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Efficient Adders to Speedup Modular Multiplication for Cryptography
Get PDFModular multiplication is an essential operation in many cryptography arithmetic operations. This work serves the modular multiplication algorithms focusing on improving their underlying binary adders. Different known adders have been considered and studied. The carry-save adder, carry-lookahead adder and carry-skip adder showed interesting features and trade-offs. The adders VHDL implementations gave some more beneficial details promising for improved crypto designs
Construction and analysis of educational tests using abductive machine learning
No full textRecent advances in educational technologies and the wide-spread use of computers in schools have fueled innovations in test construction and analysis. As the measurement accuracy of a test depends on the quality of the items it includes, item selection procedures play a central role in this process. Mathematical programming and the item response theory (IRT) are often used in automating this task. However, when the item bank is very large, the number of item combinations increases exponentially and item selection becomes more tedious. To alleviate the computational complexity, researchers have previously applied heuristic search and machine learning approaches, including neural networks, to solve similar problems. This paper proposes a novel approach that uses abductive network modeling to automatically identify the most-informative subset of test items that can be used to effectively assess the examinees without seriously degrading accuracy. Abductive machine learning automatically selects only effective model inputs and builds an optimal network model of polynomial functional nodes that minimizes a predicted squared error criterion. Using a training dataset of 1500 cases (examinees) and 45 test items, the proposed approach automatically selected only 12 items which classified an evaluation population of 500 cases with 91% accuracy. Performance is examined for various levels of model complexity and compared with that of statistical IRT-based techniques. Results indicate that the proposed approach significantly reduces the number of test items required while maintaining acceptable test quality
Stochastic Finite Element Analysis of the Free Vibration of Functionally Graded Material Plates
Get PDFApplication of PSO to design UPFC-based stabilizers
Get PDFToday, power demand grows rapidly and expansion in transmission and generation is restricted with the limited availability of resources and the strict environmental constraints. Consequently, power systems are today much more loaded than before. In addition, interconnection between remotely located power systems turned out to be a common practice. These give rise to low frequency oscillations in the range of 0.1-3.0 Hz. If not well damped, these oscillations may keep growing in magnitude until loss of synchronism results. Power system stabilizers (PSSs) have been used in the last few decades to serve the purpose of enhancing power system damping to low frequency oscillations. PSSs have proved to be efficient in performing their assigned tasks. The objective of this chapter is to investigate the potential of particle swarm optimization as a tool in designing UPFC-based stabilizers to improve power system transient stability. To estimate the controllability of each of the UPFC control signals on the electromechanical modes, singular value decomposition is employed. The problem of designing all the UPFCbased stabilizers individually is formulated as an optimization problem. Particle swarm optimizer is utilized to search for the optimum stabilizer parameter settings that optimize a given objective function. Coordinated design of the different stabilizers is also carried out by finding the best parameter settings for more than one stabilizer at a given operating condition in a coordinated manner
Arabic Text Steganography Using Multiple Diacritics
Get PDFSteganography techniques are concerned with hiding the existence of data in other cover media. Today, text steganography has become particularly popular. This paper presents a new idea for using Arabic text in steganography. The main idea is to superimpose multiple invisible instances of Arabic diacritic marks over each other. This is possible because of the way in which diacritic marks are displayed on screen and printed to paper. Two approaches and several scenarios are proposed. The main advantage is in terms of the arbitrary capacity. The approach was compared to other similar methods in terms of overhead on capacity. It was shown to exceed any of these easily, provided the correct scenario is chosen
Modeling and Analysis of Two-Flow Interactions in Wireless Networks
Get PDFInterference plays a complex and often defining role in the performance of wireless networks, especially in multi-hop scenarios. In the presence of interference, Carrier Sense Multiple Access MAC protocols are known to suffer from the hidden terminal and exposed terminal problems, which can cause poor performance and unfairness. In this paper, we examine the possible interference modes arising among two interfering one-hop connections under a Two-Disc model of interference. We classify the large set of resulting configurations into five categories and develop closed form expressions to compute their probability of occurrence. The analysis exposes two new categories, whose occurrence is common, and whose behavior differs significantly from the three known interference categories. Further, the frequency of occurrence of the categories differ significantly from existing results (obtained with a simpler unit disc model of interference). We develop throughput estimation models for the different categories and validate them using simulation
" A micro-controller based soft-starter for residential air conditioners: harmonic analysis"
No full textMeasurements of UWB through-the-wall propagation using spectrum analyzer and the Hilbert transform
No full textThis article presents a simplified approach for characterization of ultra wideband (UWB) through-the-wall propagation. The simplified approach requires spectrum analyzer rather than vector network analyzer. A minimum phase retrieval method based on Hilbert transform is used to retrieve the phase information. The proposed method is shown to be applicable to the insertion transfer function. While linear phase component cannot be retrieved, important factors for UWB receiver design such as group delay ripple and dispersion effect can be retrieved. In noisy channels, phase retrieval could be superior to direct phase measurements. Estimation of linear phase component can be achieved through matching the measured phase with the retrieved phase
Constructing optimal educational tests using GMDH-based item ranking and selection
No full textItem ranking and selection plays a key role in constructing concise and informative educational tests. Traditional techniques based on the item response theory (IRT) have been used to automate this task, but they require model parameters to be determined a priori for each item and their application becomes more tedious with larger item banks. Machine-learning techniques can be used to build data-based models that relate the test result as output to the examinees’ responses to various test items as inputs. With this approach, test item selection can benefit from the vast amount of literature on feature selection in many areas of machine learning and artificial intelligence that are characterized by high data dimensionality. This paper describes a novel technique for item ranking and selection using abductive network pass/fail classifiers based on the group method of data handling (GMDH). Experiments were carried out on a dataset consisting of the response of 2000 examinees to 45 test items together with the examinee's true ability level. The approach utilizes the ability of GMDH-based learning algorithms to automatically select optimum input features from a set of available inputs. Rankings obtained by iteratively applying this procedure are similar to those based on the average item information function (IIF) at the pass-fail ability threshold, IIF (θ=0), and the average information gain (IG). An optimum item subset derived from the GMDH-based ranking contains only one third of the test items and performs pass/fail classification with 91.2% accuracy on a 500-case evaluation subset, compared to 86.8% for a randomly selected item subset of the same size and 92% for a subset of the 15 items having the largest values for IIF (θ=0). Item rankings obtained with the proposed approach compare favorably with those obtained using neural network modeling and popular filter type feature selection methods, and the proposed approach is much faster than wrapper methods employing genetic search
Parallel Inverse Halftoning by Look-Up Table (LUT) Partitioning
Get PDFLook-Up Table (LUT) method for inverse halftoning is computation less, fast, and also yields goods results. It employs a single LUT that is stored in a ROM and contains pre-computed contone (gray level) values for inverse halftone operation. This paper proposes an algorithm that can perform parallel inverse halftone operation by partitioning the single LUT into N smaller Look-Up Tables (s-LUTs). Thereby, upto k (k≤N) pixels can be concurrently fetched from the halftone image, and their contone values can also be fetched concurrently from separate smaller Look-Up Tables (s-LUT). The parallelization increases the speed of inverse halftoning by upto k times while the total entries in all s-LUTs remains equal to the entries in the single LUT of the serial LUT method. Some degradation in image quality is possible due to pixel loss during parallel fetching. This is due to some contone values cannot be fetched in the same cycle because some other contone value is being fetched from the s-LUT. The complete implementation of the algorithm requires two CPLD devices for computational portion, external content addressable memories (CAM) and static RAMs to store s-LUTs