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We have recently proposed a structured algorithm for solving constrained nonlinear least-squares problems and established its local two-step Q-superlinear convergence rate. The approach is based on an earlier adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method. The structured adaptation makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians and adapts a structuring scheme due to Engels and Martinez. For robustness, we have employed a specific nonsmooth line search strategy, taking account of the least-squares objective. Numerical results also confirm the practical relevance of our special considerations for... 

We present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step Q-superlinear convergence. The approach is based on an adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians. We discuss the comparative results of the testing of our programs and three nonlinear programming codes from KNITRO on some randomly generated test problems due to Bartels and Mahdavi-Amiri. The results indeed confirm the... 

Increasing power densities in future technology nodes is a crucial issue in multicore platforms. As the number of cores increases in them, power budget constraints may prevent powering all cores simultaneously at full performance level. Therefore, chip manufacturers introduce a power budget constraint as Thermal Design Power (TDP) for chips. Meanwhile, multicore platforms are suitable for implementation of fault-tolerance techniques to achieve high reliability. Task Replication is a known technique to tolerate transient faults. However, careless task replication may lead to significant peak power consumption. In this paper, we consider the problem of achieving a given reliability target... 

Increasing power densities in future technology nodes is a crucial issue in multicore platforms. As the number of cores increases in them, power budget constraints may prevent powering all cores simultaneously at full performance level. Therefore, chip manufacturers introduce a power budget constraint as Thermal Design Power (TDP) for chips. Meanwhile, multicore platforms are suitable for the implementation of fault-tolerance techniques to achieve high reliability. Task Replication is a well-known technique to tolerate transient faults. However, careless task replication may lead to significant peak power consumption. In this article, we consider the problem of achieving a given reliability... 

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... 

In addition to meeting the real-time constraint, power/energy efficiency and high reliability are two vital objectives for real-time embedded systems. Recently, heterogeneous multicore systems have been considered an appropriate solution for achieving joint power/energy efficiency and high reliability. However, power/energy and reliability are two conflict requirements due to the inherent redundancy of fault-tolerance techniques. Also, because of the heterogeneity of the system, the execution of the tasks, especially real-time tasks, in the heterogeneous system is more complicated than the homogeneous system. The proposed method in this paper employs a passive primary/backup technique to... 

In order to reach a more efficient and compact heat exchanger, it is essential to optimize the design, having in mind the impact of different geometrical parameters. Many of the previously cited studies in the area of heat transfer enhancement using vortex generators were confined only to defined points in the possible design space. Thus, a multiobjective optimization study is particularly suitable in order to cover this space entirely. A CFD simulation along with Pareto method were used to simulate the air flow and heat transfer and optimize the design parameters. The angle of attack of a pair of delta-winglets mounted behind each tube is varied between β = -90° and ß = +90°. Three... 

Introduction: Due to the importance of laser light penetration and propagation in biological tissues, many researchers have proposed several numerical methods such as Monte Carlo, finite element and green function methods. Among them, the Monte Carlo method is an accurate method which can be applied for different tissues. However, because of its statistical nature, Monte Carlo simulation requires a large number of photon pockets to be traced, so it is computationally expensive and time-consuming. Although other numerical methods based on the diffusion method are fast, they have two important limitations: first, they are not valid near the bounder of sample and source, and second, their... 

For real-time embedded systems, energy consumption and reliability are two major design concerns. We consider the problem of minimizing the energy consumption of a set of periodic real-time applications when running on a multi-core system while satisfying given reliability targets. Multi-core platforms provide a good capability for task replication in order to achieve given reliability targets. However, careless task replication may lead to significant energy overhead. Therefore, to provide a given reliability level with a reduced energy overhead, the level of replication and also the voltage and frequency assigned to each task should be determined cautiously. The goal of this paper is to... 

Dynamic Voltage and Frequency Scaling (DVFS) is one of the most popular and exploited techniques to reduce power consumption in multicore embedded systems. However, this technique might lead to a task-reliability degradation because scaling the voltage and frequency increases the fault rate and the worst-case execution time of the tasks. In order to preserve taskreliability at an acceptable level as well as achieving power saving, in this letter, we have proposed an enhanced DVFS method based on reinforcement learning to reduce the power consumption of sporadic tasks at runtime in multicore embedded systems without task-reliability degradation. The reinforcement learner takes decisions based... 

Both governments and health-related organizations must immediately act after a natural disaster happened, i.e., providing essential equipment and medicines to injured people as soon as possible and adequately. To achieve this goal, planning the distribution and the inventory of crucial items during a scenario of disasters, a relief supply chain network with four echelons, namely suppliers, warehouses, disaster locations, and medical centers, is designed. In this work, a bi-objective nonlinear mathematical model that follows two main concerns is proposed. First, we wish to minimize the supply chain costs in terms of both the traveling time between echelons and the inventory costs. Second, we... 

Tackling the dark silicon problem in a heterogeneous multi-core system, the temperature constraints across the system should be addressed carefully by assigning a proper set of tasks to a pool of the heterogeneous cores during the run-time. When such a system is utilized in a reliable/realtime application, the reliability/timing constraints of the application should also be augmented to the temperature constraints and make the tasks mapping problem more and more complex. To solve the mapping problem in such a situation, we propose READY; an online reliability-and deadline-aware mapping and scheduling algorithm for heterogeneous multi-core systems. READY utilizes an adaptive power constraint... 

Low power consumption and high-reliability are often major objectives in the design of embedded systems. To reduce power consumption, embedded systems usually employ system-level power management techniques, e.g. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM). To achieve high reliability, embedded systems often exploit fault-tolerant techniques. Fault-tolerant techniques are in a trade-off with energy consumption, peak-power consumption, and temperature. Thus, different methods have been introduced that simultaneously consider reliability and power consumption as the system constraints. Several novel methods have been proposed in previous works to reduce the power... 

Tackling the dark silicon problem in a heterogeneous multicore system, the temperature constraints across the system should be addressed carefully by assigning a proper set of tasks to a pool of the heterogeneous cores during the run-time. When such a system is utilized in a reliable/real-time application, the reliability/timing constraints of the application should also be augmented to the temperature constraints and make the tasks mapping problem more and more complex. To solve the mapping problem in such a situation, we propose READY; an online reliability-and deadline-aware mapping and scheduling algorithm for heterogeneous multicore systems. READY utilizes an adaptive power constraint... 

Multicore platforms are becoming the dominant trend in designing Mixed-Criticality Systems (MCSs), which integrate applications of different levels of criticality into the same platform. A well-known MCS is the dual-criticality system that is composed of low-criticality and high-criticality tasks. The availability of multiple cores on a single chip provides opportunities to employ fault-Tolerant techniques, such as N-Modular Redundancy (NMR), to ensure the reliability of MCSs. However, applying fault-Tolerant techniques will increase the power consumption on the chip, and thereby on-chip temperatures might increase beyond safe limits. To prevent thermal emergencies, urgent countermeasures,... 

This paper proposes an efficient mechanism that mitigates crosstalk faults in Network-on-Chips (NoCs). This is done by using a Packet Manipulating mechanism called PAM for reliable data transfer of NoCs. PAM investigates the transitions of a packet to minimize the forbidden transition patterns appearing during the flit traversal in NoCs. To do this, the content of a packet is manipulated using three different manipulating mechanisms. In other words, PAM manipulates the content of packet in three manipulating modes including: vertical, horizontal and diagonal modes. Then, comparing the transitions of these manipulating mechanisms, a packet with minimum numbers of transitions is selected to be... 

Breast cancer is the most common invasive cancer in women and the second leading cause of cancer death in women after lung cancer. The purpose of this study is a targeted delivery toward in vitro (on MCF7 and 4T1 breast cancer cell lines) through niosomes-based nanocarriers. To this end, different bioactive molecules, including hyaluronic acid (HA), folic acid (FA), and polyethylene glycol (PEG), were used and compared for surface modification of niosomes to enhance endocytosis. FA-functionalized niosomes (Nio/5-FU/FA) were able to increase cell cytotoxicity and reduce cell migration and invasion compared to PEG-functionalized niosomes (Nio/5-FU/PEG), and HA-functionalized niosomes...