Sharif Digital Repository

In this brief, we use the alpha power law model for MOS devices to reach a more accurate modeling of CMOS buffers in very deep submicrometer technologies. We derive alpha model parameters of a CMOS buffer for 90-, 65-, and 45-nm technologies using HSPICE simulations. By analytical efforts we find the output resistance of a minimum-size buffer and compare it with those extracted from HSPICE simulations. We propose a new model for the output resistance of a given-size buffer in any technology, which demonstrates 3% error on average as opposed to the conventional model. Also a new buffer resistance is proposed analytically and numerically to calculate the crosstalk for interconnect analysis... 

Availability of the service delivered by cloud providers is one of the most important QoS factors of the service level agreements between providers and customers. Since current Infrastructure-as-a-Service providers use virtualization technology to manage data centers, virtual data centers (VDCs) have become a popular infrastructure for cloud computing. In order to study the service availability, a stochastic activity network (SAN) model is presented in this paper. The proposed SAN model can be appropriately used to investigate the impact of different characteristics and policies on service availability of VDCs  

Methods of human semen assessment are quite wide ranging. In this paper, we use background subtraction methods in order to detect progressive sperms whose quality of movement strongly influence fertility. Robust Principal Component Analysis (RPCA) is a powerful algorithm which has been used recently for background subtraction purposes. Sperm tracking problem can also be defined as a background subtraction problem. In RPCA algorithm, data is represented by a low rank plus sparse matrix. In our approach, the foreground data is recovered through such matrix decomposition. We compare the RPCA approach with four other background subtraction methods in order to check accuracy of algorithm as a... 

This paper studies detecting matrices in random dense and sparse Code Division Multiple Access (CDMA) systems. Detecting matrices were originally introduced in the coin weighing problem. Such matrices can be used in CDMA systems in over-loaded scheme where the number of users is greater than the number of chips. We drive some conditions in the large system limit for binary and bipolar random CDMA systems to ensure that any random matrix is a detecting matrix. Furthermore, we extend our results to sparse random ternary matrices that have been using in the sparse CDMA literature. Finally, a construction method for the sparse detecting matrices is introduced  

The electrooculogram (EOG) artifact is one of the main contaminators of electroencephalographic recording (EEG). EOG can make serious problems in results and interpretations of EEG processing. Rejecting contaminated EEG segments result in an unacceptable data loss. Many methods were proposed to correct EOG artifact mainly based on regression and blind source separation (BSS). In this study, we proposed an automatic correction method based on maximum likelihood estimation. The proposed method was applied to our simulated data (real artifact free EEG plus controlled EOG) and results show that this method gives superior performance to Schlögl and SOBI methods  

The incidence of apnea-bradycardia episodes in preterm infants may lead to neurological disorders. Prediction and detection of these episodes are an important task in healthcare systems. In this paper, a coupled hidden Markov model (CHMM) based method is applied to detect apnea-bradycardia episodes. This model is evaluated and compared with two other methods based on hidden Markov model (HMM) and hidden semi-Markov model (HSMM). Evaluation and comparison are performed on a dataset of 233 apnea-bradycardia episodes which have been manually annotated. Observations are composed of RR-interval time series and QRS duration time series. The performance of each method was evaluated in terms of... 

The remarkable properties of graphene nanoribbons (GNRs) make them attractive for nano-scale devices applications, especially for transistor and interconnect. Furthermore, for reduction interconnects signal delay, low dielectric constant materials are being introduced to replace conventional dielectrics in next generation IC technologies. With these regards, studding the effect of varying dielectric constant (e{open}r) on relative stability of graphene nanoribbons interconnect is an important viewpoint in performance evaluation of system. In this paper, Nyquist stability analysis based on transmission line modeling (TLM) for graphene nanoribbon interconnects is investigated. In this... 

The FT reaction involves the conversion of syngas which is derived from natural gas or coal to different kinds of products according to the operating conditions and the type of the catalyst. In other words, it is a practical way to convert solid fuel (coal) and natural gas to various hydrocarbons (C1-C60) and oxygenates such as alkanes, alkenes etc. The main products of the reaction are naphtha and gasoline. This paper deals with developing a proper product distribution model for FT process using the appropriate kinetic model, optimizing the respective rate constants while applying them in product distribution equations. The results revealed only 8.09% deviations from the olefin experimental... 

An Eigenvalue-based detection (EBD) scheme, is proposed as an efficient method to overcome the noise uncertainty and the SNR wall problem in conventional energy detection (ED) schemes. Despite remarkable efforts made to analyze the EBD performance, a VLSI implementation is missing in literature. In this paper, a new FFT-based EBD algorithm is introduced, which eliminates the need for filter banks and discrete wavelet packet transform to channelize the input signal. The proposed method enables the utilization of the EBD algorithm in high-resolution spectrum sensing approaches. Moreover, it enables the detection of signals with SNRs as low as -10 dB. A low-power, area-efficient yet real-time... 

Cell search is a crucial process in the synchronization procedure for the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) system. In this paper, a high-speed, low-complexity and reliable architecture is proposed for both steps of cell search: sector ID and cell ID group detection. For the sector ID detection, two novel methods, sign-bit reduction and wise resource sharing, are proposed. In addition, for the cell ID group detection, we proposed an algorithm based on the Maximum Likelihood Sequence Detection (MLSD) called 'sign-bit MLSD'. Simulations show that the proposed methods result in more than 90% reduction in area compared to the state-of-the-art. We designed and... 

Mobile Worldwide Interoperability for Microwave Access (Mobile WiMAX) is a wireless access technology based on IEEE 802.16e. The two most important concepts are introduced in the MAC layer of Mobile WiMAX networks, handover and load balancing. In this paper, we have focused on balancing the load of the system, using handover mechanisms suggested by mobile WiMAX. The proposed algorithm, WQLB, concentrates on controlling the system load and keeping it in a balanced state by using a handover process. Also, the algorithm is designed to utilize resources efficiently, supporting QoS. As load definition is an essential criterion in load balancing algorithms, we have suggested a new load model for... 

A multiple input multiple output (MIMO) radar system is an emerging research field which has attracted many studies in recent years. This type of radar, unlike conventional phased array radar, can transmit different probing signals via its antennas, that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar systems enable superior capabilities compared to conventional phased array radar. Many papers have introduced different ways for beamforming of MIMO radar. In this paper it is desirable to analysis some methods for beamforming of MIMO radars with planar arrays constellation and examine their 3D result beam-pattern of such constellations for... 

Leakage power has already become the major contributor to the total on-chip power consumption, rendering its estimation a necessary step in the IC design flow. The problem is further exacerbated with the increasing uncertainty in the manufacturing process known as process variability. We develop a method to estimate the variation of leakage power in the presence of both intra-die and inter-die process variability. Various complicating issues of leakage prediction such as spatial correlation of process parameters, the effect of different input states of gates on the leakage, and DIBL and stack effects are taken into account while we model the simultaneous variability of the two most critical... 

In this paper, jitter due to both capacitive and inductive coupling is studied. Maximum frequency of driving signal on a wire is limited by its input rise time, fall time, pulse width, and the coupling effect from its neighbors. The analytical expressions to estimate the deterministic jitter time due to these effects are presented. The estimation is based on the fastest and slowest approximation of the signal waveform components. Also, we have extracted the eye opening parameters of the eye diagram. The inductance effects significance is shown on eye opening and jitter time. The 45nm technology is used for estimating the horizontal and vertical eye opening and jitter time. The presented... 

This paper presents a dynamic multi objective model for distribution network expansion, considering the distributed generators (DGs) and network reinforcements. The proposed model simultaneously optimizes three objective functions namely, total cost, emission cost and technical satisfaction (voltage profile) by finding the optimal schemes of timing, sizing, placement and DG technologies in a long term planning period (dynamic planning). The importance of each objective function can be changed in the interactive steps. The calculation algorithm is based on Chaotic Local Search with Modified Honey Bee Mating Optimization (CLSMHBMO). The effectiveness of the proposed model and the calculation... 

In this paper, we present a new method to solve tracking problem. The proposed method combines sparse representation and motion estimation to track an object. Recently. sparse representation has gained much attention in signal processing and computer vision. Sparse representation can be used as a classifier but has high time complexity. Here, we utilize motion information in order to reduce this computation time by not calculating sparse codes for all the frames. Experimental results demonstrates that the achieved result are accurate enough and have much less computation time than using just a sparse classifier  

To scavenge the energy from the environment and extend the network lifetime, some wireless sensor networks (WSNs) have been equipped with energy harvesters recently. However, the variable amount of environmental energy can affect the reliability of energy harvesting wireless sensor networks (EH-WSNs). In addition, data transmission over a wireless media is vulnerable. Hence, utilizing suitable error control schemes are necessary to improve the reliability. Regarding this point, Automatic Repeat Request (ARQ) and Cooperative ARQ (C-ARQ) schemes are applied in this generation of WSNs. Conventional ARQ as well as C-ARQ scheme are considered and examined through simulation. A comparative... 

In this work we present a sparse dictionary learning method, specifically tuned to solve the tracking problem. Recently, sparse representation has drawn much attention because of its genuineness and strong mathematical background. In this paper we present an online method for dictionary learning which is desirable for problems such as tracking. Online learning methods are preferable because the whole data are not available at the current time. The presented method tries to use the advantages of the generative and discriminative models to achieve better performance. The experimental results show our method can overcome many tracking challenges  

Since tracking algorithms should be robust with respect to appearance changes, online algorithms has been investigated recently instead of offline ones which has shown an acceptable performance in controlled environments. The most challenging issue in online algorithms is updating of the model causing tracking failure because of introducing small errors in each update and disturbing the appearance model (drift). in this paper, we propose an online generative tracking algorithm in order to overcome the challenges such as occlusion, object shape changes, and illumination variations. In each frame, color distribution of target candidates is obtained and the candidate having the lowest distance... 

Cardiovascular diseases contribute to one third of the world's mortality and morbidity, therefore early cardiovascular disease diagnosis, treatment and monitoring has become an important market. Ideally, an early diagnosis device will need to be accurate, non-invasive, low cost and operator independent. Interestingly enough, there is a wide range of non-invasive devices available, but each with a different degree of accuracy and ease of use. In this paper, an attempt has been made to review commercially available technologies for non-invasive vascular screening. As stiffness index, reflection index, augmentation index, central aortic pressure are most commonly used to screen for vascular...