K.M. Kassak, A. Mohammad Ali, Mitra Tauk and A.M. Abdallah
Many developing countries have at some point in their quest for health reform considered decentralization as a strategy. A search of Lebanese health policy texts revealed a call…
Abstract
Many developing countries have at some point in their quest for health reform considered decentralization as a strategy. A search of Lebanese health policy texts revealed a call for some form of decentralization in the mid eighties through Decree 159. This paper highlights the experience of health centers in Lebanon and discusses the importance of implementing an incremental decentralization of the system by highlighting the importance of ensuring political commitment as well as building the capacity of administrative and clinical staff as prerequisites for the implementation of a fully decentralized system.
K.M. Kassak, A. Mohammad Ali, Mitra Tauk and A.M. Abdallah
Many developing countries have at some point in their quest for health reform considered decentralization as a strategy. A search of Lebanese health policy texts revealed a call…
Abstract
Many developing countries have at some point in their quest for health reform considered decentralization as a strategy. A search of Lebanese health policy texts revealed a call for some form of decentralization in the mid eighties through Decree 159. This paper highlights the experience of health centers in Lebanon and discusses the importance of implementing an incremental decentralization of the system by highlighting the importance of ensuring political commitment as well as building the capacity of administrative and clinical staff as prerequisites for the implementation of a fully decentralized system.
Saeedeh Hazratzadeh and Nima Jafari Navimipour
Expert Cloud as a new class of cloud systems enables its users to request and share the skill, knowledge and expertise of people by employing internet infrastructures and cloud…
Abstract
Purpose
Expert Cloud as a new class of cloud systems enables its users to request and share the skill, knowledge and expertise of people by employing internet infrastructures and cloud concepts. Since offering the most appropriate expertise to the customer is one of the clear objectives in Expert Cloud, colleague recommendation is a necessary part of it. So, the purpose of this paper is to develop a colleague recommender system for the Expert Cloud using features matrices of colleagues.
Design/methodology/approach
The new method is described in two phases. In the first phase, all possible colleagues of the user are found through the filtering mechanism and next features of the user and possible colleagues are calculated and collected in matrices. Six potential features of colleagues including reputation, expertise, trust, agility, cost and field of study were proposed. In the second phase, the final score is calculated for every possible colleague and then top-k colleagues are extracted among users. The survey was conducted using a simulation in MATLAB Software. Data were collected from Expert Cloud website. The method was tested using evaluating metrics such as precision, accuracy, incorrect recommendation and runtime.
Findings
The results of this study indicate that considering more features of colleagues has a positive impact on increasing the precision and accuracy of recommending new colleagues. Also, the proposed method has a better result in reducing incorrect recommendation.
Originality/value
In this paper, the colleague recommendation issue in the Expert Cloud is pointed out and the solution approach is applied into the Expert Cloud website.
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Keywords
Chemmalar Selvi G. and Lakshmi Priya G.G.
In today’s world, the recommender systems are very valuable systems for the online users, as the World Wide Web is loaded with plenty of available information causing the online…
Abstract
Purpose
In today’s world, the recommender systems are very valuable systems for the online users, as the World Wide Web is loaded with plenty of available information causing the online users to spend more time and money. The recommender systems suggest some possible and relevant recommendation to the online users by applying the recommendation filtering techniques to the available source of information. The recommendation filtering techniques take the input data denoted as the matrix representation which is generally very sparse and high dimensional data in nature. Hence, the sparse data matrix is completed by filling the unknown or missing entries by using many matrix completion techniques. One of the most popular techniques used is the matrix factorization (MF) which aims to decompose the sparse data matrix into two new and small dimensional data matrix and whose dot product completes the matrix by filling the logical values. However, the MF technique failed to retain the loss of original information when it tried to decompose the matrix, and the error rate is relatively high which clearly shows the loss of such valuable information.
Design/methodology/approach
To alleviate the problem of data loss and data sparsity, the new algorithm from formal concept analysis (FCA), a mathematical model, is proposed for matrix completion which aims at filling the unknown or missing entries without loss of valuable information to a greater extent. The proposed matrix completion algorithm uses the clustering technique where the users who have commonly rated the items and have not commonly rated the items are captured into two classes. The matrix completion algorithm fills the mean cluster value of the unknown entries which well completes the matrix without actually decomposing the matrix.
Findings
The experiment was conducted on the available public data set, MovieLens, whose result shows the prediction error rate is minimal, and the comparison with the existing algorithms is also studied. Thus, the application of FCA in recommender systems proves minimum or no data loss and improvement in the prediction accuracy of rating score.
Social implications
The proposed matrix completion algorithm using FCA performs good recommendation which will be more useful for today’s online users in making decision with regard to the online purchasing of products.
Originality/value
This paper presents the new technique of matrix completion adopting the vital properties from FCA which is applied in the recommender systems. Hence, the proposed algorithm performs well when compared to other existing algorithms in terms of prediction accuracy.
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Jiaxin Ye, Huixiang Xiong, Jinpeng Guo and Xuan Meng
The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of…
Abstract
Purpose
The purpose of this study is to investigate how book group recommendations can be used as a meaningful way to suggest suitable books to users, given the increasing number of individuals engaging in sharing and discussing books on the web.
Design/methodology/approach
The authors propose reviews fine-grained classification (CFGC) and its related models such as CFGC1 for book group recommendation. These models can categorize reviews successively by function and role. Constructing the BERT-BiLSTM model to classify the reviews by function. The frequency characteristics of the reviews are mined by word frequency analysis, and the relationship between reviews and total book score is mined by correlation analysis. Then, the reviews are classified into three roles: celebrity, general and passerby. Finally, the authors can form user groups, mine group features and combine group features with book fine-grained ratings to make book group recommendations.
Findings
Overall, the best recommendations are made by Synopsis comments, with the accuracy, recall, F-value and Hellinger distance of 52.9%, 60.0%, 56.3% and 0.163, respectively. The F1 index of the recommendations based on the author and the writing comments is improved by 2.5% and 0.4%, respectively, compared to the Synopsis comments.
Originality/value
Previous studies on book recommendation often recommend relevant books for users by mining the similarity between books, so the set of book recommendations recommended to users, especially to groups, always focuses on the few types. The proposed method can effectively ensure the diversity of recommendations by mining users’ tendency to different review attributes of books and recommending books for the groups. In addition, this study also investigates which types of reviews should be used to make book recommendations when targeting groups with specific tendencies.
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Keywords
Youssef Mourdi, Mohamed Sadgal, Hamada El Kabtane and Wafaa Berrada Fathi
Even if MOOCs (massive open online courses) are becoming a trend in distance learning, they suffer from a very high rate of learners’ dropout, and as a result, on average, only 10…
Abstract
Purpose
Even if MOOCs (massive open online courses) are becoming a trend in distance learning, they suffer from a very high rate of learners’ dropout, and as a result, on average, only 10 per cent of enrolled learners manage to obtain their certificates of achievement. This paper aims to give tutors a clearer vision for an effective and personalized intervention as a solution to “retain” each type of learner at risk of dropping out.
Design/methodology/approach
This paper presents a methodology to provide predictions on learners’ behaviors. This work, which uses a Stanford data set, was divided into several phases, namely, a data extraction, an exploratory study and then a multivariate analysis to reduce dimensionality and to extract the most relevant features. The second step was the comparison between five machine learning algorithms. Finally, the authors used the principle of association rules to extract similarities between the behaviors of learners who dropped out from the MOOC.
Findings
The results of this work have given that deep learning ensures the best predictions in terms of accuracy, which is an average of 95.8 per cent, and is comparable to other measures such as precision, AUC, Recall and F1 score.
Originality/value
Many research studies have tried to tackle the MOOC dropout problem by proposing different dropout predictive models. In the same context, comes the present proposal with which the authors have tried to predict not only learners at a risk of dropping out of the MOOCs but also those who will succeed or fail.
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Mahboub Okhdar and Ali Ghaffari
Based on consideration of learner needs for expanding vocabulary and the complexity of educational content, this paper introduces a model aimed at facilitating English vocabulary…
Abstract
Purpose
Based on consideration of learner needs for expanding vocabulary and the complexity of educational content, this paper introduces a model aimed at facilitating English vocabulary learning.
Design/methodology/approach
By measuring a set of effective variables regarding simplicity of English sentences, a ranking algorithm is presented in the proposed model. According to this ranking, the simplest sentence in the recommender system (RS) is selected and recommended to the user. Furthermore, Pearson correlation coefficient was used for checking the degree of correlation among the respective parameters on sentence simplicity. For evaluating the efficiency of the recommended algorithm, a prototype was designed by programming using Embarcadero Delphi XE2.
Findings
The results of the study indicated that the correlation among the parameters of word frequency, sentence length and average dependency distance were 0.723, 0.683 and 0.589, respectively. The computed final score is considered to be more accurate.
Practical implications
The application of RS in language learning and education sheds light on the theoretical validity of system thinking by highlighting its key features: its multidisciplinary nature, complexity, dynamicity and the interdependence and relation of micro and macro levels in a system.
Social implications
The proposed method has significant pedagogical implications; it can be used by second language teachers and learners for checking the degree of complexity/learnability of discourse and text.
Originality/value
This paper proposes an alternate model with a significantly higher speed for computing final sentence score.
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Keywords
K.A. Adebiyi, O.E Charles‐Owaba and M.A. Waheed
Managing a safety programme and ensuring that change is in accordance with suitable performance measures requires continuing improvement in the support of analytical power and…
Abstract
Purpose
Managing a safety programme and ensuring that change is in accordance with suitable performance measures requires continuing improvement in the support of analytical power and empirical information. This paper aims to consider different approaches and modeling efforts on safety performance evaluation.
Design/methodology/approach
Review and synthesis of literature.
Findings
Ten major safety performance evaluation approaches are identified including expectation function, risk assessment, statistical quality control, price deflation, engineering economic factor, system analysis, artificial intelligence, and systems theory. Based on the approaches, quantitative and qualitative models have been proposed. The quantitative models use measuring indicators such as frequency, severity, percentages, relative weight and economic gains/loss of safety programme. However, qualitative models employ hazard analysis and hazard operability.
Research limitations/implications
Several research questions remain to be answered in order to completely improve and optimize the impact of these provisional safety performance measures.
Originality/value
This study offers a set of interesting lessons for academics, industry and safety practitioners by providing guidelines that will assist in ensuring a correct focus to select an appropriate safety performance evaluation model.
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Swathi K.S., Gopalkrishna Barkur and Somu G.
The purpose of this paper is to review the accreditation research in specific to its effect on the performance of healthcare organizations.
Abstract
Purpose
The purpose of this paper is to review the accreditation research in specific to its effect on the performance of healthcare organizations.
Design/methodology/approach
A comprehensive search and analysis of literature on the effect of healthcare accreditation were conducted between June 2017 and May 2018. The study identified 62 empirical research studies that examined the effect of healthcare accreditation programmes. Study particulars such as year of publication, objectives, focus of the study, research settings and key findings were recorded. A content analysis was performed to identify the frequency of the main themes in the literature. Knowledge gaps needing further examination were identified.
Findings
Majority of the accreditation impact studies were carried out in the developed nations (n = 49). The thematic categories, that is the impact on “patient safety and healthcare quality” (n = 26), “healthcare professionals’ views” (n = 28) and “clinical process and outcomes” (n = 17) were addressed more times. Whereas the other two thematic categories “organizational performance” and “consumers’ views or satisfaction,” each was examined less than 10 instances. This review reveals mixed views on effect of healthcare accreditation. The varied quality of studies and the availability of a few studies on consumers’ perception of accreditation effectiveness were the important limiting factors of this review.
Originality/value
The findings are valuable to healthcare managers and hospital administrators in accreditation decisions, whereas findings are of value to researchers and academicians in terms of gaps identified for future research studies pertaining to the impact of healthcare accreditation. Future studies need to consider holistic theoretical frameworks for assessing the effect of accreditation on performance of healthcare organizations to achieve precise results.
Details
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K.A. Adebiyi and O.E. Charles‐Owaba
The manufacturing industry in Nigeria often perceives government safety standards as an attempt to increase production cost. This is due to lack of acceptable template for setting…
Abstract
Purpose
The manufacturing industry in Nigeria often perceives government safety standards as an attempt to increase production cost. This is due to lack of acceptable template for setting an attainable standards and safety programme to the manufacturing industry. It is the goal of this work to develop such a template for an effective and sustainable manufacturing safety programme.
Design/methodology/approach
A total of 30 manufacturing firms were examined and five experienced manufacturing, and three safety engineers interviewed for information on types of SP activities. Review and synthesis of literature was carried out.
Findings
Four types of accidents are identified as fatal, serious, minor and trivial wounds. Accidents causing factors are classified into human factor, deficient maintenance of facilities and environmental factors. The prevention activities were categorized into training, guarding, awareness, incentive, accident investigation and personal protective equipment (PPE).
Practical implications
This study provides baseline information for academics, industry and safety practioners to setting an attainable and effective manufacturing safety programme.
Originality/value
The paper suggests a mathematical approach for developing a manufacturing safety programme.