RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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Biometric Creation of Digital Signatures and Their Application in Blockchain
No full textBlockchain transactions are secured from falsification by appending a digital signature using the PKI (Public key infrastructure). When signing a blockchain transaction, the user must have access to his private key, which must be kept on a hardware or software token. The scientific works analyzed in this paper represent the application of Blockchain technology in payment card system, and in this way the architecture of the system is simplified. The fusion of biometric technology and blockchain technology, which allows a blockchain transaction to be signed without tokens and eliminates the need for a third-party transaction validator, has improved the functionality of current payment card systems. This paper contains three contributions. It is first demonstrated how different biometrically based digital signature models reported in the literature compare, then it is demonstrated how blockchain transactions can be digitally signed using digital signatures made using biometrics, and finally, because biometric digital signature creation methods have not attracted much attention in the scientific public, a detailed comparison of the FIBS (Fuzzy Identity Based Signature) scheme and the Fuzzy signature method was presented as for these two schemes was shown that we can implement them in Blockchain and Payment Card System
Lenses of Lean in Non-repetitive Manufacturing: Systematic Literature Review
No full textHopp & Spearman proposed a construct consisting of four lenses of lean in their attempt to guide research and implementation of lean. Authors claim that their proposition could introduce much needed systematicity into the field. In order to test if the proposed construct is useful for researching and practicing lean in non-repetitive manufacturing, authors propose a systematic literature review of 126 articles published in 72 peer-reviewed international journals. The analysis results show that lenses are addressed with different levels of attention, where Process and Flow lens dominate the literature. The construct covers some important topics for non-repetitive manufacturing, such as the context of waste, waste propagation, variability, buffering, and complexities, deeming it suitable as a foundation for considering lean in non-repetitive manufacturing. On the other hand, the construct has some fallacies which should be recognized, in general, and within the context of non-repetitive manufacturing, such as a strong focus on efficiency, disregard of some important lean topics such as responsiveness, flexibility, strategic aspects of lean, management commitment, people development, and change management
Assessment of ideal smart network strategies for logistics companies using an integrated picture fuzzy LBWA–CoCoSo framework
No full textPurpose: Nowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues. Design/methodology/approach: This study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature. Findings: According to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry. Originality/value: This study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem
Machine learning tuning by diversity oriented firefly metaheuristics for Industry 4.0
No full textThe progress of Industrial Revolution 4.0 has been supported by recent advances in several domains, and one of the main contributors is the Internet of Things. Smart factories and healthcare have both benefited in terms of leveraged quality of service and productivity rate. However, there is always a trade-off and some of the largest concerns include security, intrusion, and failure detection, due to high dependence on the Internet of Things devices. To overcome these and other challenges, artificial intelligence, especially machine learning algorithms, are employed for fault prediction, intrusion detection, computer-aided diagnostics, and so forth. However, efficiency of machine learning models heavily depend on feature selection, predetermined values of hyper-parameters and training to deliver a desired result. This paper proposes a swarm intelligence-based approach to tune the machine learning models. A novel version of the firefly algorithm, that overcomes known deficiencies of original method by employing diversification-based mechanism, has been proposed and applied to both feature selection and hyper-parameter optimization of two machine learning models-XGBoost and extreme learning machine. The proposed approach has been tested on four real-world Industry 4.0 data sets, namely distributed transformer monitoring, elderly fall prediction, BoT-IoT, and UNSW-NB 15. Achieved results have been compared to the results of eight other cutting-edge metaheuristics, that have been implemented and tested under the same conditions. The experimental outcomes strongly indicate that the proposed approach significantly outperformed all other competitor metaheuristics in terms of convergence speed and results' quality measured with standard metrics-accuracy, precision, recall, and f1-score
Optimization-Based Fuzzy Regression in Full Compliance with the Extension Principle
No full textBusiness Analytics - which unites Descriptive, Predictive and Prescriptive Analytics - represents an important component in the framework of Big Data. It aims to transform data into information, enabling improvements in making decisions. Within Big Data, optimization is mostly related to the prescriptive analysis, but in this paper, we present one of its applications to a predictive analysis based on regression in fuzzy environment.The tools offered by a regression analysis can be used either to identify the correlation of a dependency between the observed inputs and outputs; or to provide a convenient approximation to the output data set, thus enabling its simplified manipulation. In this paper we introduce a new approach to predict the outputs of a fuzzy in - fuzzy out system through a fuzzy regression analysis developed in full accordance to the extension principle. Within our approach, a couple of mathematical optimization problems are solve for each desired alpha-level. The optimization models derive the left and right endpoints of the alpha-cut of the predicted fuzzy output, as minimum and maximum of all crisp values that can be obtained as predicted outputs to at least one regression problem with observed crisp data in the alpha-cut ranges of the corresponding fuzzy observed data. Relevant examples from the literature are recalled and used to illustrate the theoretical findings
Integrating TOPSIS and ELECTRE-I methods with cubic m-polar fuzzy sets and its application to the diagnosis of psychiatric disorders
No full textMany real-world decision-making issues frequently involve competing sets of criteria, uncertainty, and inaccurate information. Some of these require the involvement of a group of decision-makers, where it is necessary to reduce the various available individual preferences to a single collective preference. To enhance the effectiveness of multi-criteria decisions, multi-criteria decision-making is a popular decision-making technique that makes the procedure more precise, reasonable, and efficient. The “Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)” and “Elimination and Choice Transforming Reality (ELECTRE)” are prominent ranking methods and widely used in the multi-criteria decision-making to solve complicated decision-making problems. In this study, two m-polar fuzzy set-based ranking methods are proposed by extending the ELECTRE-I and TOPSIS approaches equipped with cubic m-polar fuzzy (CmPF) sets, where the experts provide assessment results on feasible alternatives through a CmPF decision matrix. The first proposed method, CmPF-TOPSIS, focuses on the alternative that is closest to a CmPF positive ideal solution and farthest away from the CmPF negative ideal solution. The Euclidean and normalized Euclidean distances are used to determine the proximity of an alternative to ideal solutions. In contrast, the second developed method is CmPF-ELECTRE-I which uses an outranking directed decision graph to determine the optimal alternative, which entirely depends on the CmPF concordance and discordance sets. Furthermore, a practical case study is carried out in the diagnosis of impulse control disorders to illustrate the feasibility and applicability of the proposed methods. Finally, a comparative analysis is performed to demonstrate the veracity, superiority, and effectiveness of the proposed methods
Detecting trending topics captivating circular economy: a bibliometric-based approach
No full textCircular economy is a modern and innovative business model based on the regenerative utilisation of outputs from one process as inputs to another. Since it has many practical implementations, a few distinguished terms essentially mean the same – sharing resources is novel value creation. This paper aims to examine the trend topics corresponding to a circular economy in scientific production. Supported by the available R Studio Bibliometrix package for bibliometric analysis, the study’s results, based on publications from three different groups of countries, suggest that a few distinguished terms are the most frequently used in all publications observed. Moreover, the study concludes that the three groups' immense difference in scientific contribution is notable
Shared accommodation in Europe: Consumer behaviour analysis
No full textSharing economy is described as an economic model in which individuals and groups share
goods and resources for a defined period for a predefined price. To better understand the mechanisms
of sharing economy business models, it is important not only to observe the platforms which allow the
interactions between individuals offering assets (providers) and individuals in search for goods (users), whereas to explore the behaviour of participants in the sharing economy business model. In our research, we will focus on the behaviour of the users of a particular form of sharing economy, of shared accommodation. Our research explores did and how the behaviour of consumers changed in the last couple of years and there are some differences in the behaviour of consumers based on their income level and residence regarding the usage of shared accommodation
Modeling Blockchain System For Fashion Industry
No full textThe digitalization process affected the process of conducting supply chain management in the fashion industry. Innovative information technologies enabled improved communication between supply chain stakeholders, a more efficient and transparent way of conducting business transactions and protecting intellectual property rights. Blockchain technology has the potential to improve security and trust within fashion industry supply chains, reduce the placing of counterfeit products on the market, and provide customers insight into product authenticity. This paper focuses on the possibilities of using blockchain technologies in the supply chain of the fashion industry. The main goal of the paper is to propose a model of a blockchain system for the fashion industry. The proposed system should provide insight into the supply chain flow in the fashion industry based on using blockchain technology. Furthermore, the proposed model enables tracking all business transactions among stakeholders in the fashion industry in a transparent and immutable way, and for the customers enables insight into the product origin, authenticity and all relevant product data
Application of 3D Modeling in the Fashion Industry
No full textThis paper presents an application of 3D modeling in the fashion industry, with an emphasis on augmented reality. The benefits of 3D modeling and augmented reality in the fashion industry are discussed in detail. The purpose is to show this way of product presentation as the future of the fashion industry. This paper aims to present 3D modeling garment design using the CLO3D software tool. Using software environments for 3D clothing modeling combined with augmented reality creates a new world of digital fashion, where it is possible to wear digital fashion items in the Metaverse, but also to create and sell them as NFTs in markets