ppxscal/embedding_network huggingface dataset:
Using Decision Trees to Model an Emotional Attention Mechanism
Authors: Saman Harati Zadeh, Saeed Bagheri Shouraki, Ramin Halavati
Venue: Proceeding of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference (2008)

There are several approaches to emotions in AI, most of which are inspired by human emotional states and their arousal mechanisms. These approaches usually use high-level models of human emotions that are too complex to be directly applicable in simple artificial systems. It seems that a new approach to emotions, based on their functional role in information processing in mind, can help us to construct models of emotions that are both valid and simple. In this paper, we will try to present a model of emotions based on their role in controlling the attention. We will evaluate the performance of the model and show how it can be affected by some structural and environmental factors.
A distributed controller approach for delay-independent stability of networked control systems
Authors: Sandra Hirche, Tilemachos Matiakis, Martin Buss
Venue: Automatica (Journal of IFAC) (2009)

This article introduces a novel distributed controller approach for networked control systems (NCS) to achieve finite gain L"2 stability independent of constant time delay. The proposed approach represents a generalization of the well-known scattering transformation which applies for passive systems only. The main results of this article are (a) a sufficient stability condition for general multi-input-multi-output (MIMO) input-feedforward-output-feedback-passive (IF-OFP) nonlinear systems and (b) a necessary and sufficient stability condition for linear time-invariant (LTI) single-input-single-output (SISO) systems. The performance advantages of the proposed approach are reduced sensitivity to time delay and improved steady state error compared to alternative known delay-independent small gain type approaches. Simulations validate the proposed approach.
A Modified Projection Neural Network for Linear Variational Inequalities and Quadratic Optimization Problems
Authors: Minghui Jiang, Yongqing Zhao, Yi Shen
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Variational inequalities provide us with a tool to study a wide class of optimization arising in pure and applied sciences. In the paper,we present a neural network for solving linear variational inequalities and quadratic optimization by using a projection techniques. We also consider the global uniqueness of the solution of the neural network as well as the convergence of the modified projection neural network. Our results present a significant improvement of previously known projection methods for solving variational inequalities and related optimization problems. Two simulation examples are provided to show the effectiveness of the approach and applicability of the proposed criteria.
Parallel versus Serial Classifier Combination for Multibiometric Hand-Based Identification
Authors: Andreas Uhl, Peter Wild
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This paper presents an approach for optimizing both recognition and processing performance of a biometric system in identification mode. Multibiometric techniques facilitate bridging the gap between desired performance and current unimodal recognition rates. However, traditional parallel classifier combination techniques, such as Score sum, Borda count and Highest rank, cause further processing overhead, as they require a matching of the extracted sample with each template of the system for each feature. We examine a framework of serial combination techniques, which exploits ranking capabilities of individual features by reducing the set of possible matching candidates at each iteration, and we compare its performance with parallel schemes. Using this technique, both a reduction of misclassification and processing time in identification mode will be shown to be feasible for a single-sensor hand-based biometric system.
Family classification without domain chaining
Authors: Jacob M. Joseph, Dannie Durand
Venue: Bioinformatics (2009)

Motivation: Classification of gene and protein sequences into homologous families, i.e. sets of sequences that share common ancestry, is an essential step in comparative genomic analyses. This is typically achieved by construction of a sequence homology network, followed by clustering to identify dense subgraphs corresponding to families. Accurate classification of single domain families is now within reach due to major algorithmic advances in remote homology detection and graph clustering. However, classification of multidomain families remains a significant challenge. The presence of the same domain in sequences that do not share common ancestry introduces false edges in the homology network that link unrelated families and stymy clustering algorithms. Results: Here, we investigate a network-rewiring strategy designed to eliminate edges due to promiscuous domains. We show that this strategy can reduce noise in and restore structure to artificial networks with simulated noise, as well as to the yeast genome homology network. We further evaluate this approach on a hand-curated set of multidomain sequences in mouse and human, and demonstrate that classification using the rewired network delivers dramatic improvement in Precision and Recall, compared with current methods. Families in our test set exhibit a broad range of domain architectures and sequence conservation, demonstrating that our method is flexible, robust and suitable for high-throughput, automated processing of heterogeneous, genome-scale data. contact: jacobmj@cmu.edu
Annotation schemes and their influence on parsing results
Authors: Wolfgang Maier
Venue: Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop (2006)

Most of the work on treebank-based statistical parsing exclusively uses the Wall-Street-Journal part of the Penn treebank for evaluation purposes. Due to the presence of this quasi-standard, the question of to which degree parsing results depend on the properties of treebanks was often ignored. In this paper, we use two similar German treebanks, T&uuml;Ba-D/Z and NeGra, and investigate the role that different annotation decisions play for parsing. For these purposes, we approximate the two treebanks by gradually taking out or inserting the corresponding annotation components and test the performance of a standard PCFG parser on all treebank versions. Our results give an indication of which structures are favorable for parsing and which ones are not.
Non-contact tactile sensation synthesized by ultrasound transducers
Authors: Takayuki Hoshi, Takayuki Iwamoto, Hiroyuki Shinoda
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

This paper describes a new tactile device which produces stress fields in 3D space. Combined with mid-air and/or 3D stereoscopic displays, this device provides high-fidelity tactile feedback for interaction with visual objects. The principle is based on a nonlinear phenomenon of ultrasound; acoustic radiation pressure. The fabricated prototype device consists of 324 airborne ultrasound transducers, and the phase and intensity of each transducer are controlled individually. The total output force within the focal region is 1.6 gf. The spatial resolution is 20 mm. The prototype can produce sufficient vibrations up to 1 kHz. An interaction system including the prototype is also introduced which tracks user's hand and provides suitable touch feeling.
E-Services: Paving the Way for Mobile Clients
Authors: Guadalupe Ortiz
Venue: Proceeding of the 2008 conference on Techniques and Applications for Mobile Commerce: Proceedings of TAMoCo 2008 (2008)

The increasing demand for services for mobile customers has resulted in the need to develop service clients that could also be used from mobile devices and not only from PCs, which to date were the developers' main focus. In this paper we propose a model--driven development for these clients, whose platform-specific level attends to the specific requirements depending on the final device where the said client is to be installed. Furthermore, we propose the use of aspect-oriented techniques for the final implementation with the aim of facilitating the client's adaptation as a result of the particular device model characteristics and end user preferences.
Fuzzified Strategic Maps
Authors: Ronald Uriel Ruiz Ordóòez, Josep Lluis de la Rosa i Esteva, Javier Guzmán Obando
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

The strategy may be represented by a strategic map (SM).According to Kaplan and Norton, SM are built up to obtain constant communication of the objec-tives to all employees. They have a simple layout, are general and consistent, and help achieve better implementation of strategies so that employees tolerate changes that they initially resisted and distrusted in their companies.This paper suggests a system that to interpret the strategy and its aligned actions so that it can alert and send messages to users (the employees) to guide them according to the strategy and the behavior of other employees.A real example with a research group in a European university is presented.
Inertially Aided Visual Odometry for Miniature Air Vehicles in GPS-denied Environments
Authors: Bryce B. Ready, Clark N. Taylor
Venue: Journal of Intelligent and Robotic Systems (2009)

Unmanned miniature air vehicles (MAVs) have recently become a focus of much research, due to their potential utility in a number of information gathering applications. MAVs currently carry inertial sensor packages that allow them to perform basic flight maneuvers reliably in a completely autonomous manner. However, MAV navigation requires knowledge of location that is currently available only through GPS sensors, which depend on an external infrastructure and are thus prone to reliability issues. Vision-based methods such as Visual Odometry (VO) have been developed that are capable of estimating MAV pose purely from vision, and thus have the potential to provide an autonomous alternative to GPS for MAV navigation. Because VO estimates pose by combining relative pose estimates, constraining relative pose error is the key element of any Visual Odometry system. In this paper, we present a system that fuses measurements from an MAV inertial navigation system (INS) with a novel VO framework based on direct image registration. We use the inertial sensors in the measurement step of the Extended Kalman Filter to determine the direction of gravity, and hence provide error-bounded measurements of certain portions of the aircraft pose. Because of the relative nature of VO measurements, we use VO in the EKF prediction step. To allow VO to be used as a prediction, we develop a novel linear approximation to the direct image registration procedure that allows us to propagate the covariance matrix at each time step. We present offline results obtained from our pose estimation system using actual MAV flight data. We show that fusion of VO and INS measurements greatly improves the accuracy of pose estimation and reduces the drift compared to unaided VO during medium-length (tens of seconds) periods of GPS dropout.
MRI image enhancement by PROPELLER data fusion
Authors: Krzysztof Malczewski
Venue: International Journal of Advanced Media and Communication (2009)

Magnetic Resonance Imaging (MRI) image reconstruction, based on the frequency-domain Super-Resolution (SR) algorithm, is presented in this paper. It is shown that the approach improves MRI spatial resolution in cases where Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) sequences are used. The PROPELLER MRI method collects data in rectangular 'blades' rotated around the origin of the k-space. Inter-blade patient motion is the premise for the use of SR technique. Images obtained from sets of irregularly located frequency-domain samples are combined into the high-resolution MRI image. The SR reconstruction replaces the usually applied direct averaging of low-resolution images. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9 10 May 2008, Ottawa, ON, Canada.
I-O scheduling and performance analysis on multi-core platforms
Authors: Zhaobin Liu, Wenyu Qu, Haitao Li, Min Ruan, Wanlei Zhou
Venue: Concurrency and Computation: Practice Experience (2009)

Multi-core platforms are being widely used in many technology areas. These technology shifts not only provide a compute-intensive service, but also require us to improve the I-O-intensive service in performance. However, the existing I-O scheduling approaches lack either quantitative analysis or workload adaptability. These approaches become worse when the application scenarios have either diverse I-O tasks or heterogeneous multi-cores. Based on the analysis of traditional software pipelining technology, we first propose a reverse interleaved pipelining scheduling strategy to decrease the total I-O execution time and balance the workloads of homogeneous processors in this paper. Theoretical analysis shows that this balancing strategy is fair. As for the heterogeneous processors' circumstance, a Self-adaptive scheduling method is presented for selecting one of the most-appropriate multi-core services for the expected I-O tasks. Simulation studies show that the performance of this scheduling strategy self-adapts to application and multi-core diversity well. Copyright &copy; 2009 John Wiley & Sons, Ltd.
Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems
Authors: Leandro dos Santos Coelho, Rodrigo Clemente Thom Souza, Viviana Cocco Mariani
Venue: Mathematics and Computers in Simulation (2009)

Evolutionary algorithms (EAs) are general-purpose stochastic search methods that use the metaphor of evolution as the key element in the design and implementation of computer-based problems solving systems. During the past two decades, EAs have attracted much attention and wide applications in a variety of fields, especially for optimization and design. EAs offer a number of advantages: robust and reliable performance, global search capability, little or no information requirement, and others. Among various EAs, differential evolution (DE), which characterized by the different mutation operator and competition strategy from the other EAs, has shown great promise in many numerical benchmark problems and real-world optimization applications. The potentialities of DE are its simple structure, easy use, convergence speed and robustness. To improve the global optimization property of DE, in this paper, a DE approach based on measure of population's diversity and cultural algorithm technique using normative and situational knowledge sources is proposed as alternative method to solving the economic load dispatch problems of thermal generators. The traditional and cultural DE approaches are validated for two test systems consisting of 13 and 40 thermal generators whose nonsmooth fuel cost function takes into account the valve-point loading effects. Simulation results indicate that performance of the cultural DE present best results when compared with previous optimization approaches in solving economic load dispatch problems.
Abrupt changes detection in fatigue data using the cum ulative sum method
Authors: Z. M. Nopiah, M. N. Baharin, S. Abdullah, M. I. Khairir, C. K. E. Nizwan
Venue: WSEAS Transactions on Mathematics (2008)

The detection of abrupt changes refers to a time instant at which properties suddenly change, but before and after which properties are constant in some sense. CUSUM (Cumulative Sum) is a sequential analysis technique that is used in the detection of abrupt changes. The objective in this study is to apply CUSUM technique in analysing fatigue data for detection of abrupt changes. For the purpose of this study, a collection of nonstationary data that exhibits a random behavior was used. This random data was measured in the unit of microstrain on the lower suspension arm of a car. Experimentally, the data was collected for 60 seconds at a sampling rate of 500 Hz, which gave 30,000 discrete data points. By using CUSUM method, a CUSUM plot was constructed in monitoring the mean changes for fatigue data. Global signal statistical value indicated that the data were non Gaussian distribution in nature. The result of the study indicates that CUSUM method is only applicable for certain type of data with mixed high amplitude in a random background data.
Social Behavior Change in an Evolutionary Online-Game
Authors: Jon-Chao Hong, Ching-Ling Cheng, Hui-Chin Huang, Chia-Ying Lee, Yu-Nien Chen, Yu-Chen Li, I-Tzu Wu
Venue: Proceeding of the 2007 conference on Supporting Learning Flow through Integrative Technologies (2007)

The purpose of this study is to identify the types of social behavior which change in children during game play in cooperative and competitive scenarios. Researchers developed an evolutionary game named Strike up game, in which students have to calculate numbers to move their flags to the end, to investigate behaviors children display in competitive situations that require cooperation among participants. As the need of validity of study, the teacher and three other graduates watched the videotapes to observe and interpret the interactions taking place among children during the each Co-competition scenario. Consensus is reached after connecting, recording dialogues, and analyzing scenarios of the interaction modes.
On the Minimization of Communication Energy Consumption of Correlated Sensor Nodes
Authors: Liuguo Yin, Changmian Wang, Geir E. Øien
Venue: Wireless Personal Communications: An International Journal (2009)

Minimizing the sensor-node energy consumption is an important consideration when designing wireless sensor networks. In this paper, we focus on the energy consumption issues related to communication of data from correlated sensor nodes. An optimization algorithm is proposed for minimizing the overall energy consumption of the hardware and the physical link. We perform a detailed trade-off analysis of the circuit energy consumption, the transmission energy consumption, the transmission time, the modulation symbol size, and the channel coding rate, over a wide range of transmission distances and correlation values. Thus, a new optimized communication schedule with much lower energy consumption than our benchmark scheme of optimized uncorrelated uncoded transmission is obtained. Compared to this scheme, the total energy consumption may be reduced by more than 83.5% for a correlation value of 0.6 and a transmission distance of 100 m when using the results from the proposed optimization. This is significant with respect to increasing the lifetime of a wireless sensor network.
Parallel switch system with QoS guarantee for real-time traffic
Authors: Wen-Jie Li, Bin Liu, Yang Xu, Heng Liao
Venue: Journal of Computer Science and Technology (2006)

This paper studies the load-balancing algorithm and quality of service (QoS) control mechanism in a 320Gb/s switch system, which incorporates four packet-level parallel switch planes. Eight priorities for both unicast and multicast traffic are implemented, and the highest priority with strict QoS guarantee is designed for real-time traffic. Through performance analysis under multi-priority burst traffic, we demonstrate that the load-balancing algorithm is efficient, and the switch system not only provides excellent performance to real-time traffic, but also efficiently allocates bandwidth among other traffic of lower priorities. As a result, this parallel switch system is more scalable towards next generation core routers with QoS guarantee, as well as ensures in-order delivery of IP packets.
A Working Hypothesis for General Intelligence
Authors: Eric Baum
Venue: Proceeding of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006 (2007)

Humans can construct powerful mental programs for many domains never seen before. We address the questions of how this occurs, and how it could possibly be accomplished in software. Section one surveys a theory of natural understanding, as follows. One understands a domain when one has mental programs that can be executed to solve problems arising in the domain. Evolution created compact programs understanding domains posed by nature. According to an extrapolation of Occam's razor, a compact enough program solving enough problems drawn from a distribution can only be found if there is simple structure underlying the distribution and the program exploits this structure, in which case the program will generalize by solving most new problems drawn from the distribution. This picture has several important ramifications for attempts to develop Artificial General Intelligence (AGI), suggesting for example, that human intelligence is not in fact general, and that weak methods may not suffice to reproduce human abilities. Section 2 exemplifies this picture by discussing two particular thought processes, the mental program by which I solve levels in the game of Sokoban, and how I construct this mental program. A computer program under construction to implement my introspective picture of my mental program is based on a model of a particular mental module called Relevance Based Planning (RBP). Section 3 argues that programs to address new problems (such as my mental program to play Sokoban) can be constructed (both naturally and artificially) if and only if sufficient guidance is already present. It proposes a computational structure called a scaffold that guides rapid construction of understanding programs when confronted with new challenges.