Search results

Expert Cloud as a new class of Cloud systems provides the knowledge and skills of human resources (HRs) as a service using Cloud concepts. Task scheduling in the Expert Cloud is a vital part that assigns tasks to suitable resources for execution. The purpose of this paper is to propose a method based on genetic algorithm to consider the priority of arriving tasks and the heterogeneity of HRs. Also, to simulate a real world situation, the authors consider the human-based features of resources like trust, reputation and etc.

As it is NP-Complete to schedule tasks to obtain the minimum makespan and the success of genetic algorithm in optimization and NP-Complete problems, the authors used a genetic algorithm to schedule the tasks on HRs in the Expert Cloud. In this method, chromosome or candidate solutions are represented by a vector; fitness function is calculated based on several factors; one point cross-over and swap mutation are also used.

The obtained results demonstrated the efficiency of the proposed algorithm in terms of time complexity, task fail rate and HRs utilization.

In this paper the task scheduling issue in the Expert Cloud and improving pervious algorithm are pointed out and the approach to resolve the problem is applied into a practical example.

There is significant evidence of increasing global implementation failures in enterprise resource planning (ERP) projects; and, for this reason, critical success factors (CSF) on implementation success (IS) are of notable concern to manufacturing organizations. This paper aims to focus on these factors and the role they played toward implementation success of ERP projects in India. Furthermore, this paper will also seek to explore whether the implementation success is moderated (i.e. influenced) by the organizational culture. This will help other manufacturing organizations take appropriate decisions about the ERP implementation.

In the proposed model, the authors propose organizational culture as the moderator toward the implementation success of ERP projects in India. A survey methodology is used for the study, and a structured questionnaire was developed to get the information.

Through this study, it has been found that the organizational culture acts as a moderator and moderates the relationship between CSF and implementation success of the ERP projects in India.

This study offers both academicians and practitioners a model to research, assess, and identify the appropriate CSF such as Setting up ERP business goals and objectives (SEB), Cross-Functional Teams (CFT), Business Process Reengineering (BPR), Projects Tracking (PTG), and Data Analysis and Conversion (DAG) on IS of ERP projects in India and moderated by the organizational culture. The research is targeted on manufacturing organizations in India, and hence it has limitations in terms of scope. However, the results are quite encouraging with very good response (n=223) from the manufacturing organizations. Other manufacturing organizations planning to implement ERP soon will be highly benefited from the results of this study.

Unfortunately, few research studies define the issues related to the moderator namely the organizational culture. This paper demonstrates how this moderator played an important role in ERP implementation. The findings will encourage Indian manufacturing organizations to implement ERP when facing challenges of the competitive market for their competitive advantage. For India, this research could be among the first to its nature.

My aims in this chapter are to discuss alternative ways of doing education and research, and thereby highlight key contributions from Paulo Freire, Orlando Fals-Borda and Dorothy Lee, to active learning, participatory action-research and intercultural dialogue. These scholars were heirs of the university reform movements of the twentieth century, and their vital legacy is alive as shown in this book. The enclosed ideas and illustrations of transformative research and education draw from my academic experience in various corners of the world and points in time.

Information sharing enhances the supply chain profitability significantly, but it may result in adverse impacts also (e.g. leakages of secret information to competitors, sharing of wrong information that result into losses). So, it is important to understand the various risk factors that lead to distortion in information sharing and results in negative consequences. Information risk identification and assessment in supply chain would help in choosing right mitigation strategies. The purpose of this paper is to identify various information risks that could impact a supply chain, and develop a conceptual framework to quantify them.

Bayesian belief network (BBN) modeling will be used to provide a framework for information risk analysis in a supply chain. Bayesian methodology provides the reasoning in causal relationship among various risk factors and incorporates both objective and subjective data.

This paper presents a causal relationship among various information risks in a supply chain. Three important risk factors, namely, information security, information leakages and reluctance toward information sharing showed influence on a company’s revenue.

Capability of Bayesian networks while modeling in uncertain conditions, provides a prefect platform for analyzing the risk factors. BBN provides a more robust method for studying the impact or predicting various risk factors.

The major contribution of this paper is to develop a quantitative model for information risks in supply chain. This model can be updated when a new data arrives.

The purpose of this paper is to address a theoretical gap in the business process management (BPM) literature on factors that influence the acceptance and use of business process modelling (PM) in organisations. The paper seeks to contribute to theory building and practice in BPM through better understanding of important determinants of PM adoption and use.

A combination of literature review and 34 interviews in context was used to develop a PM acceptance model that was subsequently empirically tested using survey data from 74 companies.

The paper provides empirical insights about how business PM can be influenced by many factors in the organisational context. It suggests that PM is a complex activity mandated by management, but influenced by individual and socio‐political factors.

There is a need for future research to focus on the many opposing forces that influence business PM in organisations. Future studies should analyse influence from different stakeholder groups separately to reveal their relative influence on PM activity and its outcomes.

The paper identifies important forces in the organisational context that managers should focus on in their efforts to successfully implement business PM in their organisations.

This paper uses a triangulation of sources of information to better understand the less‐studied process of PM adoption and use in an organisational context. It contributes to theory building within BPM and to more successful BPM in organisations.

As of November 2021, six out of the 12 United Nations (UN) peacekeeping operations are in Sub-Saharan Africa, spread between the Democratic Republic of Congo (DRC), Western Sahara, Mali, Central African Republic, Abyei, South Sudan and Darfur. When considered alongside other recent conflicts in Liberia, Angola, Sierra Leone, Côte d’Ivoire and Mozambique, many of these conflicts are driven and sustained by resource looting of oil, minerals, timber, gas and fertile land and sand. Although other factors, particularly colonialism, the creation of poorly governed states, ethnic polarization, greed and extremism contribute to violence, the author argues that resource looting is central. Taking the DRC as the case study, the purpose of this paper is to examine why traditional UN peacekeeping, grounded in the international liberal order, has failed to efficiently deescalate wars and armed conflicts that are driven by resource looting and how alternative homegrown peace strategies can be more effective.

Deploying peacekeeping, peacebuilding and resource governance and theories, this paper examines the current UN peacekeeping efforts to increase our understanding of how alternative peacekeeping strategies found in African cultures, particularly indigenous epistemologies can be used to engender sustainable peace and security. The second argument is that sustainable peace and security cannot be solely exogenous, without integrating African cultural heritage, specifically African indigenous knowledge systems or epistemologies, a factor that is consistent with people’s right to self-determination and agency.

Peacekeeping that is exogenously enforced has failed to create sustainable peace and security in the DRC.

To the best of the author’s knowledge, this paper is original, based on the research conducted in the DRC. Following the academic writing norms, the data is backed up by literature.

The purpose of this paper is to investigate the feasibility of solving turbulent flows based on smoothed finite element method (S-FEM). Then, the differences between S-FEM and finite element method (FEM) in dealing with turbulent flows are compared.

The stabilization scheme, the streamline-upwind/Petrov-Galerkin stabilization is coupled with stabilized pressure gradient projection in the fractional step framework. The Reynolds-averaged Navier-Stokes equations with standard k-epsilon model are selected to solve turbulent flows based on S-FEM and FEM. Standard wall functions are applied to predict boundary layer profiles.

This paper explores a completely new application of S-FEM on turbulent flows. The adopted stabilization scheme presents a good performance on stabilizing the flows, especially for very high Reynolds numbers flows. An advantage of S-FEM is found in applying wall functions comparing with FEM. The differences between S-FEM and FEM have been investigated.

The research in this work is limited to the two-dimensional incompressible turbulent flow.

The verification and validation of a new combination are conducted by several numerical examples. The new combination could be used to deal with more complicated turbulent flows.

The applications of the new combination to study basic and complex turbulent flow are also presented, which demonstrates its potential to solve more turbulent flows in nature and engineering.

This work carries out a great extension of S-FEM in simulations of fluid dynamics. The new combination is verified to be very effective in handling turbulent flows. The performances of S-FEM and FEM on turbulent flows were analyzed by several numerical examples. Superior results were found compared with existing results and experiments. Meanwhile, S-FEM has an advantage of accuracy in predicting boundary layer profile.

The purpose of this paper is to pursue two following main goals: first, theorizing a new concept named as equivalent bus load in order to make a promising simplification over power system analysis. Second, proposing an outstanding fast and simple approach based on introduced concept for voltage estimation after multiple component outages while satisfying required accuracy.

Equivalent load bus theory introduces three transfer matrices that describe power system topology. Mentioned matrices could be calculated simply after system reconfiguration without matrix inversion. Using transfer matrices a large-scale power system can be modeled by a simple two-bus power system from the viewpoint of any desired bus so that load flow calculation leads to same value. The analysis of simplified power system yields to extract a new incremental model based on equivalent bus load theory that will be distinguished as an outstanding fast method for voltage estimation aim.

A deep study for fast voltage estimation aim is dedicated to evaluate proposed method from the accuracy and quickness point of view and the outcomes are compared to a well-known method as Distribution Factors (DF). Results and computational times unveil that presented approach is more accurate and much faster.

A novel and new fast voltage estimation method for assessment of power system component outages is introduced.

The purpose of this paper is to investigate the mechanisms of low alloyed medium-carbon steel (LAMCS) corrosion in 0.5 M H₂SO₄ inhibited by seeds oils of rubber (SOR), Neem (SON) and Jatropha (SOJ) containing varying degree of free fatty acid (FFA).

Specific gravity, acid values and FFA compositions of oils were determined. Potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM) and X-ray diffraction (XRD) are techniques used to investigate the corrosion inhibition mechanisms with evaluated Gibbs free energy of adsorption.

Corrosion inhibition efficiencies of oils reached values >99% as obtained from PDP and EIS. Protective oxide layer was formed on LAMCS consequent on containment of carbonyl and hydroxyl groups in the FFA of SOR, SON and SOJ, respectively. The SOR and SOJ are found to be mixed inhibitors, whereas SON behaved as anodic inhibitor. Mechanism of adsorption of SOR was synergistic between physisorption and chemisorption, while SON and SOJ exhibited physisorption. SEM micrographs images showed that uninhibited sample exhibited thicker mass of corrosion products. Formation of protective oxide layer was confirmed by XRD diffractograms.

This study has shown that the need for modification of vegetable seed oils containing FFA is unnecessary as the hydroxyl and carbonyl groups of the FFA contained in the respective oil were found to be the center of adsorption of the oils on the steel surface. Hence, cost and by-products associated with modification of oils used as corrosion inhibitors are eliminated.

SOR, which has the highest percentage FFA, was found to be the most influential on the corrosion inhibition mechanism of LAMCS, specifically within 0.01–0.02 g/mL concentration. FFA contained in the respective seed oil aided formation of protective oxide layer at interface between H₂SO₄ and LAMCS, relative to amount composed.

The paper aims to propose a novel dual-stage shape memory alloy (SMA) actuated gripper (DAG), of which the grasp performance is improved through primary and secondary actuation.

This paper presents a method of integrating the design of dual-stage actuation modules based on the SMA bias actuation principle to enhance the grasping shape adaptability and force modulation of a DAG. The actuation angle range and grasping performance of the DAG are investigated by thermomechanical analysis and the finite element method based numerical simulation.

The results of present experiments and simulations indicate that the actuation angle scope of the DAG is about 20° under no load, which enables the grasping space occupied by an object in the DAG from 60 mm to 120 mm. The grasping force adjusted by changing the input power of the primary main actuation module and secondary fine-tuning actuation module can reach a maximum of 2 N, which is capable of grasping objects of various sizes, weights, shapes, etc.

The contribution of this paper is to design a DAG based on SMA, and establish the solution methods for the primary main actuation module and secondary fine-tuning actuation module, respectively. It lays a foundation for the research of lightweight and intelligent robotic grippers.