A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

Electrical and magnetic properties of lithium borate glass containing iron

Journal of Materials Science Letters -     

Effect of the addition of Fe2O3 and heat treatment duration on the magnetic susceptibility of V2O5-P2O5-B2O3 glass system

The effect of the addition of Fe₂O₃ and heat treatment duration on the magnetic susceptibility of vanadium borophosphate glass were studied. The magnetic susceptibility of glass samples was found to increase with increasing Fe₂O₃ content, which may be explained by the formation of the FeO₆ group and the change of Fe²⁺ to Fe³⁺ which has higher paramagnetic properties. No detectable changes in the magnetic susceptibility with heat treatment for the samples containing 0.0, 0.5 and 1.0 mol% Fe₂O₃ was observed. The magnetic susceptibility for the heat treated samples containing 2.5, 5.0 and 7.5 mol% Fe₂O₃ decreases sharply with increasing duration of heat treatment up to 6 h and then remains almost constant. The sharp decrease in magnetic susceptibility of 2.5 mol% Fe₂O₃ is attributed to the increase in the number of ferrous ions. The sharp decrease for samples containing 5.0 and 7.5 mol% Fe₂O₃ is attributed to the increase in the number of Fe³⁺ in tetrahedral co-ordination. The rate of crystallization owing to the heat treatment was calculated and was found to increase with increasing iron oxide content. The geometry of crystallization was found to be in three-, two-and one-dimension(s) for samples containing 2.5, 5.0 and 7.5 mol% Fe₂O₃, respectively.     

Studies on the interactions of metal oxides and Na2 SO4 at 1100 and 1200 K in oxygen

The interaction of different metal oxides such as Co₃O₄, NiO, Al₂O₃, Cr₂O₃, Fe₂O₃ and SiO₂ with Na₂SO₄ at a temperature of 1100 and 1200 K in flowing oxygen has been studied. The thermogravimetric studies for each system were carried out as a function of Na₂SO₄ in the mixture. The presence of different constituents in the reaction products were identified by X-ray diffraction analysis and the morphologies of the reaction products were characterized using metallography and scanning electron microscopy (SEM). The formation of products was also investigated by thermodynamic computation of free energies of the reactions and the study of relevant equilibrium phase diagrams. The soluble species in the aqueous solutions of the reaction products were determined quantitatively using atomic absorption spectrophotometry. The high temperature interaction products usually contain a 3-phase structure namely, Na₂O·M₂O _x , M₂O _x and metal sulphide and/or metal sulphate. The formation of Na₂O·M₂O _x depends upon the solid state solubility of metal oxide in the molten salt at high temperatures. Under limited solubility conditions Na₂O·M₂O _x is invariably formed, but as soon as this condition is relaxed the oxide. M₂O _x , precipitates and forms a separate phase.     

The flame retardant mechanism of polyolefins modified with chalk and silicone elastomer

This paper presents the current understanding of the flame retardant mechanism of Casico?. The study includes the flame retardant effect of each individual component: ethylene–acrylate copolymer, chalk and silicone elastomer, as well as the formation of an intumescent structure during heating. The flame retardant properties were investigated by cone calorimetry and oxygen index tests. To obtain insight into the flame retardant mechanism, heat treatment under different conditions has also been performed. The results indicate that the flame retardant mechanism of Casico is complex and is related to a number of reactions, e.g. ester pyrolysis of acrylate groups, formation of carbon dioxide by reaction between carboxylic acid and chalk, ionomer formation and formation of an intumescent structure stabilized by a protecting char. Special emphasis is given to the formation of the intumescent structure and its molecular structure as evaluated from ¹³C MAS‐NMR and ²⁹Si MAS‐NMR, ESCA and XRD analysis. After treatment at 500°C the intumescent structure consists mainly of silicon oxides and calcium carbonate and after treatment at 1000°C the intumescent structure consists of calcium silicate, calcium oxide and calcium hydroxide. Copyright © 2003 John Wiley & Sons, Ltd.     

Effect of epitaxial realignment on the leakage behavior of arsenic-implanted,as-deposited polycrystalline Si-on-single crystal Si diodes

When dopants are indiffused from a heavily implanted polycrystalline silicon film deposited on a silicon substrate, high thermal budget annealing can cause the interfacial “native” oxide at the polycrystalline silicon-single crystal silicon interface to break up into oxide clusters, causing epitaxial realignment of the polycrystalline silicon layer with respect to the silicon substrate. Anomalous transient enhanced diffusion occurs during epitaxial realignment and this has adverse effects on the leakage characteristics of the shallow junctions formed in the silicon substrate using this technique. The degradation in the leakage current is mainly due to increased generation-recombination in the depletion region because of defect injection from the interface.     

Design and implementation of a new tuned hybrid intelligent model to predict the uniaxial compressive strength of the rock using SFS-ANFIS

This study proposes a novel design to systematically optimize the parameters for the adaptive neuro-fuzzy inference system (ANFIS) model using stochastic fractal search (SFS) algorithm. To affirm the efficiency of the proposed SFS-ANFIS model, the predicting results were compared with ANFIS and three hybrid methodologies based on ANFIS combined with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO). Accurate prediction of uniaxial compressive strength (UCS) is of great significance for all geotechnical projects such as tunnels and dams. Hence, this study proposes the use of SFS-ANFIS, GA-ANFIS, DE-ANFIS, PSO-ANFIS, and ANFIS models to predict UCS. In this regard, the fresh water tunnel of Pahang–Selangor located in Malaysia was considered and the requirement data samples were collected. Different statistical metrics such as coefficient of determination (R²) and mean absolute error were used to evaluate the models. Referring to the efficiency results of SFS-ANFIS, it can be found that the SFS-ANFIS (with the R² of 0.981) has higher ability than PSO-ANFIS, DE-ANFIS, GA-ANFIS, and ANFIS models in predicting the UCS.

     

A novel chaotic Henry gas solubility optimization algorithm for solving real-world engineering problems

The paper proposes a novel metaheuristic based on integrating chaotic maps into a Henry gas solubility optimization algorithm (HGSO). The new algorithm is named chaotic Henry gas solubility optimization (CHGSO). The hybridization is aimed at enhancement of the convergence rate of the original Henry gas solubility optimizer for solving real-life engineering optimization problems. This hybridization provides a problem-independent optimization algorithm. The CHGSO performance is evaluated using various conventional constrained optimization problems, e.g., a welded beam problem and a cantilever beam problem. The performance of the CHGSO is investigated using both the manufacturing and diaphragm spring design problems taken from the automotive industry. The results obtained from using CHGSO for solving the various constrained test problems are compared with a number of established and newly invented metaheuristics, including an artificial bee colony algorithm, an ant colony algorithm, a cuckoo search algorithm, a salp swarm optimization algorithm, a grasshopper optimization algorithm, a mine blast algorithm, an ant lion optimizer, a gravitational search algorithm, a multi-verse optimizer, a Harris hawks optimization algorithm, and the original Henry gas solubility optimization algorithm. The results indicate that with selecting an appropriate chaotic map, the CHGSO is a robust optimization approach for obtaining the optimal variables in mechanical design and manufacturing optimization problems.