Computing Machines Can't Be Intelligent (...and Turing Said So)

According to the conventional wisdom, Turing (1950) said that computing machines can be intelligent. I don't believe it. I think that what Turing really said was that computing machines –- computers limited to computing –- can only fake intelligence. If we want computers to become genuinelyintelligent, we will have to give them enough initiative (Turing, 1948, p. 21) to do more than compute. In this paper, I want to try to develop this idea. I want to explain how giving computers more ``initiative' can allow them to do more than compute. And I want to say why I believe (and believe that Turing believed) that they will have to go beyond computation before they can become genuinely intelligent.     

TEG—a hybrid approach to information extraction

This paper describes a hybrid statistical and knowledge-based information extraction model, able to extract entities and relations at the sentence level. The model attempts to retain and improve the high accuracy levels of knowledge-based systems while drastically reducing the amount of manual labour by relying on statistics drawn from a training corpus. The implementation of the model, called TEG (trainable extraction grammar), can be adapted to any IE domain by writing a suitable set of rules in a SCFG (stochastic context-free grammar)-based extraction language and training them using an annotated corpus. The system does not contain any purely linguistic components, such as PoS tagger or shallow parser, but allows to using external linguistic components if necessary. We demonstrate the performance of the system on several named entity extraction and relation extraction tasks. The experiments show that our hybrid approach outperforms both purely statistical and purely knowledge-based systems, while requiring orders of magnitude less manual rule writing and smaller amounts of training data. We also demonstrate the robustness of our system under conditions of poor training-data quality. Ronen Feldman is a senior lecturer at the Mathematics and Computer Science Department of Bar-Ilan University in Israel, and the Director of the Data Mining Laboratory. He received his B.Sc. in Math, Physics and Computer Science from the Hebrew University, M.Sc. in Computer Science from Bar-Ilan University, and his Ph.D. in Computer Science from Cornell University in NY. He was an Adjunct Professor at NYU Stern Business School. He is the founder of ClearForest Corporation, a Boston based company specializing in development of text mining tools and applications. He has given more than 30 tutorials on next mining and information extraction and authored numerous papers on these topics. He is currently finishing his book “The Text Mining Handbook” to the published by Cambridge University Press. Benjamin Rosenfeld is a research scientist at ClearForest Corporation. He received his B.Sc. in Mathematics and Computer Science from Bar-Ilan University. He is the co-inventor of the DIAL information extraction language. Moshe Fresko is finalizing his Ph.D. in Computer Science Department at Bar-Ilan University in Israel. He received his B.Sc. in Computer Engineering from Bogazici University, Istanbul/Turkey on 1991, and M.Sc. on 1994. He is also an adjunct lecturer at the Computer Science Department of Bar-Ilan University and functions as the Information-Extraction Group Leader in the Data Mining Laboratory.     

Graphical model construction based on evolutionary algorithms

Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum. However, to construct a Bayesian network that fits a given dataset is a NP-hard problem, and it also needs consuming mass computational resources. This paper develops a methodology for constructing a graphical model based on Bayesian Dirichlet metric. Our approach is derived from a set of propositions and theorems by researching the local metric relationship of networks matching dataset. This paper presents the algorithm to construct a tree model from a set of potential solutions using above approach. This method is important not only for evolutionary algorithms based on graphical models, but also for machine learning and data mining. The experimental results show that the exact theoretical results and the approximations match very well.     

Delay‐dependent fault estimation for uncertain time‐delay nonlinear systems: an LMI approach

This paper deals with the problem of robust fault estimation for uncertain time‐delay Takagi–Sugeno (TS) fuzzy models. The aim of this study is to design a delay‐dependent fault estimator ensuring a prescribed ??_∞ performance level for the fault estimation error, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of a robust fault estimator are given in terms of linear matrix inequalities (LMIs). Membership functions' (MFs) characteristics are incorporated into the fault estimator design to reduce the conservativeness of neglecting these characteristics. Finally, a numerical example is given to illustrate the effectiveness of the proposed design techniques. Copyright © 2006 John Wiley & Sons, Ltd.     

Minimum cost design of a welded orthogonally stiffened cylindrical shell

In this study the optimal design of a cylindrical orthogonally stiffened shell member of an offshore fixed platform truss, loaded by axial compression and external pressure, is investigated. Ring stiffeners of welded box section and stringers of halved rolled I-section are used. The design variables considered in the optimization are the shell thickness as well as the dimensions and numbers of stiffeners. The design constraints relate to the shell, panel ring and panel stringer buckling, as well as manufacturing limitations. The cost function includes the cost of material, forming of plate elements into cylindrical shape, welding and painting. In the optimization a number of relatively new mathematical optimization methods (leap-frog - LFOPC, Dynamic-Q, ETOPC, and particle swarm - PSO) are used, in order to ensure confidence that the finally computed optimum design is accurately determined, and indeed corresponds to a global minimum. The continuous optimization procedures are adapted to allow for discrete values of the design variables to be used in the final manufacturing of the truss member. A comparison of the computed optimum costs of the stiffened and un-stiffened assemblies, shows that significant cost savings can be achieved by orthogonal stiffening, since the latter allows for considerable reduction of the shell thickness, which results in large material and manufacturing cost savings.     

Characterization of structural effects from above-ground explosion using coupled numerical simulation

The response of a building structure to a nearby explosion is complicated by the drastic spatial and time variation of the blast load. Existing studies on the structural responses to explosion effects often employ simplified structural model with assumed loading patterns, such as element-based (beam-column, slab) models, single degree of freedom or lumped mass systems. The validity of a simplified approach depends on whether the governing response and failure mechanisms are well represented in the simplified scheme. For such validation more sophisticated models are required. This paper presents a numerical simulation study aiming to characterize the various structural effects of above-ground explosions. A coupled numerical approach with combined Lagrangian and Eulerian methods is adopted to allow for the incorporation of the essential processes, namely the explosion, shock wave propagation, shock wave-structure interaction and structural response, in the same model. The computational domain extends to the soil around the base of the structure, allowing also for an evaluation of the significance of the ground vibration effect. Results show that for a typical above-ground explosion scenario, the critical structural damage is dominated by air shock loading, while the ground shock induces only some additional vibration whose structural effect is minor. The distribution of structural damage tends to be governed by member level effects on the front face of the structure, whereas the global dynamic response of the system appears to be insignificant. Similar modeling approach may be applied to explore other blast-induced complex response phenomena.     

Bayesian testing for non-linearity in volatility modeling

Neural networks provide a tool for describing non-linearity in volatility processes of financial data and help to answer the question “how much” non-linearity is present in the data. Non-linearity is studied under three different specifications of the conditional distribution: Gaussian, Student-t and mixture of Gaussians. To rank the volatility models, a Bayesian framework is adopted to perform a Bayesian model selection within the different classes of models. In the empirical analysis, the return series of the Dow Jones Industrial Average index, FTSE 100 and NIKKEI 225 indices over a period of 16 years are studied. The results show different behavior across the three markets. In general, if a statistical model accounts for non-normality and explains most of the fat tails in the conditional distribution, then there is less need for complex non-linear specifications.     

Air cargo pickup schedule for single delivery location

In this paper, various deterministic models for determining optimal pickup times for air cargo from an airport and delivering it to a local distribution center for a global manufacturer are presented. The arrival times of the flights that can potentially bring air cargo are assumed to be deterministic and known. In addition, the custom clearance time for the air cargo and the traveling time from the airport to the local distribution center are assumed to be deterministic and known. These models are formulated mathematically as linear binary integer programming models without air cargo weight considerations. Deterministic formulations without air cargo weight information are shown to be related to the p-Median problem. The deterministic formulation of air cargo pickup times with air cargo weight consideration is shown to be a nonlinear binary integer programming model. The solutions of these models serve as an initial starting point to solve the stochastic problem with random arrival times of the flights and random custom clearance times and travel times.     

Inflatable Models

A physically-based model is presented for the simulation of a new type of deformable objects-inflatable objects, such as shaped balloons, which consist of pressurized air enclosed by an elastic surface. These objects have properties inherent in both 3D and 2D elastic bodies, as they demonstrate the behaviour of 3D shapes using 2D formulations. As there is no internal structure in them, their behaviour is substantially different from the behaviour of deformable solid objects. We use one of the few available models for deformable surfaces, and enhance it to include the forces of internal and external pressure. These pressure forces may also incorporate buoyancy forces, to allow objects filled with a low density gas to float in denser media. The obtained models demonstrate rich dynamic behaviour, such as bouncing, floating, deflation and inflation.     

Relationships among team ability composition, team mental models, and team performance.

This study examined the relationship between the similarity and accuracy of team mental models and compared the extent to which each predicted team performance. The relationship between team ability composition and team mental models was also investigated. Eighty-three dyadic teams worked on a complex skill task in a 2-week training protocol. Results indicated that although similarity and accuracy of team mental models were significantly related, accuracy was a stronger predictor of team performance. In addition, team ability was more strongly related to the accuracy than to the similarity of team mental models and accuracy partially mediated the relationship between team ability and team performance, but similarity did not. (PsycINFO Database Record (c) 2010 APA, all rights reserved)