Sharif Digital Repository

Networks-on-Chip (NoCs for short) are known as the most scalable and reliable on-chip communication architectures for multi-core SoCs with tens to hundreds IP cores. Proper mapping the IP cores on NoC tiles (or assigning threads to cores in chip multiprocessors) can reduce end-to-end delay and energy consumption. While almost all previous works on mapping consider higher priority for the application's flows with higher required bandwidth, a mapping strategy, presented in this paper, is introduced that considers multicast communication flows in addition to the normal unicast flows. To this end, multicast and unicast traffic flows are first characterized in terms of some new metrics which are... 

In this paper, two different hybrid intelligent systems are applied to develop practical soft identifiers for modeling the tool-tissue force as well as the resulted maximum local stress in laparoscopic surgery. To conduct the system identification process, a 2D model of an in vivo porcine liver was built for different probing tasks. Based on the simulation, three different geometric features, i.e. maximum deformation angle, maximum deformation depth and width of displacement constraint of the reconstructed shape of the deformed body are extracted. Thereafter, two different fuzzy inference paradigms are proposed for the identification task. The first identifier is an adaptive co-evolutionary... 

In this paper, we study the impact of sensing error and channel fading on the decision process of a multiple secondary user network in a primary network whose channel occupancy states are modelled as a Bernoulli process. We present a randomized access strategy to maximize total secondary network throughput. The proposed method guarantees that the probability of collision between primary and secondary users in each channel is less than the predefined value of P c = ξ. To find the optimal access strategy, we formulate secondary network throughput as an optimization problem. Then, using the KKT method to find the solution, we break the original problem into multiple sub-problems. Then, we... 

Cost estimation plays an essential role in the development of aerospace systems that are perhaps the most complex, time- and labor-consuming ones. Regarding this matter, it is unavoidable to take a systematic approach to build a realistic model through a deliberative, heuristical and easy-to-do process in the early stages of design. In the current study, complexity index theory is utilized to develop a heuristic complexity-based method to estimate various costs of aerospace systems. This method promises to be logically and practically more reliable and accurate than classical parametric methods. Logically, manipulating a group of parameters, instead of only one or two, reduces the... 

Discrete kinematic synthesis of discretely actuated hyper-redundant manipulators is a new practical problem in robotics. The problem concerns with determining the type of each manipulator module from among several specific types, so that the manipulator could reach several specified target frames with the lowest error. This paper suggests using a breadth-first search method and a workspace mean frame to solve this problem. To reduce errors, two heuristic ideas are proposed: two-by-two searching method and iteration. The effectiveness of the proposed method is verified through several numerical problems  

Recently, AIDA/cube testers have been revealed to be useful in building distinguishers for several cryptography schemes. χ2 tests, on the other hand, are well known and extensively used for distinguishing purposes. In this study, the notion of multi-χ2 test and AIDA/cube testers are utilised to introduce the superpoly algebraic normal form monomial test through which the output of reduced round Trivium is distinguished from being random. The test successfully distinguishes the keystream of Trivium with 830 out of 1152 initialisation rounds with a complexity of 239 operations, which is the most effective distinguisher on reduced Trivium thus far. Applying algebraic IV differential attack... 

Natural earthquake disasters are unprecedented incidents which take many lives as a consequence and cause major damages to lifeline infrastructures. Various agencies in a country are responsible for reducing such adverse impacts within specific budgets. These responsibilities range from before to after the incident, targeting one of the main phases of disaster management (mitigation, preparedness, and response). Use of OR in disaster management and coordination of its phases has been mostly ignored and highly recommended in former reviews. This paper presents a formulation to coordinate three main agencies and proposes a heuristic approach to solve the different introduced sub-problems. The... 

In this paper a highly efficient optical diode is demonstrated in photonic crystal waveguides with broken spatial symmetry. The structure is made of isotropic linear materials and does not need high power optical beams or strong magnetic fields. While the proposed structure shows almost complete light transmission (>99%) in one direction, it blocks light transmission in the opposite direction. This unidirectional transmission is retained within a wide range of frequencies (>4% of central frequency). In order to achieve an optical diode effect, the optical mode of the waveguide is manipulated by designing an ultra-compact mode converter and an efficient mode filter. The dimensions of the... 

Network-on-Chips are now the popular communication medium to support inter-IP communications in complex on-chip systems with tens to hundreds IP cores. Higher scalability (compared to the traditional shared bus and point-to-point interconnects), throughput, and reliability are among the most important advantages of NoCs. Moreover, NoCs can well match current CAD methodologies mainly relying on modular and reusable structures with regularity of structural pattern. However, since NoCs are resource-limited, determining how to distribute application load over limited on-chip resources (e.g. switches, buffers, virtual channels, and wires) in order to improve the metrics of interest and satisfy... 

A new algorithm named random particle optimization algorithm (RPOA) for local path planning problem of mobile robots in dynamic and unknown environments is proposed. The new algorithm inspired from bacterial foraging technique is based on particles which are randomly distributed around a robot. These particles search the optimal path toward the target position while avoiding the moving obstacles by getting help from the robot's sensors. The criterion of optimal path selection relies on the particles distance to target and Gaussian cost function assign to detected obstacles. Then, a high level decision making strategy will decide to select best mobile robot path among the proceeded particles,... 

Data streams have some unique properties which make them applicable in precise modeling of many real data mining applications. The most challenging property of data streams is the occurrence of "concept drift". Recurring concepts is a type of concept drift which can be seen in most of real world problems. Detecting recurring concepts makes it possible to exploit previous knowledge obtained in the learning process. This leads to quick adaptation of the learner whenever a concept reappears. In this paper, we propose a learning algorithm called Pool and Accuracy based Stream Classification with some variations, which takes the advantage of maintaining a pool of classifiers to track recurring... 

In this study, a Discrete Particle Swarm Optimization (DPSO) algorithm is assimilated to solve the Transit Network Design Problem (TNDP). First, A Mixed Integer Model is developed for the TNDP. The solution methodology utilized here is made of two major elements. A route generation module is firstly developed to generate all the feasible transit lines. Through the second part, a DPSO algorithm is utilized to select the optimal set of lines from the constructed ones. The objective function is to maximize coverage index while satisfying the operator cost upper level constraints. The efficacy and accuracy of the implemented algorithms is compared with ones obtained by an enumeration process as... 

Economic design of a control chart involves determining its basic parameters such that a cost function is minimized. This design when statistical performance measures are also considered is referred to as the economic-statistical design. In this paper, a simplex-based Nelder-Mead algorithm is used in combination with a particle swarm meta-heuristic procedure to solve both the economic and economic-statistical designs of a MEWMA control chart. The application results on extensive simulation experiments show that the particle swarm can lead the Nelder-Mead algorithm to better results. Furthermore, a comparative study is performed on the performances of three different algorithms of the... 

Multiple sequence alignment (MSA) is one of the basic and important problems in molecular biology. MSA can be used for different purposes including finding the conserved motifs and structurally important regions in protein sequences and determine evolutionary distance between sequences. Aligning several sequences cannot be done in polynomial time and therefore heuristic methods such as genetic algorithms can be used to find approximate solutions of MSA problems. Several algorithms based on genetic algorithms have been developed for this problem in recent years. Most of these algorithms use very complicated, problem specific and time consuming mutation operators. In this paper, we propose a... 

Background: Real-time crash prediction models are often structured as general log-linear categorical models which must be calibrated using an extensive database. However, there is no method to optimally select the number of categories and the values that define the boundaries between categories when representing continuous measures as categorical variables within the log-linear model. This raises the question of how important the calibration is to the safety impacts estimated when using the crash prediction model. In this paper, we examined the impact that the process used to calibrate the crash prediction model has on estimates of safety impacts of a variable speed limit system. Methods:... 

The Burr III distribution properly approximates many familiar distributions such as Normal, Lognormal, Gamma, Weibull, and Exponential distributions. It plays an important role in reliability engineering, statistical quality control, and risk analysis models. The Burr III distribution has four parameters known as location, scale, and two shape parameters. The estimation process of these parameters is controversial. Although the maximum likelihood estimation (MLE) is understood as a straightforward method in parameters estimation, using MLE to estimate the Burr III parameters leads to maximize a complicated function with four unknown variables, where using a conventional optimization such as... 

Clustering Web data is one important technique for extracting knowledge from the Web. In this paper, a novel method is presented to facilitate the clustering. The method determines the appropriate number of clusters and provides suitable representatives for each cluster by inference from a Bayesian network. Furthermore, by means of the Bayesian network, the contents of the Web pages are converted into vectors of lower dimensions. The method is also extended for hierarchical clustering, and a useful heuristic is developed to select a good hierarchy. The experimental results show that the clusters produced benefit from high quality  

The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization... 

One of the main challenges of data streams is the occurrence of concept drift. Concept drift is the change of target (or feature) distribution, and can occur in different types: sudden, gradual, incremental or recurring. Because of the forgetting mechanism existing in the data stream learning process, recurring concepts has received much attention recently, and became a challenging problem. This paper tries to exploit the existence of recurring concepts in the learning process and improve the classification of data streams. It uses a pool of concepts to detect the reoccurrence of a concept using two methods: a Bayesian, and a heuristic method. Two approaches are used in the classification... 

In this paper, we consider the problem of making simultaneous decisions on the location, service rate (capacity) and the price of providing service for facilities on a network. We assume that the demand for service from each node of the network follows a Poisson process. The demand is assumed to depend on both price and distance. All facilities are assumed to charge the same price and customers wishing to obtain service choose a facility according to a Multinomial Logit function. Upon arrival to a facility, customers may join the system after observing the number of people in the queue. Service time at each facility is assumed to be exponentially distributed. We first present several...