Sharif Digital Repository

3D Network-on-Chips (3D NoCs) have higher scalability, higher throughput, and lower power consumption over 2D NoCs. However, the reliability of data transfer in 3D NoCs is seriously threatened by thermal problems. This is due to poor heat dissipation, inappropriate traffic distribution, and cooling restriction for layers away of the chip heat-sink in 3D NoCs. To solve this problem, this paper proposes an efficient deadlock-free and traffic-And thermal-Aware routing algorithm, called Floating XY-YX. The main idea behind Floating XY-YX routing algorithm is twofold: 1) to use XY and YX routing algorithms in consecutive layers in dessicate form, and 2) to evenly load the traffic, which is... 

One of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning-based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of... 

One of the main issues in colour image processing is changing objects' colour due to colour of illumination source. Colour constancy methods tend to modify overall image colour as if it was captured under natural light illumination. Without colour constancy, the colour would be an unreliable cue to object identity. Till now, many methods in colour constancy domain are presented. They are in two categories; statistical methods and learning-based methods. This paper presents a new statistical weighted algorithm for illuminant estimation. Weights are adjusted to highlight two key factors in the image for illuminant estimation, that is contrast and brightness. The focus was on the convex part of... 

The analysis of core composition changes is complicated by the fact that the time and spatial variation in isotopic composition depend on the neutron flux distribution and vice versa. Fortunately, changes in core composition occur relatively slowly and hence the burnup analysis can be performed by dividing the burnup period into some burnup spans and assuming that the averaged flux and cross sections are constant during each step. The burnup span sensitivity analysis attempts to find that how much the burnup spans could be increased without any significant deviation in results. This goal has been achieved by developing a new MCNP-ORIGEN linkage program named as MOBC (MCNP-ORIGEN Burnup... 

The ability to accurately classify temporal relations between events is an important task in a large number of natural language processing and text mining applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved way of classifying temporal relations, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting useful syntactic features, which are automatically generated, to improve accuracy of the SVM classification method. Accordingly, a number of novel kernel functions are introduced and evaluated for temporal relation classification. Our evaluations... 

Temporal relation classification is one of contemporary demanding tasks of natural language processing. This task can be used in various applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved algorithm for classifying temporal relations, between events or between events and time, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting some useful automatically generated syntactic features to improve the accuracy of classification. Accordingly, a number of novel kernel functions are introduced and evaluated. Our evaluations clearly demonstrate that... 

Recent evaluations of mapping systems show that lack of background knowledge, most often domain specific knowledge, is one of the key problems of mapping systems these days. In fact, at present, most state of the art systems, for the tasks of mapping large ontologies, perform not with such high values of recall (~ 30%), because they mainly rely on label and structure based similarity measures. Disregarding context knowledge in ontology mapping is another drawback that almost all current approaches suffer from. In this paper we use the semantic web as background knowledge and introduce a novel approach for capturing context knowledge from the ontology for improving mapping results. We have... 

Semantic segmentation is one of the basic, yet essential scene understanding tasks for an autonomous agent. The recent developments in supervised machine learning and neural networks have enjoyed great success in enhancing the performance of the state-of-the-art techniques for this task. However, their superior performance is highly reliant on the availability of a large-scale annotated dataset. In this letter, we propose a novel fully unsupervised semantic segmentation method, the so-called Information Maximization and Adversarial Regularization Segmentation (InMARS). Inspired by human perception which parses a scene into perceptual groups, rather than analyzing each pixel individually, our... 

Grammar induction is one of attractive research areas of natural language processing. Since both supervised and to some extent semi-supervised grammar induction methods require large treebanks, and for many languages, such treebanks do not currently exist, we focused our attention on unsupervised approaches. Constituent Context Model (CCM) seems to be the state of the art in unsupervised grammar induction. In this paper, we show that the performance of CCM in free word order languages (FWOLs) such as Persian is inferior to that of fixed order languages such as English. We also introduce a novel approach, called parent-based constituent context model (PCCM), and show that by using some... 

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... 

Checkpointing with rollback recovery is a well-established technique to tolerate transient faults. However, it incurs significant time and energy overheads, which go wasted in fault-free execution states and may not even be feasible in hard real-time systems. This paper presents a low-overhead two-state checkpointing (TsCp) scheme for fault-tolerant hard real-time systems. It differentiates between the fault-free and faulty execution states and leverages two types of checkpoint intervals for these two different states. The first type is nonuniform intervals that are used while no fault has occurred. These intervals are determined based on postponing checkpoint insertions in fault-free... 

Networks-on-Chip (NoCs) play a crucial role in the performance of Chip Multi-Processors (CMPs). Routers are one of the main components determining the efficiency of NoCs. As various applications have different communication characteristics and hence, buffering requirements, it is difficult to make proper decisions in this regard in the design time. In this paper, we propose a traffic-aware reconfigurable router which can adapt its buffers structure to the changes in the traffic of the network. Our proposed router manages to achieve up to 18.8% and 44.4% improvements in terms of postponing saturation rate under synthetic traffic patterns, and average packet latency for PARSEC applications,... 

Mixed-criticality (MC) systems have recently been devised to address the requirements of real-time systems in industrial applications, where the system runs tasks with different criticality levels on a single platform. In some workloads, a high-critically task might overrun and overload the system, or a fault can occur during the execution. However, these systems must be fault tolerant and guarantee the correct execution of all high-criticality (HC) tasks by their deadlines to avoid catastrophic consequences, in any situation. Furthermore, in these MC systems, the peak-power consumption of the system may increase, especially in an overload situation and exceed the processor thermal design... 

Mixed-Criticality (MC) systems have recently been devised to address the requirements of real-time systems in industrial applications, where the system runs tasks with different criticality levels on a single platform. In some workloads, a highcritically task might overrun and overload the system, or a fault can occur during the execution. However, these systems must be fault-tolerant and guarantee the correct execution of all highcriticality tasks by their deadlines to avoid catastrophic consequences, in any situation. Furthermore, in these MC systems, the peak power consumption of the system may increase, especially in an overload situation and exceed the processor Thermal Design Power... 

Stress is a body's natural way of responding to any kind of demand or challenge that everyone experiences from time to time. Although short-Term stress typically does not impose a health burden, exposure to prolonged stress can lead to significant adverse physiological and behavioral changes. Coping with the impact of stress is a challenging task and in this context, stress assessment is essential in preventing detrimental long-Term effects. The public embracement of connected wearable Internet of Things (IoT) devices, as well as the proliferation of Artificial Intelligence (AI) and Machine Learning (ML) technologies, have generated new opportunities for personalized stress tracking and... 

Due to the battery-operated nature of embedded Mixed-Criticality Systems, simultaneous energy and reliability management is a cru-cial issue in designing these systems. We propose two comprehensive schemes, MC-2S and MC-4S, which tolerate permanent faults through exploiting the inherent redundancy of multicore systems for applying standby-sparing technique and maintaining the system re-liability against transient faults with low energy overhead. In these schemes, two copies of each high-criticality task are scheduled on different cores to guarantee their timeliness in case of permanent fault occurrence. In order to guarantee the quality of service of low-criticality tasks, in the MC-2S... 

Due to the battery-operated nature of some embedded Mixed-Criticality Systems, simultaneous energy and reliability management is a crucial issue in designing these systems. We propose two comprehensive schemes, MC-2S and MC-4S, which exploit the standby-sparing technique to tolerate permanent faults through inherent redundancy of multicore systems and maintain the system's reliability against transient faults with low energy overhead. In these schemes, two copies of each high-criticality task are scheduled on different cores to guarantee their timeliness in case of permanent fault occurrence. To guarantee the quality of service of low-criticality tasks, in the MC-2S scheme, one backup copy... 

Today's world energy-related challenges, ranging from anthropogenic climate change to continuous growth of demand for different energy forms, have enforced planners of energy systems (ESs) to concentrate on more optimal and eco-friendly operation and/or expansion planning methodologies. In this context, increased interdependencies of gas, heat and electricity ESs have recently encouraged the planners to design operation and/or expiation strategies in an integrated manner in favor of a new concept, the so-called “Energy Hub” (EH). Although this concept has been employed so far in a multitude of studies, but its real nature, advantages, difficulties, importance or inevitability aspect, and... 

The ability to accurately classify temporal relation between events is an important task for a large number of natural language processing applications such as Question Answering (QA), Summarization, and Information Extraction. This paper presents a weakly-supervised machine learning approach for classification of temporal relation between events. In the first stage, the algorithm learns a general classifier from an annotated corpus. Then, it applies the hypothesis of "one type of temporal relation per discourse" and expands the scope of "discourse" from a single document to a cluster of topically-related documents. By combining the global information of such a cluster with local decisions...