Khosrow Maleknejad, Saeed Sohrabi and Yasser Rostami
The purpose of this paper, with reference to compression of different images' portions with various qualities, is to obtain a high‐compression coefficient.
Abstract
Purpose
The purpose of this paper, with reference to compression of different images' portions with various qualities, is to obtain a high‐compression coefficient.
Design/methodology/approach
Usually, not all parts of a medical image have equal significance. Also, an image's background can be combined with noise. This method separates a part of the video which is moving from a part that is stationary.
Findings
This process results in the high‐quality compression of medical frames.
Originality/value
Separating parts of a frame using 2D and 3D wavelet transform makes a valuable contribution to biocybernetics.
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Mohammad Zamani, Zahra Sohrabi, Ladan Aghakhani, Kimia Leilami, Saeed Nosratabadi, Zahra Namkhah, Cain Clark, Neda Haghighat, Omid Asbaghi and Fatemeh Fathi
Previous research indicates that vitamin D and omega-3 co-supplementation may benefit overall health, but current evidence regarding its effects on lipid profile remains unclear…
Abstract
Purpose
Previous research indicates that vitamin D and omega-3 co-supplementation may benefit overall health, but current evidence regarding its effects on lipid profile remains unclear. The present systematic review and meta-analysis aimed to examine the effects of vitamin D and omega-3 co-supplementation on lipid profile (total cholesterol [TC], low-density lipoprotein [LDL], triglyceride [TG] and high-density lipoprotein [HDL]) in adults.
Design/methodology/approach
In this systematic review and meta-analysis, relevant studies were obtained by searching the PubMed, Scopus and Web of Science databases (from inception to January 2022). Weighted mean differences and 95% confidence intervals were estimated via a random-effects model. Heterogeneity, sensitivity analysis and publication bias were reported using standard methods.
Findings
Pooled analysis of six randomized controlled trials (RCTs) revealed that vitamin D and omega-3 co-supplementation yielded significant reductions in TG (p = 0.631). A pooled analysis of five trials indicated a significant association between omega-3 and vitamin D treatment and reductions in TC (p = 0.001) and LDL (p = 0.001). Although, pooled analyses of omega-3 and vitamin D did not significantly affect HDL.
Originality/value
The findings suggest that vitamin D and omega-3 co-supplementation lowers TG, TC and LDL in adults. Future, large-scale, RCTs on various populations are needed to elucidate further beneficial effects of vitamin D and omega-3 co-supplementation on lipid profile and establish guidelines for clinical practice.
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Xiaobo Tang, Heshen Zhou and Shixuan Li
Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly…
Abstract
Purpose
Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly cited paper prediction studies consider early citation information, so predicting highly cited papers by publication is challenging. Therefore, the authors propose a method for predicting early highly cited papers based on their own features.
Design/methodology/approach
This research analyzed academic papers published in the Journal of the Association for Computing Machinery (ACM) from 2000 to 2013. Five types of features were extracted: paper features, journal features, author features, reference features and semantic features. Subsequently, the authors applied a deep neural network (DNN), support vector machine (SVM), decision tree (DT) and logistic regression (LGR), and they predicted highly cited papers 1–3 years after publication.
Findings
Experimental results showed that early highly cited academic papers are predictable when they are first published. The authors’ prediction models showed considerable performance. This study further confirmed that the features of references and authors play an important role in predicting early highly cited papers. In addition, the proportion of high-quality journal references has a more significant impact on prediction.
Originality/value
Based on the available information at the time of publication, this study proposed an effective early highly cited paper prediction model. This study facilitates the early discovery and realization of the value of scientific and technological achievements.
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Saeed Baghdadi, Abbas Khamseh and Seyed Hesamedin Madani
The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas…
Abstract
Purpose
The purpose of this paper is to develop a commercialization model based on gaining economic benefits through the transfer of technological capabilities in the oil and gas industry. Since commercialization models are mostly based on the implement of technology to produce and sell new products, this study focuses on developing a specific independent technology commercialization model.
Design/methodology/approach
The method of this research is qualitative based on the grounded theory. For this purpose, general variables with content analysis were extracted by reviewing documents (Literature review) and then for identifying special components, interviewing experts in the Iranian oil and gas industry. Participations were selected using snowball sampling for semistructured interviews.
Findings
The findings of this research were extracted based on grounded theory with data analysis in MAXQDA software. In this research, first, 210 open codes were identified based on qualitative content analysis of relevant documents and results of interviews with experts. Then the classification of open codes was done, and 46 subcategories (variables) were determined in the commercialization model. Finally, 46 subcategories were classified into 10 categories as axial codes in grounded theory as components of the commercialization model.
Research limitations/implications
The results of this research have led to the creation of new practical and theoretical implications. In this research, a new perspective of commercialization with the aim of transferring technology and obtaining its economic benefits for oil and gas industry companies was discussed. Also, based on the practical implications explained in this research, policymakers can use the suggested model to effectively implement independent technology commercialization to acquire economic benefits.
Originality/value
This study is purely original and the outcome of the research conducted by the authors. The research findings are the outcome of in-depth study on technology commercialization in the Iranian oil and gas industry.
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Hossein Sohrabi and Esmatullah Noorzai
The present study aims to develop a risk-supported case-based reasoning (RS-CBR) approach for water-related projects by incorporating various uncertainties and risks in the…
Abstract
Purpose
The present study aims to develop a risk-supported case-based reasoning (RS-CBR) approach for water-related projects by incorporating various uncertainties and risks in the revision step.
Design/methodology/approach
The cases were extracted by studying 68 water-related projects. This research employs earned value management (EVM) factors to consider time and cost features and economic, natural, technical, and project risks to account for uncertainties and supervised learning models to estimate cost overrun. Time-series algorithms were also used to predict construction cost indexes (CCI) and model improvements in future forecasts. Outliers were deleted by the pre-processing process. Next, datasets were split into testing and training sets, and algorithms were implemented. The accuracy of different models was measured with the mean absolute percentage error (MAPE) and the normalized root mean square error (NRSME) criteria.
Findings
The findings show an improvement in the accuracy of predictions using datasets that consider uncertainties, and ensemble algorithms such as Random Forest and AdaBoost had higher accuracy. Also, among the single algorithms, the support vector regressor (SVR) with the sigmoid kernel outperformed the others.
Originality/value
This research is the first attempt to develop a case-based reasoning model based on various risks and uncertainties. The developed model has provided an approving overlap with machine learning models to predict cost overruns. The model has been implemented in collected water-related projects and results have been reported.
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Maryam Sadat Seyedi, Mahmoud Reza Sohrabi, Fereshteh Motiee and Saeid Mortazavinik
The purpose of this paper is to analyze nano zero-valent iron (nZVI)-activated carbon/Nickel (nZVI-AC/Ni) by a novel method. The synthesized adsorbent was used to degrade reactive…
Abstract
Purpose
The purpose of this paper is to analyze nano zero-valent iron (nZVI)-activated carbon/Nickel (nZVI-AC/Ni) by a novel method. The synthesized adsorbent was used to degrade reactive orange 16 (RO 16) azo dye.
Design/methodology/approach
The optimum conditions for the highest removal of RO 16 dye were determined. Characterization of nZVI-AC/Ni was done by scanning electron microscopy, Fourier-transform infrared spectroscopy, X-ray diffraction and energy-dispersive X-ray spectroscopy. The nZVI-AC/Ni were used for the removal of dye RO 16 and the parameters affecting were discussed such as pH, adsorbent dosage, contact time and concentration of dye. To investigate the variables and interaction between them, an analysis of variance test was performed.
Findings
The characterization results show that the synthesis of nZVI-AC/Ni caused no aggregation of nanoparticles. The maximum dye removal efficiency of 99.45% occurred at pH 4, the adsorbent dosage = 0.1 gL-1 and the dye concentration of 10 mgL-1. Among various algorithms of feed-forward backpropagation neural network, Levenberg–Marquardt with mean square error (MSE) = 9.86 × 10–22 in layer = 5 and the number of neurons = 9 was selected as the best algorithm. On the other hand, the MSE of the radial basis function model was 0.2159 indicating the good ability of the model to predict the percentage of dye removal.
Originality/value
There are two main innovations. One is that the novel nZVI-AC/Ni was prepared successfully. The other is that the optimized conditions were obtained for the removal of RO 16 dye from an aqueous solution. Furthermore, to the best of the knowledge, no study has ever investigated the removal of RO 16 by nZVI-AC/Ni produced.
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This study aims to explore the long- and short-run effects of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) for Kuwait. This is the first study that was…
Abstract
Purpose
This study aims to explore the long- and short-run effects of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) for Kuwait. This is the first study that was applied to the case of Kuwait.
Design/methodology/approach
We employed the autoregressive distributed lag (ARDL) model of Pesaran et al. (2001) and the nonlinear autoregressive distributed lag (NARDL) model of Shin et al. (2001) for daily data over the period March 2020 to August 2021.
Findings
The findings first document the existence of a long-run relationship (cointegration). Second, the findings of the ARDL model show a significant positive long-run effect of daily confirmed cases of COVID-19 (Ct) on daily stock returns (Rt) but a significant negative short-run effect. As for the NARDL model, the findings showed that the increase and decrease of daily confirmed cases of COVID-19
Originality/value
To the best of the author’s knowledge, this is the first study that was applied to the case of Kuwait.
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Amir Mohammad Fakoor Saghih and Saeid Nosrati
To perceive the reasons for misusing the internet at work, an activity known as cyberloafing, efforts were made to find a new approach to reduce this negative behavior among…
Abstract
Purpose
To perceive the reasons for misusing the internet at work, an activity known as cyberloafing, efforts were made to find a new approach to reduce this negative behavior among employees. Thus, this study aims to identify the antecedents of job embeddedness (JE) and their effects on cyberloafing among the employees of public universities in eastern Iran.
Design/methodology/approach
To this end, the antecedents of JE were first extracted by reviewing the literature in this regard. In the next step, the opinions of the expert team were taken into account to select five variables. Subsequently, the conceptual model and hypotheses were presented and tested through structural equation modeling. A 57-item questionnaire was then distributed among the employees of eastern Iranian universities, who were selected through random stratified sampling. Finally, the data collected from of 510 questionnaires were analyzed.
Findings
According to the findings, it can be argued that JE with its five antecedents of family support, work support, job flexibility, work practices and task significance is able to significantly reduce cyberloafing. Moreover, the full mediating role of JE was confirmed.
Originality/value
Cyberloafing is a term describing the actions of employees who use their internet access at work for personal purposes pretending to do legitimate work. It has been turned into a serious challenge in developing countries such as Iran. It is, therefore vital to identify its factors and antecedents to diminish the counterproductive behavior in the workplace.
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Adrian J. Cahill and Cormac J. Sreenan
This paper examines the design and evaluation of a TV on Demand (TVoD) system, consisting of a globally accessible storage architecture where all TV content broadcast over a…
Abstract
This paper examines the design and evaluation of a TV on Demand (TVoD) system, consisting of a globally accessible storage architecture where all TV content broadcast over a period of time is made available for streaming. The proposed architecture consists of idle Internet Service Provider (ISP) servers that can be rented and released dynamically as the client load dictates. This paper examines issues of resource management and content placement within this Video Content Distribution Network (VCDN). The existing placement algorithm is computationally expensive and in some cases, infeasible to execute within any reasonable length of time. This work proposes a number of new placement heuristics each of which attempts intelligently to reduce the search space so that only the best proxies are considered for replica placement. An extensive evaluation of these placement algorithms is carried out to identify a good placement algorithm without being computationally expensive.
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Mohsin Abdur Rehman, Saira Hanif Soroya, Zuhair Abbas, Farhan Mirza and Khalid Mahmood
This study aims to debate and highlight the challenges faced by university students regarding e-learning during the global pandemic emergency. Furthermore, it sketches the…
Abstract
Purpose
This study aims to debate and highlight the challenges faced by university students regarding e-learning during the global pandemic emergency. Furthermore, it sketches the solutions of e-learning using a theoretical lens of emergency management theory (EMT). Finally, the study argues a case for improvement in existing e-learning systems to enable higher education systems, particularly in a developing country, to recover the losses and increase education quality.
Design/methodology/approach
A qualitative research design and phenomenology research approach were applied to conduct the current study. A total of 10 in-depth online interviews were recorded from students studying in Pakistan and the UK. Verbatim transcriptions were analysed using the reflexive thematic analysis approach.
Findings
The current study results explained in detail the numerous challenges, including lack of preparedness (students and institutions), low quality of interaction, lack of motivation, lack of class activities and forceful adoption of e-learning. Alternatively, few opportunities also emerged through a set of suggestions such as a comprehensive emergency management plan, introduction of strong student counselling programmes and a strategic plan for quality of online learning content.
Originality/value
This study’s contribution stands out in crucial times of the global pandemic. EMT is applied to understand the different dimensions of preparedness, response, mitigation and recovery from a students’ perspective. Furthermore, considering students as important members of higher education institutions and understanding students’ opinions regarding quality assurance during the global pandemic was imperative.