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Johansson, Anette, Hanna-Kaisa Ellonen i Ari Jantunen. "Magazine Publishers Embracing New Media: Exploring their Capabilities and Decision Making Logic". Journal of Media Business Studies 9, nr 2 (czerwiec 2012): 97–114. http://dx.doi.org/10.1080/16522354.2012.11073546.
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Namagembe, Sheila, Joseph Ntayi Mpeera i Awad Kalid. "An examination of SME involvement in public procurement under bid lot sizing". Journal of Public Procurement 21, nr 4 (11.10.2021): 370–98. http://dx.doi.org/10.1108/jopp-04-2020-0031.
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Purpose This study aims to examine the influence of market logics on tendering capabilities and small and medium enterprise (SME) involvement in public procurement, the influence of SME governance mechanisms on tendering capabilities and SME involvement in public procurement and the influence of tendering capabilities on SME involvement in public procurement. Design/methodology/approach Data was collected from owners/managers of SMEs registered by the Public Procurement and Disposal of Public Assets Authority. The SPSS software and CB-SEM software were used to obtain results on the influence of market logics on tendering capabilities and SME involvement in public procurement, the influence of SME governance mechanisms on tendering capabilities and SME involvement in public procurement and the influence of tendering capabilities on SME involvement in public procurement. Findings Findings indicated that SME involvement in public procurement is mainly influenced by their governance mechanisms whilst both market logics and governance mechanisms had a positive influence on tendering capabilities of SME firms. Market logics and tendering capabilities had no effect on SME involvement. Research limitations/implications The study mainly focussed on SMEs’ involvement in public procurement. The research has implications for decision makers in government and SME firms concerned with enhancing levels of SME involvement in public procurement activities. Originality/value Many governments are now focussing on procurement lot sizing so as to increase SME involvement in public procurement. Despite the use of lot sizing, SME involvement in public procurement is still low in many developing countries and also declining in others. Aspects such as market logics and governance mechanisms that may help understand the variations in involvement have not been given significant attention.
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Sadykov, Rafael Faritovich, i Mikhail Usamovich Mandrykin. "Complete decision procedure for the theory of bounded pointer arithmetic based on quantifier instantiation and SMT". Proceedings of the Institute for System Programming of the RAS 33, nr 4 (2021): 177–94. http://dx.doi.org/10.15514/ispras-2021-33(4)-13.
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The process of developing C programs is quite often prone to errors related to the uses of pointer arithmetic and operations on memory addresses. This promotes a need in developing various tools for automated program verification. One of the techniques frequently employed by those tools is invocation of appropriate decision procedures implemented within existing SMT-solvers. But at the same time both the SMT standard and most existing SMT-solvers lack the relevant logics (combinations of logical theories) for directly and precisely modelling the semantics of pointer operations in C. One of the possible ways to support these logics is to implement them in an SMT solver, but this approach can be time-consuming (as requires modifying the solver’s source code), inflexible (introducing any changes to the theory’s signature or semantics can be unreasonably hard) and limited (every solver has to be supported separately). Another way is to design and implement custom quantifier instantiation strategies. These strategies can be then used to translate formulas in the desired theory combinations to formulas in well-supported decidable logics such as QF_UFLIA. In this paper, we present an instantiation procedure for translating formulas in the theory of bounded pointer arithmetic into the QF_UFLIA logic. We formally proved soundness and completeness of our instantiation procedure in Isabelle/HOL. The paper presents an informal description of this proof of the proposed procedure. The theory of bounded pointer arithmetic itself was formulated based on known errors regarding the correct use of pointer arithmetic operations in industrial code as well as the semantics of these operations specified in the C standard. Similar procedure can also be defined for a practically relevant fragment of the theory of bit vectors (monotone propositional combinations of equalities between bitwise expressions). Our approach is sufficient to obtain efficient decision procedures implemented as Isabelle/HOL proof methods for several decidable logical theories used in C program verification by relying on the existing capabilities of well-known SMT solvers, such as Z3 and proof reconstruction capabilities of the Isabelle/HOL proof assistant.
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Haryanto, Joko, i Seng Hansun. "Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)". Jurnal ULTIMA Computing 7, nr 1 (22.08.2016): 12–18. http://dx.doi.org/10.31937/sk.v7i1.448.
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This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy.
Index Terms—fuzzy logic, decision support system, UMN, selection of major
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Glaser, Vern L., Neil Pollock i Luciana D’Adderio. "The Biography of an Algorithm: Performing algorithmic technologies in organizations". Organization Theory 2, nr 2 (kwiecień 2021): 263178772110046. http://dx.doi.org/10.1177/26317877211004609.
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Algorithms are ubiquitous in modern organizations. Typically, researchers have viewed algorithms as self-contained computational tools that either magnify organizational capabilities or generate unintended negative consequences. To overcome this limited understanding of algorithms as stable entities, we propose two moves. The first entails building on a performative perspective to theorize algorithms as entangled, relational, emergent, and nested assemblages that use theories—and the sociomaterial networks they invoke—to automate decisions, enact roles and expertise, and perform calculations. The second move entails building on our dynamic perspective on algorithms to theorize how algorithms evolve as they move across contexts and over time. To this end, we introduce a biographical perspective on algorithms which traces their evolution by focusing on key “biographical moments.” We conclude by discussing how our performativity-inspired biographical perspective on algorithms can help management and organization scholars better understand organizational decision-making, the spread of technologies and their logics, and the dynamics of practices and routines.
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Paulauskaite-Taraseviciene, Agne, Vaidas Jukavicius, Nerijus Morkevicius, Raimundas Jasinevicius, Vytautas Petrauskas i Vygintas Kazanavicius. "Statistical Evaluation of Four Technologies used for Intelectualization of Smart Home Environment". Information Technology And Control 44, nr 3 (24.09.2015): 334–44. http://dx.doi.org/10.5755/j01.itc.44.3.11965.
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This paper addresses the issues of decision-making methods and their usage capabilities for intelligent control based on resident’s habits. Learning from the behaviour of the resident is essential for the system to adapt and provide intelligent control based on behaviour patterns. Different homes have different conditions and habits which have to be taken into account for the intelligent system to be useful. However, even deeply ingrained habits are subject to change over time. Therefore, an intelligent system has to respond to changing and diverse environment. Various decision-making methods have the potential of a number of benefits in providing intelligent control for the Smart home systems. In this paper, concurrent decision-making methods, including Artificial Neural Networks, Fuzzy Logic, Linear Programing and Bayesian, are employed with particular algorithms in order to provide control based on resident’s habits. These approaches are tested and compared within experimental scenarios for intelligent lightning control.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.11965
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Florez Zuluaga, Jimmy Anderson, Esteban Patiño Carrasco, Jose David Ortega Pabon, Kelly Gallego Leon i O. Lucia Quintero Montoya. "A Data Fusion System for Simulation of Critical Scenarios and Decision-Making". Ciencia e Ingeniería Neogranadina 30, nr 1 (12.11.2019): 89–106. http://dx.doi.org/10.18359/rcin.4131.
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The decision-making (DM) process in critical environments is a complex process that can be simulated due to current telematic capabilities, which allow the real time interaction of large amounts of data. This document describes the proposed architecture from a research process, developed by the FAC Aerospace Technology Development Center (CETAD), where using computational and expert system tools, allowed to create a computational environment for decision maker evaluated his options to prepares for real events, simulating characteristics, resources and strategies in a real time environment.
This document describes an investigation product resulted in a simulation system, based on a combination of fuzzy logic, genetic algorithms and decision trees which let modelled and simulated various entities and their automatic response according to simulated patterns and situations, in which, through operators, decision maker can modify entities behaviour, according to parameterized restrictions and physical conditions. Also based on business intelligence tools, reports are generated to evaluate the decisions made. This type of technologies improves planning capacity and facilitate the decision-making process.
System allows simulating any media deployment in national security and critical events context. Thus, a case study was developed for implementation of a support in natural disaster scenario simulation
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Liu, Mai-di, Ke-wei Yang, Qing-qing Yang i Zhi-wei Yang. "C3I cooperative decision system simulation and optimization based on genetic algorithm for surface warship formation". MATEC Web of Conferences 277 (2019): 03004. http://dx.doi.org/10.1051/matecconf/201927703004.
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The C3I cooperative decision system is the guarantee for combat capabilities of surface warship formations. At present, research on the C3I system simulation lays more emphasis on finding structural logic defects by executing the simulation model, lacking the application of intelligent optimization algorithms to optimize parameters in the system. In this paper, the cooperative decision-making process of surface warship formation defense system is studied. Meanwhile, modelling and optimization methods for cooperative decision system are proposed. Based on simulation models built on the ExtendSim platform, this paper optimizes the staffing strategy of decision makers based on the genetic algorithm, to improve the per capita decision efficiency. The optimized staffing strategy meets objectives and requirements. The research in this paper can provide a scientific and objective reference for relevant decision-makers and researchers.
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Sadiku, Matthew N. O., Yonghui Wang, Suxia Cui i Sarhan M. Musa. "SOFT COMPUTING: AN INTRODUCTION". International Journal of Advanced Research in Computer Science and Software Engineering 8, nr 6 (30.06.2018): 63. http://dx.doi.org/10.23956/ijarcsse.v8i6.615.
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Soft computing (SC) is a newly emerging multidisciplinary field. It is a collection of computational techniques, such as expert systems, fuzzy logic, neural networks, and evolutionary algorithms, which provide information processing capabilities to solve complex practical problems. The major benefit of SC lies in its ability to tolerate imprecision, uncertainty, partial truth, and approximation in processing imprecise and inaccurate information and simulating human decision making at low cost. This paper provides a brief introduction on soft computing.
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Princes, Elfindah, Harjanto Prabowo, Mohammad Hamsal i Andi William. "Strategic Impulses Urgency in the era of Industry 4.0". Asia Proceedings of Social Sciences 4, nr 2 (22.04.2019): 146–48. http://dx.doi.org/10.31580/apss.v4i2.769.
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The speed of changes in the era of Industry 4.0 has left us no choice but to be agile, adaptive and have dynamic capabilities to keep the firm performance on the track(Gilchrist, 2016). Being adaptive and agile means innovation, the firms must innovate and managing innovation. Studies confirm that only 12% of organizations succesfully manage innovation and only half of these do so consistently across time(Kleinknecht et al., 2009). Without any doubts, there are many times when the top managements are having hard time adapting to the situation, especially when inevitable events happen and they must respond at once. This is the part where the strategic impulses are very important, though it is long debated, as Impulse-driven logics are notoriously difficult to identify, isolate and describe (Hunt and Lerner, 2017) and rational decision-making often result in an optimal response of inaction. But it is also undeniable that strategic impulses have given lots of benefits and have lots of business opportunities (Daniel Lerner and Dimo Dimov, 2016). Strategic impulses in the era of industry 4.0 are without any doubt a must to firm performance if the firm wants to survive and increase its performance.
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Manickam, Pandiaraj, Siva Ananth Mariappan, Sindhu Monica Murugesan, Shekhar Hansda, Ajeet Kaushik, Ravikumar Shinde i S. P. Thipperudraswamy. "Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare". Biosensors 12, nr 8 (25.07.2022): 562. http://dx.doi.org/10.3390/bios12080562.
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Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, cancer diagnosis, and diabetes management. The role of AI in supporting advanced robotic surgeries developed for advanced biomedical applications is also discussed in this article. The position and importance of AI in improving the functionality, detection accuracy, decision-making ability of IoMT devices, and evaluation of associated risks assessment is discussed carefully and critically in this review. This review also encompasses the technological and engineering challenges and prospects for AI-based cloud-integrated personalized IoMT devices for designing efficient POC biomedical systems suitable for next-generation intelligent healthcare.
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Alziari, Lucien. "A chief HR officer’s perspective on talent management". Journal of Organizational Effectiveness: People and Performance 4, nr 4 (4.12.2017): 379–83. http://dx.doi.org/10.1108/joepp-05-2017-0047.
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Purpose The HR function has been through a palette of names and identities, with talent management or human capital management being one more. There is a lack of consistency in the way that HR practitioners think about talent management and this is often the cause of credibility issues with business colleagues. The purpose of this paper is to identify core beliefs that underpin the practice of talent management if the function is to build credibility. Design/methodology/approach The paper identifies five core beliefs that should structure a discussion around, and underpin, the practice of talent management: notions of human capital management; questions about whether talent is generic or not; distinctions between talent management and HRM; decisions about who makes decisions about talent management; and moments of truth. It uses the case setting of Maersk to illustrate these beliefs and position the preferred conduct of talent management against them. Findings Organizations make distinctions between where good (not average) is “good enough” and where they need world-class talent to drive true competitive advantage. This capability perspective results in three different clusters of effort in terms of talent management. They manage investments so that they do not over-invest in less critical capabilities but can marshal scarce resources in areas where they need to be world class. Practical implications What is defined as talent in one setting might not be so in others. Strategies define capabilities and capabilities define talent. Attention must be given to all the other processes that support the deployment of talent to build specific organizational capabilities. As talent decisions are made by business leaders there needs to be a common mindset and decision-making logic for them to use. The 9 Box model is one such logic. Adopting any decision logic does not denote the outcome, rather it is how companies use the tool that determines the output. Originality/value The paper positions talent management within the strategic management discipline of business models and analysis of how organizations need to compete. It uses an industrial setting and professional experience base to link talent management to the wider management of organizational capabilities.
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Adjali, Omar, i Amar Ramdane-Cherif. "Knowledge Processing Using EKRL for Robotic Applications". International Journal of Cognitive Informatics and Natural Intelligence 11, nr 4 (październik 2017): 1–21. http://dx.doi.org/10.4018/ijcini.2017100101.
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This article describes a semantic framework that demonstrates an approach for modeling and reasoning based on environment knowledge representation language (EKRL) to enhance interaction between robots and their environment. Unlike EKRL, standard Binary approaches like OWL language fails to represent knowledge in an expressive way. The authors show in this work how to: model environment and interaction in an expressive way with first-order and second-order EKRL data-structures, and reason for decision-making thanks to inference capabilities based on a complex unification algorithm. This is with the understanding that robot environments are inherently subject to noise and partial observability, the authors extended EKRL framework with probabilistic reasoning based on Markov logic networks to manage uncertainty.
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Di Pinto, Floriana, Giuseppe De Giacomo, Domenico Lembo, Maurizio Lenzerini i Riccardo Rosati. "Acquiring Ontology Axioms through Mappings to Data Sources". Future Internet 11, nr 12 (13.12.2019): 260. http://dx.doi.org/10.3390/fi11120260.
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Although current languages used in ontology-based data access (OBDA) systems allow for mapping source data to instances of concepts and relations in the ontology, several application domains need more flexible tools for inferring knowledge from data, which are able to dynamically acquire axioms about new concepts and relations directly from the data. In this paper we introduce the notion of mapping-based knowledge base (MKB) to formalize the situation where both the extensional and the intensional level of the ontology are determined by suitable mappings to a set of data sources. This allows for making the intensional level of the ontology as dynamic as the extensional level traditionally is. To do so, we resort to the meta-modeling capabilities of higher-order description logics, in particular the description logic Hi ( DL-Lite R ) , which allows seeing concepts and relations as individuals, and vice versa. The challenge in this setting is to design efficient algorithms for answering queries posed to MKBs. Besides the definition of MKBs, our main contribution is to prove that answering instance queries posed to MKBs expressed in Hi ( DL-Lite R ) can be done efficiently.
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McGill, William L., i Bilal M. Ayyub. "Multicriteria Security System Performance Assessment Using Fuzzy Logic". Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 4, nr 4 (październik 2007): 356–76. http://dx.doi.org/10.1177/154851290700400405.
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Modern security problems focus on sensibly allocating resources to decrease the magnitude of potential hazards, decrease the chances of adversary success given an attempt, or minimize loss following a successful attack. The focus of this paper is on developing a simple, yet analytically sound tool that facilitates rapid assessments of security system non-performance in terms of probability of adversary success at the facility or asset level using concepts from fuzzy logic. Beginning with a short overview of how security system performance fits within an overall security risk analysis frame-work, this paper presents the basic concepts of fuzzy systems and applies them to develop a model that approximates the true relationship between defensive capabilities and probability of adversary success. A simple example demonstrating the proposed model to support decision making accompanies this discussion. This paper concludes with a strategy for implementation of the proposed model in an operational setting.
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Hofstetter, Dominic. "Transformation Capital: The Challenge of Designing and Testing a New Investment Logic for the Sustainable Development Goals". LAS ALIANZAS MULTIACTOR Y PLATAFORMAS DE INNOVACIÓN ABIERTA: NUEVAS INFRAESTRUCTURAS PARA ABORDAR PROBLEMAS COMPLEJOS 02, MAYO 2020 (31.05.2020): 15–26. http://dx.doi.org/10.36852/2695-4427_2020_02.01.
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The most tangible and pressing problems of the 21st century are complex systemic issues. Addressing them requires deep structural changes within the socio-technical systems that constitute modern civilization. As financial capital is an important lever of change in such systems, the way in which we deploy capital affects our ability to accomplish the UN’s Sustainable Development Goals. The problem is that today’s capital markets operate under a set of axioms, paradigms, and structures that make them ill-suited to fuel systemic transformations. There is thus a need for an investment logic that deploys capital with a different intent and mindset and with different methodologies, structures, capabilities, and decision-making frameworks. Residing at the intersection of systems thinking and finance practice, Transformation Capital is such a logic. This article introduces Transformation Capital and discusses how it can be tested through real-world prototyping.
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Sales Leite, Dinah Eluze, i Milton De Freitas Chagas Junior. "Desenvolvimento de um Modelo Dinâmico e Adaptativo como Ferramenta para a Orientação Estratégica em Organizações do Setor Aeroespacial". Future Studies Research Journal: Trends and Strategies 12, nr 2 (1.05.2020): 242–63. http://dx.doi.org/10.24023/futurejournal/2175-5825/2020.v12i2.472.
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Objective: The article proposes a strategic model, dynamic and adaptive, aiming to improve the capture and use of opportunities in the selection of the technology portfolio in complex and uncertain environments.Method: The methodology defined in this research is the study of multiple cases in the Design Science approach. We seek to generate scientific knowledge about the selection of technologies in organizations in the aerospace sector through the development and application of the proposed model. The study also considers a combination of inductive and abductive logic to deal with the inherent uncertainty in the RD environment.Originality/Relevance: From a theoretical point of view, the main gaps in technological strategy in the aerospace sector can be highlighted: decision making under uncertainty, the lack of integration between areas in decision making, and limitations in the time horizon of strategic development.Results: The main expected results, with the application of the model, are: (1) improve the capture, and use of opportunities, (2) improve the competitive advantage of the organization, and (3) contribute to a more flexible technology strategy in the long term. The cases explored allowed the detailing of the impacts of decision making on strategic development and the technologies domain in the definition of technological routes.Theoretical contributions: From a theoretical point of view, the research contributes to the dynamic capabilities model, including seizing to generative sensing.Management contributions: From a practical point of view, the development of the model contributes to aerospace organizations' strategic management to make them more robust, agile, and flexible.
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Ghaemi, Sehraneh, Sohrab Khanmohammadi i Mohammadali Tinati. "Driver's Behavior Modeling Using Fuzzy Logic". Mathematical Problems in Engineering 2010 (2010): 1–29. http://dx.doi.org/10.1155/2010/172878.
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In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model calledModel Iis presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules calledModel IIandModel IIIby using Sugeno fuzzy inference.Model IIandModel IIIhave less linguistic terms thanModel Ifor the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.
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Di Pinto, Floriana, Giuseppe De Giacomo, Maurizio Lenzerini i Riccardo Rosati. "Ontology-Based Data Access with Dynamic TBoxes in DL-Lite". Proceedings of the AAAI Conference on Artificial Intelligence 26, nr 1 (20.09.2021): 719–25. http://dx.doi.org/10.1609/aaai.v26i1.8223.
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In this paper we introduce the notion of mapping-based knowledge base (MKB) to formalize the situation where both the extensional and the intensional level of the ontology are determined by suitable mappings to a set of (relational) data sources. This allows for making the intensional level of the ontology as dynamic as traditionally the extensional level is. To do so, we resort to the meta-modeling capabilities of higher-order Description Logics, which allow us to see concepts and roles as individuals, and vice versa. The challenge in this setting is to design tractable query answering algorithms. Besides the definition of MKBs, our main result is that answering instance queries posed to MKBs expressed in Hi(DL-LiteR) can be done efficiently. In particular, we define a query rewriting technique that produces first-order (SQL) queries to be posed to the data sources.
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Blagden, David. "Do Democracies Possess the Wisdom of Crowds? Decision Group Size, Regime Type, and Strategic Effectiveness". International Studies Quarterly 63, nr 4 (11.09.2019): 1192–95. http://dx.doi.org/10.1093/isq/sqz072.
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Abstract What is it about democracies—if anything—that enables them to avoid war with each other while navigating conflictual international politics in pursuit of their own interests? Recent research in International Studies Quarterly by Brad LeVeck and Neil Narang (2017) provides an elegant new answer to this longstanding question. Drawing on “wisdom of crowds” logic—the insight that a large-enough group of inexpert judges is more likely to average towards an accurate estimate of a continuous variable than a smaller group, even when the smaller group contains relevant experts—supported by experimental evidence, they suggest that democracies’ strategic advantages lie in their large, diverse decision-making communities. If such crowd wisdom equips democracies to accurately assess others’ capabilities and intentions, so the argument goes, then they should be better than alternative regime types at maximizing their own interests while still avoiding the bargaining failure that is resort to war. Unfortunately, however, the politics of democratic foreign policy-making compromise the crowd-wisdom mechanism. This response article thus elucidates key flaws in the argument that crowd wisdom underpins democratic peace, before progressing to explain how the crowd-wisdom insight nonetheless carries important implications—irrespective of regime type—for strategic effectiveness.
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Cegarra-Navarro, Juan-Gabriel, Stephen Eldridge i Antonio L. Gamo Sánchez. "How an unlearning context can help managers overcome the negative effects of counter-knowledge". Journal of Management & Organization 18, nr 2 (marzec 2012): 231–46. http://dx.doi.org/10.1017/s1833367200000973.
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AbstractCustomer relations provide a valuable link between customers and the companies who produce the products they buy and the services they use. Every organisational member carries out actions which reflect the existence of counter-knowledge (i.e., obsolete knowledge and inappropriate knowledge structures) which in turn can lead to detrimental effects on customers. A decision to reorientate counter-knowledge takes an extended period of time to produce significant results as this process involves the integration of existing capabilities with newly acquired knowledge. Crucially, however, it also involves the unlearning of capabilities which are no longer relevant. Unlearning is the process by which firms eliminate old logics and behaviours and make room for new ones. With the development of this paper, we intend to address the following question: How can managers help to correct counter-knowledge in order to foster customer relations? These relationships are examined through an empirical investigation of 164 small and medium enterprises in the Spanish construction industry. Our results show that an unlearning context (i.e., the examination of lens fitting, the framework for changing individual habits and the framework for consolidating emergent understandings) is an important solution for the process of counteracting the negative effects of counter-knowledge (e.g., misunderstandings and misconceptions). The results also shed light on a tangible means for managers to enhance customer relations through unlearning practices.
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Cegarra-Navarro, Juan-Gabriel, Stephen Eldridge i Antonio L. Gamo Sánchez. "How an unlearning context can help managers overcome the negative effects of counter-knowledge". Journal of Management & Organization 18, nr 2 (marzec 2012): 231–46. http://dx.doi.org/10.5172/jmo.2012.18.2.231.
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AbstractCustomer relations provide a valuable link between customers and the companies who produce the products they buy and the services they use. Every organisational member carries out actions which reflect the existence of counter-knowledge (i.e., obsolete knowledge and inappropriate knowledge structures) which in turn can lead to detrimental effects on customers. A decision to reorientate counter-knowledge takes an extended period of time to produce significant results as this process involves the integration of existing capabilities with newly acquired knowledge. Crucially, however, it also involves the unlearning of capabilities which are no longer relevant. Unlearning is the process by which firms eliminate old logics and behaviours and make room for new ones. With the development of this paper, we intend to address the following question: How can managers help to correct counter-knowledge in order to foster customer relations? These relationships are examined through an empirical investigation of 164 small and medium enterprises in the Spanish construction industry. Our results show that an unlearning context (i.e., the examination of lens fitting, the framework for changing individual habits and the framework for consolidating emergent understandings) is an important solution for the process of counteracting the negative effects of counter-knowledge (e.g., misunderstandings and misconceptions). The results also shed light on a tangible means for managers to enhance customer relations through unlearning practices.
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Haj Youssef, Moustafa Salman, Hiba Maher Hussein i Hoda Awada. "The more you value, the less you practice: a study on culture and managerial discretion". Cross Cultural & Strategic Management 27, nr 1 (2.12.2019): 26–50. http://dx.doi.org/10.1108/ccsm-03-2018-0044.
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Purpose The purpose of this paper is to examine cross-cultural differences in managerial discretion and the extent to which variations and interaction of cultural practices and values affect the degree of freedom in decision making that is accorded to executives. This paper offers a holistic approach to investigating culture in addition to acknowledging its paradoxical nature. Design/methodology/approach Using a panel of prominent management consultants to rate discretion across 18 countries, the authors further develop the national-level construct of managerial discretion by empirically investigating the influence of cultural practices and values on CEOs’ discretion. Findings The study reveals that cultural values moderate the relationship between cultural practices and managerial discretion for three cultural dimensions: individualism, uncertainty tolerance and power distance (PD). By adopting the logic of marginal utility, the authors also show that the more a society values individualism, uncertainty tolerance and PD, the weaker the effect of their practices on managerial discretion. Originality/value Few research has attempted to assess both cultural values and practices in relation to managerial discretion. By showing the mechanism in which culture affects the level of managerial discretion, the authors offer new theoretical insights and practical implications, overall contributing to the field of cross-cultural and strategic management. Finally, this will offer CEO’s a new perspective of leveraging culture as a tool, enhancing their decision-making capabilities in the aim of improving organizational performance.
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Omari, Rollin M., i Masoud Mohammadian. "Rule based fuzzy cognitive maps and natural language processing in machine ethics". Journal of Information, Communication and Ethics in Society 14, nr 3 (8.08.2016): 231–53. http://dx.doi.org/10.1108/jices-10-2015-0034.
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Purpose The developing academic field of machine ethics seeks to make artificial agents safer as they become more pervasive throughout society. In contrast to computer ethics, machine ethics is concerned with the behavior of machines toward human users and other machines. This study aims to use an action-based ethical theory founded on the combinational aspects of deontological and teleological theories of ethics in the construction of an artificial moral agent (AMA). Design/methodology/approach The decision results derived by the AMA are acquired via fuzzy logic interpretation of the relative values of the steady-state simulations of the corresponding rule-based fuzzy cognitive map (RBFCM). Findings Through the use of RBFCMs, the following paper illustrates the possibility of incorporating ethical components into machines, where latent semantic analysis (LSA) and RBFCMs can be used to model dynamic and complex situations, and to provide abilities in acquiring causal knowledge. Research limitations/implications This approach is especially appropriate for data-poor and uncertain situations common in ethics. Nonetheless, to ensure that a machine with an ethical component can function autonomously in the world, research in artificial intelligence will need to further investigate the representation and determination of ethical principles, the incorporation of these ethical principles into a system’s decision procedure, ethical decision-making with incomplete and uncertain knowledge, the explanation for decisions made using ethical principles and the evaluation of systems that act based upon ethical principles. Practical implications To date, the conducted research has contributed to a theoretical foundation for machine ethics through exploration of the rationale and the feasibility of adding an ethical dimension to machines. Further, the constructed AMA illustrates the possibility of utilizing an action-based ethical theory that provides guidance in ethical decision-making according to the precepts of its respective duties. The use of LSA illustrates their powerful capabilities in understanding text and their potential application as information retrieval systems in AMAs. The use of cognitive maps provides an approach and a decision procedure for resolving conflicts between different duties. Originality/value This paper suggests that cognitive maps could be used in AMAs as tools for meta-analysis, where comparisons regarding multiple ethical principles and duties can be examined and considered. With cognitive mapping, complex and abstract variables that cannot easily be measured but are important to decision-making can be modeled. This approach is especially appropriate for data-poor and uncertain situations common in ethics.
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Trinh Dinh, Toan. "A fuzzy-based methodology for anticipating trend of incident traffic congestion on expressways". Transport and Communications Science Journal 73, nr 4 (15.05.2022): 381–96. http://dx.doi.org/10.47869/tcsj.73.4.4.
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Traffic control decisions for incident congestion management on expressways are often made in the face of uncertainty because it entails using many forms of both current and predicted traffic data and incident information to arrive at control decisions under critical-time pressure. For these reasons, an effective traffic control strategy during incidents often relies on techniques that deal efficiently with problems of uncertainty and imprecision. Motivated by this, the author has carried out a research project that develops a multi-stage Fuzzy Logic Controller (MS-FLC) as a tool to support traffic operator’s decision-making at the operational level. The research project aims at establishing a systematic procedure in deriving control actions for ramp control during incidents on expressways following fuzzy-logic approach. For proactive ramp control, the trend of traffic condition on expressways during incidents should be properly anticipated. This paper presents the first two stages of the MS-FLC: (1) evaluation of traffic condition upon incident occurrences, and (2) anticipation of traffic condition during incidents. The results show that the MS-FLC provides a systematic procedure in deriving control actions using fuzzy-based methodology, which possesses excellent capabilities in data-handling and knowledge representation to deliver linguistic expressions that is easy to understand by the operators for making decisions. With both current and anticipated types of information obtained from these two stages, the MS-FLC operates on both reactive and proactive control manners so as to enhance performance of the incident management on expressways.
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Chen, Tser-Yieth, i Chi-Jui Huang. "A Two-Tier Scenario Planning Model of Environmental Sustainability Policy in Taiwan". Sustainability 11, nr 8 (18.04.2019): 2336. http://dx.doi.org/10.3390/su11082336.
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This study proposes a two-tier scenario planning model, consisting of scenario development and policy portfolio planning, to demonstrate the environmental sustainability policy planning process. Scenario development embodies future scenarios that incorporate the uncertainties regarding the decision values and technological alternatives. Policy portfolio planning is used to assess the selected policy alternatives under each scenario and to develop a robust and responsive plan. We organized first- and second-tier committees of 10–12 experts from diverse professional fields to undertake environmental sustainability policy planning in Taiwan. The first-tier committee generated three scenarios: “live at the mercy of the elements”, “industry convergence”, and “technology pilot”. The second-tier committee ensured that, from cradle-to-cradle (C2C), green supply chain management (GSCM), and industry symbiosis (IS), life-cycle type policies enhance green willingness and capabilities in the businesses. This is the first study to consider the first-tier process with scenario development and the second-tier process with policy portfolio planning for environmental sustainability, and contributes by considering intuitive logics approach-based scenarios and robust policies for extant portfolio plans, providing life-cycle- type policy profiles in environmental sustainability.
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Vyas, Sonali, Shaurya Gupta, Deepshikha Bhargava i Rajasekhar Boddu. "Fuzzy Logic System Implementation on the Performance Parameters of Health Data Management Frameworks". Journal of Healthcare Engineering 2022 (12.04.2022): 1–11. http://dx.doi.org/10.1155/2022/9382322.
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The development of wireless sensors and wearable devices has led health care services to the new paramount. The extensive use of sensors, nodes, and devices in health care services generate an enormous amount of health data which is generally unstructured and heterogeneous. Many generous methods and frameworks have been developed for efficient data exchange frameworks, security protocols for data security and privacy. However, very less emphasis has been devoted to structuring and interpreting health data by fuzzy logic systems. The wireless sensors and device performances are affected by the remaining battery/energy, which induces uncertainties, noise, and errors. The classification, noise removal, and accurate interoperation of health data are critical for taking accurate diagnosis and decision making. Fuzzy logic system and algorithms were found to be effective and energy efficient in handling the challenges of raw medical data uncertainties and data management. The integration of fuzzy logic is based on artificial intelligence, neural network, and optimization techniques. The present work entails the review of various works which integrate fuzzy logic systems and algorithms for enhancing the performance of healthcare-related apps and framework in terms of accuracy, precision, training, and testing data capabilities. Future research should concentrate on expanding the adaptability of the reasoning component by incorporating other features into the present cloud architecture and experimenting with various machine learning methodologies.
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Soares, Rogério Barbosa, Samiria Maria Oliveira Silva, Francisco de Assis de Souza, Ticiana Marinho de Carvalho Studart i Renata Locarno Frota. "Groundwater vulnerability to agrochemical contamination". Revista Brasileira de Ciências Ambientais (Online) 55, nr 4 (2020): 440–55. http://dx.doi.org/10.5327/z2176-947820200531.
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This research aimed at evaluating groundwater vulnerability to agrochemical contamination. To that end, we developed an index called Hydric Vulnerability and Agrochemical Contamination Index (HVACI), which integrates a geographic information system and fuzzy logic to measure catchment vulnerability to agrochemical contamination. Our case study investigates two sub-basins, the Baixo Jaguaribe and the Médio Jaguaribe, in the state of Ceará, Brazil. We built a logical relationship matrix involving economic and environmental information as a tool to enhance public managers' decision-making capabilities. Evaluation was based on four categories of vulnerability — high, medium-high, medium-low, and low —, and we found that the joint area of the Baixo Jaguaribe and Médio Jaguaribe sub-basins presented the following levels of risk contamination: 80.3% of the area had low vulnerability, 3.5% had medium-low vulnerability, 3.0% had medium-high vulnerability, and 13.2% had high vulnerability. Geographically, the municipalities with high vulnerability to contamination by pesticides were Aracati, Icapuí, Limoeiro do Norte, Tabuleiro do Norte, and Quixeré. Therefore, HVACI is an important tool for directing environmental management efforts toward areas identified as highly vulnerable to agrochemical contamination.
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Ушков, М. Е., i В. Л. Бурковский. "STRUCTURE OF THE DECISION SUPPORT INFORMATION SYSTEM BY THE NPP OPERATOR". ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, nr 6 (14.01.2022): 8–12. http://dx.doi.org/10.36622/vstu.2021.17.6.001.
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Рассматривается структура системы информационной поддержки процессов принятия решений оператором АЭС в оперативных условиях. Анализируются функциональные возможности системы информационной поддержки оператора (СИПО) на примере Нововоронежской атомной электростанции (НВ АЭС). Данная система дает возможность оператору, управляющему распределенным комплексом технологических объектов АЭС, проводить качественный анализ и обработку больших объемов сложностpуктурированной информации и принимать своевременные адекватные решения в темпе реального времени. Кроме того, рассматривается объект управления и его структура, приводятся рекомендации, направленные на увеличение функциональных возможностей СИПО на базе искусственных нейронных сетей. Одной из многочисленных функций СИПО является прогнозирование состояния объекта управления на основе реализации программно-технологического комплекса модели энергоблока (ПТК МЭ). Однако существующая модель не способна учесть все факторы, влияющие на производственный процесс. Альтернативой здесь выступает искусственная нейронная сеть, которая в процессе обучения может сформировать искомые зависимости между большим числом параметров объекта управления и получить более полный и достоверный прогноз. Предложена структура искусственной нейронной сети на базе нечёткой системы вывода, которая реализует возможности нейронных сетей и нечеткой логики We considered the structure of the information support system for decision-making by the NPP operator in operational conditions. We analyzed the functional capabilities of the operator information support system (SIPO) using the example of the Novovoronezh nuclear power plant (NV NPP). This system provides the operator managing the distributed complex of NPP technological facilities to carry out high-quality analysis and processing of large volumes of complex structured information and make timely adequate decisions in real time. In addition, we considered the control object and its structure and made recommendations aimed at increasing the functionality of the SIPO based on artificial neural networks. One of the many functions of the SIPO is to predict the state of the control object based on the implementation of the software and technological complex of the power unit model. However, the existing model is not able to take into account all the factors influencing the production process. An alternative here is an artificial neural network, which in the learning process can form the required dependencies between a large number of parameters of the control object and get a more complete and reliable forecast. The proposed structure of an artificial neural network based on a fuzzy inference system, which implements the capabilities of neural networks and fuzzy logic
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Mele, Cristina, Maria Colurcio i Tiziana Russo-Spena. "Research traditions of innovation". Managing Service Quality 24, nr 6 (4.11.2014): 612–42. http://dx.doi.org/10.1108/msq-10-2013-0223.
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Purpose – The purpose of this paper is to offer a fresh framing of innovation, as service innovation/value innovation. Design/methodology/approach – By examining the visions, patterns and outcomes of three different research approaches to understanding innovation – goods-dominant (G-D) logic, the resource-based approach and service-dominant (S-D) logic – the authors strive to outline the contribution of each to the debate on innovation. This investigation involves a comprehensive literature review. Scrutiny of a case company provides a means of identifying and illustrating how these approaches play out in a real business context. Findings – A framework for innovation builds on the comparison of the three research approaches. G-D logic, when analysed in terms of new product development and new service development, positions innovation as an output (a new good or service) of a business's internal processes, with the firm as the main actor. The resource-based approach establishes the drivers of innovation as knowledge, capabilities and relationships, but the firm is still the main innovator. S-D logic addresses “open” innovation processes in which all actors in the network can mobilize and integrate their resources to become value co-innovators. Research limitations/implications – This study builds on the literature review by offering a more systematic way of dealing with the different research traditions in innovation debate. Practical implications – This study spurs managers to question the validity of dominant logic and how it affects the decision-making process. The conceptualization of innovation within S-D logic provides new avenues for decision makers and practitioners to tackle topical challenges of global competition. Originality/value – The value of this paper lies in defending the premise that S-D logic is better suited than the other two research traditions to frame current innovation within the context of global competition because it moves innovation beyond mainstream conceptualization: from “products and services” to “service and value”, from “buyer-seller dyads” to “ecosystem relationships”, and from “closed/linear process” to “open/co-created process”.
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Farid, Hafiz Muhammad Athar, Rukhsana Kausar, Muhammad Riaz, Dragan Marinkovic i Miomir Stankovic. "Linear Diophantine Fuzzy Fairly Averaging Operator for Suitable Biomedical Material Selection". Axioms 11, nr 12 (15.12.2022): 735. http://dx.doi.org/10.3390/axioms11120735.
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Nowadays, there is an ever-increasing diversity of materials available, each with its own set of features, capabilities, benefits, and drawbacks. There is no single definitive criteria for selecting the perfect biomedical material; designers and engineers must consider a vast array of distinct biomedical material selection qualities. The goal of this study is to establish fairly operational rules and aggregation operators (AOs) in a linear Diophantine fuzzy context. To achieve this goal, we devised innovative operational principles that make use of the notion of proportional distribution to provide an equitable or fair aggregate for linear Diophantine fuzzy numbers (LDFNs). Furthermore, a multi-criteria decision-making (MCDM) approach is built by combining recommended fairly AOs with evaluations from multiple decision-makers (DMs) and partial weight information under the linear Diophantine fuzzy paradigm. The weights of the criterion are determined using incomplete data with the help of a linear programming model. The enhanced technique might be used in the selection of compounds in a variety of applications, including biomedical programmes where the chemicals used in prostheses must have qualities similar to those of human tissues. The approach presented for the femoral component of the hip joint prosthesis may be used by orthopaedists and practitioners who will choose bio-materials. This is due to the fact that biomedical materials are employed in many sections of the human body for various functions.
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Seletkov, Ilya. "APPLICATION OF MATRIX APPROACH OF FUZZY LOGIC FOR DECISION SUPPORT IN OIL MINING EQUIPMENT SERVICE". Applied Mathematics and Control Sciences, nr 4 (15.12.2020): 65–88. http://dx.doi.org/10.15593/2499-9873/2020.4.05.
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The work solves the problem of building an intelligent decision support system for servicing oil production equipment. At the first stage – the choice of an intelligent model – it is shown that in the existing conditions it is difficult to obtain a training sample in digital form. On the other hand, there is an opportunity to gain knowledge of subject matter experts – masters and technologists – in the form of a set of linguistic rules. Based on this, a conclusion about the effectiveness of the use of fuzzy logic to solve this problem is made. At the stage of constructing an intelligent model, the use of the matrix approach of fuzzy logic is proposed. To elaborate this approach an algorithm of fuzzy inference based on vector fuzzy predicates is developed. Capabilities and advantages of new algorithm are demonstrated. In particular, it is shown that the matrix representation makes possible reducing computations to solving a system of linear equations. Matrix inference also allows to explicitly determine the range of values of the analyzed parameters at which the knowledge base does not allow making a clear conclusion. A model of a fuzzy logic machine in the form of a fuzzy combinational circuit that analyzes an external memory block is proposed for the analysis of retrospective information on the change in the values of the parameters of technological equipment over time. Specific cases allowing the transition from a state machine to a combinational circuit are shown. Article also shows how this can be done. The main advantage of this approach is the absence of the need to use the difficult to formalize concept of a fuzzy state, which leads to a simplified construction of fuzzy logical devices with memory. At the end work contains brief conclusions about the application of the proposed methods and algorithms for building, testing, implementing a decision support system and about its effectiveness.
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Moselhi, Osama, Tarek Hegazy i Paul Fazio. "Potential applications of neural networks in construction". Canadian Journal of Civil Engineering 19, nr 3 (1.06.1992): 521–29. http://dx.doi.org/10.1139/l92-061.
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During the past decade, several engineering disciplines, including construction, have embarked on developing “intelligent” decision support systems based on artificial intelligence (AI) techniques, including expert systems, symbolic knowledge representation, and logic programming. These systems attempt to capture the domain experts' intelligent behaviour and reasoning process utilized in decision-making, without regard to the underlying mechanisms producing that behaviour. This approach involves describing behaviours, usually with rules and symbols. In contrast, neural networks (NN), another AI-based technique that has been pursued on a large scale during the past few years, does not describe behaviours but rather imitate them. Neural networks are particularly superior to traditional expert systems in providing timely solutions based primarily on analogy with previous experience, rather than reasoning or computation. As such, neural networks have a great potential to work either as a supplement or as a complement to algorithmic and (or) other AI-based systems, providing more suitable tools for solving the industry ill-structured problems.This paper describes several characteristics of neural networks and outlines the advantages and limitations of commonly used NN paradigms. Potential applications of each paradigm in construction are identified. Two example applications are provided to demonstrate the problem-solving capabilities of neural networks: (i) estimation of hourly production rate of an excavation equipment; and (ii) estimation of productivity level for a construction trade. Future possibilities of integrating neural networks with other problem-solving techniques are described. Key words: construction, management techniques, neural networks, expert systems, pattern recognition, computer applications.
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Veltri, Stefania, Andrea Venturelli i Giovanni Mastroleo. "Measuring intellectual capital in a firm belonging to a strategic alliance". Journal of Intellectual Capital 16, nr 1 (12.01.2015): 174–98. http://dx.doi.org/10.1108/jic-06-2014-0069.
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Purpose – The purpose of this paper is to propose a method to measure intellectual capital (IC) in firms involved in strategic alliances, an area that has received scant attention in the literature, as existing research is focused mainly on organizational level mainly and increasingly on macro-level unit such as regions or nations. There are very few works at the meso-level (i.e. alliances, clusters), and the paper aims to fill this void, by providing researchers and practitioners with a tool capable of combining measurement and management aims, developed at organizational level with the active participation of the researchers. Design/methodology/approach – The method of analysis is based on a model formalized through a fuzzy expert system (FES). The FES are able to merge the capabilities of an expert system to simulate the decision-making process with the vagueness typical of human reasoning, maintaining the ability to still have a numeric value as a response. Its construction requires the participation of experts, whose knowledge of the problem is accumulated in the form of blocks of rules. These features make it possible to formalize the decision-making process related to the IC valuation, handling qualitative and quantitative variables, and exploring the cognitive mechanisms underlying this process. Findings – The outcome of the application is a system designed to measure the intangible performance deriving from participation in a strategic alliance using FES. This study contributes to the broadening of the research community’s understanding regarding the alternative measurement of IC created within strategic alliances. Research limitations/implications – To the best of the authors’ knowledge, IC literature lacks methods expressly designed to measure the incremental value of IC originating from collaboration among firms. From a measurement perspective, the results may be regarded as valuable proof that IC performance within strategic alliances can be measured quantitatively. Practical implications – On the management side, the possibility of retracing the determinants of different IC intermediate indicators composing the final IC index allows strategic alliances managers to use this information for decision-making purposes. Originality/value – To the best of the authors’ knowledge this is the first study applying FES to measure IC in a firm belonging to a strategic alliance. In the authors’ opinion, fuzzy logic methodology, recently applied in empirical work designed to evaluate IC, represents a reliable methodology because of the “fuzzy” nature of IC.
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Ugulava, Gocha. "REVIEW OF THEORETICAL APPROACHES TO USING OF ARTIFICIAL INTELLIGENCE FOR PLANNING PROBLEMS IN ECONOMICS". Economic Profile 16, nr 2(22) (15.01.2022): 107–22. http://dx.doi.org/10.52244/ep.2021.22.11.
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Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operate with big data, non-linear, exponentially growing, critically overloaded data scenarios. In these conditions, the need to introduce artificial intelligence technologies is due to the exhaustion of the intellectual and analytical capabilities of a person. The article discusses a variety of methods and approaches of artificial intelligence, examines the content of key algorithms, models and theories, their strengths and weaknesses in such important areas of the economy as planning and decision-making. The focus is on their classification. Due to the dependence of the planning process on environmental factors, both classical and non-classical planning environments are discussed. If the environment is fully observable, deterministic and static (external changes are ignored) and discrete in terms of time and action, then we are dealing with a classical planning environment. In the case of a partially observable or stochastic environment, we get a non-classical planning environment. The simplest and most intuitive approach to the planning process algorithms is a Total Order Planning. A scheduling algorithm with parallel execution of actions or without specifying the sequence of their execution is a Partial Order Planning algorithm. Recent research into the development of efficient algorithms has sparked interest in one of the earliest planning approaches – Prepositional Logic Planning. With the Critical Path Method, a schedule of activities is drawn up as part of a plan with zero critical travel time margin for each activity, taking into account the calculation of the time margin for each activity and sequence of activities. A forward-looking planning method for solving complex problems is a hierarchical decomposition based on a Hierarchical Task Networks. The influence of time and resource factors on planning procedures is separately highlighted. Approaches and methods used in a non-classical planning environment: compatible planning, conditional planning, continuous planning, multi-agent planning. Special attention is paid to the issues of constructing planning models in conditions of uncertainty based on the theoretical-probabilistic (stochastic) approaches. Bayesian networks are used to represent vagueness. The Relational Probability Model includes certain constraints on the presentation means, thereby guaranteeing a fully defined probability distributions. The main tasks of probabilistic representation in temporal models are: filtering, forecasting, smoothing, determining a probabilistic explanation. By combining these algorithms and additional enhancements, three large blocks of temporal models can be obtained: Hidden Markov Models, Kalman Filter, and Dynamic Bayesian Network. Decision theory allows the agent to determine the sequence of actions to be performed. A simpler formal system for solving decision-making problems is decision-making networks. The use of expert systems containing information about utility creates additional opportunities. Sequential multiple decision problems in an uncertain environment, such as Markov Decision Processes, are defined using transition models. When several agents interact simultaneously, game theory is used to describe the rational behavior of agents. As we can see, planning has recently become one of the most interesting and relevant directions in the field of artificial intelligence research. There is still a long way to go: it is necessary to develop a clear vision of the problem of choosing the appropriate specific methods depending on the type of task, perhaps by creating completely new methods and approaches.
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Muhammad, Khan, Mohammad S. Obaidat, Tanveer Hussain, Javier Del Ser, Neeraj Kumar, Mohammad Tanveer i Faiyaz Doctor. "Fuzzy Logic in Surveillance Big Video Data Analysis". ACM Computing Surveys 54, nr 3 (czerwiec 2021): 1–33. http://dx.doi.org/10.1145/3444693.
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CCTV cameras installed for continuous surveillance generate enormous amounts of data daily, forging the term Big Video Data (BVD). The active practice of BVD includes intelligent surveillance and activity recognition, among other challenging tasks. To efficiently address these tasks, the computer vision research community has provided monitoring systems, activity recognition methods, and many other computationally complex solutions for the purposeful usage of BVD. Unfortunately, the limited capabilities of these methods, higher computational complexity, and stringent installation requirements hinder their practical implementation in real-world scenarios, which still demand human operators sitting in front of cameras to monitor activities or make actionable decisions based on BVD. The usage of human-like logic, known as fuzzy logic, has been employed emerging for various data science applications such as control systems, image processing, decision making, routing, and advanced safety-critical systems. This is due to its ability to handle various sources of real-world domain and data uncertainties, generating easily adaptable and explainable data-based models. Fuzzy logic can be effectively used for surveillance as a complementary for huge-sized artificial intelligence models and tiresome training procedures. In this article, we draw researchers’ attention toward the usage of fuzzy logic for surveillance in the context of BVD. We carry out a comprehensive literature survey of methods for vision sensory data analytics that resort to fuzzy logic concepts. Our overview highlights the advantages, downsides, and challenges in existing video analysis methods based on fuzzy logic for surveillance applications. We enumerate and discuss the datasets used by these methods, and finally provide an outlook toward future research directions derived from our critical assessment of the efforts invested so far in this exciting field.
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Indriyanti, Prastika, Muhamad Fazalika Hismawan i Mujiono Mujiono. "Penerapan Decision tree dalam pengambilan keputusan untuk pemain Texas Holdem Poker". Jurnal Ilmiah FIFO 12, nr 2 (5.03.2021): 167. http://dx.doi.org/10.22441//fifo.2020.v12i2.006.
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Abstract Texas holdem poker is a popular poker game. This game is played by millions of people every day, both to find additional income or just for fun. But in fact not everyone who plays poker with these goals gets according to what they have planned. Some people actually experience losses after playing. They unconsciously develop the logic of gambler's fallacy that causes them to play poker without using strategy. This research made a system that can prove the defect of gambler's fallacy and made a tool for playing poker. The processed dataset is a dataset containing information of cards used in poker and their probability of occurrence. The method used in this research are iterative deepening search tree and decision tree. The main results of this research is a tool that can provide insight as a basis for decision making. However, this tool has not been able to prove its capabilities in helping to increase the winning percentage, so that further study is needed. In addition, this study also shows that playing with gambler's fallacy logic only gives 48.13% wins of 6,000 trials. These results proved that using gambler's fallacy logic in playing poker is a mistake.Keywords – Tree, Poker, Probability, Gambler’s Fallacy Abstrak Texas holdem poker merupakan permainan poker yang populer. Permainan ini dimainkan oleh jutaan orang setiap harinya, baik untuk mencari penghasilan tambahan ataupun hanya untuk bersenang-senang. Namun pada kenyataanya tidak semua orang yang bermain poker dengan tujuan tersebut mendapatkan sesuai dengan apa yang mereka rencanakan. Sebagian orang justru mengalami kerugian pasca bermain. Mereka tanpa sadar mengembangkan logika berpikir gambler’s fallacy yang mengakibatkan bermain tanpa strategi. Makalah ini menyajikan hasil studi penerapan pohon keputusan dan pohon pencarian untuk membuktikan kecacatan gambler’s fallacy dan membantu dalam bermain poker. Dataset yang diolah adalah dataset yang berisi informasi kartu-kartu yang dipakai dalam permainan serta probabilitas kemunculannya. Metode yang digunakan pada penelitian ini adalah metode pencarian pada struktur tree dan metode pohon keputusan. Hasil utama dari penelitian ini adalah alat bantu yang mampu memberikan insight sebagai dasar pengambilan keputusan. Namun, alat bantu ini belum bisa dibuktikan kapabilitasnya dalam membantu menaikkan persentase kemenangan sehingga diperlukan studi lanjutan. Selain itu, penelitian ini juga menunjukkan bahwa bermain dengan logika gambler’s fallacy hanya memberikan 48.13% kemenangan dari 6000 percobaan. Hasil tersebut membuktikan bahwa menggunakan logika gambler’s fallacy dalam bermain poker merupakan suatu kesalahan.Kata kunci – Tree, Poker, Probabilitas, Gambler’s Fallacy
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Taneva, Tanya, Nevena Naydenova i Petya Genova. "ECONOMIC RATIONALITY OF AGRICULTURAL ENTREPRENEURS IN BULGARIA". Trakia Journal of Sciences 17, Suppl.1 (2019): 577–85. http://dx.doi.org/10.15547/tjs.2019.s.01.092.
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The article presents the results of an empirical survey among entrepreneurs in the agrarian sector in Bulgaria. In view of the serious problems facing its development, the personal potential for entrepreneurial activity of economic agents is crucial for the future of the industry. Therefore, the problem of the rationality of economic decisions and economic behavior is significantly relevant. The main findings of the empirical study show that entrepreneurs have a high degree of rationality for decisions regarding purposefulness, analysis and decision-making, autonomy of intent for action, clarity, logic and consistency in actions. Less rationality is manifested in the prediction of consequences, the realization of the usefulness of business activity and the capabilities for its implementation, the realism, the consistency and the adaptability to circumstances. Overall, behavioral rationality is higher than the rationality of decisions. Subjective assessments of the economic risk of agrarian sector entrepreneurs are high, so preference is given to lower but secure profits. Educational level seems to be a very important factor for business success, but overall, agribusiness operators find it difficult to assess current market situation. There is satisfaction with profit accrued from their business and persistent intention to continue working with high subjective probabilities for success in future.
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Witherell, Paul, Sundar Krishnamurty, Ian R. Grosse i Jack C. Wileden. "Improved knowledge management through first-order logic in engineering design ontologies". Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24, nr 2 (2.09.2009): 245–57. http://dx.doi.org/10.1017/s0890060409990096.
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AbstractThis paper presents the use of first-order logic to improve upon currently employed engineering design knowledge management techniques. Specifically, this work uses description logic in unison with Horn logic, to not only guide the knowledge acquisition process but also to offer much needed support in decision making during the engineering design process in a distributed environment. The knowledge management methods introduced are highlighted by the ability to identify modeling knowledge inconsistencies through the recognition of model characteristic limitations, such as those imposed by model idealizations. The adopted implementation languages include the Semantic Web Rule Language, which enables Horn-like rules to be applied to an ontological knowledge base and the Semantic Web's native Web Ontology Language. As part of this work, an ontological tool, OPTEAM, was developed to capture key aspects of the design process through a set of design-related ontologies and to serve as an application platform for facilitating the engineering design process. The design, analysis, and optimization of a classical I-beam problem are presented as a test-bed case study to illustrate the capabilities of these ontologies in OPTEAM. A second, more extensive test-bed example based on an industry-supplied medical device design problem is also introduced. Results indicate that well-defined, networked relationships within an ontological knowledge base can ultimately lead to a refined design process, with guidance provided by the identification of infeasible solutions and the introduction of “best-case” alternatives. These case studies also show how the application of first-order logic to engineering design improves the knowledge acquisition, knowledge management, and knowledge validation processes.
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Rommetvedt, Hilmar. "the multiple logics of decision-making". European Political Science 5, nr 2 (24.05.2006): 193–208. http://dx.doi.org/10.1057/palgrave.eps.2210077.
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Meda, Srikanth, i Raveendra Babu Bhogapathi. "An Efficient and Scalable Heart Disease Diagnosis System with Attribute Impact Based Weights and Genetic Correlation Analysis". Revue d'Intelligence Artificielle 35, nr 1 (28.02.2021): 47–53. http://dx.doi.org/10.18280/ria.350105.
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Fuzzy neural network (FNN) is playing a vital role in processing of complex data mining applications like medical diagnosis, speech recognition, text processing, image processing etc. Fuzzy neural networks simulate the human brain functionality with fuzzy logic decision making capabilities, to achieve more accuracy in feature selection process of complex data mining applications. Today cardiovascular diseases become a serious global health issue and approximately more than 31% of all global deaths are happening due to cardiovascular diseases reported by WHO. In order to prevent and control the cardiovascular diseases, an efficient and accurate heart disease diagnosis system (HDDS) has to be designed with the state of the art feature based data classifiers. In recent, some research articles introduced HDDS using popular data mining techniques like FNN, but they are suffering from accuracy in allocation of attribute weights and attribute correlation analysis, pattern recognition, forecasting. To address the problems in designing the HDDS, in this paper, Fuzzy Neural Networks has been used with empowered input layer and hidden layers to achieve the high accuracy and performance, while processing the huge set of medical data records. We designed an Attribute Impact calculation procedure to assign the accurate weight values to the attributes and we proposed a Genetic Correlation Analysis algorithm to do correlation analysis which helps in improving the performance.
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Bin Rodzman, Shaiful Bakhtiar, Nordin Abu Bakar, Yun-Huoy Choo, Syed Ahmad Aljunid, Normaly Kamal Ismail, Nurazzah Abd Rahman i Marshima Mohd Rosli. "I-OnAR: a rule-based machine learning approach for intelligent assessment in an online learning environment". Indonesian Journal of Electrical Engineering and Computer Science 17, nr 2 (1.02.2020): 1021. http://dx.doi.org/10.11591/ijeecs.v17.i2.pp1021-1028.
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Intelligent systems are created to automate decision making process that is similar to human intelligence. Incorporating intelligent component has achieved promising results in many applications, including in education. Intelligence modules in a tutoring system would bring the application and its capability closer to a human's ability to serve its human users and to solve problems. However, the majority of the online learning provided in the literature review especially in Malaysia, normally only provide the lecture notes, assignments and tests and rarely suggest or give feedbacks on what the students should study or do next in order to fully understand the subjects. Hence, the researchers propose an online learning environment called Intelligent Online Assessment and Revision (I-OnAR). It facilitates the learning process at multiple learning phases such as test creation, materials revision, feedback for improvement and performance analysis. These components are incorporated into the tutoring system to assist self-pace learning at anytime and anywhere. The intelligent agent uses a Rule-based Machine Learning method for the adaptive capabilities such as automated test creation and feedbacks for improvement. The system has been tested on a group of students and found to be useful to support learning process. The results have shown that 60% of the subjects’ performance have improved with the help of the system. The students were given feedbacks on the topic they did poorly as well as how to improve their performance. This proves that the Intelligent Online Assessment and revision (I-OnAR) can be a useful tool to help online students intelligently, systematically and efficiently. For the future works, the researchers would like to apply the usage of other techniques such as Fuzzy Logic to strengthen the analysis and decision of the current system.
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Choi, Soki, i Mats Brommels. "Logics of pre‐merger decision‐making processes". Journal of Health Organization and Management 23, nr 2 (22.05.2009): 240–54. http://dx.doi.org/10.1108/14777260910960966.
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Vershinina, Natalia, Rowena Barrett i Peter McHardy. "Logics and rationalisations underpinning entrepreneurial decision-making". Journal of Small Business and Enterprise Development 24, nr 1 (20.02.2017): 158–75. http://dx.doi.org/10.1108/jsbed-06-2016-0092.
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Purpose The purpose of this paper is to explore the logics that expert entrepreneurs use when faced with a critical incident threat. Design/methodology/approach Attempts have been made to define “entrepreneurial logic”. This paper is influenced by Sarasvathy’s work on high-performance entrepreneurs, which finds that when faced with uncertainty entrepreneurs employ unconventional logic, and encompasses later research acknowledging social contexts where entrepreneurs operate. A typology of decision-making logics is developed, taking into account the situation of crisis. Seven expert entrepreneurs who faced crisis and, despite this, are still successfully operating businesses were interviewed. The paper develops a critical incidents methodology. Findings Experienced entrepreneurs were found to tend towards causal logic when “the stakes were high” and the decision may affect the survival of their business. They also weigh up options before acting and tend to seek advice from trusted “others” within their network before or after they have made a decision. A mixture of causal and intuitive logic is evident in decisions dealing with internal business problems. Research limitations/implications The decisions that entrepreneurs make shape and define their business and their ability to recover from crisis. If researchers can develop an understanding of how entrepreneurs make decisions – what information they draw upon, what support systems they use and the logic of their decision-making and rationalisation – then this can be used to help structure support. Originality/value By exploring decision-making through critical incidents we offer an innovative way to understand context-rich, first-hand experiences and behaviours of entrepreneurs around a focal point.
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Syawfi, Idil, i Robby Cahyadi. "Russia’s Failure as a Benign Hegemon: The Domination of Hobbesian Culture in the 2008 Russo-Georgian War". Global: Jurnal Politik Internasional 23, nr 1 (9.07.2021): 51. http://dx.doi.org/10.7454/global.v23i1.522.
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This paper aims to explain the advent of the 2008 Russo-Georgian war. It is an important question to answer due to the historical, cultural, and economic relations between the two states, as well as Russia’s aspiration as a benign hegemon should have prevented the war from happening. The fact that two closely related ex-Soviet states went to war against each other points to a fundamental problem in their relationship that could happen to other states with similar preconditions, such as Ukraine, Azerbaijan, Armenia, Moldova, and more. In order to address this issue, Wendtian Constructivism is used to analyse the social interaction, key events, and the culture of anarchy that led to open warfare. This paper mainly relies on official documents and previous research as the primary sources, using news and media coverage to validate truths and opinions on key events. Based on that, this paper finds that: 1) social interaction between the two states was consistent with the Hobbesian culture of anarchy; 2) Russia’s aspiration as a benign hegemon failed to reproduce itself due to rejection from Georgia and their success in balancing Russia with the U.S., giving Georgia the capabilities to resist Russian narratives; 3) Georgia’s confrontative behaviours led to reciprocal actions from Russia, and; 4) the Georgian offensive on Tskhinvali was the trigger that confirmed the suspicions from both sides, making both countries decision to be based on the logic of enmity.
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Izmailova, O., H. Krasovska i K. Krasovska. "Module for expected losses assessing in the information security risk management system of a construction company". Ways to Improve Construction Efficiency 1, nr 50 (11.11.2022): 81–92. http://dx.doi.org/10.32347/2707-501x.2022.50(1).81-92.
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The article examines the problem of the expected losses effective assessment in a construction company upon materialization of information security threats. One of the ways to partially solve this problem is proposed. It is suggested to improve the capabilities of the respective module of the risk management system, which provides the user with a human-machine toolkit for expert assessment of expected losses. This toolkit consists of several stages. The toolkit considers the most effective evaluation scenario given the existing situational decision-making conditions. In order to ensure the operation of the module, the informational and logical connections between the evaluation stages are also defined and the apparatus for the formation of various evaluation scenarios is designed. In addition, to increase the accuracy of the results and increase the flexibility of the proposed algorithm, the possibility of selecting the evaluation scenario by the user with the appropriate role is provided. Since the paper considers the problem of multi-criteria evaluation, the hierarchy of criteria is formalized, and the weight of their influence on the calculation results is also taken into account. When building a logical-mathematical apparatus, the possibility of realizing various types of threats to various information assets (IA) of the enterprise is also considered. The assessment of the consequences of information security threats can be carried out at different levels: general and distributed, taking into account various indicators such as violations of confidentiality, integrity and availability of information. The methods of direct expert evaluation, analytic hierarchy process (AHP), Delphi, linear convolution of criteria, probabilistic modeling are used in the development of the logico-mathematical apparatus. A qualitative-quantitative scale is used to formalize expert judgments. The necessary roles of experts for effective evaluation have been defined. Summarization of experts' assessments is carried out with control of the adequacy of the degree of logic and dispersion of the opinions of each expert, in accordance with the established requirements for the degree of agreement of the opinions of a group of experts. Competence of the experts is also taken into account during assessment.
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Messick, David M. "Alternative logics for decision making in social settings". Journal of Economic Behavior & Organization 39, nr 1 (maj 1999): 11–28. http://dx.doi.org/10.1016/s0167-2681(99)00023-2.
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Manish Patidar. "ANFIS based data rate prediction for cognitive radio". International Journal of Engineering Research Updates 3, nr 2 (30.11.2022): 075–84. http://dx.doi.org/10.53430/ijeru.2022.3.2.0062.
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Intelligence is needed to keep up with the rapid evolution of wireless communications, especially in terms of managing and allocating the scarce, radio spectrum in the highly varying and disparate modern environments. Cognitive radio (CR) systems promise to handle this situation by utilizing intelligent software packages that enrich their transceiver with radio-awareness, adaptability and capability to learn. Its system participates in a continuous process, “the cognition cycle”, during which it adjusts its operating parameters, observes the results and, eventually takes actions, that is to say, decides to operate in a specific radio configuration (i.e., radio access technology, carrier frequency, modulation type, etc.) expecting to move the radio toward some optimized operational state. In such a process, learning mechanisms utilize information from measurements sensed from the environment, gathered experience and stored knowledge and guide in decision making. This paper evaluates learning schemes that are based on adaptive neuro-fuzzy inference system (ANFIS) for predicting the capabilities (e.g. data rate) that can be achieved by a specific radio configuration in cognitive radio. While CR is an intelligent emergent technology, where learning schemes are needed to assist in its functioning. On the other side, ANFIS based scheme is one of the good learning artificial intelligence method, that combines best features of neural network and fuzzy logic. Here proposed method is able to assist a cognitive radio system to help in selecting the best one radio configuration to operate in. Performance metric like root mean square error (RMSE), prediction accuracy of ANFIS learning has been used as performance index.
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Karas, S. I., S. O. Kolganov, S. B. Kochetkov, E. V. Grakova, M. V. Balakhonova, V. V. Datsyuk, G. K. Nozdrin i in. "Development of computer-based methodology for remote advanced training of medical doctors". Siberian Journal of Clinical and Experimental Medicine 35, nr 4 (25.12.2020): 150–60. http://dx.doi.org/10.29001/2073-8552-2020-35-4-150-160.
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Aim. To formulate the methodology for developing the interactive virtual computer simulations with a rating assessment of trainees’ decisions and the capability of remote access.Material and Methods. The methods of knowledge engineering were used to extract and formalize expert knowledge about the structure, significance, and relevance of clinical diagnostic information. The materials for creating virtual computer simulations were based on texts from the archival medical records, laboratory data, and multimedia results of instrumental methods of study. A three-tier network architecture was applied to provide the capabilities of remote access. It was organizationally represented by three components: a client layer, a business logic layer, and a data layer. Data transfer was provided by the Web protocols while microservices represented the infrastructure.Results. The information was formalized and structured after expert analysis and identification of significant diagnostic and prognostic data. The process included defining the domain model, identifying the aggregates and connections between them, and designing software and user interfaces. Possible solutions for trainees are now presented in the form of interactive reference lists. The artifacts of the user’s work are saved in the storage represented by the module for working with the server file system and the object-relational database management system. Each task module contains static and interactive blocks of information. The purpose of static blocks is to provide trainees with the necessary information for making clinical and diagnostic decisions. The interactive blocks allow selecting one or more solutions from the list. The content and sequence of further information presentation are determined by the trainees’ answers to the questions of an interactive block. Trainees’ decision-making competencies are evaluated using the rating system. The final personal rating is calculated as a multiplication of all coefficients related to the trainees’ decisions. This approach integrates a rating system with the trajectory chosen by the trainee for task completion.Conclusions. The distance learning technologies, developed for clinical disciplines in this study, are quite new and innovative. The repository of virtual computer simulations is under development to improve the methodological support of remote clinical training.
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Smolka, Katrin M., Ingrid Verheul, Katrin Burmeister–Lamp i Pursey P. M. A. R. Heugens. "Get it Together! Synergistic Effects of Causal and Effectual Decision–Making Logics on Venture Performance". Entrepreneurship Theory and Practice 42, nr 4 (13.06.2018): 571–604. http://dx.doi.org/10.1177/1042258718783429.
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Entrepreneurs rely on different decision–making logics when starting new ventures, including causal and effectual reasoning. Extant research suggests that venture performance is positively associated with both causal business planning and effectual action–orientation, but studies have not yet tested the synergistic potential of these two logics. We contribute to the debate on entrepreneurial decision making by exploring the interrelationship between causation and effectuation, detailing their main and interactive effects on venture performance. Using survey data collected on 1,453 entrepreneurs residing in 25 countries, we find that ventures benefit from using these two entrepreneurial logics in tandem.