Sharif Digital Repository

Multi-site photoplethysmography is an optoelectronic technique that measures changes in blood volume associated with cardiac contraction. Photoplethysmogram (PPG) recording enables researchers to study the vascular and hemodynamic properties of human subjects. Currently, there is no commercial system available in the market to perform multi-channel PPG recording. The measurements can be obtained from fingertips, ear lobes and toes due to their low absorption and high degree of vasculature. The main objective of this project is to develop a suitable data compression algorithm for two-channel simultaneous high resolution wireless PPG recording system. MATLAB software was used during the... 

New inner and outer bounds on the achievable compression-equivocation rate region for generalised secure data compression with side information are given that do not match in general. In this setup, two senders, Alice and Charlie intend to transmit information to Bob via channels with limited capacity so that he can reliably reconstruct their observations. The eavesdropper, Eve, has access to one of the channels at each instant and is interested in the source of the same channel at the time. Bob and Eve also have their own observations, which are correlated with Alice's and Charlie's observations. In this model, two equivocation and compression rates are defined with respect to the sources... 

A Monte Carlo model on the basis of hardness input is developed to predict the annealing microstructure of deformed specimens in tensile, compression, and tensile + compression tests. From experimental value of hardness, the stored energy of the deformed specimens is calculated and entered into the Monte Carlo model. The consistency between the simulation results and experimental data shows that the developed model based on hardness input can be more practical since the effect of different deformation states is considered for estimating of stored energy. © 2008 Elsevier B.V. All rights reserved  

In this paper a strategy is proposed for compressing the test data while using concurrent hybrid-BIST methodologyfor testing SoCs. In the proposed method, in addition tousing BIST strategy for testing cores with deterministic sequential test patterns in an SoC( Without using scan chains), (ATE) is used for testing cores with deterministic test patterns through Test Access Mechanism (TAM) or functional bus. As will be shown in experimental results, this process compresses hybrid-BIST overall test patterns considerably that affects the overall Test Application Time (TAT) in comparison with pure deterministic, pure pseudo random, and combination of deterministic and pseudo random test patterns  

Wireless sensor networks (WSNs) use energy for their sensing, computation, and communication. To increase the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is not possible in most applications. Therefore, energy consumption needs to be monitored and limited to increase the energy consumption performance of the network. The communication module uses the highest amount of energy in a WSN. Among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. This paper illustrates an energy consumption reduction in WSN by... 

Emerging non-volatile memories (NVMs) are notable candidates for replacing traditional DRAMs. Although NVMs are scalable, dissipate lower power, and do not require refreshes, they face new challenges including shorter lifetime and security issues. Efforts toward securing the NVMs against probe attacks pose a serious downside in terms of lifetime. Cryptography algorithms increase the information density of data blocks and consequently handicap the existing lifetime enhancement solutions like Flip-N-Write. In this paper, based on the insight that compression can relax the constraints of lifetime-security trade-off, we propose CryptoComp, an architecture that, taking the advantage of block size... 

In this paper, the problem of spatial error concealment for real-time applications is addressed. The proposed method can be categorized in exemplar-based error concealment approaches. In this category, a patch of corrupted pixels are replaced by another patch of the image that contains correct pixels. For splitting the erroneous block to different patches, a novel context-dependent exemplar-based algorithm based on a previously proposed segmentation method is proposed. The capability of the proposed method for concealment in diverse image regions is depicted. Our detailed conducted experiments show that the proposed method outperforms the state-of-the-art spatial error concealment methods in... 

Background: The issue of medial image resolution enhancement is one of the most important topics for medical imaging that helps improve the performance of many post-processing aspects like classification and segmentation towards medical diagnosis. Objective: Our aim in this paper is to evaluate different types of pixel selection models in terms of pixel originality in medical image reconstruction problems. A previous investigation showed that selecting far original pixels has highly better performance than using near unoriginal/estimated pixels while magnifying some benchmarks in digital image processing. Material and Methods: In our technical study, we apply two classical inter-polators,... 

In this paper, an infrastructure for debug of complex SoCs that employs assertions is introduced. The proposed infrastructure combines traditional off-chip analysis techniques with on-chip at-speed debug facilities. The main part of on-chip debug hardware consists of data and transaction monitors. The monitor hardware is automatically generated by synthesizing the assertions that were used for verification and validation before manufacturing. We have integrated the proposed method in a system-level design methodology. By synthesizing various assertions from different kinds in a case study we have studied the overhead of our method. © 2007 IEEE  

Deep Neural networks (DNNs) are getting deeper and larger which intensify the data movement and compute demands. Prior work focuses on reducing data movements and computation through exploiting sparsity and similarity. However, none of them exploit input similarity and only focus on sparsity and weight similarity. Synergistically analysing the similarity and sparsity of inputs and weights, we show that memory accesses and computations can be reduced by 5.7× and 4.1×, more than what can be decreased by exploiting only sparsity, and 3.9× and 2.1×, more than what can be decreased by exploiting only weight similarity. We propose a new data-aware compression approach, called DANA, to effectively... 

With the advance of multimedia systems and wireless mobile communications, there has been a growing need to support multimedia services (such as mobile teleconferencing, mobile TV, telemedicine, and distance learning) using mobile multimedia technologies. Despite the research done in the field of mobile multimedia, delivery of real-time interactive video over noisy wireless channels is still a challenge for researchers. This paper presents a method for prioritising data partitioned MPEG-4 video in a way suitable for transmission over a mobile network. The effectiveness of the technique is demonstrated by examing its performance when the transport of the prioritized video streams can be... 

In this paper, we provide a simple framework for deriving one-shot achievable bounds for some problems in quantum information theory. Our framework is based on the joint convexity of the exponential of the collision relative entropy and is a (partial) quantum generalization of the technique of Yassaee et al. from classical information theory. Based on this framework, we derive one-shot achievable bounds for the problems of communication over classical-quantum channels, quantum hypothesis testing, and classical data compression with quantum side information. We argue that our one-shot achievable bounds are strong enough to give the asymptotic achievable rates of these problems even up to the... 

Wireless sensor networks (WSNs) consume energy for their sensing, computation, and communication. To extend the lifetime of the network, sensor nodes are equipped with energy storage devices. Recharging of their batteries is impossible in most applications. Therefore, energy consumption needs to be monitored and limited to extend the high performance operation of the network. In this network, the communication module consumes the highest amount of energy. This paper demonstrates that among several methods offered to reduce the energy consumption, data compression has the highest effect on the energy usage by reducing the number of bits to be broadcasted. To determine the energy efficiency of... 

In this study, a detector/estimator is proposed for compressed sensing radars, which does not need to reconstruct the radar signal, and which works directly from compressive measurements. More precisely, through direct processing of the measurements, and without the need for reconstructing the original radar signal, the system performs target detection, and then estimates range, Doppler frequency shift and radar cross section in the presence of a Gaussian clutter. It can be seen that for large compression ratios, the detection performance and estimation quality is comparable with a common radar system while having a much lower data rate and with less computational load  

We have developed a Gaussian Process Regression method with adaptive kernels for concealment of the missing macro-blocks of block-based video compression schemes in a packet video system. Despite promising results, the proposed algorithm introduces a solid framework for further improvements. In this paper, the problem of estimating lost macro-blocks will be solved by estimating the proper covariance function of the Gaussian process defined over a region around the missing macro-blocks (i.e. its kernel function). In order to preserve block edges, the kernel is constructed adaptively by using the local edge related information. Moreover, we can achieve more improvements by local estimation of...