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1 – 10 of over 23000Xiaoshuang Ma, Xixiang Liu, Chen-Long Li and Shuangliang Che
This paper aims to present a multi-source information fusion algorithm based on factor graph for autonomous underwater vehicles (AUVs) navigation and positioning to address the…
Abstract
Purpose
This paper aims to present a multi-source information fusion algorithm based on factor graph for autonomous underwater vehicles (AUVs) navigation and positioning to address the asynchronous and heterogeneous problem of multiple sensors.
Design/methodology/approach
The factor graph is formulated by joint probability distribution function (pdf) random variables. All available measurements are processed into an optimal navigation solution by the message passing algorithm in the factor graph model. To further aid high-rate navigation solutions, the equivalent inertial measurement unit (IMU) factor is introduced to replace several consecutive IMU measurements in the factor graph model.
Findings
The proposed factor graph was demonstrated both in a simulated and vehicle environment using IMU, Doppler Velocity Log, terrain-aided navigation, magnetic compass pilot and depth meter sensors. Simulation results showed that the proposed factor graph processes all available measurements into the considerably improved navigation performance, computational efficiency and complexity compared with the un-simplified factor graph and the federal Kalman filtering methods. Semi-physical experiment results also verified the robustness and effectiveness.
Originality/value
The proposed factor graph scheme supported a plug and play capability to easily fuse asynchronous heterogeneous measurements information in AUV navigation systems.
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Florina Livia Covaci and Pascale Zaraté
This paper aims to overcome some of the limitations of previous works regarding automated supply chain formation (SCF). Hence, it proposes an algorithm for automated SCF using…
Abstract
Purpose
This paper aims to overcome some of the limitations of previous works regarding automated supply chain formation (SCF). Hence, it proposes an algorithm for automated SCF using multiple contract parameters. Moreover, it proposes a decision-making mechanism that provides means for incorporating risk in the decision-making process. To better emphasize the features of the proposed decision-making mechanism, the paper provides some insights from the petroleum industry. This industry has a strategic position, as it is the base for other essential activities of the economy of any country. The petroleum industry is faced with volatile feed-stock costs, cyclical product prices and seasonal final products demand.
Design/methodology/approach
The authors have modeled the supply chain in terms of a cluster graph where the nodes are represented by clusters over the contract parameters that suppliers/consumers are interested in. The suppliers/consumers own utility functions and agree on multiple contract parameters by message exchange, directly with other participant agents, representing their potential buyer or seller. The agreed values of the negotiated issues are reflected in a contract which has a certain utility value for every agent. They consider uncertainties in crude oil prices and demand in petrochemical products and model the decision mechanism for a refinery by using an influence diagram.
Findings
By integrating the automated SCF algorithm and a mechanism for decision support under uncertainty, the authors propose a reliable and practical decision-making model with a practical application not only in the petroleum industry but also in any other complex industry involving a multi-tier supply chain.
Research limitations/implications
The limitation of this approach reveals in situations where the parameters can take values over continuous domains. In these cases, storing the preferences for every agent might need a considerable amount of memory depending on the size of the continuous domain; hence, the proposed approach might encounter efficiency issues.
Practical implications
The current paper makes a step forward to the implementation of digital supply chains in the context of Industry 4.0. The proposed algorithm and decision-making mechanism become powerful tools that will enable machines to make autonomous decisions in the digital supply chain of the future.
Originality/value
The current work proposes a decentralized mechanism for automated SCF. As opposed to the previous decentralized approaches, this approach translates the SCF optimization problem not as a profit maximization problem but as a utility maximization. Hence, it incorporates multiple parameters and uses utility functions to find the optimal supply chain. The current approach is closer to real life scenarios than the previous approaches that were using only cost as a mean for pairwise agents because it uses utility functions for entities in the supply chain to make decision. Moreover, this approach overcomes the limitations of previous approaches by providing means to incorporate risk in the decision-making mechanism.
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Riddhi Rajendra Thavi, Vaibhav S. Narwane, Rujuta Hemal Jhaveri and Rakesh D. Raut
The paper focuses on reviewing and theorizing the factors that affect the adoption of cloud computing in the education sector narrowing the focus to developing countries such as…
Abstract
Purpose
The paper focuses on reviewing and theorizing the factors that affect the adoption of cloud computing in the education sector narrowing the focus to developing countries such as India.
Design/methodology/approach
Through an extensive literature survey, critical factors of cloud computing for education were identified. Further, the fuzzy DEMATEL approach was used to define their interrelationship and its cause and effect.
Findings
A total of 17 factors were identified for the study based on the literature survey and experts' input. These factors were classified as causes and effects and ranked and interrelated. “Required Learning Skills and Attitude,” “Lack of Infrastructure,” “Learners' Ability” and “Increased Investment” are found to be the most influential factors.
Practical implications
The resultant ranking factors can be used as a basis for managing the process of cloud adoption in several institutions. The study could guide academicians, policymakers and government authorities for the effective adoption of cloud computing in education.
Originality/value
The study investigates interdependency amongst the factors of cloud computing for education in context with developing economy. This is one of first study in higher education institutes of India.
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Daifeng Li, Andrew Madden, Chaochun Liu, Ying Ding, Liwei Qian and Enguo Zhou
Internet technology allows millions of people to find high quality medical resources online, with the result that personal healthcare and medical services have become one of the…
Abstract
Purpose
Internet technology allows millions of people to find high quality medical resources online, with the result that personal healthcare and medical services have become one of the fastest growing markets in China. Data relating to healthcare search behavior may provide insights that could lead to better provision of healthcare services. However, discrepancies often arise between terminologies derived from professional medical domain knowledge and the more colloquial terms that users adopt when searching for information about ailments. This can make it difficult to match healthcare queries with doctors’ keywords in online medical searches. The paper aims to discuss these issues.
Design/methodology/approach
To help address this problem, the authors propose a transfer learning using latent factor graph (TLLFG), which can learn the descriptions of ailments used in internet searches and match them to the most appropriate formal medical keywords.
Findings
Experiments show that the TLLFG outperforms competing algorithms in incorporating both medical domain knowledge and patient-doctor Q&A data from online services into a unified latent layer capable of bridging the gap between lay enquiries and professionally expressed information sources, and make more accurate analysis of online users’ symptom descriptions. The authors conclude with a brief discussion of some of the ways in which the model may support online applications and connect offline medical services.
Practical implications
The authors used an online medical searching application to verify the proposed model. The model can bridge users’ long-tailed description with doctors’ formal medical keywords. Online experiments show that TLLFG can significantly improve the searching experience of both users and medical service providers compared with traditional machine learning methods. The research provides a helpful example of the use of domain knowledge to optimize searching or recommendation experiences.
Originality/value
The authors use transfer learning to map online users’ long-tail queries onto medical domain knowledge, significantly improving the relevance of queries and keywords in a search system reliant on sponsored links.
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Neeraj Kumar Goyal, Ravindra Babu Misra and Sanjay Kumar Chaturvedi
This paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.
Abstract
Purpose
This paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.
Design/methodology/approach
The proposed approach breaks a non‐series‐parallel network to obtain its sub‐networks by excluding the source node from rest of the network. The reliabilities of these sub‐networks are thereafter computed by first applying the series‐parallel‐reductions to it and if any sub‐network results into another non‐series‐parallel network then it is solved by the recursive application of SNEM.
Findings
The proposed method has been applied on a variety of network and found to be quite simple, robust, and fast for terminal pair reliability evaluation of large and complex networks.
Practical implications
The proposed approach is quite simple in application and applicable to any general networks, i.e. directed and undirected. The method does not require any prior information such as path (or cut) sets of the network and their pre‐processing thereafter or perform complex tests on networks to match a predefined criterion.
Originality/value
The proposed approach provides an easy to develop and easy to use tool to determine terminal pair reliability of a communication network. The approach is particularly useful for communication network designer and analysts.
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Elaheh Bigdeli, Mohammadreza Motadel, Abbas Toloie Eshlaghy and Reza Radfar
This paper aims to present a dynamic model based on casual relationships among the most important effective factors on business–IT alignment in Agile businesses by using system…
Abstract
Purpose
This paper aims to present a dynamic model based on casual relationships among the most important effective factors on business–IT alignment in Agile businesses by using system dynamics modeling approach.
Design/methodology/approach
To study the most important factors on agility and alignment, the data were collected by questionnaires filled by 201 experts and were analyzed by SPSS and PLS. Casual relationships among studied factors and efficiency coefficients of each factor were identified by fuzzy DEMATEL technique and analyzed by MATLAB and EXCELL. Finally, the dynamic model was plotted by VENSIM.
Findings
According to the results, only “learning IT capabilities” are the most important casual factor that has the highest influence on the other factors. “Business responding capabilities” take the highest effect from the system, and “business sensing capabilities” are in the next rank.
Practical implications
This study underpins effective IT deployment toward developing efficient IT capabilities to gain greater agility.
Originality/value
The dynamic capabilities view (DCV) has emerged as an influential theoretical and management framework in modern IS and agility researches. In this regard, we propose a conceptualization of dynamic capabilities in the form of an alignment model. Based on the dynamic capabilities, and on the alignment perspectives found in Henderson and Venkatraman’s seminal model, IT alignment is modeled as a process of reconfiguration of the firm’s IT and organizational resources, competencies and capabilities.
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Vera Teresa Foti and Giuseppe Timpanaro
The study aims to demonstrate that farmers' markets can represent a model of environmental, social and governance reference for modern agri-food systems facing the challenge of…
Abstract
Purpose
The study aims to demonstrate that farmers' markets can represent a model of environmental, social and governance reference for modern agri-food systems facing the challenge of post COVID-19 pandemic reconstruction, responding to consumer expectations in terms of health, safety and wholesomeness of agri-food products.
Design/methodology/approach
A sample of consumers was surveyed in farmers' markets and social network analysis (SNA) was adopted as a methodological approach to reconstruct the links between the worlds of production and consumption and to derive the relative importance attributed to various factors that promote relational structures.
Findings
The work demonstrates the importance of sustainability – as a productive and behavioural model of firms – for the construction of efficient and durable relationship systems in two farmer markets in Sicily. In particular, four fundamental components emerge in the construction of networks represented by consumer sensitivity to sustainability processes, the individual behavioural model of purchasing and consumption, the expectation of political direction and the level and factors of knowledge of the firm. The clustering elements of the relationships were found to be the territory and local products, the environmentalist attitude and the protection of resources, as well as the adoption of a rational waste disposal policy, the fight against food waste, the encouragement of healthier and more sustainable consumption styles, clear and transparent communication and the activation of sustainable supply chain processes in line with the Sustainable Development Goals (SDGs).
Originality/value
The paper aims to demonstrate how alternative food systems can become a useful model for large enterprises, which are committed to rebuilding their business strategy to overcome the current crisis.
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Yi Jiang, Ting Wang, Shiliang Shao and Lebing Wang
In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM…
Abstract
Purpose
In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization.
Design/methodology/approach
First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection.
Findings
The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness.
Originality/value
To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.
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Changiz Valmohammadi and Vahid Shahrashoob
Due to the important role of strategic human resources in fulfilling the main objectives of organizations on the one hand and the necessity of having suitable functional…
Abstract
Purpose
Due to the important role of strategic human resources in fulfilling the main objectives of organizations on the one hand and the necessity of having suitable functional strategies in place to operationalize the developmental programs on the other hand, this study aims to identify the factors and sub-factors of developmental programs and their priorities as well as the relationship and interactions of the identified criteria in human capital developmental programs through a hybrid fuzzy decision-making trial and evaluation laboratory –analytic network process approach. Also, the rank of functional strategies to achieve these human resource developmental programs is determined using fuzzy VIsekriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) technique.
Design/methodology/approach
Through an in-depth review of the relevant literature, the most important criteria and sub-criteria were determined. Then, a questionnaire was designed and distributed among 20 top managers and experts of the surveyed bank. Using geometric mean, the criteria were screened. In the next step, the second pairwise questionnaire was designed and distributed among eight experts, to determine the relations and interrelations among these factors their relevant sub-factors and prioritize them. Finally, using the third designed questionnaire and fuzzy, VIKOR (FVIKOR) technique the ranks of functional strategies were determined.
Findings
Analysis of the results showed that “future wellness and retirement” is the most influential factor and the “retention” factor is the most permeable factor. Also, human capital planning is the most important factor of this department’s developmental programs in achieving its strategic objectives. Factors “recruiting and hiring,” “retention,” “empowerment” and “future wellness and retirement” were ranked second to fifth, respectively. Finally, the application of the FVIKOR technique revealed that “enhancement and improvement of incentive systems” is the best functional strategy to achieve the developmental plans of the human capital department.
Research limitations/implications
One of the limitations of this study is the generalizability of the findings, which may be limited by the single case study method used.
Practical implications
This study presents a comprehensive and effective tool which could specifically help policymakers and top managers of the survey company and other managers of the banking sector in general, to use a quantitative approach toward identification and prioritizations of the determinants factors of the human capital developmental programs toward achieving functional strategic objectives to enhance the satisfaction of their internal customer as the most important asset of their organizations which might lead to the increased external customer satisfaction and, subsequently, increased competitive advantage.
Originality/value
To the best knowledge of the authors, this is one the first studies of its kind which attempts through a hybrid fuzzy analytical network process and fuzzy DEMATEL approach, presents a structural network model to examine the interrelationships among the human capital developmental programs and prioritizes them, also simultaneously rank the functional strategies toward achieving these programs using FVIKOR technique.
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Isabel Silva Lopes, Sérgio Dinis Sousa and Eusébio Nunes
The purpose of this paper is to present a methodology to represent the uncertainty generated in performance measures (PMs) during the operational step or “use step” of the…
Abstract
Purpose
The purpose of this paper is to present a methodology to represent the uncertainty generated in performance measures (PMs) during the operational step or “use step” of the performance measurement process (PMP). The different steps of the methodology are described and exemplified through an application example.
Design/methodology/approach
An index that reflects the level of uncertainty originated by the factors and the strength of their inter-relationships is developed through the use of graph theory. A graph is developed considering all sources or factors of uncertainty that may be present in this process. Based on the graph, the methodology includes the use of a matrix and the determination of the associated permanent function which is used for determining the uncertainty index.
Findings
During the development of the methodology, it was found that the use of a scale that includes zero for assigning values of the elements of the matrix is not appropriate when using graph theory and permanent function calculation, since in this case the permanent function is insensible to changes in some matrix elements.
Originality/value
This paper identifies all the sources that can affect the quality of performance measurement values during the operational step of the PMP and proposes a method to characterize the strength of this uncertainty. Beyond alerting decision makers to the level of uncertainty associated with a PM, it also allows defining appropriate actions to improve PMs’ quality.
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