ppxscal/embedding_network huggingface dataset:
Spectrum Steganalysis of WAV Audio Streams
Authors: Qingzhong Liu, Andrew H. Sung, Mengyu Qiao
Venue: Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition (2009)

In this paper, we propose an audio steganalysis method called reference based Fourier Spectrum Steganalysis. The mean values and the standard deviations of the high frequency spectrum of the second and high order derivatives are extracted from the testing signals and the reference versions. A Support Vector Machine (SVM) is employed to discriminate the unadulterated carrier signals and the steganograms wherein covert messages were embedded. Experimental results show that our method delivers very good performance and holds great promise for effective detection of steganograms produced by Hide4PGP, Invisible Secrets, S-tools4 and Steghide.
Syntactic Pattern Recognition Using Finite Inductive Strings
Authors: Paul Fisher, Howard Fisher, Jinsuk Baek, Cleopas Angaye
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

A syntactic pattern recognition technique is described based upon a mathematical principle associated with finite sequences of symbols. The technique allows for fast recognition of patterns within strings, including the ability to recognize expected symbols that are close to the desired symbols, and mutations as well as both local and global substring matching. This allowance of deviation permits sequences to be subject to error and still be recognized. Some examples are provided illustrating the technique.
Discourse annotation and semantic annotation in the GNOME corpus
Authors: Massimo Poesio
Venue: Proceedings of the 2004 ACL Workshop on Discourse Annotation (2004)

The GNOME corpus was created to study the discourse and semantic properties of discourse entities that affect their realization and interpretation, and particularly salience. We discuss what information was annotated and the methods we followed.
Integration of Full-Coverage Probabilistic Functional Networks with Relevance to Specific Biological Processes
Authors: Katherine James, Anil Wipat, Jennifer Hallinan
Venue: Proceedings of the 6th International Workshop on Data Integration in the Life Sciences (2009)

Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to specific biological functions or processes. This problem may be overcome by extracting process-specific sub-networks, but this approach discards useful information and is of limited use in poorly annotated areas of the network. Here we describe an extension to existing integration methods which exploits dataset biases in order to emphasise interactions relevant to specific processes, without loss of data. We apply the method to high-throughput data for the yeast Saccharomyces cerevisiae, using Gene Ontology annotations for ageing and telomere maintenance as test processes. The resulting networks perform significantly better than unbiased networks for assigning function to unknown genes, and for clustering to identify important sets of interactions. We conclude that this integration method can be used to enhance network analysis with respect to specific processes of biological interest.
Personalization for Specific Users: Designing Decision Support Systems to Support Stimulating Learning Environments
Authors: Laura Măruşter, Niels R. Faber, Rob J. Haren
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

Creating adaptive systems becomes increasingly attractive in the context of specific groups of users, such as agricultural users. This group of users seems to differ with respect to information processing, knowledge management and learning styles. In this work we aim to offer directions toward increasing decision support systems usability, by tailoring toward user learning styles. The results show that decision support systems need to be redesigned toward providing agricultural users with a more efficient time management and study environment, and facilitating group interaction.
Semantic ambient media--an introduction
Authors: Artur Lugmayr, Thomas Risse, Bjoern Stockleben, Kari Laurila, Juha Kaario
Venue: Multimedia Tools and Applications (2009)

The medium is the message! And the message was literacy, media democracy and music charts. Mostly one single distinguishable medium such as TV, the Web, the radio, or books transmitted the message. Now in the age of ubiquitous and pervasive computing, where information flows through a plethora of distributed interlinked media--what is the message ambient media will tell us? What does semantic mean in this context? Which experiences will it open to us? What is content in the age of ambient media? Ambient media are embedded throughout the natural environment of the consumer--in his home, in his car, in restaurants, and on his mobile device. Predominant sample services are smart wallpapers in homes, location based services, RFID based entertainment services for children, or intelligent homes. The goal of this article is to define semantic ambient media and discuss the contributions to the Semantic Ambient Media Experience (SAME) workshop, which was held in conjunction with the ACM Multimedia conference in Vancouver in 2008. The results of the workshop can be found on: www.ambientmediaassociation.org .
Analysis of Some Mating and Collaboration Strategies in Evolutionary Algorithms
Authors: Anca Gog, Camelia Chira, D. Dumitrescu, Daniela Zaharie
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

The selection of mates in an evolutionary algorithm cansignificantly influence the exploration and the exploitationabilities of the search process. Currently there are severalstrategies to guide the mate selection or to restrict the matingpool. The aim of this paper is to analyze the behavior of afitness guided mate selection strategy and of a collaborationstrategy between population elements which use different matingrules. The behavior is analyzed empirically for mate selection inDifferential Evolution algorithms by considering that thepopulation is divided in two subpopulations characterized bydifferent mating rules. The dynamics of these subpopulations sizesis also theoretically analyzed.
An algorithm better than AO*?
Authors: Blai Bonet, Héctor Geffner
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 3 (2005)

Recently there has been a renewed interest in AO* as planning problems involving uncertainty and feedback can he naturally formulated as AND/OR graphs. In this work, we carry out what is prohably the first detailed empirical evaluation of AO* in relation to other AND/OR search algorithms. We compare AO* with two other methods: the well-known Value Iteration (VI) algorithm, and a new algorithm, Learning in Depth-First Search (LDFS). We consider instances from four domains. usc three different heuristic functions, and focus on the optimization of cost in the worst case (Max AND/OR graphs). Roughly we find that while AO* does better than VI in the presence of informed heuristics, VI does better than recent extensions of AO* in the presence of cycles in the AND/OR graph. At the same time, LOFS and its variant Bounded LOFS, which can be regarded as extensions of IDA*, are almost never slower than either AO* or VI, and in many cases, are orders-of-magnitude faster.
RavenCalendar: a multimodal dialog system for managing a personal calendar
Authors: Svetlana Stenchikova, Basia Mucha, Sarah Hoffman, Amanda Stent
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

Dialog applications for managing calendars have been developed for every generation of dialog systems research (Heidorn, 1978; Yankelovich, 1994; Constantinides and others, 1998; Horvitz and Paek, 2000; Vo and Wood, 1996; Huang and others, 2001). Today, Web-based calendar applications are widely used. A spoken dialog interface to a Web-based calendar application permits convenient use of the system on a handheld device or over the telephone.
Research on Lifetime Distribution for Nonmetallic Gasket Sealing
Authors: Yuyan Li, Boqin Gu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 03 (2009)

The research on product lifetime distribution is an important basis for assessing and improving product reliability level. The accelerated life test on nonmetallic gaskets was carried out and the failure data were obtained. After analyzing and processing these data by using the methods of least square procedure and K-S hypothesis testing, the lifetime of these gaskets was found to obey the Weibull distribution. According to the probability density function of the lifetime distribution, the reliability characteristics such as life expectancy and failure rate were obtained then. The research of lifetime distribution here provides a theoretical basis for predicting lifetime of the product and assessing its reliability characteristics as well as applying reliability growth technical measures in the nonmetallic gasket sealing.
Adaptive stabilization of a von Karman plate equation with a boundary output feedback control
Authors: Jong Yeoul Park, Yong Han Kang, Sun Hye Park
Venue: Computers Mathematics with Applications (2009)

We consider a von Karman plate equation with boundary memory condition and output feedback control. We prove the existence of solutions using the Galerkin method and then investigate the stabilization of the corresponding solutions by choosing a suitable Lyapunov functional.
Coverage Efficient Clustering with a Minimum Number of Active Sensors for Wireless Sensor Networks
Authors: Ji Gong, Gihwan Cho
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Energy efficient operations are essential to increase the lifetime of wireless sensor network. A clustering-based protocol is an approach that reduces energy during a data aggregation. In addition, allowing redundant nodes to be in a sleep mode at each round also reduces the energy consumption of the network. A redundant node is a sensor that its sensing area is covered by its nearby sensor nodes. In this paper, redundant nodes are determined by the minimum disc cover set concept at first. Then, cluster heads are selected among active nodes. The simulation results show that the proposed algorithm reduces the number of active nodes which is helpful to reduce system energy consumption and prolong network lifespan.
Multimodal Interaction for Mobile Learning
Authors: Irina Kondratova
Venue: Proceedings of the 5th International on ConferenceUniversal Access in Human-Computer Interaction. Part II: Intelligent and Ubiquitous Interaction Environments (2009)

This paper discusses issues associated with improving usability of user interactions with mobile devices in mobile learning applications. The focus is on using speech recognition and multimodal interaction in order to improve usability of data entry and information management for mobile learners. To assist users in managing mobile devices, user interface designers are starting to combine the traditional keyboard or pen input with "hands free" speech input, adding other modes of interaction such as speech-based interfaces that are capable of interpreting voice commands. Several research studies on multimodal mobile technology design and evaluations were carried out within our state-of the art laboratories. Results demonstrate feasibility of incorporating speech and multimodal interaction in designing applications for mobile devices. However, there are some important contextual constrains that limit applications with speech-only interfaces in mobile learning, including social and environmental factors, as well as technology limitations. These factors are discussed in detail.
Catoms: moving robots without moving parts
Authors: Brian Kirby, Jason Campbell, Burak Aksak, Padmanabhan Pillai, James Hoburg, Todd Mowry, Seth Copen Goldstein
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

We demonstrate modular robot prototypes developed as part of the Claytronics Project (Goldstein et al. 2005). Among the novel features of these robots ("catoms") is their ability to reconfigure (move) relative to one another without moving parts. The absence of moving parts is central to one key aim of our work, namely, plausible manufacturability at smaller and smaller physical scales using high-volume. low-unit-cost techniques such as batch photolithography, multimaterial submicron 3D lithographic processing, and self assembly. Claytronics envisions multi-million-module robot ensembles able to form into three dimensional scenes, eventually with sufficient fidelity so as to convince a human observer the scenes are real. This work presents substantial challenges in mechanical and electronic design, control, programming, reliability, power delivery, and motion planning (among other areas), and holds the promise of radically altering the relationship between computation, humans, and the physical world.
Analysis of EEG Epileptic Signals with Rough Sets and Support Vector Machines
Authors: Joo-Heon Shin, Dave Smith, Roman Swiniarski, F. Edward Dudek, Andrew White, Kevin Staley, Krzysztof J. Cios
Venue: Proceedings of the 12th Conference on Artificial Intelligence in Medicine: Artificial Intelligence in Medicine (2009)

Epilepsy is a common chronic neurological disorder that impacts over 1% of the population. Animal models are used to better understand epilepsy, particularly the mechanisms and the basis for better antiepileptic therapies. For animal studies, the ability to identify accurately seizures in electroencephalographic (EEG) recordings is critical, and the use of computational tools is likely to play an important role. Electrical recording electrodes were implanted in rats before kainate-induced status epilepticus (one in each hippocampus and one on the surface of the cortex), and EEG data were collected with radio-telemetry. Several data mining methods, such as wavelets, FFTs, and neural networks, were used to develop algorithms for detecting seizures. Rough sets, which were used as an additional feature selection technique in addition to the Daubechies wavelets and the FFTs, were also used in the detection algorithm. Compared with the seizure-at-once method by using the RBF neural network classifier used earlier on the same data [12], the new method achieved higher recognition rates (i.e., 91%). Furthermore, when the entire dataset was used, as compared to only 50% used earlier, preprocessing using wavelets, Principal Component Analysis, and rough sets in concert with Support Vector Machines resulted in accuracy of 94% in identifying epileptic seizures.
Gérard
Authors: Charly Awad, Kyle Duarte, Thibaut Naour
Venue: Proceedings of the 9th International Conference on Intelligent Virtual Agents (2009)

Our aim is to implement a motion capture database for the synthesis of virtual agents signing in French Sign Language (LSF), taking into account the semantic information implicitly contained in language data. The Gérard system is a first iteration along the path toward efficient and convincing animations of an LSF signer.
A mathematical model for slip phenomenon in a cavity-filling process of nanoimprint lithography
Authors: Nam Woong Kim, Kug Weon Kim, Hyo-Chol Sin
Venue: Microelectronic Engineering (2009)

Squeeze flow theory has been used as an effective tool to clarify how and which process conditions determine cavity-filling behavior in nanoimprint lithography (NIL). Conventional squeeze flow models used in NIL research fields have assumed no-slip conditions at the solid-to-liquid boundaries, that is, at the stamp-to-polymer or polymer-to-substrate boundaries. The no-slip assumptions are often violated, however, in micrometer- to nanometer-scale fluid flow. It is therefore necessary to adopt slip or partial slip boundary conditions. In this paper, an analytical mathematical model for the cavity-filling process of NIL that takes into account slip or partial slip boundary conditions is derived using squeeze flow theory. Velocity profiles, pressure distributions, imprinting forces, and evolutions of residual thickness can be predicted using this analytical model. This paper also aims to elucidate how far the slip phenomenon is able to promote the process rate.
The Presentation of the Properties of Vector-valued Higher-dimensional Wavelet Packets with Three-scale
Authors: Delin Hua, Hong-e Wu
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Wavelet analysis has become a popular subject in scientific research in the past twenty years. Nowadays, it has been a powerful tool for exploring and solving many complicated problems in natural science and engineering computation. In this article, the notion of orthogonal vector-valued wavelet packets with 3I_s-dilation matrix in higher dimensions is introduced. A procedure for constructing them is presented. Their orthogonal properties are characterized by virtue of finite group theory, time-frequency analysis method and matrix theory, and orthogonality formulas are obtained.
Effect of small Sn-3.5Ag-0.5Cu additions on the structure and properties of Sn-9Zn solder in ball grid array packages
Authors: Asit Kumar Gain, Y. C. Chan, Ahmed Sharif, Winco K. C. Yung
Venue: Microelectronic Engineering (2009)

Sn-9Zn with various additions of Sn-3.5Ag-0.5Cu powder was prepared by mechanically dispersing different weight percentages (1, 3, 5 and 7) of Sn-Ag-Cu powder into Sn-9Zn solder paste. In the Sn-Zn solder, scallop-shaped AuZn"3 intermetallic compound was found at the interfaces. On the other hand, in the Sn-3.5Ag-0.5Cu content solders, an additional @e-AgZn"3 intermetallic compound layer was found to be well adhered on the top surface of the AuZn"3 layer and the @e-AgZn"3 layer thickness increased with the number of reflow cycles. In addition, fine spherical-shaped @e-AgZn"3 intermetallic compound particles as well as an acicular-shaped Zn-rich phase was clearly observed in the @b-Sn matrix. On increasing the Sn-Ag-Cu content, the shear load was increased from 1.80 to 2.03kg after one reflow cycle. In the Sn-3.5Ag-0.5Cu content solders, the fracture surfaces exhibited typical ductile behavior with very rough dimpled surfaces while the fracture surface in the Sn-Zn solder gave fractures with a brittle appearance. In the fracture surface of the Sn-3.5Ag-0.5Cu content solders, some dimples were clearly observed associated with the formation of spherical-shaped @e-AgZn"3 intermetallic compound particles.
Analysis with ADAMS/ANSYS on Dynamic Properties of Rotating Hook-Lift Garbage Truck
Authors: Guanglin Shi, Shuxun Chen, Guangmin Liang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This paper realized structural analysis of rotating hook-lift garbage truck based on ADAMS/ANSYS. Firstly, software ADAMS was used to realize dynamic simulation of working process. In order to get curves of dynamic parameters of each component simultaneously, it took external loads and equilibrium of reaction forces of each part as checking conditions. Secondly, this research took the information got from ADAMS as boundary conditions of finite element analysis, and then finished precise intensity analysis. Based on different working cases this paper designed experiments to compare the results of analysis, it showed destroyed position was just the position of maximum stress in analysis results, which proved this analysis was right, moreover this analysis supplied technique instructions to realize optimization of dynamic properties of rotating hook-lift.
Shadow art
Authors: Niloy J. Mitra, Mark Pauly
Venue: ACM Transactions on Graphics (TOG) (2009)

"To them, I said, the truth would be literally nothing but the shadows of the images." - Plato, The Republic Shadow art is a unique form of sculptural art where the 2D shadows cast by a 3D sculpture are essential for the artistic effect. We introduce computational tools for the creation of shadow art and propose a design process where the user can directly specify the desired shadows by providing a set of binary images and corresponding projection information. Since multiple shadow images often contradict each other, we present a geometric optimization that computes a 3D shadow volume whose shadows best approximate the provided input images. Our analysis shows that this optimization is essential for obtaining physically realizable 3D sculptures. The resulting shadow volume can then be modified with a set of interactive editing tools that automatically respect the often intricate shadow constraints. We demonstrate the potential of our system with a number of complex 3D shadow art sculptures that go beyond what is seen in contemporary art pieces.
A Simple Simulation Predicting Driver Behavior, Attitudes and Errors
Authors: Aladino Amantini, Pietro Carlo Cacciabue
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

This paper presents the simulation tool called SSDRIVE (Simple Simulation of Driver performance). Following a brief description of the theoretical background and basic algorithms that describe the performance of drivers, the paper presents two case studies of DVE interactions, predicting dynamic situations according to different driver attitudes, in similar traffic conditions. In this way the potential ability of the simulation tool to consider behaviors and errors at different levels of complexity is demonstrated.
Online co-localization in indoor wireless networks by dimension reduction
Authors: Jeffrey Junfeng Pan, Qiang Yang, Sinno Jialin Pan
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

This paper addresses the problem of recovering the locations of both mobile devices and access points from radio signals that come in a stream manner, a problem which we call online co-localization, by exploiting both labeled and unlabeled data from mobile devices and access points. Many tracking systems function in two phases: an offline training phase and an online localization phase. In the training phase, models are built from a batch of data that are collected offline. Many of them can not cope with a dynamic environment in which calibration data may come sequentially. In such case, these systems may gradually become inaccurate without a manually costly re-calibration. To solve this problem, we proposed an online co-localization method that can deal with labeled and unlabeled data stream based on semi-supervised manifold-learning techniques. Experiments conducted in wireless local area networks show that we can achieve high accuracy with less calibration effort as compared to several previous systems. Furthermore, our method can deal with online stream data relatively faster than its two-phase counterpart.