Sharif Digital Repository

This paper presents a stochastic model for optimal generating units' restoration planning. Restoration plans will be performed based on different objectives i.e. total system risk, total served energy in the period of restoration, and total restoration time. The proposed model is a multi objective stochastic program in which generating units' restoration plan is assumed to optimize different kinds of objective function. The proposed approach to the optimal restoration of generating units can be used by vertically integrated utilities as well as the ISOs in electricity markets. The approach coordinates the optimal start up of generating units within the restoration period. Physical... 

This paper presents a novel sectionalizing method for the build-up strategy in power system restoration. Power system restoration is the procedure of restoring power system elements after a partial or a complete blackout. Because of its economic and political importance, different strategies have been developed for power system restoration. One of the most practical and economical is the build-up strategy that includes the process of restoring separated parts (islands) in the power system and interconnecting them afterwards. This paper intends to develop a systematic algorithm for sectionalizing a power system considering various constraints such as black-start capability of generators,... 

We study a new class of visibility problems based on the notion of α-visibility. Given an angle α and a collection of line segments in the plane, a segment t is said to be α-visible from a point p, if there exists an empty triangle with one vertex at p and the side opposite to p on t such that the angle at p is α. In this model of visibility, we study the classical variants of point visibility, weak and complete segment visibility, and the construction of the visibility graph. We also investigate the natural query versions of these problems, when α is either fixed or specified at query time  

We study a new class of visibility problems based on the notion of α-visibility. Given an angle α and a collection of line segments S in the plane, a segment t is said to be α-visible from a point p, if there exists an empty triangle with one vertex at p and the side opposite to p on t such that the angle at p is α. In this model of visibility, we study the classical variants of point visibility, weak and complete segment visibility, and the construction of the visibility graph. We also investigate the natural query versions of these problems, when α is either fixed or specified at query time  

Motivated by the bus escape routing problem in printed circuit boards, we study the following rectangle escape problem: given a set S of n axis-aligned rectangles inside an axis-aligned rectangular region R, extend each rectangle in S toward one of the four borders of R so that the maximum density over the region R is minimized. The density of each point p∈R is defined as the number of extended rectangles containing p. We show that the problem is hard to approximate to within a factor better than 3/2 in general. When the optimal density is sufficiently large, we provide a randomized algorithm that achieves an approximation factor of 1+ε with high probability improving over the current best... 

In this research, the modal parameters of a beam in free-free condition are extracted by performing different experiments in the laboratory. For this purpose, two different techniques are employed. The first methodology is considered as a time domain method in Operational Modal Analysis. The other one is frequency domain impact hammer test which is categorized as an Experimental Modal Analysis method and can be regarded as the most common method in modal analysis. Checking the results obtained by the two methods, one can notice a distinct inconsistency in modal damping ratios extracted by each method. However, based on recent publications on the subject, it can be inferred that the time... 

Motivated by the bus escape routing problem in printed circuit boards, we revisit the following problem: given a set of n axis-parallel rectangles inside a rectangular region R, find the maximum number of rectangles that can be extended toward the boundary of R, without overlapping each other. We provide an efficient algorithm for solving this problem in O(n2 log3 n log log n) time, improving over the current best O(n3)-time algorithm available for the problem  

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

There are different choices for auction and settlement mechanisms in electricity markets; however, selecting the appropriate mechanisms is too hard. Traditionally, the offer cost minimization (OCM) mechanism that minimizes the total offer cost is used as the clearing mechanism, and payments are calculated based on locational marginal prices (LMPs). Under this setup, the clearing and settlement mechanisms are inconsistent, since the minimized cost is different from the total payment cost. Some recent studies have proposed the payment cost minimization (PCM) mechanism. However, the discussion is still open, and different aspects of these mechanisms are yet needed to be analyzed. This paper... 

The main focus of this study is on reserve market settlement in an electricity market with marginal pricing scheme as the pricing mechanism. Following a day-ahead market clearing, the marginal prices are found using the appropriate Lagrange multipliers as the bi-products of the optimisation process. The payments to energy and reserve providers can then be found based on these prices. However, it is hard to find an appropriate settlement scheme that provides the fair and justifiable consumer payments based on marginal pricing scheme considering the actual reserve functions in power systems. In this study, a reserve marginal pricing that is based on a proper reserve marginal price definition... 

Among the different options available for market clearing mechanisms, offer cost minimisation mechanism is being used in most electric power markets. The payments are then calculated based on locational marginal prices (LMPs). The payments can be significantly higher due to the inconsistency of the clearing and pricing mechanisms. Payment cost minimisation (PCM) mechanism which directly minimises the total payment has been recently proposed to solve this issue. In this study, an auction mechanism is proposed for payment to suppliers minimisation (PSM) based on the LMPs instead of consumers payment minimisation (CPM). Using a proper formulation for the supply side reserve LMPs, the complete... 

The development of polymer-based composites with thermal transport capability has now become essential in response to the efficient thermal management required in electronic and energy conversion devices. In this work, a novel hybrid filler consisting of graphene nanoplatelet (GNP) and boron nitride microparticles (micro-BN) is used to improve the thermal conductivity of epoxy composite. The GNPs with an average lateral size of 8 µm and an average thickness of 5 nm are in the same volume range with the 1 µm size micro-BN particles. According to the results, the thermal conductivity of the composites changes abruptly with increasing micro-BN loading at fixed GNP loading, which is attributed... 

The use of hybrid filler is a promising strategy for development of thermally conductive polymer composites. This paper reported the measurement of thermal conductivity of the epoxy composite filled with a hybrid filler of graphene nanoplatelet (GNP) and silicon carbide (SiC) microparticles. For this hybrid filler, the effect of the average size of SiC on composite thermal conductivity was examined. The results showed that the thermal synergistic effect was highly affected by the average size of the SiC. By using a hybrid filler of 11% vol. GNP and 9% vol. 1 µm-size SiC micro-particles thermal conductivity has reached 3.44 W m−1 K−1. This value is 42% higher than the thermal conductivity of... 

Data are presented on the solidification of aluminum alloys and their macro segregation behavior. Three alloys with different solidification ranges were prepared in two temperatures. Two types of molds were also prepared by sand and metallic materials. The solidification of Al alloys were studied and the effects of four parameters were determined, including cooling rate, casting temperature, degassing and nucleation effects on solidification and a comparison was conducted to Scheil model performance. Three types of aluminum alloys (Al-12.1%Si, Al-6.9%Si and Al-4.4% Cu) with short, medium and wide solidification ranges were studied and the results showed that degassing, nucleation, increasing... 

For a simple polygon P of size n, we define weak visibility counting problem (WVCP) as finding the number of visible segments of P from a query line segment pq. We present different algorithms to compute WVCP in sub-linear time. In our first algorithm, we spend O(n7) time to preprocess the polygon and build a data structure of size O(n6), so that we can optimally answer WVCP in O(logn) time. Then, we reduce the preprocessing costs to O(n4+ε) time and space at the expense of more query time of O(log5n). We also obtain a trade-off between preprocessing and query time costs. Finally, we propose an approximation method to reduce the preprocessing costs to O(n2) time and space and O(n1/2+ε) query... 

We revisit the problem of finding (Formula presented.) paths with a minimum number of shared edges between two vertices of a graph. An edge is called shared if it is used in more than one of the (Formula presented.) paths. We provide a (Formula presented.)-approximation algorithm for this problem, improving the best previous approximation factor of (Formula presented.). We also provide the first approximation algorithm for the problem with a sublinear approximation factor of (Formula presented.), where (Formula presented.) is the number of vertices in the input graph. For sparse graphs, such as bounded-degree and planar graphs, we show that the approximation factor of our algorithm can be... 

We revisit the problem of finding k paths with a minimum number of shared edges between two vertices of a graph. An edge is called shared if it is used in more than one of the k paths. We provide a ⌊k/2⌋-approximation algorithm for this problem, improving the best previous approximation factor of k - 1. We also provide the first approximation algorithm for the problem with a sublinear approximation factor of O(n3/4), where n is the number of vertices in the input graph. For sparse graphs, such as bounded-degree and planar graphs, we show that the approximation factor of our algorithm can be improved to O(√n). While the problem is NP-hard, and even hard to approximate to within an O(log n)... 

Localization and quantification of structural damage and estimating the failure probability are key outputs in the reliability assessment of structures. In this study, an Artificial Neural Network (ANN) is used to reduce the computational effort required for reliability analysis and damage detection. Toward this end, one demonstrative structure is modeled and then several damage scenarios are defined. These scenarios are considered as training data sets for establishing an ANN model. In this regard, the relationship between structural response (input) and structural stiffness (output) is established using ANN models. The established ANN is more economical and achieves reasonable accuracy in... 

Recognition of human speech has long been a hot topic among artificial intelligence and signal processing researches. Most of current policies for this subject are based on extraction of precise features of voice signal and trying to make most out of them by heavy computations. But this focus on signal details has resulted in too much sensitivity to noise and as a result, the necessity of complex noise detection and removal algorithms, which composes a trade-off between fast or noise robust recognition. This paper presents a novel approach to speech recognition using fuzzy modeling and decision making that ignores noise instead of its detection and removal. To do so, the speech spectrogram... 

There are several approaches to emotions in AI, most of which are inspired by human emotional states and their arousal mechanisms. These approaches usually use high-level models of human emotions that are too complex to be directly applicable in simple artificial systems. It seems that a new approach to emotions, based on their functional role in information processing in mind, can help us to construct models of emotions that are both valid and simple. In this paper, we will try to present a model of emotions based on their role in controlling the attention. We will evaluate the performance of the model and show how it can be affected by some structural and environmental factors. © 2008 The...