Sharif Digital Repository

Control charts are the best tools to monitor main process parameters, and the Multivariate Exponentially Weighted Moving Average, MEWMA, type of this tool is used when there are several correlated quality characteristics to be monitored simultaneously where detecting small deviations of the characteristics is desired. In this paper, the models of both the economic and the economic-statistical design problems of MEWMA control charts are solved by a Particle Swarm Optimization (PSO) approach. The comparison study between the economic and the economic-statistical designs shows better statistical performances of the economic-statistical design with negligible increase in cost. Furthermore, in... 

Purpose: Healthcare failure mode and effect analysis (HFMEA) identifies potential risks and defines preventive actions to reduce the effects of risks. In addition, a discrete event simulation (DES) could evaluate the effects of every improvement scenario. Consequently, a proposed integrated HFMEA-DES model is presented for quality improvement in a general hospital. Design/methodology/approach: In the proposed model, HFMEA is implemented first. As any risk in the hospital is important and that there are many departments and different related risks, all defined risk factors are evaluated using the risk priority number (RPN) for which related corrective actions are defined based on experts'... 

Purpose: Healthcare failure mode and effect analysis (HFMEA) identifies potential risks and defines preventive actions to reduce the effects of risks. In addition, a discrete event simulation (DES) could evaluate the effects of every improvement scenario. Consequently, a proposed integrated HFMEA-DES model is presented for quality improvement in a general hospital. Design/methodology/approach: In the proposed model, HFMEA is implemented first. As any risk in the hospital is important and that there are many departments and different related risks, all defined risk factors are evaluated using the risk priority number (RPN) for which related corrective actions are defined based on experts'... 

In economic design of profiles, parameters of a profile are determined such that the total implementation cost is minimized. These parameters consist of the number of set points, n, the interval between two successive sampling, h, and the parameters of a control chart used for monitoring. In this paper, the Lorenzen-Vance cost function is extended to model the costs associated with implementing profiles. The in-control and the out-of-control average run lengths, ARL0 and ARL1, respectively, are used as two statistical measures to evaluate the statistical performances of the proposed model. A genetic algorithm (GA) is developed for solving both the economic and the economic-statistical... 

Economic design of a control chart involves determining its basic parameters such that a cost function is minimized. This design when statistical performance measures are also considered is referred to as the economic-statistical design. In this paper, a simplex-based Nelder-Mead algorithm is used in combination with a particle swarm meta-heuristic procedure to solve both the economic and economic-statistical designs of a MEWMA control chart. The application results on extensive simulation experiments show that the particle swarm can lead the Nelder-Mead algorithm to better results. Furthermore, a comparative study is performed on the performances of three different algorithms of the... 

Advancement of Cyber-Physical Systems has attracted attention to Mixed-Criticality Systems (MCSs), both in research and in industrial designs. As multicore platforms are becoming the dominant trend in MCSs, joint energy and reliability management is a crucial issue. In addition, providing guaranteed service level for low-criticality tasks in critical mode is of great importance. To address these problems, we propose LETR-MC scheme that simultaneously supports certification, energy management, fault-tolerance, and guaranteed service level in mixed-criticality multicore systems. In this paper, we exploit task-replication to not only satisfy reliability requirements, but also to improve the QoS... 

Today, academic research plays a very influential role in the economic development of countries. These researches are often recorded and disseminated in the form and structure of theses and dissertations in scientific institutes. The better the quality of this data in the systems that collect and distribute it, the more it can be used and exploited by organizations and businesses. Therefore, providing this data requires proper monitoring to put the output of the recording and dissemination process in good condition. This paper offers a framework for evaluating theses and dissertation data quality. In the framework, the data inconsistency coding structure is introduced and presented in Word... 

Control charts are statistical tools to monitor a process or a product. However, some processes cannot be controlled by monitoring a characteristic; instead, they need to be monitored using profiles. Economic-statistical design of profile monitoring means determining the parameters of a profile monitoring scheme such that total costs are minimized while statistical measures maintain proper values. While varying sampling interval usually increases the effectiveness of profile monitoring, economic-statistical design of variable sampling interval (VSI) profile monitoring is investigated in this paper. An extended Lorenzen–Vance function is used for modeling total costs in VSI model where the... 

Employing profiles using variable sample size (VSS) may improve its effectiveness and hence is investigated in this paper. Besides, the implementation cost of a profile is an important factor in determining the main parameters. In this paper, the Lorenzen-Vance function is first extended to model implementation cost of VSS linear profiles. Then, the resulted economic model is solved using a genetic algorithm (GA). The average run length criterion when process is in control, ARL0 and the average run length measure when process goes out of control, ARL1 , is used to evaluate statistical properties of the designed profile. Moreover, a sensitivity analysis on the main parameters of the... 

This paper proposes a design technique for the implementation of a class-EM power amplifier (PA). Class- EM mode of operation has been proposed as an improved version of class-E in terms of efficiency and power gain, provided that the current fall time of switch is an appreciable portion of a period; the frequency of operation is high enough that the switching time of transistor can no longer be considered instantaneous. A novel approach for harmonic injection required for class-EM operation is proposed, followed by the system of equations and the design methodology governing the proposed circuit. As a proof of concept and verification of the proposed design method, a class-EM PA is designed... 

An economic-statistical design with multiple assignable causes following exponential distribution is presented in this paper for linear profiles. For this purpose, a tri-objective optimization model is proposed to minimize the cost with desired statistical performances. Average Run Length (ARL) as the primary statistical measure is employed for the appraisal of the designed linear profiles. The first objective to be minimized is a cost function that models the implementation cost in different states. The second objective is to maximize ARL or the in-control average run-length of the monitoring scheme. The third objective to be minimized is ARL 1 or the out-of-control average run-length of... 

Aim of study: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most patients in the first year due to ineffective treatment. Different clinical, biomedical, and image data features are needed to analyze GBM, increasing complexities. Besides, they lead to weak performances for machine learning models due to ignoring physicians' knowledge. Therefore, this paper proposes a hierarchical model based on Fuzzy C-mean (FCM) clustering, Wrapper feature selection, and twelve classifiers to analyze treatment plans. Methodology/Approach: The proposed method finds the effectiveness of previous and current treatment plans, hierarchically determining the best decision for... 

Migration from Two Dimensional Integrated Circuits (2D ICs) to Three Dimensional Integrated Circuits (3D ICs) reduces the delay due to the shorter wire length between sender and receiver. However, Through-Silicon-Vias (TSVs) that connect layers in the structure of 3D ICs can seriously increase the delay due to capacitance coupling between TSVs and lead to crosstalk fault. The severity of crosstalk faults depends on transitions appearing on TSVs that is called transition patterns. To propose an efficient crosstalk tackling mechanisms in 3D ICs, an accurate probability analytical model is required to predict the delay caused by TSVs (3D ICs) in the attendance of these transition patterns. In... 

Multicore platforms are becoming the dominant trend in mixed-criticality systems (MCSs). Multicores provide great opportunities to realize task-level redundancy for reliability enhancement. However, they may experience limited utility in battery-powered mixed-criticality embedded systems. Hence, joint energy and reliability management is a crucial issue in designing MCSs. In this article, we propose the low energy standby-sparing mechanism in mixed-criticality system (LESS-MICS) scheme, which uses the inherent redundancy of multicores to apply the standby-sparing technique for fault-tolerance. Also, by using the inherent redundancy, the LESS-MICS scheme proposes the Parallelism and Reduction... 

Estimation of 3D human pose from a single image is a challenging task because of ambiguities in projection from 3D space to the 2D image plane. A new two-stage deep convolutional neural network-based method is proposed for regressing the distance and angular difference matrices among body joints. Using the angular difference between body joints in addition to the distance between them in articulated objects such as human body can better model the structure of the shapes and increases the modelling capability of the learning method. Experimental results on HumanEva I and Human3.6M datasets show that the proposed method has substantial improvement in the mean per joint position error measure... 

Multiple human 3D pose estimation is a useful but challenging task in computer vison applications. The ambiguities in estimation of 2D and 3D poses of multiple persons can be verified by using multi-view frames, in which the occluded or self-occluded body parts of some persons might be visible in other camera views. But, when cameras are moving and uncalibrated, estimating the association of multiple human body parts among different camera views is a challenging task. This paper presents novel methods for multiple human 3D pose estimation and pose association in multi-view camera frames in an uncalibrated camera setup using an adversarial learning framework. The generator is a 3D pose... 

Multiple human 3D pose estimation is a useful but challenging task in computer vison applications. The ambiguities in estimation of 2D and 3D poses of multiple persons can be verified by using multi-view frames, in which the occluded or self-occluded body parts of some persons might be visible in other camera views. But, when cameras are moving and uncalibrated, estimating the association of multiple human body parts among different camera views is a challenging task. This paper presents novel methods for multiple human 3D pose estimation and pose association in multi-view camera frames in an uncalibrated camera setup using an adversarial learning framework. The generator is a 3D pose... 

Nowadays, data and information are recognized as a precious resource in an organization. Data quality indicators help organizations manage the quality of data quantitatively and improve organizational processes. Organizations manage data and information with the help of information systems and make decisions within the framework of data collected and analyzed. On the other hand, continuous evaluation of the quality of data flow in systems can lead to a preventive program to formulate strategies for improving performance. This can be done effectively and efficiently in the form of control charts. In this paper, control charts are employed to monitor the quality of data flow in information...