that UWM-Id has good performance and can be used for urban water management system. (shrink)

With the rise and public accessibility of AI-enabled decision-support systems, individuals outsource increasingly more of their decisions, even those that carry ethical dimensions. Considering this trend, scholars have highlighted that uncritical deference to these systems would be problematic and consequently called for investigations of the impact of pertinent technology on humans’ ethical decision-making. To this end, this article conducts a systematic review of existing scholarship and derives an integrated framework that demonstrates how intelligent decision-support systems (IDSSs) shape humans’ (...) ethical decision-making. In particular, we identify resulting consequences on an individual level (i.e., deliberation enhancement, motivation enhancement, autonomy enhancement and action enhancement) and on a societal level (i.e., moral deskilling, restricted moral progress and moral responsibility gaps). We carve out two distinct methods/operation types (i.e., processoriented and outcome-oriented navigation) that decision-support systems can deploy and postulate that these determine to what extent the previously stated consequences materialize. Overall, this study holds important theoretical and practical implications by establishing clarity in the conceptions, underlying mechanisms and (directions of) influences that can be expected when using particular IDSSs for ethical decisions. (shrink)

The development of educational technologies is enhancing a distinctive feature of learning environments: the learner’s personalized environment. However, the current literature in e-learning seems to neglect an important discussion: will individuals and organizations face an enhancement concerning ethical dilemmas due to this evolution? To promote this discussion, this paper builds on a consideration of e-learning definition and its ethical dilemmas, and human-centred learning concept and its dimensions, to examine the implications of integrating social and cultural contexts. By examining the evolution (...) of e-learning management systems the argument progresses to a discussion of the relationships between pedagogy and ethics. By framing evidence at different scales, the authors critically reflect on the ethical dilemmas embedded in e-learning systems. The discussion concludes with advocating the adoption of an extension of “three P” mode of pedagogy to become the “P3E” model: personalization, participation, productivity, lecturer’s ethics, learner’s ethics, and organizational ethics. (shrink)

Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of the knowledge requires the input of legal experts, we focus in this article on NLP applications that semi-automate essential time-consuming and lower-skill tasks—classifying legal documents, identifying cross-references and legislative amendments, linking legal terms to (...) the most relevant definitions, and extracting key elements of legal provisions to facilitate clarity and advanced search options. The use of Natural Language Processing tools to semi-automate such tasks makes the proposal a realistic commercial prospect as it helps keep costs down while allowing greater coverage. (shrink)

Every organization has to deal with operational risks, arising from the execution of a company’s primary business functions. In this paper, we describe a legal knowledge management system which helps users understand the meaning of legislative text and the relationship between norms. While much of the knowledge requires the input of legal experts, we focus in this article on NLP applications that semi-automate essential time-consuming and lower-skill tasks—classifying legal documents, identifying cross-references and legislative amendments, linking legal terms to (...) the most relevant definitions, and extracting key elements of legal provisions to facilitate clarity and advanced search options. The use of Natural Language Processing tools to semi-automate such tasks makes the proposal a realistic commercial prospect as it helps keep costs down while allowing greater coverage. (shrink)

Meeting the security requests in transportation is nowadays a must. The intelligent transport systems represent the support for addressing such a challenge, due to their ability to make real-time adaptive decisions. We propose a new variant of the travelling salesman problem integrating security constraints inspired from ITSs. This optimization problem is called the secure TSP and considers a set of security constraints on its integer variables. Similarities with fuzzy logic are presented alongside the mathematical model of the introduced TSP (...) variant. (shrink)

Obtaining a sufficient amount of measurable and reliable results of student surveys has always posed a challenge for university teams tasked with the provision of the quality of education. This is especially visible at faculties where education is based on the classic classroom-based model, which then transfers to clinical units, hospital wards, and specialist laboratories. The highly unpredictable pandemic situation caused by the SARS-CoV-2 virus raises the bar for the evaluation of didactics. Fortunately, the continuous technological progress in the area (...) of Artificial Intelligence makes it possible to design the implementation of tools that would improve the position of systems for the management of courses of studies. The evaluation survey for didactic classes, as one of the last output data obtained during the process, may finally become a fully recognized source of information about the conducted classes and the teachers themselves. On the other hand, it may become a tool for those surveyed to influence the quality of classes, express their opinion, present suggestions and propositions generally pertaining to changes in the process of education. New information technologies not only make it possible to improve the effectiveness of reaching the recipients, but also provide completely new, very reliable methods of acquisition of credible behaviour, used as integration data in solutions based on machine communication. Using Artificial Intelligence coupled with data may make it possible to use intelligent communication for effective management of the process of surveying – a solution that has so far been used in business, in the form of the so-called bots. As a result, this would lead to an ongoing, fully quantitative and qualitative, assessment of classes. (shrink)

This paper connects to Jon Bing’s great vision of an integrated national legal information system. The intention of this paper is to variegate Bing’s vision of an integrated information system by shifting the focus to the lay users, thus to those, who are subject to the law. The modified vision is an integrated information system that supports intelligible access to law for the citizens. This presupposes however an unambiguous and transparent legal system. Accordingly, (...) it is also stressed that intelligent legal knowledge engineering has high potential to increase precision and rationality in law, and hence safeguard the predictability of law and legal certainty. The central hypothesis is that putting the person who is subject to the law at the centre provides more rational reason to aim for the greatest possible precision of law by exploiting the means and technologies of our time than to uphold strategic vagueness. On this basis, the paper proposes the development of a basic set of controllable and justiciable basic legal drafting standards on EU and on national level, and promotes a transparency by design approach for legal knowledge engineering in order to enhance precision, integrity, comprehensibility and accessibility of law. Similarly to Jon Bing’s vision, this modified vision of an integrated legal information systems is, most probably, also likely to remain unfulfilled. However, what would science be without visions and (science) fictions? (shrink)

Nowadays, social media analysis systems are feeding on user contributed data, either for beneficial purposes, such as emergency management, or for user profiling and mass surveillance. Here, we carry out a discussion about the power and pitfalls of public accessibility to social media-based systems, with specific regards to the emergency management application EARS. We investigate whether opening such systems to the population at large would further strengthen the link between communities of volunteer citizens, intelligent systems, and decision (...) makers, thus going in the direction of developing more sustainable and resilient societies. Our analysis highlights fundamental challenges and provides interesting insights into a number of research directions with the aim of developing human-centered social media-based systems. (shrink)

Power provision is coming to be the most important constraint to data center development. The efficient management of power consumption according to the loads of the data center is urgent. As the load for every application hosted in every server node of the data center and corresponding Service Level Agreement requirements can be quite different, it is hard to deploy a power strategy at application. The asynchronies and abruptness characteristics of workload fluctuation make power management policymaking using periodic (...) resource scheduling method invalid. In this article, the design and implementation of the request–response distributed power management scheme is elaborated. Bound by linear time complexity, the method proposed integrates dynamic voltage/frequency scaling, power-on–power-off, and virtual machine migration mechanisms and dynamically optimizes the power consumption of a cloud data center. The significant advantage of the scheme is that it does not need synchronous scheduling between all SNs. Simulation results showed that the scheme could effectively decrease the power consumption of the data center, with a tiny reduction in performance as centralized control methods. (shrink)

Basic tendencies of enterprises' innovative development management have been considered from the perspective of postfordist tranformations. It has been determined that mobility is a specificity of postfordist industrial management. Mobility provides dispersion of structural subdivisions all over the world, it doesn't need any governmental support and strict control. Total diversification of the kind allows to implement «high» technologies through global data revolution practically into all spheres of social life. The evolution of social relations types from feudalism up to (...) Post-Fordism has been provided and their specifics defined. Analytical studies carried out have enabled to discover formed world innovative centres and – from global economic perspective – those of half-peripheral countries with low level of innovative development. The directions of China management of innovative development, whose combined innovation level steadily increases, have been described. It has been determined that a great many of world countries is not currently being on the postfordist stage, since an industrial labour is characteristic for them which defines their type as traditional or early industrial pre-modern. We've also found that innovation development governance at the global level through the prism of postfordist transformations manifests itself in looking for niche, strict subordination to global market mechanisms, decentralization under control of transnational corporations; at the national level: in decentration of social space and thinking, marginalization of urban population, migration; at the meso level: in orientation on consumer needs, considerable mobility of production, individualization under global standardization; at the micro level: in project approach, faster time to market, cost minimization. It has been determined that technological breakthrough evokes such social concerns as total control, alienation, job and security loss. (shrink)

This theoretical paper takes an agency-theoretic approach to questions of corporate social responsibility (CSR). A comparison of various extant frameworks focusses on how CSR agency emerges in complex multi-agent and multi-sector stakeholder networks. The discussion considers the respective capabilities and relevance of these frameworks – culminating in an integrative CSR practice model. A short literature review of the evolution of CSR since the 1950’s provides the backdrop for understanding multi-agent cross-sectoral stakeholder coalitions as a strategic determinant of today’s organizational behavior. (...) The paper turns to Werhane’s coupling of moral imagination and systems thinking and forging stakeholder coalitions in problem contexts that were traditionally deemed intractable by for-profit organizations. However, it identifies the problem that the systems approach treats macro-agents (organizations, stakeholders) as given (“black-boxed”) and shies away from more radically re-imagining the possibilities of reassembling agency from the bottom up. Actor Network Theory (ANT) provides such a method, which strictly commits to treating organizational behavior as a product of technological, human and environmental micro-processes. ANT, however, is lacking a genuine moral deliberative stance in designing complex CSR coalitions. In an attempt to capitalize on the respective strengths of these frameworks (Systems thinking and ANT) the paper tends to a recent iterative series of “situational transactive” models that are rooted in the US pragmatist tradition and seek to capture intelligent planning processes in complex problematic contexts. The contribution proposes a new CSR practice model, which assigns specific roles to the theoretical contributions of ANT, system thinking and pragmatism in complex deliberation processes. This model can be industry-tested in a future study. (shrink)

HANDBOOK OF DEFEASIBLE REASONING AND UNCERTAINTY MANAGEMENT SYSTEMS EDITORS: DOV M. ... and A. Hunter Volume 3: Belief Change Edited by D. Dubois and H. Prade HANDBOOK OF DEFEASIBLE REASONING AND ...