bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stable method for solving the Cauchy problem with the use of Chebyshev polynomials
Authors: Joachimiak Magda , Ciałkowski Michał , Frąckowiak Andrzej 
Published: October 2019

Purpose
The purpose of this paper is to present the method for solving the inverse Cauchy-type problem for the Laplace’s equation. Calculations were made for the rectangular domain with the target temperature on three boundaries and, additionally, on one of the boundaries, the heat flux distribution was selected. The purpose of consideration was to determine the distribution of temperature on a section of the boundary of the investigated domain (boundary Γ1) and find proper method for the problem regularization.

Design/methodology/approach
The solution of the direct and the inverse (Cauchy-type) problems for the Laplace’s equation is presented in the paper. The form of the solution is noted as the linear combination of the Chebyshev polynomials. The collocation method in which collocation points had been determined based on the Chebyshev nodes was applied. To solve the Cauchy problem, the minimum of functional describing differences between the target and the calculated values of temperature and the heat flux on a section of the domain’s boundary was sought. Various types of the inverse problem regularization, based on Tikhonov and Tikhonov–Philips regularizations, were analysed. Regularization parameter α was chosen with the use of the Morozov discrepancy principle.

Findings
Calculations were performed for random disturbances to the heat flux density of up to 0.01, 0.02 and 0.05 of the target value. The quality of obtained results was next estimated by means of the norm. Effect of the disturbance to the heat flux density and the type of regularization on the sought temperature distribution on the boundary Γ1 was investigated. Presented methods of regularization are considerably less sensitive to disturbances to measurement data than to Tikhonov regularization.

Practical implications
Discussed in this paper is an example of solution of the Cauchy problem for the Laplace’s equation in the rectangular domain that can be applied for determination of the temperature distribution on the boundary of the heated element where it is impossible to measure temperature or the measurement is subject to a great error, for instance on the inner wall of the boiler. Authors investigated numerical examples for functions with singularities outside the domain, for which values of gradients change significantly within the calculation domain what corresponds to significant changes in temperature on the wall of the boiler during the fuel combustion.

Originality/value
In this paper, a new method for solving the Cauchy problem for the Laplace’s equation is described. To solve this problem, the Chebyshev polynomials and nodes were used. Various types of regularization of this problem were considered.
Inter-professional physician-nurse collaboration in Lebanon
Authors: Ahmadieh Hala , Majzoub Ghali H. , Abou Radi Faraj M. , Abou Baraki Areej H. 
Published: October 2019

PurposeA physician–nurse relationship is a complex, professional and shared-decision-making process, which is an important predictor of high-quality patient care. The purpose of this paper is to explore the attitude of the physician–nurse relationship in Southern Lebanon hospitals.Design/methodology/approachA descriptive institutional cross-sectional study was conducted among different departments of three hospitals in Southern Lebanon using a validated Jefferson Scale of Attitude.FindingsIn sum, 89 physicians and 245 nurses accepted to participate. The nurses’ mean age was 32 and the physicians’ was 44. The mean score was found to be 46 for all participants, with significantly higher scores noted among nurses compared to physicians (48 vs 43, respectively) and higher scores among females compared to males (48 vs 46, respectively). However, the study scored no significant difference in relation to the degrees attained by nurses and the participants’ years of experience. The majority had agreed that the shortage in the nurses’ staff affects proper patient care delivery. One fourth of the physicians disagreed that nurses should be considered as a collaborator and colleague. Therefore, more work is required to improve this collaboration.Research limitations/implicationsThere is a complex relationship normally displayed by physicians and nurses, which cannot be easily interpreted and analyzed. Physicians and nurses may have given socially desirable responses while filling the questionnaire. Even more, this study was conducted in Hospitals in Southern Lebanon, and it would be nice to extend this study to include further hospitals in other regions in Lebanon as well.Practical implicationsNurses had higher scores toward collaboration, with females scoring higher than males. However, overall scores are considered to be lower compared to other countries. Thus, more efforts should be done on improving this communication among nurses and physicians, through promoting inter-professional undergraduate and postgraduate education training toward more effective communication.Social implicationsQuality of patient care would be improved if more work is done on improving the collaboration between physicians and nurses, and this was shown to be required as per study results.Originality/valueThere is a gap in literature assessing this important topic which is the collaboration and attitude of nurses and physicians toward their relationship in Lebanon. It is extremely important that efforts should be taken in order to determine the type of nurse–physician relationship in every local context as this relationship affects quality of patients’ care.
Implementing and analysing FAR and FRR for face and voice recognition (multimodal) using KNN classifier
Authors: D.S. Dinesh Kumar , Rao P.V. 
Published: October 2019

Purpose
The purpose of this paper is to incorporate a multimodal biometric system, which plays a major role in improving the accuracy and reducing FAR and FRR performance metrics. Biometrics plays a major role in several areas including military applications because of robustness of the system. Speech and face data are considered as key elements that are commonly used for multimodal biometric applications, as they are simultaneously acquired from camera and microphone.

Design/methodology/approach
In this proposed work, Viola‒Jones algorithm is used for face detection, and Local Binary Pattern consists of texture operators that perform thresholding operation to extract the features of face. Mel-frequency cepstral coefficients exploit the performances of voice data, and median filter is used for removing noise. KNN classifier is used for fusion of both face and voice. The proposed method produces better results in noisy environment with better accuracy. In this proposed method, from the database, 120 face and voice samples are trained and tested with simulation results using MATLAB tool that improves performance in better recognition and accuracy.

Findings
The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.

Originality/value
The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.
Mentorship and well-being
Authors: Al Makhamreh Maha , Stockley Denise 
Published: October 2019

PurposeThe purpose of this paper is to examine how doctoral students experienced mentorship in their supervision context and how the mentorship they received impacted their well-being.Design/methodology/approachAn interpretive phenomenological methodology was selected to frame the research design. This research approach seeks to study the individual lived experience by exploring, describing and analyzing its meaning.FindingsThe findings revealed three different quality levels of mentorship in this context authentic mentorship, average mentorship and below average/toxic mentorship. Doctoral students who enjoyed authentic mentorship experiences were more motivated and satisfied, students who reported average mentorships needed more attention and time from their supervisors, and students who had below average/toxic mentorships were stressed out and depleted.Research limitations/implicationsA limitation of this study is the lack of generalizability owing to the small sample size typical in qualitative studies. Another limitation is that this research did not include students who quit their programs because of dysfunctional supervision experiences.Practical implicationsStudents and supervisors can use the findings to reflect on their beliefs and practices to evaluate and improve their performances. Also, authentic mentors can benefit from the findings to create a positive culture for all students to receive support. Finally, current supervisory policies can be reviewed in light of this paper’s findings.Social implicationsThe findings show the nature of mentorship in an authoritative context, and how it can be toxic when power is misused.Originality/valueThis study provides new knowledge in relation to the different types of mentorship experiences that exist in doctoral supervision, and how each type can influence students’ well-being differently. Additionally, it reveals that doctoral students can graduate, even in the face of toxic mentorship, but at the expense of their well-being.
Analysing causal relationships between delay factors in construction projects
Authors: Jahangoshai Rezaee Mustafa , Yousefi Samuel , Chakrabortty Ripon K. 
Published: October 2019

PurposeAnalyzing factors of delays in construction projects and determining their impact on project performance is necessary to better manage and control projects. Identification of root factors which may lead to project delay and increased cost is vital at the early or planning stage. Better identification of delay factors at the early stage can help the practitioners to reduce their impacts over the long run. Hence, the purpose of this paper is to propose an intelligent method to analyze causal relationships between delay factors in construction projects. The proposed approach is further validated by a real case study of the construction projects in West Azerbaijan province in Iran.Design/methodology/approachDuring the first phase, the fuzzy cognitive map (FCM) is drawn to indicate the causal relationships between the delay factors and the evaluation factors. For this purpose, the causal relationships between 20 delay factors and four evaluation factors are considered. Afterward, the effect of each factor on management goals is evaluated by using a hybrid learning algorithm. Delay factors are further prioritized by applying fuzzy data envelopment analysis (FDEA). In the second phase, an interpretive structural modeling (ISM) is employed to determine the root causes of delay factors.FindingsResults of the first phase show that “supervision technical weaknesses for overcoming technical and executive workshop problems” and “Inaccurate estimation of workload, required equipment and project completion time” are the most significant delay factors. In contrary, “non-use of new engineering contracts” has the lowest impact on the management goals. Meanwhile, the results of the second phase conclude that factors like “Inaccurate estimation of workload, required equipment and project completion time” “weakness of laws and regulations related to job responsibilities” and “lack of foreseen of fines and encouragements in the contracts” are the most significant root factors of delay in construction projects.Originality/valueThis paper integrates three methods including FCM method, FDEA and ISM. In the first phase, FCM is drawn according to the experts’ opinions and concerning management goals and delay factors. Later, these factors are prioritized according to the results of running the algorithm and using the FDEA model. The second phase, the seven-step in the ISM methodology, is done to identify the root factors. To ensure that the root factors of the delay are at a lower level of hierarchical structure, delay factors are partitioned by drawing the ISM model.
Understanding supply chain analytics capabilities and agility for data-rich environments
Authors: Fosso Wamba Samuel , Akter Shahriar 
Published: October 2019

Purpose
Big data-driven supply chain analytics capability (SCAC) is now emerging as the next frontier of supply chain transformation. Yet, very few studies have been directed to identify its dimensions, subdimensions and model their holistic impact on supply chain agility (SCAG) and firm performance (FPER). Therefore, to fill this gap, the purpose of this paper is to develop and validate a dynamic SCAC model and assess both its direct and indirect impact on FPER using analytics-driven SCAG as a mediator.

Design/methodology/approach
The study draws on the emerging literature on big data, the resource-based view and the dynamic capability theory to develop a multi-dimensional, hierarchical SCAC model. Then, the model is tested using data collected from supply chain analytics professionals, managers and mid-level manager in the USA. The study uses the partial least squares-based structural equation modeling to prove the research model.

Findings
The findings of the study identify supply chain management (i.e. planning, investment, coordination and control), supply chain technology (i.e. connectivity, compatibility and modularity) and supply chain talent (i.e. technology management knowledge, technical knowledge, relational knowledge and business knowledge) as the significant antecedents of a dynamic SCAC model. The study also identifies analytics-driven SCAG as the significant mediator between overall SCAC and FPER. Based on these key findings, the paper discusses their implications for theory, methods and practice. Finally, limitations and future research directions are presented.

Originality/value
The study fills an important gap in supply chain management research by estimating the significance of various dimensions and subdimensions of a dynamic SCAC model and their overall effects on SCAG and FPER.
A new algorithm for detecting communities in social networks based on content and structure information
Authors: Akachar ELyazid , Ouhbi Brahim , Frikh Bouchra 
Published: October 2019

Purpose
The purpose of this paper is to present an algorithm for detecting communities in social networks.

Design/methodology/approach
The majority of existing methods of community detection in social networks are based on structural information, and they neglect the content information. In this paper, the authors propose a novel approach that combines the content and structure information to discover more meaningful communities in social networks. To integrate the content information in the process of community detection, the authors propose to exploit the texts involved in social networks to identify the users’ topics of interest. These topics are detected based on the statistical and semantic measures, which allow us to divide the users into different groups so that each group represents a distinct topic. Then, the authors perform links analysis in each group to discover the users who are highly interconnected (communities).

Findings
To validate the performance of the approach, the authors carried out a set of experiments on four real life data sets, and they compared their method with classical methods that ignore the content information.

Originality/value
The experimental results demonstrate that the quality of community structure is improved when we take into account the content and structure information during the procedure of community detection.
An eco-friendly closed loop supply chain network with multi-facility allocated centralized depots for bidirectional flow in a battery manufacturing industry
Authors: Sherif S. Umar , Sasikumar P. , Asokan P. , Jerald J. 
Published: October 2019

Purpose
Due to the economic benefits and environmental awareness, most of the battery manufacturing industries in India are interested to redesign their existing supply chain network or to incorporate the effective closed loop supply chain network (CLSCN). The purpose of this paper is to develop CLSCN model with eco-friendly distribution network and also enhance recycling to utilize recycled lead for new battery production. The existing CLSCN model of a battery manufacturing industry considered for case study is customized for attaining economic benefit and environmental safety. Hence, single objective, multi-echelon, multi-period and multi-product CLSCN model with centralized depots (CD) is developed in this work to maximize the profit and reduce the emission of CO2 in transportation.

Design/methodology/approach
The proposed CD has the facility to store new batteries (NB), scrap batteries (SB) and lead ingot. The objective of the proposed research work is to identify potential location of CD using K-means clustering algorithm, to allocate facilities with CD using multi-facility allocation (MFA) algorithm and to minimize overall travel distance by allowing bidirectional flow of materials and products between facilities. The proposed eco-friendly CLSCN-CD model is solved using GAMS 23.5 for optimal solutions.

Findings
The performance of the proposed model is validated by comparing with existing model. The evaluation reveals that the proposed model is better than the existing model. The sensitivity analysis is demonstrated with different rate of return of SB, different proportion of recycled lead and different type of vehicles, which will help the management to take appropriate decision in the context of cost savings.

Originality/value
This research work has proposed single objective, multi echelon, multi period and multi product CLSCN-CD model in the battery manufacturing industry to maximize the profit and reduce the CO2 emission in transportation, by enhancing the bidirectional flow of materials/products between facilities of entire model.
Improving consumers’ eating habits: what if a brand could make a difference?
Authors: Guèvremont Amélie 
Published: October 2019

PurposeThis research sheds light on behavioral change by demonstrating the transformative power of a brand on the process of eating behavioral change. The selected brand isThree Times a Day(a culinary blog whose mission is to encourage a healthier diet). This study aims to identify food-related behavioral changes as a result of consumers’ relationship with this brand and identify antecedents to such changes.Design/methodology/approachA netnography of the brand online community and 14 individual in-depth interviews were conducted.FindingsNetnography results identify four categories of behavioral changes emerging from the relationship with the brand (e.g. choosing healthier/more varied foods, developing an interest in cooking and adopting a healthier lifestyle). Analysis of the individual interviews substantiate the role of brand attachment as a driver of positive change and identify three antecedents: brand-self connection (through past, actual and ideal self), brand exposure and satisfaction of individual needs (i.e. autonomy, competence and relatedness).Research limitations/implicationsResults enrich the literature on behavioral change and highlight the positive role of a brand in the context of improving eating habits. Findings extend the understanding of the consequences of attachment beyond its influence at the attitudinal level by focusing on concrete consumer behavior.Social implicationsIt is recognized that despite good intentions, individuals keep making poor food choices. This important issue is associated with several diseases and increasing social costs. This research explores how to influence consumers in adopting better eating habits.Originality/valueThis study is one of the first to examine the power of a food-related brand to enhance positive eating practices and improve diet.
Changing clinicians’ perceptions of the role that risk formulation and the HCR-20v3 play in the assessment and management of violence
Authors: Covernton Emma Elizabeth , Moores Amy , Lowenstein Joseph Aaron 
Published: October 2019

Purpose
The assessment and management of risk towards others is an integral part of clinical practice, particularly in forensic and other psychiatric settings. Version 3 of the HCR-20 is the latest version of a comprehensive set of professional guidelines based on the Structured Professional Judgement model. It is the most widely used and best validated tool available to assess risk of violence; however, clinicians perceive it as an additional task with limited clinical usefulness, which requires undergoing expensive training and takes considerable time to implement. The paper aims to discuss these issues.

Design/methodology/approach
Training was delivered to 148 clinicians to improve perceptions with regard to risk formulation and the HCR-20v3 as an effective and clinically useful tool in generating individual and robust care plans to minimise risk of violence.

Findings
Results indicated significant score increase post-training, indicating higher regard for the HCR-20 in terms of its usefulness, anticipated impact upon working, anticipated impact upon managing risk, ease of completion and perceived relevance to clinical practice. This was also consistent with qualitative feedback indicating improved risk management and care planning with reference to how learning would support respective roles. Feedback also highlighted the added value of certain aspects of the training provided, which may be useful to consider when designing HCR-20 training packages.

Research limitations/implications
This study demonstrates the importance of engaging clinicians in bespoke training on the practicalities of HCR-20 completion and the fundamentals of risk formulation.

Practical implications
This study highlights the importance of incorporating a training package for staff of all disciplines in changing perceptions of risk management tools and thus their use in the practical management of violence. The useful aspects of training may assist changing perceptions of the role that risk formulation and the HCR-20v3 play in the assessment and management of violence.

Originality/value
This research suggests that if this can be done successfully, it may lead to a change in the perception of the role that the HCR-20v3 can play in assessing risk of violence and generating meaningful management plans to reduce the future likelihood of violence.