The Relationship between Decision Trees and the Scale of Train Data Set

Decision Trees need train samples in the train data set to get classification rules. If the number of train data was too small, the important information might be missed and thus the model could not explain the classification rules of data. While it is not affirmative that large scale of train data set can get well model. This Paper analysis the relationship between decision trees and the train data scale. We use nine decision tree algorithms to experiment the accuracy, complexity and robustness of decision tree algorithms. Some results are demonstrated.

One-step digit-set-restricted modified signed-digit adder using an incoherent correlator based on a shared content-addressable memory

An efficient one-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In this technique, carry propagation is avoided by introducing reference digits to restrict the intermediate carry and sum digits to {1,0} and {0,1}, respectively. The proposed technique requires significantly fewer minterms and simplifies system complexity compared to the reported one-step MSD addition techniques. An incoherent correlator based on an optoelectronic shared content-addressable memory processor is suggested to perform the addition operation. In this technique, only one set of minterms needs to be stored, independent of the operand length. (C) 2002 society or Photo-Optical Instrumentation Engineers.

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Efficient two-step digit-set-restricted modified signed-digit algorithm based on optoelectronic shared content-addressable memory

A two-step digit-set-restricted modified signed-digit (MSD) adder based on symbolic substitution is presented. In the proposed addition algorithm, carry propagation is avoided by using reference digits to restrict the intermediate MSD carry and sum digits into {(1) over bar ,0} and {0, 1}, respectively. The algorithm requires only 12 minterms to generate the final results, and no complementarity operations for nonzero outputs are involved, which simplifies the system complexity significantly. An optoelectronic shared content-addressable memory based on an incoherent correlator is used for experimental demonstration. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Compact Reconfigurable Binary-Decision-Diagram Logic Circuit on a GaAs Nanowire Network

We describe a reconfigurable binary-decision-diagram logic circuit based on Shannon's expansion of Boolean logic function and its graphical representation on a semiconductor nanowire network. The circuit is reconfigured by using programmable switches that electrically connect and disconnect a small number of branches. This circuit has a compact structure with a small number of devices compared with the conventional look-up table architecture. A variable Boolean logic circuit was fabricated on an etched GaAs nanowire network having hexagonal topology with Schottky wrap gates and SiN-based programmable switches, and its correct logic operation together with dynamic reconfiguration was demonstrated.

On the performance analysis and design of a novel shared-layer integrated devices using RCE-p-i-n-PD/SHBT - art. no. 67820J

We have explored the shared-layer integration fabrication of an resonant-cavity-enhanced p-i-n photodector (RCE- p-i-n-PD) and a single heterojunction bipolar transistor (SHBT) with the same epitaxy grown layer structure. MOCVD growth of the different layer structure for the GaAs based RCE- p-i-n-PD/SHBT require compromises to obtain the best performance of the integrated devices. The SHBT is proposed with super-lattice in the collector, and the structure of the base and the collector of the SHBT is used for the RCE. Up to now, the DC characteristics of the integrated device have been obtained.

Design and path planning for a remote-brained service robot

This paper presents a novel robot named "TUT03-A" with expert systems, speech interaction, vision systems etc. based on remote-brained approach. The robot is designed to have the brain and body separated. There is a cerebellum in the body. The brain with the expert systems is in charge of decision and the cerebellum control motion of the body. The brain-body. interface has many kinds of structure. It enables a brain to control one or more cerebellums. The brain controls all modules in the system and coordinates their work. The framework of the robot allows us to carry out different kinds of robotics research in an environment that can be shared and inherited over generations. Then we discuss the path planning method for the robot based on ant colony algorithm. The mathematical model is established and the algorithm is achieved with the Starlogo simulating environment. The simulation result shows that it has strong robustness and eligible pathfinding efficiency.

An automata theoretic decision procedure for the propositional mu-calculus

The propositional mu-calculus is a propositional logic of programs which incorporates a least fixpoint operator and subsumes the propositional dynamic logic of Fischer and Ladner, the infinite looping construct of Streett, and the game logic of Parikh. We give an elementary time decision procedure, using a reduction to the emptiness problem for automata on infinite trees. A small model theorem is obtained as a corollary.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

社会困境中的行为决策――社会身份与地位的影响

Social dilemmas are defined as such situations in which short-term individual and long-term collective interests are at odds (Hardin, 1968; Messick & Brewer, 1983). Severe social problems lead more and more researchers to pay attention to the issue of social dilemmas. Until now, research has widely examined the factors influencing cooperation in social dilemmas, and provided solutions to social dilemmas. In the need of theory development, previous research generally simplified the situation of realistic social dilemmas. Therefore, few studies have explored the issue of cooperation in social dilemmas in an intergroup situation. On the other hand, there has been little empirical attention for such issues in countries outside of United States and Western Europe. To meet this gap, the present study grounded itself in social identity theories and examined the effect of unequal group status on behavioral decision making in social dilemmas. To this end, the study designed three experiments to examine how individuals with different group status response psychologically and behaviorally to cooperation in intragroup and intergroup social dilemmas. In experiment 1, the study examined how independent and interdependent self- construals affect cooperative behavior in an intragroup social dilemma. The results showed that when individuals were primed with interdependent (as opposed to independent) self-construal, they consistently contributed highly, regardless of context manipulation. In contrast, those primed with independent self-construal contributed less in the investment game but only when placed in a context where group members were encouraged to think about their individual (versus shared) fate. Results supported the idea that independent self-construal in a low interdependent context produces the most competitive behavior and that this effect was partially mediated by the feeling of interaction within a group. In experiment 2, the study examined how the effect of group status on different level of cooperation in a nested social dilemma was moderated by individual status, and what roles ingroup and superordinate identifications played in the above effect. Results found that individuals in higher status groups tended to allocate more to private account and less to subgroup account compared to those in lower status group; individuals in higher status groups allocated more to higher level accounts than to private account, whereas those in lower status acted in a reverse way. The results indicated that group status (compared to individual status) exerted a positive influence on behavioral decision making in social dilemmas, with higher group status contributing more to subgroup as well as collective interests. Results also found that the effect of group status and/or individual status on cooperation in social dilemmas was moderated by sex. As for individual status, results showed that the effect of individual status on subgroup interest was significantly moderated only by the combination of higher ingroup identification and lower superordinate identification. In experiment 3, the study explored how group stability and cognitive categorization interactively influenced the relationship between group status and behavioral decision making in a social dilemma. Results did not support the prediction that group status and stability interactively affected behavioral decision-making in social dilemmas. However, it was found that this relationship was moderated by which level individuals categorized themselves at. When categorization at the individual level was salient, individuals in high status group contributed more to subgroup account than those in low status group if they perceived a stable status hierarchy; whereas they contributed more to private account and less to collective account if they perceived that the status was instable. On the other hand, when categorization at the subgroup level was salient, individuals in high status group contributed less to collective account than those in low status group if they perceived that the status was stable; whereas they contributed less to private account and more to subgroup account if they perceived an instable status relation. In summary, the present study suggests that cooperation with ingroup forms the basis of social harmony, and higher status for everyone in any given group is a necessary for social development. On the other hand, individuals in higher status group tend to be more selfish once they realize that their current status hierarchy is unstable. However, activating their collective identity will to some degree increase the level of their cooperation with the collective. The study thus provides psychological explanations on how to construct group harmony and management suggestions on how to solve social conflicts.