ppxscal/embedding_network huggingface dataset:
Perception of differences in natural-image stimuli: Why is peripheral viewing poorer than foveal&quest;
Authors: M.P.S. To, I.D. Gilchrist, T. Troscianko, J.S.B. Kho, D.J. Tolhurst
Venue: ACM Transactions on Applied Perception (TAP) (2009)

Visual Difference Predictor (VDP) models have played a key role in digital image applications such as the development of image quality metrics. However, little attention has been paid to their applicability to peripheral vision. Central (i.e., foveal) vision is extremely sensitive for the contrast detection of simple stimuli such as sinusoidal gratings, but peripheral vision is less sensitive. Furthermore, crowding is a well-documented phenomenon whereby differences in suprathreshold peripherally viewed target objects (such as individual letters or patches of sinusoidal grating) become more difficult to discriminate when surrounded by other objects (flankers). We examine three factors that might influence the degree of crowding with natural-scene stimuli (cropped from photographs of natural scenes): (1) location in the visual field, (2) distance between target and flankers, and (3) flanker-target similarity. We ask how these factors affect crowding in a suprathreshold discrimination experiment where observers rate the perceived differences between two sequentially presented target patches of natural images. The targets might differ in the shape, size, arrangement, or color of items in the scenes. Changes in uncrowded peripheral targets are perceived to be less than for the same changes viewed foveally. Consistent with previous research on simple stimuli, we find that crowding in the periphery (but not in the fovea) reduces the magnitudes of perceived changes even further, especially when the flankers are closer and more similar to the target. We have tested VDP models based on the response behavior of neurons in visual cortex and the inhibitory interactions between them. The models do not explain the lower ratings for peripherally viewed changes even when the lower peripheral contrast sensitivity was accounted for; nor could they explain the effects of crowding, which others have suggested might arise from errors in the spatial localization of features in the peripheral image. This suggests that conventional VDP models do not port well to peripheral vision.
Application of Epipolar Line Rectification to the Stereovision-Based Measurement of Workpieces
Authors: He-xi Li, Guo-rong Wang, Yong-hua Shi
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

A general epipolar line constraint equation for binocolar stereo vision is first established for the measurement of workpiece surface, in which the intrinsic parameters of two cameras and their extrinsic structural parameters with respect to a reference base are included. To overcome the drawback of the relative distortion between left image and right image, An epipolar line rectification technique is used for the corresponding point detection in the stereovision-based measurement system. Instead of traditional rectangular window, a circular window sliding onepipolar lines is used to compute the correlation coefficient between the regions surrounding a selected point in the left image and its corresponding point in the right image. The stereovision-based measurement of a T-shaped circular pipe (as an example of workpieces) is carried out using the rectified epipolar lines and the workpiece surface is reconstructed with its acquired three-dimensional coordinates. Experimental results show that the relative distortion of left and right images can be eliminated and the measurement accuracy can be greatly improved after the application of epipolar line rectification, and the workpiece surface is reconstructed with less errors.
Multi-Relational Data Mining Based on Higher-Order Inductive Logic Programming
Authors: Wei Zhang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

This paper presents a novel multi-relational data mining (MRDM) approach from a perspective of considering higher-order inductive logic programming to dealing with the representation formalism problems of existing multi-relational data mining approaches. In our approach, examples, background knowledge,hypotheses and target concepts are represented in Escher, a higher-order logic programming language.Escher can describe semantically complicated data and patterns, and explicitly supports a variety of data types, including graph. Moreover, our approach explores and exploits the techniques of HILP based on Escher to efficiently construct search space and proposal a novel methodology of MRDM.Furthermore, we present an architecture for efficiency and scalability of MRDM based on HILP. We believe that our approach based on higher-order inductive logic programming will has a key role to play in the growth of MRDM while several majorcall for algorithms that explicitly exploit the semantically complicated and topological substructures of data.
Security and Tradeoffs of the Akl-Taylor Scheme and Its Variants
Authors: Paolo D'Arco, Alfredo Santis, Anna Lisa Ferrara, Barbara Masucci
Venue: Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009 (2009)

In 1983 Akl and Taylor [Cryptographic Solution to a Problem of Access Control in a Hierarchy, ACM Transactions on Computer Systems, 1(3), 239---248, 1983] first suggested the use of cryptographic techniques to enforce access control in hierarchical structures. Over time, their scheme has been used in several different contexts, including mobile agents environments and broadcast encryption. However, it has never been fully analyzed from the security point of view.We provide a rigorous analysis of the Akl-Taylor scheme and prove that it is secure against key recovery. We also show how to obtain different tradeoffs between the amount of public information and the number of steps required to perform key derivation. Moreover, we propose a general construction to set up a key assignment scheme secure w.r.t. key indistinguishability, given any key assignment scheme secure against key recovery. Finally, we show how to use our construction, along with our tradeoffs, to obtain a variant of the Akl-Taylor scheme, secure w.r.t key indistinguishability, requiring a constant amount of public information.
The Complexity of Global Cardinality Constraints
Authors: Andrei A. Bulatov, Dániel Marx
Venue: Proceedings of the 2009 24th Annual IEEE Symposium on Logic In Computer Science (2009)

In a constraint satisfaction problem (CSP) the goal is to find an assignment of a given set of variables subject to specified constraints. A global cardinality constraint is an additional requirement that prescribes how many variables must be assigned a certain value. We study the complexity of the problem CCSP(Gamma), the constraint satisfaction problem with global cardinality constraints that allows only relations from the set Gamma. The main result of this paper characterizes sets Gamma that give rise to problems solvable in polynomial time, and states that the remaining such problems are NP-complete.
Distance metric learning vs. Fisher discriminant analysis
Authors: Babak Alipanahi, Michael Biggs, Ali Ghodsi
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 2 (2008)

There has been much recent attention to the problem of learning an appropriate distance metric, using class labels or other side information. Some proposed algorithms are iterative and computationally expensive. In this paper, we show how to solve one of these methods with a closed-form solution, rather than using semidefinite programming. We provide a new problem setup in which the algorithm performs better or as well as some standard methods, but without the computational complexity. Furthermore, we show a strong relationship between these methods and the Fisher Discriminant Analysis.
Segmentation of 3D microscopy data with an energy based interaction model
Authors: Michele Ceccarelli, Vincenzo Paduano, Carlo Sansone
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Biological imaging has recently received a strong impulse by the development of fluorescent probes and new high-resolution microscopes. It is presently having a profound impact on the way research is being conducted in the life sciences. Biologists can now visualize subcellular components and processes in vivo, both structurally and functionally. Observations can be made in two or three dimensions, at different wavelengths (spectroscopy), possibly with time-lapse imaging to investigate cellular dynamics. The observation of many biological processes relies on the ability to identify and locate specific proteins within their cellular environment. High content screening is the combination of modern cell biology, with all its molecular tools, with automated high resolution microscopy and robotic handling. Image analysis is then used to measure changes in properties of the cells caused by external treatment such as chemical inhibitors or RNA interference. Therefore the methods for automatically determine and measure the number and shape of cells within a given multichannel image constitute a basic step in much of the applications of high throughput screening. Here the problem of a fully automatic segmentation of 3D high throughput images is approached. The adopted method is an extension to the three dimensional domain of a recently proposed energy based method. This is a two step process, first there is the detection of nuclei and then an energy based surface evolution approach tries to separate the surfaces of the various cells in the image. The adopted energy model is an adaptation of the repulsion competition approach, already proposed in a two-dimensional framework by Yan, Zhou and Shah Here we use a different nucleus identification method suited for three dimensional images and an efficient extension of the level set surface evolution algorithm. Experimental results on samples of the HeLa cell image database are reported.
User-centered design, activity-centered design, and goal-directed design: a review of three methods for designing web applications
Authors: Ashley Williams
Venue: Proceedings of the 27th ACM international conference on Design of communication (2009)

When conducting research with users in order to design web applications, the practitioner has a variety of methods from which to choose. This paper examines three such methods'User-Centered Design (UCD), Goal-Directed Design (GDD), and Activity-Centered Design (ACD)'in terms of their foundations, processes, and deliverables.
A relational representation for procedural task knowledge
Authors: Stephen Hart, Roderic Grupen, David Jensen
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

This paper proposes a methodology for learning joint probability estimates regarding the effect of sensorimotor features on the predicated quality of desired behavior. These relationships can then be used to choose actions that will most likely produce success. relational dependency networks are used to learn statistical models of procedural task knowledge. An example task expert for picking up objects is learned through actual experience with a humanoid robot. We believe that this approach is widely applicable and has great potential to allow a robot to autonomously determine which features in the world are salient and should be used to recommend policy for action.
Evaluation of User-Interfaces for Mobile Application Development Environments
Authors: Florence Balagtas-Fernandez, Heinrich Hussmann
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

This paper discusses about the different user-interfaces of mobile development and modeling environments in order to extract important details in which the user-interfaces for such environments are designed. The goal of studying such environments is to come up with a simple interface which would help people with little or no experience in programming, develop their own mobile applications through modeling. The aim of this research is to find ways in order to present the user interface in a clear manner such that the balance between ease-of-use and ease of learning is achieved.
A communication efficient probabilistic algorithm for mining frequent itemsets from a peer-to-peer network
Authors: Souptik Datta, Hillol Kargupta
Venue: Statistical Analysis and Data Mining (2009)

Data intensive large-scale distributed systems like peer-to-peer (P2P) networks are becoming increasingly popular where centralization of data is impossible for mining and analysis. Unfortunately, most of the existing data mining algorithms work only when data can be accessed in its entirety. Finding all the network-wide frequent itemsets is computationally difficult and usually has large communication overhead in such environment. This paper focuses on developing a communication efficient algorithm for discovering frequent itemsets from a P2P network. A sampling-based approach is adopted to find approximate solution instead of an exact solution with probabilistic guarantee. The benefit of approximation technique is reflected in the low communication overhead in discovering majority of frequent itemsets with probabilistic guarantee. The main principal followed by the algorithm assumes that an independent and identically distributed (iid) sample of the entire data is available at one location to generate a set of candidate itemsets. Collecting iid sample from a P2P network is a challenging problem because of varying degrees of connectivity and sizes of data shared. The paper first addresses this issue and shows how an iid sample of nodes and data can be collected from a P2P network using random walk. It applies the proposed sampling technique to identify most of the frequent itemsets from a P2P network. Theoretical analysis shows how to decide about optimum sample size and minimize communication to compute the results. Experimental results show that the proposed algorithm discovers all of the network-wide frequent itemsets using communication that scales sublinearly with network and datasize. &copy; 2009 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 2: 48-69, 2009
Interruption management: A comparison of auditory and tactile cues for both alerting and orienting
Authors: C. A. P. Smith, Benjamin A. Clegg, Eric D. Heggestad, Pamela J. Hopp-Levine
Venue: International Journal of Human-Computer Studies (2009)

Tactile and auditory cues have been suggested as methods of interruption management for busy visual environments. The current experiment examined attentional mechanisms by which cues might improve performance. The findings indicate that when interruptive tasks are presented in a spatially diverse task environment, the orienting function of tactile cues is a critical component, which directs attention to the location of the interruption, resulting in superior interruptive task performance. Non-directional tactile cues did not degrade primary task performance, but also did not improve performance on the secondary task. Similar results were found for auditory cues. The results support Posner and Peterson's [1990. The attention system of the human brain. Annual Review of Neuroscience 13, 25-42] theory of independent functional networks of attention, and have practical applications for systems design in work environments that consist of multiple, visual tasks and time-sensitive information.
Novel OFDMA Uplink Initial Ranging Scheme for IEEE 802.16e
Authors: Hengli Pang, Bingbing Li, Gang Liu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

OFDMA uplink synchronization for IEEE 802.16e is mainly accomplished by initial ranging, thus initial ranging which includes multiuser ranging code detection, multiuser timing offset and power estimation at the base station is one of the most important processes for TDD OFDMA systems. To overcome the existing ranging method's drawbacks namely high complexity, high probability of a false alarm and of misdetection, a novel OFDMA uplink initial ranging scheme is present in this paper. Simulations indicate that this scheme offers lower computational complexity and better performance over the existing methods for a wide range of SNR values and with a large number of ranging users.
The Effect of Object Features on Multiple Object Tracking and Identification
Authors: Tianwei Liu, Wenfeng Chen, Yuming Xuan, Xiaolan Fu
Venue: Proceedings of the 8th International Conference on Engineering Psychology and Cognitive Ergonomics: Held as Part of HCI International 2009 (2009)

Tracking of multiple objects is challenging for computer vision system under certain circumstance. We investigated this problem with human observers. In our experiment, observers were asked to track multiple moving items as well as to maintain their identities. We found that the capacity of maintaining multiple moving object identities of human is about three to four items, and uniqueness improves the general tracking and ID performance. It also showed that observers' capacity of ID task was dependent on feature type, and suggests that a less resource-demanding process of identity-related feature would lead to more effective improvement on tracking. These results provide some indications for the design of computer vision system which involves human monitoring, and suggest that creating a featural space to map the identity of multiple objects may aid the automatic object tracking.
Four Statistical Approaches for Multisensor Data Fusion under Non-Gaussian Noise
Authors: Wangqiang Niu, Jin Zhu, Wei Gu, Jianxin Chu
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

Multisensor data fusion methods for Gaussian noise are widely reported, while fusion approaches for non-Gaussian noise are seldom met in the literature. In this study, four statistical fusion methods are presented for a mixture of Gaussians noise. These four methods are the minimum variance approach, the maximum kurtosis approach, the minimum kurtosis approach, and the minimum mean absolute error approach. Preliminary numerical simulations demonstrate that the maximum kurtosis method shows the worst fusion performance, while the rest three methods shows equivalent better fusion performance.
The Camera Calibration Approach of Pipeline Detecting Robot
Authors: Dehui Liu, Gaohua Liao
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Camera calibration is a key technology in computer vision field. Many kinds of distortions are existed in ordinary CCD camera. Among these distortions the radial distortion is more serious. A camera self-calibration algorithm based on active vision taking account of one-degree radial distortion is proposed in this paper in order to make the calibration more quickly effective and accurate. Based on pinhole camera model, considered the camera lens distortion effects of radial and tangential distortion effect, it reduces the iterative times and avoids errors that come from decomposing parameters in linear calibration. The results show that the algorithm for high precision and with a certain degree of robustness, achieve fast and accurate calibration of vision cameras for weld inspection robot.
A meeting scheduling problem respecting time and space
Authors: Florian Berger, Rolf Klein, Doron Nussbaum, Jörg-Rüdiger Sack, Jiehua Yi
Venue: Geoinformatica (2009)

We consider the problem of determining suitable meeting times and locations for a group of participants wishing to schedule a new meeting subject to already scheduled meetings possibly held at a number of different locations. Each participant must be able to reach the new meeting location, attend for the entire duration, and reach the next meeting location on time. In particular, we give two solutions to the problem instance where each participant has two scheduled meetings separated by a free time interval. We present an O(n logn) algorithm for n participants obtained by purely geometrical arguments. Our second approach uses the concept of LP-type problems and leads to a randomized algorithm with expected running time O(n). We also consider a graph-based model where participants belong to different groups and can travel along the edges of a graph. For the meeting, only one member out of each group is required. The resulting problem can be solved using furthest color Voronoi diagrams on graphs.
The semantics of variables in action descriptions
Authors: Vladimir Lifschitz, Wanwan Ren
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

Action description language C+ is more expressive than ADL in many ways; for instance, it addresses the ramification problem. On the other hand, ADL is based on first-order logic, while C+ is only propositional; expressions with variables, which are frequently used when action domains are described in C+, are merely schemas describing finite sets of causal laws that are formed according to the same pattern. In this paper we propose a new approach to the semantics of action descriptions with variables that combines attractive features of ADL and C+.
Examining Individual Differences Effects: An Experimental Approach
Authors: Wan Adilah Wan Adnan, Nor Laila Md. Noor, Nik Ghazali Nik Daud
Venue: Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009 (2009)

Role of individual differences has been emphasized for system success. Many researchers claim about the need for a better understanding of individual differences as empirical evidence is still very limited. The purpose of this paper is to examine the extent to which individual differences affects one's decision performance and decision processes. This study focuses on decision making style and gender as the dimensions of individual differences characteristics. Their potential effects are investigated using experimental approach. Empirical findings from this study support for the user-centered approach that emphasize on user in the design of an information system.
Application Research of WSN in Precise Agriculture Irrigation
Authors: Shu-ming Xiong, Liang-min Wang, Xiao-qian Qu, Yong-zhao Zhan
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

In order to accurately get extent of the water deficit and therefore realize effective and water-saving irrigation, the application of wireless sensor networks (WSN) to precision irrigation system is explored based on the acoustic emission principle for crop water stress. Cluster based multi-hop routing algorithm is proposed to reduce energy consumption of node transmitting data. By the newest gateway in WSN, the system realizes bridging between wireless networks and wired networks. It runs distributed and possesses many advantages, such as good robustness, extensibility, scalability, and so forth. Simulation results show that the application is correct and reasonable and enables user to precisely acquire the crop water requirement information. The system can be effectively applied to some water-saving agriculture areas, for example, the cropland, the nursery garden, the greenhouse, etc.