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Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple

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Computers, Materials & Continua 2018年第10期57卷 81-96页

作者： Tiejun Wang Tao Wu Amir Homayoon Ashrafzadeh Jia He Department of Computer Science Chengdu University of Information and TechnologyChengdu610025China. CSIT Department School of ScienceRMIT UniversityMelbourne3058Australia.

Crowdsourcing is widely used in various fields to collect goods and services from large participants.Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate.In this paper,we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’questionnaires described by linguistic 2-tuple terms.Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’impact on the evaluation.The crowd grade would be updated at the end of each feedback so it can guarantee the evaluation accurately.Moreover,a simulated case is shown to illustrate how to apply this framework to assess teaching quality in the classroom.Finally,we developed a prototype and carried out some experiments on a series of real questionnaires and two sets of modified data.The results show that teachers can locate the weak points of teaching and furthermore to identify the abnormal students to improve the teaching quality.Meanwhile,our approach provides a strong tolerance for the abnormal student to make the evaluation more accurate.

关键词： Teaching quality evaluation crowdsourcing linguistic 2-tuple group decision making

A Novel Quantum-Behaved Particle Swarm Optimization Algorithm

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Computers, Materials & Continua 2020年第5期63卷 873-890页

作者： Tao Wu Lei Xie Xi Chen Amir Homayoon Ashrafzadeh Shu Zhang School of Computer Science Chengdu University of Information TechnologyChengdu610225China School of Computer Science and Technology Southwest Minzu UniversityChengdu610041China CSIT Department School of ScienceRMIT UniversityMelbourne3058Australia Department of Emergency Medicine West China HospitalSichuan UniversityChengdu610041China

The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs.Quantum-behaved Particle Swarm Optimization(QPSO)algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling.This paper analyzed the motion pattern of particles in a square potential well,given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well(BC-QSPSO).In this novel algorithm,the intrinsic cognitive link between particles’experience information and group sharing information was created by using normal Copula function.After that,the control parameters chosen strategy gives through experiments.Finally,the simulation results of the test functions show that the improved algorithms outperform the original QPSO algorithm and due to the error gradient information will not be over utilized in square potential well,the particles are easy to jump out of the local optimum,the BC-QSPSO is more suitable to solve the functions with correlative variables.

关键词： Ambulance routing problem quantum-behaved particle swarm optimization square potential well convergence

Detailed seismic risk analysis of electrical substation equipment using a reliability based approach

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Earthquake Engineering and Engineering Vibration 2023年第2期22卷 495-511页

作者： amir Ghahremani Baghmisheh Milad Khodaei Ali Zare Feiz Abadi homayoon E.Estekanchi Department of Civil Engineering University of British ColumbiaVancouver V6T 2B8Canada Department of Civil Engineering University of TabrizTabriz 51666Iran Department of Civil Engineering Sharif University of TechnologyTehran 11155-9313Iran

This paper proposes a risk analysis framework for substation structures based on reliability methods.Even though several risk assessment approaches have been developed for buildings,detailed risk analysis procedures for infrastructure components have been lacking in prior studies.The proposed framework is showcased by its application to a system of interconnected structures at a power substation in Tehran.Finite element models of structures are developed and validated in accordance with previous experiments.The uncertainties in the material,mass,and geometric properties of structures are described by random variables that are input to the finite element model.An artificial ground motion model is employed to comprehensively consider uncertainty in ground motion.Monte Carlo sampling is subsequently conducted on the library of probabilistic models.The analysis resulted in the loss distribution in the life cycle of structures.Additionally,the loss associated with six earthquake scenarios having specific magnitudes and return periods is computed.The application provides insight into the most vulnerable equipment in the considered system.Furthermore,introduced risk measures can guide stakeholders to make risk-based decisions to optimize design or prioritize a retrofit of infrastructure components under conditions of uncertainty.

关键词： seismic risk reliability analysis infrastructure components loss estimation uncertainty

Halothane hepatitis in Iran:A review of 59 cases

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World Journal of Gastroenterology 2008年第34期14卷 5322-5326页

作者： Payam Eghtesadi-Araghi amir-Ali Sohrabpour homayoon Vahedi Mehdi Saberi-Firoozi Digestive Disease Research Center Shariati HospitalMedical Sciences/University of Tehran Gastroenterology Research Center Shiraz University of Medical Sciences Digestive Disease Research Center Shariati Hospital Medical Sciences/University of Tehran

AIM:To study halothane hepatitis (HH) in Iran and its associated risk factors. METHODS: We retrospectively studied files of all cases diagnosed with HH referred to three referral hospitals and four private centers in Iran from April 1994 to September 2006. Information on age at surgery, gender, medications history, obesity, history of previous exposure, previous reaction to halothane, familial history, type of surgery, perioperative hypoxia or sepsis, morbidity and mortality were recorded and analyzed. RESULTS: A total of 59 cases were identifi ed. Forty- eight (81%) were women. The median age at the time of surgery was 44 years (range, 18 to 80 years). Sixty percent of patients were above 40-year-old. Obesity was observed in 22.2%. Previous history of exposures to halothane was noted in 61% of which 50% had history of post-exposure reaction. Coronary artery bypass graft (CABG), cholecystectomy, and cosmetic surgeries (mainly weight reduction) were the most frequent surgeries. The mortality rate was 12.2%. In patients developing encephalopathy, it was as high as 50%. CONCLUSION: HH remains an important cause of morbidity and mortality in centers still using this anesthetic. However, a large percentage of these casescould have been avoided. To lessen occurrence of further cases of HH, the authors suggest that in female patients having a history of surgery (or delivery) with general anesthesia, the use of halothane should be absolutely avoided. Utilization of proper substitutes in adults’ anesthesia is advocated.

关键词：麻醉手术氟烷麻醉药肝炎伊朗

Is nonlinear model predictive control with fuzzy predictive model proper for managing the blood glucose level in typeI diabetes?

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Journal of Biomedical Science and Engineering 2012年第2期5卷 63-74页

作者： Maryam Ahmadi amir homayoon Jafari Department of Biomedical Engineering Tehran University Tehran Iran Young Researcher Club Central Tehran Branch Islamic Azad University Tehran Iran

In recent decades, due to the increasing risk of diabetes, the measurement and control of the blood sugar is of great importance. In typeI diabetes, because of the lack of insulin secretion, the cells cannot absorb glucose, and thus have a low level of glucose. To control blood glucose, the insulin must be injected to the body. In fact, the injection must be in a completely controlled environment. If the level of the insulin exceeds the physiological limits, it may cause death. This paper presents an online approach to control the blood glucose level using a nonlinear model predictive control. This method, maintains the level of blood glucose concentration within a normal range. Thus, the blood glucose level is measured in each minute and predicted for the next time interval. If that is not in the normal range, amount of the insulin which must be injected will be determined. The proposed control approach includes important features such as model uncertainties and prevents acute decrease in the blood glucose level, and instability. In order to assess performance of the proposed controller, computer simulations have been carried out in Matlab/Simulink. Simulation results will reveal the effectiveness of the proposed nonlinear model predictive controller in adjusting the blood glucose level by injecting required insulin. So if the nutrition of the person decreases instantly, the hypoglycemia does not happen.

关键词： Diabetes Delay of Insulin-Glucose Regulatory System Blood Glucose Level Nonlinear Model Predictive Control