ppxscal/embedding_network huggingface dataset:
Autonomous development of a grounded object ontology by a learning robot
Authors: Joseph Modayil, Benjamin Kuipers
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it to represent a physical object with a cluster of sensations that violate a static world model, track that cluster over time, extract percepts from that cluster, form concepts from similar percepts, and learn reliable actions that can be applied to objects. We present a formalism for representing the ontology for objects and actions, a learning algorithm, and the results of an evaluation with a physical robot.
Improving Children's Writing Ability
Authors: Joana Pereira, Luís Carriço, Carlos Duarte
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part IV: Interacting in Various Application Domains (2009)

This paper presents IWA, a platform to aid children when learning how to write. The proposed system offers both tutor and child a certain degree of autonomy. IWA provides tutor and child with different interfaces. The features available to the tutor allow the definition and configuration of repetition exercises comprising letters, numerals and freeform gestures. The child interface supports the child in the task of solving those exercises. The system has been evaluated in two sessions with children. From the evaluation results and the feedback provided by a school teacher we conclude this to be a very promising system towards optimizing the repetition process required for perfecting hand-writing.
The impact of time on the accuracy of sentiment classifiers created from a web log corpus
Authors: Kathleen T. Durant, Michael D. Smith
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

We investigate the impact of time on the predictability of sentiment classification research for models created from web logs. We show that sentiment classifiers are time dependent and through a series of methodical experiments quantify the size of the dependence. In particular, we measure the accuracies of 25 different time-specific sentiment classifiers on 24 different testing timeframes. We use the Naive Bayes induction technique and the holdout validation technique using equal-sized but separate training and testing data sets. We conducted over 600 experiments and organize our results by the size of the interval (in months) between the training and testing timeframes. Our findings show a significant decrease in accuracy as this interval grows. Using a paired t-test we show classifiers trained on future data and tested on past data significantly outperform classifiers trained on past data and tested on future data. These findings are for a topic-specific corpus created from political web log posts originating from 160 different web logs. We then define concepts that classify months as examplar, infrequent thread, frequent thread or outlier; this classification reveals knowledge on the topic's evolution and the utility of the month's data for the timeframe.
Quantitative Mapping of Soil Nitrogen Content Using Field Spectrometer and Hyperspectral Remote Sensing
Authors: Jian Wu, Yaolin Liu, Dan Chen, Jing Wang, Xu Chai
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

Mapping and dating soil total nitrogen is of great importance in soil use and evaluation. In this study we examine the feasibility of soil nitrogen content by using hyperspectrally reflective remote sensing methodology. This technique was tested in Hengshan County, northern Shanxi Province of China. The soil reflectance properties of samples were measured in the laboratory by ASD field spectrometer. The correlation analysis related with nitrogen content was processed with the spectral reflectance factors (the first derivative reflectance, the logarithmic reflectance and absorption depth). The results show that the first derivative reflectance at sensitive bands of 480nm, 980nm and 2210nm has more notable correlation coefficient as compared to other parameters. Knowing these correlations we were able to build up the multivariate regression model and map the soil total nitrogen content by calculating each pixel of Hyperion image. The accuracy assessment by relating predicted nitrogen values with measured ones of a linear regression showed that the map is reliable and significantly correlative with known stabilization processes throughout the study area. Moreover, this quantitative methodology developed in this study for mapping soil total nitrogen content can also be applied to other regions throughout the world.
Observation-based model for BDI-agents
Authors: Kaile Su, Abdul Sattar, Kewen Wang, Xiangyu Luo, Guido Governatori, Vineet Padmanabhan
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

We present a new computational model of BDI-agents, called the observation-based BDI-model. The key point of this BDI-model is to express agents' beliefs, desires and intentions as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our BDI-model is computationally grounded in that we are able to associate the BDI-agent model with a computer program, and formulas, involving agents' beliefs, desires (goals) and intentions, can be understood as properties of program computations. We present a sound and complete proof system with respect to our BDI-model and explore how symbolic model checking techniques can be applied to model checking BDI-agents. In order to make our BDI-model more flexible and practically realistic, we generalize it so that agents can have multiple sources of beliefs, goals and intentions.
Topic Significance Ranking of LDA Generative Models
Authors: Loulwah Alsumait, Daniel Barbará, James Gentle, Carlotta Domeniconi
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Topic models, like Latent Dirichlet Allocation (LDA), have been recently used to automatically generate text corpora topics, and to subdivide the corpus words among those topics. However, not all the estimated topics are of equal importance or correspond to genuine themes of the domain. Some of the topics can be a collection of irrelevant words, or represent insignificant themes. Current approaches to topic modeling perform manual examination to find meaningful topics. This paper presents the first automated unsupervised analysis of LDA models to identify junk topics from legitimate ones, and to rank the topic significance. Basically, the distance between a topic distribution and three definitions of "junk distribution" is computed using a variety of measures, from which an expressive figure of the topic significance is implemented using 4-phase Weighted Combination approach. Our experiments on synthetic and benchmark datasets show the effectiveness of the proposed approach in ranking the topic significance.
Position Based Cryptography
Authors: Nishanth Chandran, Vipul Goyal, Ryan Moriarty, Rafail Ostrovsky
Venue: Proceedings of the 29th Annual International Cryptology Conference on Advances in Cryptology (2009)

We consider what constitutes identities in cryptography. Typical examples include your name and your social-security number, or your fingerprint/iris-scan, or your address, or your (non-revoked) public-key coming from some trusted public-key infrastructure. In many situations, however, where you are defines your identity. For example, we know the role of a bank-teller behind a bullet-proof bank window not because she shows us her credentials but by merely knowing her location. In this paper, we initiate the study of cryptographic protocols where the identity (or other credentials and inputs) of a party are derived from its geographic location.We start by considering the central task in this setting, i.e., securely verifying the position of a device. Despite much work in this area, we show that in the Vanilla (or standard) model, the above task (i.e., of secure positioning) is impossible to achieve. In light of the above impossibility result, we then turn to the Bounded Storage Model and formalize and construct information theoretically secure protocols for two fundamental tasks: Secure Positioning; and Position Based Key Exchange. We then show that these tasks are in fact universal in this setting --- we show how we can use them to realize Secure Multi-Party Computation.Our main contribution in this paper is threefold: to place the problem of secure positioning on a sound theoretical footing; to prove a strong impossibility result that simultaneously shows the insecurity of previous attempts at the problem; and to present positive results by showing that the bounded-storage framework is, in fact, one of the "right" frameworks (there may be others) to study the foundations of position-based cryptography.
The effect of dialogue system output style variation on users' evaluation judgments and input style
Authors: Ivana Kruijff-Korbayová, Olga Kukina
Venue: Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue (2008)

A dialogue system can present itself and/or address the user as an active agent by means of linguistic constructions in personal style, or suppress agentivity by using impersonal style. We compare system evaluation judgments and input style alignment of users interacting with an in-car dialogue system generating output in personal vs. impersonal style. Although our results are consistent with earlier findings obtained with simulated systems, the effects are weaker.
The mobile Oracle: a tool for early user involvement
Authors: Charlotte Magnusson, Martin Pielot, Margarita Anastassova, Kirsten Rassmus-Gröhn, Konrad Tollmar, Samuel Roselier
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

This paper describes a novel tool for eliciting user requirements early in the design process of mobile applications. The "Mobile Oracle", as we have called it, is intended to help developers and designers obtain a better understanding of what the user wants at different points in space and time. It is an extension of a lo-fi version of the well-established Wizard of Oz technique, but it adds an "on demand" component to force users to explicitly request the information they need. The technique has been tested in an investigation involving 15 users (sighted, visually impaired, and elderly). Our preliminary results show it to generate valuable information concerning the ways people ask about directions and distances, as well as the services they would like to have in future mobile applications.
Microphone Classification Using Fourier Coefficients
Authors: Robert Buchholz, Christian Kraetzer, Jana Dittmann
Venue: Information Hiding: 11th International Workshop, IH 2009, Darmstadt, Germany, June 8-10, 2009, Revised Selected Papers (2009)

Media forensics tries to determine the originating device of a signal. We apply this paradigm to microphone forensics, determining the microphone model used to record a given audio sample. Our approach is to extract a Fourier coefficient histogram of near-silence segments of the recording as the feature vector and to use machine learning techniques for the classification. Our test goals are to determine whether attempting microphone forensics is indeed a sensible approach and which one of the six different classification techniques tested is the most suitable one for that task. The experimental results, achieved using two different FFT window sizes (256 and 2048 frequency coefficients) and nine different thresholds for near-silence detection, show a high accuracy of up to 93.5% correct classifications for the case of 2048 frequency coefficients in a test set of seven microphones classified with linear logistic regression models. This positive tendency motivates further experiments with larger test sets and further studies for microphone identification.
Self- or pre-tuning?: deep linguistic processing of language variants
Authors: António Branco, Francisco Costa
Venue: Proceedings of the Workshop on Deep Linguistic Processing (2007)

This paper proposes a design strategy for deep language processing grammars to appropriately handle language variants. It allows a grammar to be restricted as to what language variant it is tuned to, but also to detect the variant a given input pertains to. This is evaluated and compared to results obtained with an alternative strategy by which the relevant variant is detected with current language identification methods in a preprocessing step.
Backstepping Approach for Controlling a Quadrotor Using Lagrange Form Dynamics
Authors: Abhijit Das, Frank Lewis, Kamesh Subbarao
Venue: Journal of Intelligent and Robotic Systems (2009)

The dynamics of a quadrotor are a simplified form of helicopter dynamics that exhibit the same basic problems of underactuation, strong coupling, multi-input/multi-output design, and unknown nonlinearities. Control design for the quadrotor is more tractable yet reveals corresponding approaches for helicopter and UAV control design. In this paper, a backstepping approach is used for quadrotor controller design. In contrast to most other approaches, we apply backstepping on the Lagrangian form of the dynamics, not the state space form. This is complicated by the fact that the Lagrangian form for the position dynamics is bilinear in the controls. We confront this problem by using an inverse kinematics solution akin to that used in robotics. In addition, two neural nets are introduced to estimate the aerodynamic components, one for aerodynamic forces and one for aerodynamic moments. The result is a controller of intuitively appealing structure having an outer kinematics loop for position control and an inner dynamics loop for attitude control. The control approach described in this paper is robust since it explicitly deals with unmodeled state-dependent disturbances and forces without needing any prior knowledge of the same. A simulation study validates the results obtained in the paper.
Simultaneous Document Margin Removal and Skew Correction Based on Corner Detection in Projection Profiles
Authors: M. Mehdi Haji, Tien D. Bui, Ching Y. Suen
Venue: Proceedings of the 15th International Conference on Image Analysis and Processing (2009)

Document images obtained from scanners or photocopiers usually have a black margin which interferes with subsequent stages of page segmentation algorithms. Thus, the margins must be removed at the initial stage of a document processing application. This paper presents an algorithm which we have developed for document margin removal based upon the detection of document corners from projection profiles. The algorithm does not make any restrictive assumptions regarding the input document image to be processed. It neither needs all four margins to be present nor needs the corners to be right angles. In the case of the tilted documents, it is able to detect and correct the skew. In our experiments, the algorithm was successfully applied to all document images in our databases of French and Arabic document images which contain more than two hundred images with different types of layouts, noise, and intensity levels.
Ubiquitous Services for Senior Citizens - Living Process Detection and Middleware
Authors: Antero Metso, Petri Pulli, Seamus Hickey, Xiaosong Zheng
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

Ubiquitous services are designed to help senior citizens’ daily lives. Living processes and middleware are the key enablers of ubiquitous services. In this paper a ubiquitous service system is established with detailed descriptions of its key components and their functions. Game engine is proposed as middleware for ubiquitous services. This paper discusses ubiquitous service system, living process detection and middleware building in details. At the end of the paper conclusions are made and future research directions are outlined.
Knowledge-reuse Networks of an On-line PBL Framework
Authors: H. H. Yang, J. C. Yu, H. J. Yang, L. M. Chen, L. H. Kuo
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

Knowledge workers reuse knowledge to identify problem, to recognize problem, and to resolve the problem. Knowledge steams within group provide professional connections among team-members. Problem-based learning is the bridge to connected learner with real world and is the trigger setting for high level thinking skill. On-line technology is supporting our learning in many ways. There is a need to understand not only what a framework could help conducting on-line problem-based learning but also learner’s professional networks. The purpose of this study was to explore both feasibility and knowledge-reuse networking of on-line problem-based learning. Based on literature review, a theory framework was identified. An implementation of this framework was conducted to verify the feasibility. Knowledge-reuse network was constructed according to on-line activity log. For the framework of on-line PBL, the results of the evaluation conducted in this study imply that the feasibility exists. For the knowledge-reuse network, the higher group density tends to acts with higher reuse frequency. It was conclude that both in-degree and out-degree of knowledge-reuse networks index are significant predictor of PBL learning achievement of out learners.
A Dolphin Partner Optimization
Authors: Yang Shiqin, Jiang Jianjun, Yan Guangxing
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 01 (2009)

In this paper, based on the bionic study on dolphin, a philosophy of dolphin Partner Optimization (DPO) was formulated and a so-called “Nucleus” was introduced to predict the best position according to the positions and fitness of the team members. After that, we test the DPO algorithm on several benchmark functions and the experiment result show it has rapid and niche character and good adaptability for different objective functions.
Improved Imprecise DEA Model with AHP Preference Cone
Authors: Jianyong Liu, Ling Li, Chengqun Fu, Zhongjun Wu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

In this paper, we proposed an imprecise DEA (Data Envelopment Analysis) model improved by analytical hierarchy process (AHP) preference cone. On the basis of traditional DEA model, we extended inputs and outputs of decision making units to interval issue, which formed imprecise DEA model. To reflect the preference of decision makers, AHP method was utilized to build the preference cone. It restricts the weights of imprecise DEA model. The hybrid model can provide us both objective and subjective solution. Possibility degree formula was applied to rank the interval efficiency scores. Finally, a numerical example illustrates the application of the improved model. The results show its availability and efficiency.
Primary Study on Response of Water Quality to Land Use Pattern in a Medium-Sized Watershed, Southeast of China
Authors: Huang Jinliang, Li Qingsheng, Hong Huasheng
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Geoinformations technology and multivariate statistical analysis method were coupled to reveal the response of water quality to land use pattern in Jiulong river watershed, the second largest watershed of Fujian province with intensive agricultural activies. The study results obtained show that in entire watershed level, arable land(ALU) is the most important factor influencing DO in stream, moreover, buildup land (ULU) is the important predictor for BOD5, CODMN , NH3-N. In the buffer-zone level, BOD5 and NH3-N are positive correlated to ULU, and negative correlative to waterbody area, DO is positive correlated to natural land use(NLU), and negative correlated to ALU, which all are similar to the results obtained at entire watershed scale. To great extent, buffer zone of land use pattern can predict river water quality in study watershed. Multiple regression of relationship between land use pattern and water quality in different spatial levels enable us to improve comprehensive understanding of the relationship between land use pattern and land use in a medium-sized watershed in southeast of China.
A simplex Armijo downhill algorithm for optimizing statistical machine translation decoding parameters
Authors: Bing Zhao, Shengyuan Chen
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

We propose a variation of simplex-downhill algorithm specifically customized for optimizing parameters in statistical machine translation (SMT) decoder for better end-user automatic evaluation metric scores for translations, such as versions of BLEU, TER and mixtures of them. Traditional simplex-downhill has the advantage of derivative-free computations of objective functions, yet still gives satisfactory searching directions in most scenarios. This is suitable for optimizing translation metrics as they are not differentiable in nature. On the other hand, Armijo algorithm usually performs line search efficiently given a searching direction. It is a deep hidden fact that an efficient line search method will change the iterations of simplex, and hence the searching trajectories. We propose to embed the Armijo inexact line search within the simplex-downhill algorithm. We show, in our experiments, the proposed algorithm improves over the widely-applied Minimum Error Rate training algorithm for optimizing machine translation parameters.
Technical communique: An improved phase method for time-delay estimation
Authors: Svante Björklund, Lennart Ljung
Venue: Automatica (Journal of IFAC) (2009)

A promising method for estimation of the time-delay in continuous-time linear dynamical systems uses the phase of the all-pass part of a discrete-time model of the system. We have discovered that this method can sometimes fail totally and we suggest a method for avoiding such failures.
Optimal beam scheduling for multicasting in wireless networks
Authors: Karthikeyan Sundaresan, Kishore Ramachandran, Sampath Rangarajan
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

We consider the problem of efficient link-layer multicasting in wireless networks with switched beamforming antennas. The inherent tradeoff between multicasting and beamforming -- the broadcast advantage of low-gain omni-directional transmissions versus the high-gain but spatially restricted transmissions of beamforming antennas -- makes this problem especially challenging. In this paper, we design and evaluate optimal algorithms, and easy-to-implement greedy algorithms with performance guarantees, that generate and schedule efficient beam patterns for multicast transmissions. These algorithms are built upon the novel usage of composite beams that provide a knob to control the operating point of the tradeoff curve. This is in contrast to the sub-optimal usage of either purely directional or omni-directional beams by existing schemes. We further consider two models for composite beam pattern generation: one in which transmit power is (a) equally split, and (b) asymmetrically split between the constituent main lobes. A systematic evaluation, using real world traces obtained from measurements using an eight element switched beamforming antenna in an indoor office environment, indicates significant gains of about four folds over omni and two folds over prior art schemes.