Majlesi Journal of Electrical Engineering
Volume:4 Issue: 2, Jun 2010

In this paper, the results of a finite element analysis are carried out on new stator geometry of a three phase longitudinal flux Linear Switched Reluctance Motor (LSRM). In the new geometry, pole shoes are affixed to the stator poles. Static and dynamic characteristics for the proposed structure have been highlighted. Motor performance for variable load conditions is discussed. The 2-Dimensional (2-D) finite element analysis (FEA) and the experimental results of this paper prove that LSRMs are one of the strong candidates for linear propulsion drive

Relevance feedback (RF) approaches are use to improve the performance of content-based image retrieval (CBIR) systems. In this paper, a RF approach based on modification of similarity measure using particle swarm optimization (PSO) in a medical X-ray image retrieval system is proposed. In this algorithm, using PSO, the significance of each feature in the similarity measure is modified to image retrieval. This modification causes that good features have major effect in relevant image retrieval. The defined fitness function in PSO uses relevant and irrelevant retrieved images with different strategies, simultaneously. The relevant and irrelevant images are used to exhort and penalize similarity measure, respectively. To evaluate, the proposed RF is integrated to a CBIR system based on semantic classification. In this system, using merging scheme in a hierarchical structure, the overlapped classes are merged together and determined search space for each query image. The proposed RF evaluated on a database consisting of 10000 medical X-ray images of 57 classes. The proposed algorithm provides the improvement, effectiveness more than the literature.

The problem of Economic Dispatch (ED) in electric power systems is to schedule the power output for each committed generator unit such that the operating cost is minimized and simultaneously, the customer load demand is matched and the generator operating limits are met. Nowadays with increasing awareness of environmental pollution caused by burning of fossil fuels, emission of pollutants is also a criterion for economic dispatch of the plants. The environmental objective of generation dispatch is to minimize the total environmental cost or the total pollutant emission. This paper presents an efficient and simple approach for solving the emission constrained economic dispatch problem using the proposed Hybrid Particle Swarm Optimization Technique (HPSO). The convergence and usefulness of the proposed HPSO is demonstrated through its application to a test system. The computational results reveal that the proposed algorithm has an excellent convergence characteristic and has the potential to apply to other power system problems.

Enterprises are now global, virtual and dependent on dynamic information access. Naturally, digital information is constant throughout its lifecycle. In this shifting landscape, the battlefront in security is rapidly changing from securing the perimeter to protecting the information itself. The primary advantage of public-key cryptography is increased security and convenience: private keys never need to be transmitted or revealed to anyone, but loss of a private key may cause the loss of valuable data. In this paper, we proposed a new method of using iris biometric instead of private keys, so that the iris cannot be lost, stolen or even misused. The two first stages of iris recognition are implemented as the preliminary result. Our approach is feasible to produce an iris template for using as a private key in identity identification and biometric watermarking applications.

Motion estimation (ME) is a part of video codecs which results in further compression of video data. But it requires a huge amount of computations. To overcome this drawback, there have been offered too many techniques yet. In this paper with the aid of fuzzy inference, an efficient algorithm is devised. The proposed algorithm exploits spatial correlation as well as temporal correlation among motion vectors. This algorithm uses fuzzy rules to determine the initial motion vector. After that, a local search around initial vector is carried out. In order to decrease the complexity of the algorithm, a look-up table is used. In this table, defuzzified values are stored. Also, to further reduction of complexity, few computations are performed in the proposed algorithm for stationary and quasi stationary blocks. To determine which block can be regarded as stationary or quasi stationary block, a simple comparison with a predefined threshold is done. The experimental results show that the proposed algorithm performs better than other fast block matching algorithms in terms of picture quality and computational complexity.

In this paper, we develop a non-visual automatic wrapper to extract data records from search engine results pages which contain important information for computer users. Our wrapper consists of a series of data filter to detect and remove irrelevant data from the web page. In the filtering stages, we incorporate two main algorithms which are able to check the similarity of data records and to detect and extract the correct data region based on their component sizes. To evaluate the performance of our algorithm, we carry out experimental and deletion tests. Experimental tests show that our wrapper outperforms the existing state of the art wrappers such as ViNT and DEPTA. Deletion studies by replacing our novel techniques with state of the art conventional techniques show that our wrapper design is efficient and could robustly extract data records from search engine results pages. With the speed advantages, our wrapper could be beneficial in processing large amount of web sites data, which could be helpful in meta search engine development.

Nowadays using DG (distributed generation) in vast variety of cases has been more considerable due to its beneficial advantages, but interconnecting DG to radial distribution systems has some impact on the coordination of protection devices. The main point in the protection scheme is the diagnosis of fault locations, so producing a new method to identify fault location with high accuracy is necessary.This paper presents a novel approach to fault location identification with DG in distributed systems by the means of neural networks. According to this method using a distributed system as intentional islanding in necessary conditions is pos­s­­ible and reduces the ENS (Energy Not Supplied) of the net. Using separate NNs (neural networks) for each island (zone) will increase the accuracy of this method. Impl­e­m­entation results of this scheme on actual distributed systems has been simulated and reported

In this paper, we propose a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD). The proposed method consists of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization using genetic algorithms (GA) to perform efficient and effective noise removal. Our idea is to utilize MAD and ROAD as measures of noise probability of a pixel. Fuzzy inference system is used to justify the degree of which a pixel can be categorized as noisy. Based on the fuzzy inference result, the fuzzy switching scheme that adopts median filter as the main estimator is applied to the filtering. The GA training aims to find the best parameters for the fuzzy sets in the fuzzy noise detection. By the experimental results, the proposed method has successfully removed mixed impulse noise in low to medium probabilities, while keeping the uncorrupted pixels less affected by the median filtering. It also surpasses the other methods, either classical or soft computing-based approaches to impulse noise removal, in MAE and PSNR evaluations.