Current Issue : July - September Volume : 2013 Issue Number : 3 Articles : 6 Articles
Since its introduction, the basin hopping (BH) framework has proven useful for hard nonlinear optimization problems with\r\nmultiple variables and modalities. Applications span a wide range, from packing problems in geometry to characterization of\r\nmolecular states in statistical physics. BH is seeing a reemergence in computational structural biology due to its ability to obtain a\r\ncoarse-grained representation of the protein energy surface in terms of local minima. In this paper, we show that the BH framework\r\nis general and versatile, allowing to address problems related to the characterization of protein structure, assembly, and motion\r\ndue to its fundamental ability to sample minima in a high-dimensional variable space. We show how specific implementations\r\nof the main components in BH yield algorithmic realizations that attain state-of-the-art results in the context of ab initio protein\r\nstructure prediction and rigid protein-protein docking.We also show that BH can map intermediate minima related with motions\r\nconnecting diverse stable functionally relevant states in a protein molecule, thus serving as a first step towards the characterization\r\nof transition trajectories connecting these states....
We propose a new approach for determining the adequate sense of Arabic words. For that, we propose an algorithm based\r\non information retrieval measures to identify the context of use that is the closest to the sentence containing the word to be\r\ndisambiguated. The contexts of use represent a set of sentences that indicates a particular sense of the ambiguous word. These\r\ncontexts are generated using the words that define the senses of the ambiguous words, the exact string-matching algorithm, and\r\nthe corpus. We use the measures employed in the domain of information retrieval, Harman, Croft, and Okapi combined to the\r\nLesk algorithm, to assign the correct sense of those proposed....
Transistors are the basic building blocks of any circuit. As the conventional metal oxide field-effect transistor (MOSFET) is scaled down, quantum mechanical effects become dominant. It is required to have accurate quantum transport simulators to explore the essential device physics as a design aid. However, due to the complexity of the analysis, it is very important to simulate the quantum mechanical model with high speed and accuracy. In this paper, the modeling of Transistor based on an adaptive neuro-fuzzy inference system (ANFIS) is presented whose main strength are that they are universal approximators with the ability to solicit interpretable IF-THEN rules. The ANFIS model reduces the computational time while keeping the accuracy of physics-based models. Finally, the ANFIS model is imported into the circuit simulator software as a sub circuit. The results have shown that the compact model based on ANFIS is an efficient tool for the simulation of nanoscale circuits....
This paper compares the two preference artificial intelligent (AI) techniques, namely, artificial neural network (ANN) and genetic\r\nalgorithm optimized least square support vector machine (GA-LSSVM) approach, to allocate the real power output of individual\r\ngenerators to system loads. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine\r\nreal power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized\r\nto estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to\r\nillustrate the effectiveness of the AI techniques compared to those of the MNE method. The AI methods provide the results in a\r\nfaster and convenient manner with very good accuracy....
We propose a preprocessing method to improve the performance of Principal Component Analysis (PCA) for classification\r\nproblems composed of two steps; in the first step, the weight of each feature is calculated by using a feature weighting method.\r\nThen the features with weights larger than a predefined threshold are selected. The selected relevant features are then subject to\r\nthe second step. In the second step, variances of features are changed until the variances of the features are corresponded to their\r\nimportance. By taking the advantage of step 2 to reveal the class structure, we expect that the performance of PCA increases in\r\nclassification problems. Results confirm the effectiveness of our proposed methods....
This paper proposes a new mechanism for pruning a search game tree in computer chess. The algorithm stores and then reuses\r\nchains or sequences of moves, built up fromprevious searches. Thesemove sequences have a built-in forward-pruningmechanism\r\nthat can radically reduce the search space. A typical search process might retrieve a move from a Transposition Table, where the\r\ndecision of what move to retrieve would be based on the position itself. This algorithm stores move sequences based on what\r\nprevious sequences were better, or caused cutoffs. The sequence is then returned based on the current move only. This is therefore\r\nposition independent and could also be useful in games with imperfect information or uncertainty, where the whole situation is\r\nnot known at any one time. Over a small set of tests, the algorithm was shown to clearly out perform Transposition Tables, both in\r\nterms of search reduction and game-play results. Finally, a completely new search process will be suggested for computer chess or\r\ngames in general....
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