An Intelligent Tutoring System for Cloud Computing

Intelligent tutoring system (ITS) is a computer system which aims to provide immediate and customized or reactions to learners, usually without the intervention of human teacher's instructions. Secretariats professional to have the common goal of learning a meaningful and effective manner through the use of a variety of computing technologies enabled. There are many examples of professional Secretariats used in both formal education and in professional settings that have proven their capabilities. There is a close relationship between private lessons intelligent, cognitive learning and design theories; and there are ongoing to improve the effectiveness of ITS research. And it aims to find a solution to the problem of over-reliance on students' teachers for quality education. The program aims to provide access to high-quality education to every student, and therefore the reform of the education system as a whole. In this paper, we will use Intelligent Tutoring System Builder (ITSB) to build an education system on cloud computing in terms of the concept of cloud computing and components and how to take advantage of cloud computing in the field

Hints

The systematic use of hints in the learning-from-examples paradigm is the subject of this review. Hints are the properties of the target function that are known to us independently of the training examples. The use of hints is tantamount to combining rules and data in learning, and is compatible with different learning models, optimization techniques, and regularization techniques. The hints are represented to the learning process by virtual examples, and the training examples of the target function are treated on equal footing with the rest of the hints. A balance is achieved between the information provided by the different hints through the choice of objective functions and learning schedules. The Adaptive Minimization algorithm achieves this balance by relating the performance on each hint to the overall performance. The application of hints in forecasting the very noisy foreign-exchange markets is illustrated. On the theoretical side, the information value of hints is contrasted to the complexity value and related to the VC dimension

ITSB: An Intelligent Tutoring System Authoring Tool

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented

Financial model calibration using consistency hints

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market

Hints and the VC Dimension

Learning from hints is a generalization of learning from examples that allows for a variety of information about the unknown function to be used in the learning process. In this paper, we use the VC dimension, an established tool for analyzing learning from examples, to analyze learning from hints. In particular, we show how the VC dimension is affected by the introduction of a hint. We also derive a new quantity that defines a VC dimension for the hint itself. This quantity is used to estimate the number of examples needed to "absorb" the hint. We carry out the analysis for two types of hints, invariances and catalysts. We also describe how the same method can be applied to other types of hints

ON THE DYNAMICS OF THE ISRAELI-ARAB ARMS RACE

This paper investigates the causal relationships between the military expenditures and military burden of the four major sides of the Israeli-Arab conflict, namely, Egypt, Israel, Jordan and Syria over the period 1960-2004. We utilize both the causality test suggested by Toda and Yamamoto (1995) and the generalized forecast error variance decomposition method of Pesaran and Shin (1998). Our findings suggest weak causality that runs usually from Israel’s to Arab’s military spending. The strongest links are between Israel and Syria that are still in a state of enmity. No causality was detected between Israel’s and Jordan’s military spending.Arms race, Middle East, Israeli-Arab conflict, Causality, Generalized Forecast Error Variance Decomposition

The Vapnik-Chervonenkis Dimension: Information versus Complexity in Learning

When feasible, learning is a very attractive alternative to explicit programming. This is particularly true in areas where the problems do not lend themselves to systematic programming, such as pattern recognition in natural environments. The feasibility of learning an unknown function from examples depends on two questions: 1. Do the examples convey enough information to determine the function? 2. Is there a speedy way of constructing the function from the examples? These questions contrast the roles of information and complexity in learning. While the two roles share some ground, they are conceptually and technically different. In the common language of learning, the information question is that of generalization and the complexity question is that of scaling. The work of Vapnik and Chervonenkis (1971) provides the key tools for dealing with the information issue. In this review, we develop the main ideas of this framework and discuss how complexity fits in

STRUCTURAL BREAKS IN MILITARY EXPENDITURES: EVIDENCE FOR EGYPT, ISRAEL,JORDAN AND SYRIA

This paper endogenously determines the timing of structural breaks in military expenditures and military burdens for the major parties involved in the Israeli-Arab conflict, namely Egypt, Israel, Jordan, and Syria over the period 1960-2004. Utilizing a test proposed by Vogelsang (1997), we find that all these countries experienced structural breaks, though at different periods in the late 70s and during the 80s. These structural breaks mark a sharp decline in the military burden that can be attributed to the peace talks that were initiated shortly after the 1973 war. When applying the Bai and Perron (1998, 2003) multiple structural break tests we detect two structural breaks for every country. The first break occurred during the 60s and demonstrated a significant rise in the military burden prior to the 1973 war, whereas the second break occurred in the late 70s and during the 80s and was characterized by a sharp decline in the military burden following the instigation of peace negotiations.Military Expenditures, Military Burden, Middle-East, Israeli-Arab Conflict, Structural Breaks.