Sharif Digital Repository

Advances in semiconductor technology have made integration of multiple processing cores into one single die a promising trend towards increasing processing performance, lowering power consumption, and increasing reliability for embedded systems. Multicore processors, due to their intrinsic redundancies, are good choices for critical embedded systems for which the reliability is a crucial component. In this paper, an aging-aware adaptive fault tolerance method for DVFS-enabled multicore processors is presented. The analytical results show 3 to 6 order of magnitude increase in reliability of the system without addition of cores or redundant software. By using an aging-aware approach, the... 

Multicore processors are becoming popular in safety-critical applications. A series of these applications comprises of kernels where inexact computations may produce results within the boundary of sufficient quality though, for which the reliability should stay at the maximum possible level. Intrinsic core-level redundancy in multicore processors can be leveraged to achieve the desired reliability level in form of N-modular redundancy (NMR). While NMR provides a proactive means of reliability for critical systems, it has two main drawbacks: Increase in the area and energy consumption that are both limiting factors in the embedded systems. This paper presents a software-based method to... 

Multicore processors are becoming popular in safety-critical applications. A series of these applications comprises of kernels where inexact computations may produce results within the boundary of sufficient quality though, for which the reliability should stay at the maximum possible level. Intrinsic core-level redundancy in multicore processors can be leveraged to achieve the desired reliability level in form of N-modular redundancy (NMR). While NMR provides a proactive means of reliability for critical systems, it has two main drawbacks: Increase in the area and energy consumption that are both limiting factors in the embedded systems. This paper presents a software-based method to... 

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier... 

Aluminum reduction cells have benefited from point feeding technology for a long time, but there are still smelters which are using the old technology of center break and center feed system. Due to several factors this system is no longer approved and there have been a few attempts worldwide to upgrade these cells so as to implement the newer technology by applying mechanical and automation changes. In this paper we will present an attempt which was made in order to retrofit a so-called center break cell to point feeder cell. The results show that this project has decreased the energy consumption and anode effect frequency. Furthermore, there has been a significant increase in current... 

In the eld of supply chain, selecting a suitable green supplier could signi cantly help us decrease the cost and risks of the operations and increase the quality of green supply. This paper develops an integrated two-stage approach based on Fuzzy Analytic Hierarchy Process (FAHP) and multi-objective mixed-integer linear programming to select suppliers and allocate order in the green supply chain. In the rst stage, suppliers are evaluated using FAHP method and in the second stage, a multi-product multi-period supply chain is developed considering green location-routing problem, discounting, and time window under uncertainty. Then, a fuzzy solution approach is applied to solve the proposed... 

The increasing level of customer awareness and application of environmental laws by governments, on the one hand, and the increasing number of competitors, on the other hand, has obliged industry owners to include green activities in the design of the supply chain network. Green activities include any type of action that reduces environmental degradation. Hence, this study seeks to develop a bi-objective, mixed integer linear programming (MILP) model for designing a green supply chain network. In the proposed model, the minimisation of costs and detrimental environmental effects are discussed. LP metric method is used to solve the bi-objective model and the proposed model is run by using... 

Technology scaling has exacerbated the aging impact on the performance and reliability of integrated circuits. By entering into nanotechnology era in recent years, the power density per unit of area has increased, which leads to a higher chip temperature. Aging in a chip is originated from multiple phenomena; all of them are intensified by increased temperature. Several circuit- and architecture-level schemes tried to mitigate the aging in the literature. However, these schemes are not sufficient for multi-core systems due to their unawareness of the unique constraints and features of these platforms. In this paper, we propose a system-level aging mitigation method, so-called Adaptive Task... 

Technology scaling has exacerbated the aging impact on the performance and reliability of integrated circuits. By entering into nanotechnology era in recent years, the power density per unit of area has increased, which leads to a higher chip temperature. Aging in a chip is originated from multiple phenomena; all of them are intensified by increased temperature. Several circuit- and architecture-level schemes tried to mitigate the aging in the literature. However, these schemes are not sufficient for multi-core systems due to their unawareness of the unique constraints and features of these platforms. In this paper, we propose a system-level aging mitigation method, so-called Adaptive Task... 

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a... 

Municipal solid waste (MSW) directly impacts community health and environmental degradation; therefore, the management of MSW is crucial. Medical waste is a specific type of MSW which is generally divided into two categories: infectious and non-infectious. Wastes generated by coronavirus disease 2019 (COVID-19) are classified among infectious medical wastes; moreover, these wastes are hazardous because they threaten the environment and living organisms if they are not appropriately managed. This paper develops a bi-objective mixed-integer linear programming model for medical waste management during the COVID-19 outbreak. The proposed model minimizes the total costs and risks, simultaneously,...