This article proposes that visual encoding learning improves reading fluency by widening the span over which letters are recognized from a fixated text image so that fewer fixations are needed to cover a text line. Encoder is a connectionist model that learns to convert images like the fixated text images human readers encode into the corresponding letter sequences. The computational theory of ...

Collaborative networked organizations (CNOs) are complex entities whose proper understanding, design, implementation, and management require the integration of different modeling perspectives. A large number of modeling tools and theories that have been developed in other disciplines have a potential applicability in this domain. Therefore, an identification of the most promising approaches is ...

the problem of finding the minimum cost multi-commodity flow in an undirected and completenetwork is studied when the link costs are piecewise linear and convex. the arc-path model and overflowmodel are presented to formulate the problem. the results suggest that the new overflow model outperformsthe classical arc-path model for this problem. the classical revised simplex, frank and wolf and a ...

estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

In text analysis documents are often represented as disorganized bags of words; models of such count features are typically based on mixing a small number of topics [1,2]. Recently, it has been observed that for many text corpora documents evolve into one another in a smooth way, with some features dropping and new ones being introduced. The counting grid [3] models this spatial metaphor litera...

In the present study, we tested a computer-based procedure for assessing very concise summaries (50 words long) of two types of text (narrative and expository) using latent semantic analysis (LSA) in comparison with the judgments of four human experts. LSA was used to estimate semantic similarity using six different methods: four holistic (summary-text, summary-summaries, summary-expert summari...

In 2014 the International Journal for Academic Development (IJAD) issued a call papers ‘Beyond learning and teaching: Extending frontiers of academic development’. Though it was never published, conceptual definitional opacity that this special issue expected to address, along with prevalent epistemic parochialism, remain problematic development scholarship, article focuses on them. The incorpo...

E ective Static Debugging via Componential Set-Based Analysis by Cormac Flanagan Sophisticated software systems are inherently complex. Understanding, debugging and maintaining such systems requires inferring high-level characteristics of the system's behavior from a myriad of low-level details. For large systems, this quickly becomes an extremely di cult task. MrSpidey is a static debugger tha...

Automatic heart disease prediction is a major global health concern. Effective cardiac treatment requires an accurate prognosis. Therefore, this paper proposes new classification model based on the support vector machine (SVM) algorithm for improved detection. To increase accuracy, ?2 statistical optimum feature selection technique was used. The suggested model’s performance then validated by c...