ORCID Profile
0000-0002-5168-2078
Current Organisations
Simcere Pharmaceutical (China)
,
Curtin University
,
Bu Ali Sina University
,
Amirkabir University of Technology
,
University of Technology Sydney
,
UNSW Graduate Research School
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Publisher: Elsevier BV
Date: 03-2011
Publisher: Elsevier BV
Date: 11-2012
Publisher: Elsevier BV
Date: 03-2013
Publisher: Elsevier BV
Date: 07-2011
Publisher: Informa UK Limited
Date: 2019
Publisher: ACM
Date: 23-08-2017
Publisher: Springer International Publishing
Date: 17-08-2017
Publisher: Springer International Publishing
Date: 11-07-2021
Publisher: Inderscience Publishers
Date: 2010
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 12-2022
Publisher: Elsevier BV
Date: 10-2013
Publisher: IEEE
Date: 09-2010
Publisher: Emerald
Date: 05-06-2017
DOI: 10.1108/BPMJ-02-2015-0018
Abstract: Contact centers (CCs) are one of the main touch points of customers in an organization. They form one of the inputs to customer relationship management (CRM) to enable an organization to efficiently resolve customer queries. CCs have an important impact on customer satisfaction and are a strategic asset for CRM systems. The purpose of this paper is to review the current literature on CCs and identify their shortcomings to be addressed in the current digital age. The current literature on CCs can be classified into the analytical and the managerial aspects of CCs. In the former, data mining, text mining, and voice recognition techniques are discussed, and in the latter, staff training, CC performance, and outsourced CCs are discussed. With the growth of information and communication technologies, the information that CCs must handle both in terms of type and volume, has changed. To deal with such changes, CCs need to evolve in terms of their operation and public relations. The authors present a state-of-the-art review of the challenges in identifying the gaps in order to have the next generation of CCs. Lack of an interactive CC and lack of data integrity for CCs are highlighted as important issues that need to be dealt with properly by CCs. As far as the authors know, this is the first paper that reviews CCs’ literature by providing the comprehensive survey, critical evaluation, and future research.
Publisher: Springer Science and Business Media LLC
Date: 14-09-2018
Publisher: Frontiers Media SA
Date: 31-10-2019
Publisher: Springer Science and Business Media LLC
Date: 11-12-2018
Publisher: Elsevier BV
Date: 05-2015
Publisher: Springer Science and Business Media LLC
Date: 06-12-2017
Publisher: Springer Science and Business Media LLC
Date: 12-11-2021
Publisher: IEEE
Date: 2010
Publisher: Elsevier BV
Date: 04-2015
Publisher: Elsevier BV
Date: 03-2011
Publisher: IEEE
Date: 03-2012
Publisher: IEEE
Date: 07-2014
Publisher: IEEE
Date: 18-12-2022
Publisher: Inderscience Publishers
Date: 2009
Publisher: Elsevier BV
Date: 08-2012
Publisher: IEEE
Date: 10-2018
Publisher: Science Alert
Date: 03-2009
Publisher: IEEE
Date: 06-2008
Publisher: IEEE
Date: 06-2008
Publisher: Springer Science and Business Media LLC
Date: 17-06-2021
Publisher: Informa UK Limited
Date: 02-01-2013
Publisher: Springer International Publishing
Date: 2015
Publisher: Elsevier BV
Date: 02-2015
Publisher: Informa UK Limited
Date: 08-11-2017
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Wiley
Date: 07-08-2014
DOI: 10.1002/SRES.2199
Publisher: Springer Science and Business Media LLC
Date: 02-03-2020
Publisher: Springer Science and Business Media LLC
Date: 28-11-2019
Publisher: IEEE
Date: 10-2018
Publisher: Springer Science and Business Media LLC
Date: 15-09-2022
Publisher: Emerald
Date: 10-08-2023
DOI: 10.1108/JEIM-03-2021-0143
Abstract: The purpose of this paper is to develop an effective approach to support and guide production improvement processes utilising online product reviews. This paper combines two methods: (1) natural language processing (NLP) to support advanced text mining to increase the accuracy of information extracted from product reviews and (2) quality function deployment (QFD) to utilise the extracted information to guide the product improvement process. The paper proposes an approach to automate the process of obtaining voice of the customer (VOC) by performing text mining on available online product reviews while considering key factors such as the time of review and review usefulness. The paper enhances quality management processes in organisations and advances the literature on customer-oriented product improvement processes. Online product reviews are a valuable source of information for companies to capture the true VOC. VOC is then commonly used by companies as the main input for QFD to enhance quality management and product improvement. However, this process requires considerable time, during which VOC may change, which may negatively impact the output of QFD. This paper addresses this challenge by providing an improved approach.
Publisher: SAGE Publications
Date: 10-04-2016
Abstract: In today’s economic environment, performance and efficiency assessment is essential for organizations in order to survive and raise their market share. Energy efficient consumption is a major issue in the energy planning of each country which is a big concern of managers, hence, exploitation of a strong approach for efficiency evaluation and assessment seems necessary in the energy section. In this study, a novel performance assessment model is proposed based on the concept of trust, using two popular fuzzy operators called T-norm and S-norm. The developed model is applied for a real case study of energy consumption efficiency assessment for 36 countries. An adaptive network based fuzzy inference system (ANFIS) is used to measure the efficiencies. Also, to predict efficiency rates of the future time periods, a regression model is applied as a time series model. The obtained results indicate the superiority and applicability of the proposed methodology. To the best of our knowledge, this is the first study that proposes a novel performance measurement approach based on trust context by using fuzzy T-norm and S-norm operators.
Publisher: Springer International Publishing
Date: 28-11-2019
Publisher: Elsevier BV
Date: 04-2009
Publisher: Springer Science and Business Media LLC
Date: 14-09-2011
Publisher: Elsevier BV
Date: 06-2010
Publisher: IEEE
Date: 06-2014
Publisher: IEEE
Date: 02-2014
Publisher: IEEE
Date: 06-2009
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 05-2019
Publisher: IEEE
Date: 09-2016
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 11-05-2017
Publisher: Springer International Publishing
Date: 2022
Publisher: Springer International Publishing
Date: 2018
Publisher: CRC Press
Date: 24-06-2010
Publisher: Elsevier BV
Date: 06-2019
Publisher: Elsevier BV
Date: 10-2009
Publisher: Elsevier BV
Date: 03-2021
Publisher: Springer Science and Business Media LLC
Date: 18-04-2013
Publisher: Springer Science and Business Media LLC
Date: 08-2011
Publisher: IEEE
Date: 06-2014
Publisher: Elsevier BV
Date: 12-2018
Publisher: IEEE
Date: 10-2021
Publisher: IEEE
Date: 09-2015
Publisher: Elsevier BV
Date: 2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: MDPI AG
Date: 29-01-2021
DOI: 10.3390/SU13031413
Abstract: Due to increase in the public and stakeholders’ awareness regarding economic, environmental, and social issues, the construction industry tends to follow the sustainability policies and practices in supply chain management. Hence, one of the most crucial aspects for a construction company in this regard is sustainable supplier selection, and, to this end, an accurate and reliable model is required. In this paper a hybrid fuzzy best-worst method and fuzzy inference system model is developed for sustainable supplier selection. In the first phase of this study, after determining 19 criteria in three main aspects, the final weight of each aspect and criterion is obtained using fuzzy best-worst method approach. In the second phase, the most sustainable supplier is selected by running the weighted fuzzy inference system both in aspect and criterion level, providing more accurate results compared to the use of other available models. Finally, two different tests are employed to validate the results and evaluate the robustness of the proposed model. The novel developed model enables the decision-maker to simulate the decision-making process, reduce the calculations loads, consider a large number of criteria in decision making, and resolve the inherited uncertainties in experts’ responses.
Publisher: IEEE
Date: 05-2019
Publisher: Elsevier BV
Date: 08-2008
Publisher: Elsevier BV
Date: 09-2014
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 08-2010
Publisher: Springer Science and Business Media LLC
Date: 10-05-2021
Publisher: Elsevier BV
Date: 02-2021
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: Springer Science and Business Media LLC
Date: 22-02-2018
Publisher: Elsevier BV
Date: 03-2011
Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: Elsevier BV
Date: 2023
Publisher: Inderscience Publishers
Date: 2013
Publisher: Springer International Publishing
Date: 17-08-2017
Publisher: Elsevier BV
Date: 05-2014
Publisher: Elsevier BV
Date: 05-2018
Publisher: Hindawi Limited
Date: 07-2021
DOI: 10.1155/2021/5944828
Abstract: In Iran, location is usually done by temporary relief organizations without considering the necessary standards or conditions. The inappropriate and unscientific location may have led to another catastrophe, even far greater than the initial tragedy. In this study, the proposed locations of crisis management in the region and the optimal points proposed by the Geographic Information System (GIS), taking into account the opinions of experts and without the opinion of experts, were evaluated according to 18 criteria. First, the optimal areas have been evaluated according to standard criteria extracted by GIS and the intended locations of the region for accommodation in times of crisis. Then, the position of each place is calculated concerning each criterion. The resulting matrix of optimal options was qualitatively entered into the Preference Ranking Organization Method for Evaluation (PROMETHEE) for analysis. The triangular fuzzy aggregation method for weighting and standard classification of criteria for extracting optimal areas using GIS and integrating entropy and the Multiobjective Optimization Based on Ratio Analysis (MOORA) method for prioritizing places in the region are considered in this research. Finally, by applying constraints and using net input and output flows, optimal and efficient options are identified by PROMETHEE V. Among the research options, only four options were optimal and efficient. A case study of the Tehran metropolis is provided to show the ability of the proposed approach for selecting the points in three modes, with/without applying weights and applying crisis management.
Publisher: Inderscience Publishers
Date: 2012
Publisher: Elsevier BV
Date: 11-2019
Publisher: Informa UK Limited
Date: 14-02-2021
Publisher: IEEE
Date: 07-2013
Publisher: Elsevier BV
Date: 03-2023
Publisher: Springer Science and Business Media LLC
Date: 14-01-2015
Publisher: Springer Science and Business Media LLC
Date: 25-06-2010
Publisher: Elsevier BV
Date: 04-2007
Publisher: IEEE
Date: 11-2014
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 06-2010
Publisher: Elsevier BV
Date: 11-2013
Publisher: Springer Science and Business Media LLC
Date: 28-08-2020
Publisher: Korean Institute of Intelligent Systems
Date: 30-09-2017
Publisher: Springer Science and Business Media LLC
Date: 19-08-2023
DOI: 10.1007/S00521-023-08930-1
Abstract: Skin cancer, primarily resulting from the abnormal growth of skin cells, is among the most common cancer types. In recent decades, the incidence of skin cancer cases worldwide has risen significantly (one in every three newly diagnosed cancer cases is a skin cancer). Such an increase can be attributed to changes in our social and lifestyle habits coupled with devastating man-made alterations to the global ecosystem. Despite such a notable increase, diagnosis of skin cancer is still challenging, which becomes critical as its early detection is crucial for increasing the overall survival rate. This calls for advancements of innovative computer-aided systems to assist medical experts with their decision making. In this context, there has been a recent surge of interest in machine learning (ML), in particular, deep neural networks (DNNs), to provide complementary assistance to expert physicians. While DNNs have a high processing capacity far beyond that of human experts, their outputs are deterministic, i.e., providing estimates without prediction confidence. Therefore, it is of paramount importance to develop DNNs with uncertainty-awareness to provide confidence in their predictions. Monte Carlo dropout (MCD) is vastly used for uncertainty quantification however, MCD suffers from overconfidence and being miss calibrated. In this paper, we use MCD algorithm to develop an uncertainty-aware DNN that assigns high predictive entropy to erroneous predictions and enable the model to optimize the hyper-parameters during training, which leads to more accurate uncertainty quantification. We use two synthetic (two moons and blobs) and a real dataset (skin cancer) to validate our algorithm. Our experiments on these datasets prove effectiveness of our approach in quantifying reliable uncertainty. Our method achieved 85.65 ± 0.18 prediction accuracy, 83.03 ± 0.25 uncertainty accuracy, and 1.93 ± 0.3 expected calibration error outperforming vanilla MCD and MCD with loss enhanced based on predicted entropy.
Publisher: Springer International Publishing
Date: 2015
Publisher: Informa UK Limited
Date: 02-11-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: IEEE
Date: 2011
Publisher: Elsevier BV
Date: 11-2020
Publisher: IEEE
Date: 07-2017
Publisher: IEEE
Date: 11-2017
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 10-2016
Publisher: IEEE
Date: 06-2009
Publisher: IEEE
Date: 06-2009
Publisher: Elsevier BV
Date: 08-2023
Publisher: Springer Science and Business Media LLC
Date: 10-11-2018
Publisher: Emerald
Date: 02-12-2011
Publisher: Springer International Publishing
Date: 17-08-2017
Publisher: Science Publications
Date: 10-2008
Publisher: CRC Press
Date: 10-07-2012
DOI: 10.1201/B12322
Publisher: IEEE
Date: 09-2016
Publisher: IEEE
Date: 11-2010
DOI: 10.1109/EMS.2010.56
Publisher: Elsevier BV
Date: 12-2018
Publisher: Elsevier BV
Date: 12-2013
Publisher: IEEE
Date: 07-2008
Publisher: Korean Institute of Industrial Engineers
Date: 30-09-2015
Publisher: IEEE
Date: 07-2014
Publisher: Springer Science and Business Media LLC
Date: 14-06-2012
Publisher: IEEE
Date: 12-09-2022
Publisher: Elsevier BV
Date: 12-2009
Publisher: Inderscience Publishers
Date: 2011
Publisher: Inderscience Publishers
Date: 2010
Publisher: Inderscience Publishers
Date: 2010
Publisher: Springer Science and Business Media LLC
Date: 13-01-2013
Publisher: ACM
Date: 23-08-2017
Publisher: Springer Science and Business Media LLC
Date: 19-12-2014
Publisher: Georg Thieme Verlag KG
Date: 11-09-2009
Abstract: Shenmai injection (SMI), a mixture of Radix Ginseng and Radix Ophiopogonis, is one of the most popular herbal medicinal products and is widely used for the treatment of coronary atherosclerotic cardiopathy and viral myocarditis. The purpose of this study was to investigate the effect of SMI, in vivo and in vitro, on the metabolic activities of hepatic cytochrome CYP450 3A1/2, 2C6, 2E1, and 1A2 in rats. After a single or multiple pretreatment with SMI, the rats were administrated intravenously a cocktail containing midazolam (1 mg/kg), diclofenac (0.5 mg/kg), theophylline (1 mg/kg), and chlorzoxazone (0.5 mg/kg) as probe substrates of rat CYP450 3A1/2, 2C6, 1A2, and 2E1, respectively. Single and multiple SMI pretreatment to rats resulted in a rise of 33.8 % (p < 0.01) and 25.6 % (p < 0.01) in AUC for midazolam, and an increase in AUC for diclofenac by 14.7 % (p < 0.05) and 31.2 % (p < 0.01), respectively. However, the pharmacokinetics of chlorzoxazone and theophylline in rats was not altered markedly. In rat liver microsomes, linear mixed-type inhibition of SMI against the enzyme activities of CYP3A1/2, CYP2C6, and CYP1A2 was shown with IC(50) values of 3.3 %, 2.0 %, and 3.1 % and K(i) values of 3.8 %, 1.5 %. and 1.9 %, respectively. These in vivo and in vitro results demonstrated that SMI had the potential to inhibit the activities of hepatic CYP3A1/2 and CYP2C6, but might not significantly affect CYP1A2 and CYP2E1-mediated metabolism in rats.
Publisher: Elsevier BV
Date: 03-2015
Publisher: IEEE
Date: 12-2018
Publisher: Elsevier BV
Date: 11-2011
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 02-2011
Publisher: Springer Science and Business Media LLC
Date: 02-03-2012
Publisher: IEEE
Date: 05-2011
Publisher: IEEE
Date: 11-2011
Publisher: Elsevier BV
Date: 2022
Publisher: IEEE
Date: 05-2018
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 02-2018
Publisher: Elsevier BV
Date: 12-2011
Publisher: IEEE
Date: 06-2011
Publisher: ACM
Date: 23-08-2017
Publisher: IEEE
Date: 05-2011
Publisher: Springer Nature Switzerland
Date: 2023
Publisher: Elsevier BV
Date: 2013
Publisher: IEEE
Date: 11-2023
Publisher: Informa UK Limited
Date: 12-2011
Publisher: Springer Science and Business Media LLC
Date: 21-06-2022
DOI: 10.1007/S11192-022-04429-Z
Abstract: Research on academic paper ranking has received great attention in recent years, and many algorithms have been proposed to automatically assess a large number of papers for this purpose. How to evaluate or analyse the performance of these ranking algorithms becomes an open research question. Theoretically, evaluation of an algorithm requires to compare its ranking result against a ground truth paper list. However, such ground truth does not exist in the field of scholarly ranking due to the fact that there does not and will not exist an absolutely unbiased, objective, and unified standard to formulate the impact of papers. Therefore, in practice researchers evaluate or analyse their proposed ranking algorithms by different methods, such as using domain expert decisions (test data) and comparing against predefined ranking benchmarks. The question is whether using different methods leads to different analysis results, and if so, how should we analyse the performance of the ranking algorithms? To answer these questions, this study compares among test data and different citation-based benchmarks by examining their relationships and assessing the effect of the method choices on their analysis results. The results of our experiments show that there does exist difference in analysis results when employing test data and different benchmarks, and relying exclusively on one benchmark or test data may bring inadequate analysis results. In addition, a guideline on how to conduct a comprehensive analysis using multiple benchmarks from different perspectives is summarised, which can help provide a systematic understanding and profile of the analysed algorithms.
Publisher: Elsevier BV
Date: 08-2022
Publisher: IEEE
Date: 13-03-2023
Publisher: Informa UK Limited
Date: 13-09-2022
Location: United States of America
Location: Iran (Islamic Republic of)
No related grants have been discovered for Morteza Saberi.