Structure Selection of Polynomial NARX Models using Two Dimensional (2D) Particle Swarms

The present study applies a novel two-dimensional learning framework (2D-UPSO) based on particle swarms for structure selection of polynomial nonlinear auto-regressive with exogenous inputs (NARX) models. This learning approach explicitly incorporates the information about the cardinality (i.e., the number of terms) into the structure selection process. Initially, the effectiveness of the proposed approach was compared against the classical genetic algorithm (GA) based approach and it was demonstrated that the 2D-UPSO is superior. Further, since the performance of any meta-heuristic search algorithm is critically dependent on the choice of the fitness function, the efficacy of the proposed approach was investigated using two distinct information theoretic criteria such as Akaike and Bayesian information criterion. The robustness of this approach against various levels of measurement noise is also studied. Simulation results on various nonlinear systems demonstrate that the proposed algorithm could accurately determine the structure of the polynomial NARX model even under the influence of measurement noise

Adaptive Protection and Control in Power System for Wide-Area Blackout Prevention

This paper presents a new approach in adaptive outof-step (OOS) protection settings in power system in real-time. The proposed method uses extended equal area criterion (EEAC) to determine the critical clearing time (CCT) and critical clearing angle (CCA) of the system, which are vital information for OOS protection setting calculation. The dynamic model parameters and the coherency groups of the system for EEAC analysis are determined in real time to ensure that the newly calculated settings suit with the prevalent system operating condition. The effectiveness of the method is demonstrated in a simulated data from 16-machine 68-bus system model

Provisions of Quran Tajweed Ontology (Articulations Points of the Letters, UN Vowel Noon and Tanween)

The Holy Quran has rules that the reader must learn so that he can read the Qur'an correctly (Tajweed).The objective of this research is to design an ontology for some of Tajweed (Articulations Points of the Letters, Un Vowel Noon and Tanween) to support the learning of this part of Tajweed and to facilitate the sharing of knowledge with the other Holy Quran applications. In order to achieve this goal, the researchers adopted the applied approach using protégé framework with OWL to the provisions build the Ontology. The provisions of Quran Tajweed Ontology (Articulations Points of the Letters, Un Vowel Noon and Tanween) use knowledge representation to define the key concepts in Un Vowel Noon and Tanween (Clearness, Merge, Hiding, Change) and The Letters Articulations, and show the relationships between these concepts and its properties. The fundamental concepts in the ontology are based on the knowledge extracting from the Books of Tajweed, and some verses of the Holy Quran to infer the Provisions. The designed ontology can retrieves information about Articulations Points of the Letters, Un Vowel Noon and Tanween. Furthermore, it can be shared and reused in applications related to Holy Quran Tajweed

Provisions of Quran Tajweed Ontology (Articulations Points of the Letters, UN Vowel Noon and Tanween)

The Holy Quran has rules that the reader must learn so that he can read the Qur'an correctly (Tajweed).The objective of this research is to design an ontology for some of Tajweed (Articulations Points of the Letters, Un Vowel Noon and Tanween) to support the learning of this part of Tajweed and to facilitate the sharing of knowledge with the other Holy Quran applications. In order to achieve this goal, the researchers adopted the applied approach using protégé framework with OWL to the provisions build the Ontology. The provisions of Quran Tajweed Ontology (Articulations Points of the Letters, Un Vowel Noon and Tanween) use knowledge representation to define the key concepts in Un Vowel Noon and Tanween (Clearness, Merge, Hiding, Change) and The Letters Articulations, and show the relationships between these concepts and its properties. The fundamental concepts in the ontology are based on the knowledge extracting from the Books of Tajweed, and some verses of the Holy Quran to infer the Provisions. The designed ontology can retrieves information about Articulations Points of the Letters, Un Vowel Noon and Tanween. Furthermore, it can be shared and reused in applications related to Holy Quran Tajweed

Chronic hyperplastic candidosis/candidiasis (candidal leukoplakia)

Chronic hyperplastic candidosis/candidiasis (CHC; syn. candidal leukoplakia) is a variant of oral candidosis that typically presents as a white patch on the commissures of the oral mucosa. The major etiologic agent of the disease is the oral fungal pathogen Candida predominantly belonging to Candida albicans, although other systemic co-factors, such as vitamin deficiency and generalized immune suppression, may play a contributory role. Clinically, the lesions are symptomless and regress after appropriate antifungal therapy and correction of underlying nutritional or other deficiencies. If the lesions are untreated, a minor proportion may demonstrate dysplasia and develop into carcinomas. This review outlines the demographic features, etiopathogenesis, immunological features, histopathology, and the role of Candida in the disease process. In the final part of the review, newer molecular biological aspects of the disease are considered together with the management protocols that are currently available, and directions for future research.published_or_final_versio

Straighthead disease of rice (Oryza sativa L.) induced by arsenic toxicity

Straighthead disease is a physiological disorder of rice (Oryza sativa L.) characterized by sterility of the florates/spikelets leading to reduced grain yield. Though the exact cause of straighthead is unknown, a glass house experiment was conducted to investigate the effect of inorganic arsenic on straighthead disease in rice (Oryza sativa L.). BRRI dhan 29, a popular Bangladeshi rice strain, was grown in soils spiked with arsenic (prepared from sodium arsenate, Na2HAsO4·7H2O) at the rate of 10, 20, 30, 40, 50, 60, 70, 80 and 90 mg of As kg-1 and one control treatment was also run to compare the results. Although there may be some other soil physico-chemical factors involved, arsenic concentration was found to be closely associated with straighthead of rice. With the increase of soil arsenic concentration, the severity of straighthead increased significantly. Up to the 50 mg of As kg-1 soil treatments, the severity of straighthead incidences were not prevalent. Straighthead resulted in sterile florets with distorted lemma and palea, reduced plant height, tillering, panicle length and grain yield. Straighthead caused approximately 17-100% sterile florates/spikelets formation and about 16-100% loss of grain yield. Straighthead also causes the reduction of panicle formation and panicle length significantly (p < 0.01). In the present study, panicle formation was found to be reduced by 21-95% by straighthead. © 2007 Elsevier B.V. All rights reserved

Seed and Seedling Anatomy in Euterpe oleraceae Mart. during the Germination Process

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Arsenic accumulation in rice (Oryza sativa L.) varieties of Bangladesh: A glass house study

A glass house study was conducted to investigate the accumulation of arsenic in tissues of five widely cultivated rice (Oryza sativa L.) varieties of Bangladesh namely BRRI dhan 28, BRRI dhan 29, BRRI dhan 35, BRRI dhan 36, BRRI hybrid dhan 1. Arsenic concentrations were measured in straw, husk and brown and polish rice grain to see the differential accumulation of arsenic among the rice varieties. The results showed that the concentrations of arsenic in different parts of all rice varieties increased significantly (p BRRI dhan 35 > BRRI dhan 36 > BRRI dhan 29 > BRRI hybrid dhan 1. The order of arsenic contents in tissues of rice was: straw > husk > brown rice grain > polish rice grain. © 2007 Springer Science+Business Media B.V