This paper describes in very general terms a strategy for converting the retrospective catalogs of the nation's research libraries into machine readable form. The method envisages a class-by-class conversion and printing out in main entry order of the shelflist of the Library of Congress. The larger libraries would compare their shelflists against these lists adding their location symbols and u...

Any program, machine or person engaged in computerenabled work is a cyber agent. Can such agents be made collaborate effectively? Both empirical evidence and theory suggest that there are simple rules for designing certain problem-solving organizations, called asynchronous teams, in which collaboration is automatic and scaleeffective (adding cyber agents tends to improve solutionquality, and ad...

We experiment with adding semantic role information to a string-to-tree machine translation system based on the rule extraction procedure of Galley et al. (2004). We compare methods based on augmenting the set of nonterminals by adding semantic role labels, and altering the rule extraction process to produce a separate set of rules for each predicate that encompass its entire predicate-argument...

Machine Translation is one of the major oldest and the most active research area in Natural Language Processing. Currently, Statistical Machine Translation (SMT) dominates the Machine Translation research. Statistical Machine Translation is an approach to Machine Translation which uses models to learn translation patterns directly from data, and generalize them to translate a new unseen text. T...

Treating a human mind like a machine is an essential component of dehumanization, whereas attributing a humanlike mind to a machine is an essential component of anthropomorphism. Here we tested how a cue closely connected to a person's actual mental experience-a humanlike voice-affects the likelihood of mistaking a person for a machine, or a machine for a person. We predicted that paralinguisti...

We present a systematic study of the effect of crowdsourced translations on Machine Translation performance. We compare Machine Translation systems trained on the same data but with translations obtained using Amazon’s Mechanical Turk vs. professional translations, and show that the same performance is obtained from Mechanical Turk translations at 1/5th the cost. We also show that adding a Mech...

Multi-objective optimization problems are often accompanied by complex black-box functions which not only increases the difficulty of solving, but also solving time. In order to reduce computational cost such multi-objective problems, this paper proposes an ARBF-MLPA (Adaptive Radial Basis Function neural network combined with Machine Learning Point Adding) method, uses ABRF Function) and OLHS ...

Embedded system debuggers deal with several layers of target system abstraction, including circuit, machine code, assembly code, procedural code and extension code layers. The Luxdbg debugger contains an explicit API for each of these layers, providing opportunities for networked distribution at any of them. Having evolved in an environment of assembly code debugging for small-footprint signal ...

We present a framework for statistical machine translation of natural languages based on direct maximum entropy models, which contains the widely used source-channel approach as a special case. All knowledge sources are treated as feature functions, which depend on the source language sentence, the target language sentence and possible hidden variables. This approach allows a baseline machine t...