ppxscal/embedding_network huggingface dataset:
A comparative analysis of principal component and independent component techniques for electrocardiograms
Authors: M. P. S. Chawla
Venue: Neural Computing and Applications (2009)

Principal component analysis (PCA) is used for ECG data compression, denoising and decorrelation of noisy and useful ECG components or signals. In this study, a comparative analysis of independent component analysis (ICA) and PCA for correction of ECG signals is carried out by removing noise and artifacts from various raw ECG data sets. PCA and ICA scatter plots of various chest and augmented ECG leads and their combinations are plotted to examine the varying orientations of the heart signal. In order to qualitatively illustrate the recovery of the shape of the ECG signals with high fidelity using ICA, corrected source signals and extracted independent components are plotted. In this analysis, it is also investigated if difference between the two kurtosis coefficients is positive than on each of the respective channels and if we get a super-Gaussian signal, or a sub-Gaussian signal. The efficacy of the combined PCA&#x2013;ICA algorithm is verified on six channels V1, V3, V6, AF, AR and AL of 12-channel ECG data. ICA has been utilized for identifying and for removing noise and artifacts from the ECG signals. ECG signals are further corrected by using statistical measures after ICA processing. PCA scatter plots of various ECG leads give different orientations of the same heart information when considered for different combinations of leads by quadrant analysis. The PCA results have been also obtained for different combinations of ECG leads to find correlations between them and demonstrate that there is significant improvement in signal quality, i.e., signal-to-noise ratio is improved. In this paper, the noise sensitivity, specificity and accuracy of the PCA method is evaluated by examining the effect of noise, base-line wander and their combinations on the characteristics of ECG for classification of true and false peaks.
On Enhancing Event-to-Sink Data Delivery Throughput in Sensor Networks
Authors: Md. Abdur Razzaque, Choong Seon Hong, Cho Jin Woong, Lee Jang Yeon
Venue: Proceedings of the 2009 Ninth Annual International Symposium on Applications and the Internet (2009)

The many-to-one multihop traffic pattern of Wireless Sensor Networks (WSNs) puts a great challenge on enhancing the event-to-sink data delivery throughput. Because, in CSMA/CA driven medium access control protocols, contention of the shared medium raises both at the event detection area and near the sink, which in turn increases the packet collisions greatly. In this paper, we exploit the amount of traffic load a node carries to control its medium access frequency by assigning the minimum contention window (CWmin) value in a differentiated way. The proposed scheme is fully distributed. The performance of the proposed scheme is evaluated by ns-2 simulations and the results show that it can significantly decrease the packet losses due to collisions and buffer drops, which in turn helps to enhance event-to-sink throughput. It also outperforms the existing approaches.
DGTS: Integrated Typing and Pointing
Authors: Iman Habib, Niklas Berggren, Erik Rehn, Gustav Josefsson, Andreas Kunz, Morten Fjeld
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

Capacitive sensing is used in many different fields of application. It has been implemented in such devices as mobile phones and remote controls. However, up until now the physical sensing area has remained limited despite the widespread use of larger input devices such as keyboards. We present DGTS, which seamlessly integrates keyboard typing and cursor pointing. This input device offers multi-finger operation for scrolling and other specialized input commands. The objective of this work is to replace computer mice and touchpads by integrating capacitive sensing into a layer within the keyboard thereby reducing the space required for pointing devices. This paper gives the technical background, shows our contribution, and concludes with initial tests.
The Research of the Classroom Teaching Quality Based on AHP and Fuzzy Comprehensive Evaluation
Authors: Yan-ming Qi, Chang-long Wang
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

It is of great importance to evaluate scientifically teachers’ teaching quality in the classroom. The methods of AHP and Fuzzy comprehensive evaluation are applied to evaluation of classroom teaching quality. By analyzing constituent elements of teaching quality, proposed that the index system should be on the basis of teaching attitude, teaching method, teaching content and teaching effectiveness, index weights should be determined by using of AHP, the model should be established by using of Fuzzy comprehensive evaluation, which turns out that the evaluation results can reflect the management of teaching quality more objectively, so as to provide a new way for evaluation of classroom teaching quality, thus it has theoretical and practical value.
Proceedings of the Workshop on Grammar Engineering Across Frameworks
Venue: ACL Workshops (2008)

The GEAF workshop aims to bring together grammar engineers from different frameworks to compare research and methodologies, particularly around the themes of evaluation, modularity, maintainability, relevance to theoretical and computational linguistics, and applications of "deep" grammars to real-world domains and NLP tasks. Recent years have seen the development of techniques and resources to support robust, deep grammatical analysis of natural language in real-world domains and applications. The demands of these types of tasks have resulted in significant advances in areas such as parser efficiency, hybrid statistical/symbolic approaches to disambiguation, and the acquisition of large-scale lexicons. The effective acquisition, development, maintenance and enhancement of grammars is a central issue in such efforts, and the size and complexity of realistic grammars makes these tasks extremely challenging; indeed, these tasks are often tackled in ways that have much in common with software engineering. This workshop aims to bring together grammar engineers from different frameworks --- for example LFG, HPSG, TAG, CCG, dependency grammar --- to compare their research and methodologies.
On hierarchical loglinear models in capture-recapture studies
Authors: Na You, Chang Xuan Mao
Venue: Computational Statistics Data Analysis (2009)

Hierarchical loglinear models are widely used in capture-recapture studies. It is important to implement these models so that a full model selection procedure can be carried out. An algorithm used to count the number of monotone boolean functions is adopted to generate all the monotone boolean functions, which in turn is used to generate all coefficient matrices of hierarchical loglinear models. The proposed methods are implemented in an R package. Two real examples are analyzed for illustration.
Truthful Mechanisms via Greedy Iterative Packing
Authors: Chandra Chekuri, Iftah Gamzu
Venue: Proceedings of the 12th International Workshop and 13th International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (2009)

An important research thread in algorithmic game theory studies the design of efficient truthful mechanisms that approximate the optimal social welfare. A fundamental question is whether an ¿-approximation algorithm translates into an ¿-approximate truthful mechanism. It is well-known that plugging an ¿-approximation algorithm into the VCG technique may not yield a truthful mechanism. Thus, it is natural to investigate properties of approximation algorithms that enable their use in truthful mechanisms.The main contribution of this paper is to identify a useful and natural property of approximation algorithms, which we call loser-independence; this property is applicable in the single-minded and single-parameter settings. Intuitively, a loser-independent algorithm does not change its outcome when the bid of a losing agent increases, unless that agent becomes a winner. We demonstrate that loser-independent algorithms can be employed as sub-procedures in a greedy iterative packing approach while preserving monotonicity. A greedy iterative approach provides a good approximation in the context of maximizing a non-decreasing submodular function subject to independence constraints. Our framework gives rise to truthful approximation mechanisms for various problems. Notably, some problems arise in online mechanism design.
Clustering-Based Construction of Hidden Markov Models for Generative Kernels
Authors: Manuele Bicego, Marco Cristani, Vittorio Murino, Elżbieta Pękalska, Robert P. Duin
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the first and mostly-used representative, which lies on a widely investigated mathematical background. The manufacture of a generative kernel flows down through a two-step serial pipeline. In the first, "generative" step, a generative model is trained, considering one model for class or a whole model for all the data; then, features or scores are extracted, which encode the contribution of each data point in the generative process. In the second, "discriminative" part, the scores are evaluated by a discriminative machine via a kernel, exploiting the data separability. In this paper we contribute to the first aspect, proposing a novel way to fit the class-data with the generative models, in specific, focusing on Hidden Markov Models (HMM). The idea is to perform model clustering on the unlabeled data in order to discover at best the structure of the entire sample set. Then, the label information is retrieved and generative scores are computed. Experimental, comparative test provides a preliminary idea on the goodness of the novel approach, pushing forward for further developments.
Study on Temperature Field and Thermal Deformation of Roll Sleeve in Twin-Roll Strip Casting
Authors: Zheng Chang, Guangming Zhu
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

In strip casting, casting roll is a key equipment, for its temperature distribution and hot deformation can determine the casting process. In the paper, nonlinear thermo-structural finite element method (FEM) is used to analyze casting roll temperature distribution and hot deformation. Then distribution discipline of casting roll temperature and hot deformation is figured out. After that, the influence of casting velocity to the casting roll is analyzed and the conclusion is drawn that during stable casting period, casting roll temperature only fluctuates in the surface of the casting roll, and in the core, the temperature is relatively stable, moreover, casting velocity is lower, the fluctuation amplitude is larger.
Comprehensive Evaluation on the Durability of Concrete Structure Base on Uncertain Measurements
Authors: Chang-long Wang
Venue: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009) (2009)

It is unascertained and non-linear that evaluates the durability of concrete structure factors and their impact. Accordingly, selected the most impact on the durability of concrete structures to assess factors as indexes, established unascertained measure comprehensive evaluation model. Applications by the model showed that the assessment result can objectively reflect the durability of concrete structure, which provided a new method and way for assessment of concrete durability and has theoretical and practical value. Due to the ordered division of assessment space, the unascertained measure model improves distinguish level. It has reliable assessment result and is a practical model.
Recovering Affine Deformations of Fuzzy Shapes
Authors: Attila Tanács, Csaba Domokos, Nataša Sladoje, Joakim Lindblad, Zoltan Kato
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Fuzzy sets and fuzzy techniques are attracting increasing attention nowadays in the field of image processing and analysis. It has been shown that the information preserved by using fuzzy representation based on area coverage may be successfully utilized to improve precision and accuracy of several shape descriptors; geometric moments of a shape are among them. We propose to extend an existing binary shape matching method to take advantage of fuzzy object representation. The result of a synthetic test show that fuzzy representation yields smaller registration errors in average. A segmentation method is also presented to generate fuzzy segmentations of real images. The applicability of the proposed methods is demonstrated on real X-ray images of hip replacement implants.
Designing for Change: Engineering Adaptable and Adaptive User Interaction by Focusing on User Goals
Authors: Bruno S. Silva, Ariane M. Bueno, Simone D. Barbosa
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends (2009)

In the human-computer interaction area, research work in end-user programming, end-user development, and user or system-driven adaptation of interactive systems has attempted to cope with variations in users' intents, context changes and evolutions. In the field of requirements engineering, research that addresses similar issues has been called variability analysis. Most work in variability analysis, however, focuses on prioritizing one or few possible solutions to be implemented in the final product, whereas in human-computer interaction many researchers advocate that we should strive to enable users to adjust and adapt the product as needed. This paper presents an approach to bring the results obtained in requirements engineering to inform the choice of interaction design solutions to cope with variability.
The impact of vertical specialization on hierarchical multi-agent systems
Authors: Steven Okamoto, Paul Scerri, Katia Sycara
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Hierarchies are one of the most common organizational structures observed in multi-agent systems. In this paper we study vertical specialization as a reason for hierarchical structures. In vertically specialized systems, more highly skilled agents are also more costly. By using less capable agents to initially process tasks and forwarding only exceptional tasks to more capable agents, such systems may be able to economize on the number of highly capable agents. The result is a hierarchical structure with least capable agents at the bottom. However, such a structure increases the delay in completing some tasks, because they must pass through multiple levels of control. Thus, vertical specialization presents a tradeoff between economizing on skilled agents and increasing task completion time. We find that for a wide range of settings, vertical specialization induces an optimal hierarchy of height at most three. This suggests that a multi-agent system designer interested in exploiting vertical specialization needs to use at most three levels of specialization in order to reap most of the benefits.
CU-TMP: temporal relation classification using syntactic and semantic features
Authors: Steven Bethard, James H. Martin
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

We approached the temporal relation identification tasks of TempEval 2007 as pair-wise classification tasks. We introduced a variety of syntactically and semantically motivated features, including temporal-logic-based features derived from running our Task B system on the Task A and C data. We trained support vector machine models and achieved the second highest accuracies on the tasks: 61% on Task A, 75% on Task B and 54% on Task C.
POSSLT: a Korean to English spoken language translation system
Authors: Donghyeon Lee, Jonghoon Lee, Gary Geunbae Lee
Venue: Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations on XX (2007)

The POSSLT is a Korean to English spoken language translation (SLT) system. Like most other SLT systems, automatic speech recognition (ASR), machine translation (MT), and text-to-speech (TTS) are coupled in a cascading manner in our POSSLT. However, several novel techniques are applied to improve overall translation quality and speed. Models used in POSSLT are trained on a travel domain conversational corpus.
Manifold Answer-Set Programs for Meta-reasoning
Authors: Wolfgang Faber, Stefan Woltran
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

In answer-set programming (ASP), the main focus usually is on computing answer sets which correspond to solutions to the problem represented by a logic program. Simple reasoning over answer sets is sometimes supported by ASP systems (usually in the form of computing brave or cautious consequences), but slightly more involved reasoning problems require external postprocessing. Generally speaking, it is often desirable to use (a subset of) brave or cautious consequences of a program P 1 as input to another program P 2 in order to provide the desired solutions to the problem to be solved. In practice, the evaluation of the program P 1 currently has to be decoupled from the evaluation of P 2 using an intermediate step which collects the desired consequences of P 1 and provides them as input to P 2. In this work, we present a novel method for representing such a procedure within a single program, and thus within the realm of ASP itself. Our technique relies on rewriting P 1 into a so-called manifold program, which allows for accessing all desired consequences of P 1 within a single answer set. Then, this manifold program can be evaluated jointly with P 2 avoiding any intermediate computation step. For determining the consequences within the manifold program we use weak constraints, which is strongly motivated by complexity considerations. As an application, we present an encoding for computing the ideal extension of an abstract argumentation framework.
Transferring localization models over time
Authors: Vincent Wenchen Zheng, Evan Wei Xiang, Qiang Yang, Dou Shen
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 3 (2008)

Learning-based localization methods typically consist of an offline phase to collect the wireless signal data to build a statistical model, and an online phase to apply the model on new data. Many of these methods treat the training data as if their distributions are fixed across time. However, due to complex environmental changes such as temperature changes and multi-path fading effect, the signals can significantly vary from time to time, causing the localization accuracy to drop. We address this problem by introducing a novel semisupervised Hidden Markov Model (HMM) to transfer the learned model from one time period to another. This adaptive model is referred to as transferred HMM (TrHMM), in which we aim to transfer as much knowledge from the old model as possible to reduce the calibration effort for the current time period. Our contribution is that we can successfully transfer out-of-date model to fit a current model through learning, even though the training data have very different distributions. Experimental results show that the TrHMM method can greatly improve the localization accuracy while saving a great amount of the calibration effort.
Process and Location-Aware Information Service System for the Disabled and the Elderly
Authors: Manchul Han, Gunhee Kim, Sehyung Park, Laehyun Kim, Sungdo Ha
Venue: Proceedings of the 5th International Conference on Universal Access in Human-Computer Interaction. Part III: Applications and Services (2009)

This paper presents a context-aware information service system for people with disabilities and for older adults. The system guides users who have difficulties in performing complicated tasks or finding paths at public places such as hospitals or government offices. The system is composed of sensor networks and a local information system which work together to gather the location and the process information, a user device which directly provides guidance to the user, and an information service server which understands the user context and provides guide contents.
Adaptive range-based mobile multicast
Authors: Shengling Wang, Yong Cui, Ke Xu, Sajal Das, Jianping Wu
Venue: Proceedings of the 1st ACM workshop on Mobile internet through cellular networks (2009)

This paper proposes an efficient, Adaptive Range-Based Mobile Multicast (ARBMoM) protocol. ARBMoM uses the Multicast Home Agent (MHA) to deliver multicast packets to mobile users. The MHA of a user in ARBMoM is decided not only by its location, but also by its mobility and service characteristics. This makes each router act as either a regular foreign agent (FA) or an MHA, thus balancing the load. To find an optimal service range for an MHA to trade off between the multicast packet delivery and the multicast service disruption latency, we model the user's movement in 2-D mesh network using Markov chain. To reduce the computational complexity, we aggregate the states by using the mobile movement symmetry. In addition, we propose a method to easily obtain the aggregate state set and the transition probability between any two aggregate states once the service range is given. In addition, ARBMoM is compatible with any multicast tree configuration algorithm. Both simulation and numerical results demonstrate that ARBMoM enhances the system performance.
Balancing Design Freedom and Constraints in Wall Posters Masquerading as AR Tracking Markers
Authors: Ryuhei Tenmoku, Akito Nishigami, Fumihisa Shibata, Asako Kimura, Hideyuki Tamura
Venue: Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009 (2009)

This paper describes how to construct a mixed reality (MR) environment by adopting a geometric registration method using visually unobtrusive flat posters on the wall. The proposed method is one of the several approaches of the semi-fiducial invisibly coded symbols (SFINCS) research project, the purpose of which is achieving a good balance between elegance with regard to the environment and robust registration. In this method, posters tentatively used for geometric registration are designed to blend with the environment. However, they are recognized as markers based on certain design rules. Posters in a real scene can be found in real time using these design rules. This paper introduces procedures for developing poster design rules using toolkits developed by us.