Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.     

A new approach to modelling of single droplet drying

A model was developed to predict the change in droplet mass and temperature when it is exposed to hot air, as in spray drying of droplets containing solids. The droplet was assumed first to undergo sensible rapid heating with no mass change. Then the droplet experiences some shrinkage, with no temperature change but rapid mass losses, followed by a period of crust formation with a significant change in droplet mass and temperature and finally a short period of sensible heating of the dried particle. The model, unlike previous models, accounts for shrinkage and for the temperature distribution in the droplet. It provided a good prediction for the change in droplet temperature and mass for some of the experimental measurements available in the literatures.     

Gastric ECL-cell hyperplasia produces enhanced basal and stimulated gastric acid output but not gastric erosion formation in the rat

Cervical involvement is one of the major prognostic factors in carcinoma of the endometrium confined to the uterus. The purpose of this study was to determine whether intrauterine ultrasound with a high-frequency miniature probe can depict the degree of cervical involvement of the disease. Thirty-two women with endometrial carcinoma underwent preoperative transvaginal and intrauterine sonography. By both scans, the degree of cervical involvement was prospectively evaluated. Sonograms were compared with the findings from histologic examination. Intrauterine sonography was completed in 30 of the 32 patients. In these 30 patients, the degree of cervical involvement (none, endocervical gland, or cervical stroma) based on transvaginal scan was correct in 23 cases (77%), and that based on intrauterine scan was correct in 26 cases (87%). Three tumors with endocervical glandular involvement were correctly diagnosed by intrauterine sonography, whereas they were incorrectly diagnosed by transvaginal scan. The specificity and positive predictive value of intrauterine sonography for the assessment of the presence of cervical stromal invasion are 100% (26/26 and 3/3, respectively). Although this study is preliminary, our experience with intrauterine sonography shows that it has potential for assessing cervical stromal invasion in endometrial carcinoma.     

Effect of short-term storage on phenolic content,o-diphenolase and peroxidase activities of cut yam tubers (Dioscorea sp)

The effect of short-term storage on the protein, phosphorus and phenolic content as well as peroxidase and o-diphenolase activities of cut, harvested Jamaican yam (Dioscorea sp) tubers (D rotundata. D alata and D cayenensis) was studied. There was an initial increase in the total phenolic content up to the third week of storage followed by a gradual decrease to the sixth week. Phenolic content was found to be highest in D cayenensis followed by D rotundata and D alata. The activities of peroxidase (EC 1. 11. 1. 7) and o-diphenolase (EC 1. 10.3.1) increased steadily up to the third week of storage and thereafter decreased to the fifth week. The intensity and rapidity of browning in tubers when cut, correlated very closely with the tuber o-diphenolase and phenolic content levels while the onset of rotting correlated with the peroxidase activity levels in the species studied.     

Morphological responses in thermally conditioned linear low density polyethylene

An octene-modified linear low density polyethylene has been used to examine the mechanisms involved during thermal annealing. Annealing temperatures ranged from 60 to 100°C. Annealing results in crystallinity increments and these respond to two concurrent effects. One involves the segregation from crystalline regions of low molecular weight moieties in the polymer's molecular weight distribution; the other is lamellar thickening, leading to the formation of more highly perfected crystalline domains. In the present polymer, the two effects were found to be in balance at annealing temperatures near 80°C leading to the optimum distribution of crystalline regions in the amorphous portions of the polymer. The effect of thermal conditioning on mechanical properties of the polymer was illustrated in terms of the initial modulus and the polymer's yield strength. The twin mechanisms of molecular fractionation and lamellar thickening were found to influence both of the mechanical property parameters.     

A novel silicon Schottky diode for NLTL applications

The design and simulation of a novel silicon Schottky diode for nonlinear transmission line (NLTL) applications is discussed in this paper. The Schottky diode was fabricated on a novel silicon-on-silicide-on-insulator (SSOI) substrate for minimized series resistance. Ion implantation technology was used as a low-cost alternative to molecular beam epitaxy to approximate the delta (/spl delta/) doping profile, which results in strong nonlinear CV characteristics. The equivalent circuit model of the Schottky diode under reverse bias conditions was extracted from the S-parameter measurement performed on the diode. The measured CV characteristics show strong nonlinearity, the junction capacitance varies from 182 to 47.5 fF as the reverse bias voltage is varied from 0 to -5 V. A parasitic inductance of 40 pH was measured for the silicon Schottky diode, which is much smaller than a comparable sized GaAs Schottky diode. This small inductance is an advantage for the silicon Schottky diode offering improvement in the silicon NLTL performance.     

Pyramid collaborative filtering technique for an intelligent autonomous guide agent

This article presents an autonomous guide agent that can observe a community of learners on the web, interpret the learners' inputs, and then assess their sharing. The goal of this agent is to find a reliable helper (tutor or other learner) to assist a learner in solving his task. Despite the growing number of Internet users, the ability to find helpers is still a challenging and important problem. Although helpers could have much useful information about courses to be taught, many learners fail to understand their presentations. For that, the agent must be able to deal autonomously with the following challenges: Do helpers have information that the learners need? Will helpers present information that learners can understand? And can we guarantee that these helpers will collaborate effectively with learners? We have developed a new filtering framework, called a pyramid collaborative filtering model, to whittle the number of helpers down to just one. We have proposed four levels for the pyramid. Moving from one level to another depends on three filtering techniques: domain model filtering, user model filtering, and credibility model filtering. A new technique is filtering according to helpers' credibilities. Our experiments show that this method greatly improves filtering effectiveness. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1065–1082, 2007.     

CONTEXTUALIZING LEARNING OBJECTS USING ONTOLOGIES

Educational research over the past three years has intensified such that the context of learning resources needs to be properly modeled. Many researchers have described and even mandated the use of ontologies in the research being conducted, yet the process of actually connecting one or more ontologies to a learning object has not been extensively discussed. This paper describes a practical model for associating multiple ontologies with learning objects while making full use of the IEEE LOM specification. The model categorizes these ontologies according to five major categories of context based on the most popular fields of study actively being pursued by the educational research community: Thematic context, Pedagogical context, Learner context, Organizational context, and Historical/Statistical context.