ppxscal/embedding_network huggingface dataset:
Adaptive K-Local Hyperplane (AKLH) Classifiers on Semantic Spaces to Determine Health Consumer Webpage Metadata
Authors: Guocai Chen, Jim Warren, Tao Yang, Vojislav Kecman
Venue: Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems (2008)

In this paper we look at automated classification to determine a metadata attribute related to the 'tone' of a consumer-oriented breast cancer webpage as Medical or Supportive. We use a semantic space model called Hyperspace Analog to Language (HAL), based on word co-occurrence, to provide features for webpage classification. Adaptive K-Local Hyperplane (AKLH), an extension of K Nearest Neighbour, is then applied to training and testing data. We observe 92% classification accuracy on test cases. This combination of methods appears promising for identifying non-trivial metadata attributes of consumer health webpages, with potential use embedded in a search engine or as a meta-data coding support tool.
Wireless C45 based vital-signs monitoring system for patient after heart operation care
Authors: S. Noimanee, T. Tunkasiri, K. Siriwitayakorn, J. Tuntrakoon
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

The use of vital-signs monitoring to detect patient vital signs with the intent to prevent patients dead after heart operation falls. This paper presents mobile patient monitoring system laboratory prototype, which provides patient electrocardiogram signals transferring via mobile extension technology with old version mobile phone in Thailand. At the patient's location, a wireless old mobile phone C45-based monitor is used to acquire continuously the patient's vital signs, including heart rate, standard-lead electrocardiography, etc. The system has been evaluated by physician verification and laboratory test. Through the mobile extension services in Thailand, the patient's vital signs signals can be transmitted in real-time to a central management unit, and authorized medical staffs or physician can access the ECG wave form, data and the case history of each patient by mobile personal digital assistant or PC trough Wi-Fi technology, either by the central management unit or the wireless devices. The results were that the prototype reduced the risk of heart attack by 15%. Most benefit was due to 30% drop in the risk of heart-related death. Their also show that the mobile PDA is superior to the currently used monitors both in mobility and in usability, therefore, better suited to patient transport.
Directional Properties of Human Hand Force Perception in the Maintenance of Arm Posture
Authors: Yoshiyuki Tanaka, Toshio Tsuji
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

This paper discusses the directional properties of human hand force perception during maintained arm posture in operation of a robotic device by means of robotic and psychological techniques. A series of perception experiments is carried out using an impedance-controlled robot depending on force magnitudes and directions in the different arm postures. Experimental results demonstrate that human hand force perception is much affected by the stimulus direction and can be expressed with an ellipse. Finally, the relationship between hand force perception properties and hand force manipulability is analyzed by means of human force manipulability ellipse.
Effect of the accelerated reader program on academic achievement
Authors: Pamela Sallee
Venue:  (2008)

This dissertation was designed to investigate the effect the Accelerated Reader program had on academic achievement as measured by questionnaires and computerized assessment data following two months of participation and non-participation in the Accelerated Reader program. Primary and elementary school principals and their faculties, drawn from four schools in the Appling County School System, were surveyed. Student assessment data were analyzed in terms of achievement, participation, and ethnicity. Questionnaires revealed that teachers promoted use of the Accelerated Reader program as a component to the reading curriculum; however, it was an overwhelming consensus that the program be used as a supplement to the reading series, not as a single adopted reading program. Pre- and post-assessment data revealed significant gains in reading comprehension. Additionally, it was determined that gender and ethnicity did have an effect on reading achievement, but not significantly.
Semi-supervised Nasopharyngeal Carcinoma Lesion Extraction from Magnetic Resonance Images Using Online Spectral Clustering with a Learned Metric
Authors: Wei Huang, Kap Luk Chan, Yan Gao, Jiayin Zhou, Vincent Chong
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

In this paper, we consider the extraction of nasopharyngeal carcinoma lesion from MR images as a region segmentation problem. We propose a semi-supervised segmentation approach to segment the lesion in two steps. First, a metric is learned in a supervised fashion, which maximizes the separation between two groups of pixels (tumor or non-tumor) with minimal user interaction. Second, the learned metric is used to complete extraction of tumor region in an unsupervised fashion. Several experiments were conducted to evaluate the performance of similar methods with learned metrics for grouping or classifying pixels to form the tumor region. It is observed that the spectral clustering-based method performs well and the performance is comparable or marginally better than the discriminative SVM-based method.
An empirical assessment of the crosscutting concern problem
Authors: Alfred Aho
Venue:  (2008)

Modularity is essential for creating evolvable software. Traditional programming languages limit the level of modularity that can be achieved because they provide only one way to structure the program, e.g., as a hierarchy of types. Regardless of how a program is structured, some features, requirements, or other types of concerns of the program cannot be modularized; that is, they cut across the program's structure. These so-called crosscutting concerns result in programs that are difficult to understand and reason about, to divide into manageable pieces, to reuse, and to evolve. In this dissertation, we assess the impact of crosscutting concerns on software quality. Little is known about the impact because determining the concerns of a program and how they are implemented is difficult, existing metrics for quantifying crosscutting are inadequate, and empirical evidence is lacking. To locate the source code that implements a concern, i.e., concern location, we present a new technique called prune dependency analysis, which can be combined with existing concern location techniques to dramatically improve accuracy. We developed CERBERUS, a potent hybrid technique for locating concerns that combines information retrieval, execution tracing, and prune dependency analysis . Our experiments show that prune dependency analysis can boost the recall of information-retrieval-based concern location by 155% and execution tracing by 104%. In addition, we show that our combined technique outperformed other techniques when run individually or in pairs. After using our techniques to locate all the code that implements a concern, our novel concern metrics quantify the amount of crosscutting that exists. We assessed the crosscutting concern problem by performing rigorous empirical studies of five medium-sized programs. We found a moderate to strong statistically significant correlation between the amount of crosscutting and the number of defects. That is, the more a concern crosscuts the program, the more likely it is to have defects. We also found that the crosscutting concern problem was prevalent: 86% of the concerns we analyzed were crosscutting, concerns were implemented by 6 classes on average, and classes implement 10 concerns on average.
Creation of environmental health information system for public health service: A pilot study
Authors: Ling Li, Li Xu, Hueiwang Anna Jeng, Dayanand Naik, Thomas Allen, Maria Frontini
Venue: Information Systems Frontiers (2008)

Despite more than a decade of research on medical information systems, deficiencies exist in our capability of establishing an effective environmental health information infrastructure. In this research, we present a pilot study on creating a feasible environmental health information infrastructure. The newly-developed environmental health information system is a web-based platform that integrates databases, decision-making tools, geographic information systems for supporting public health service and policy making. The study, which is a part of a comprehensive effort known as Environmental Public Health Tracking proposed by the Center for Disease Control and Prevention, opens the door for future research on a large scale nation-wide healthcare information infrastructure.
Competition and Fraud in Online Advertising Markets
Authors: Bob Mungamuru, Stephen Weis
Venue: Financial Cryptography and Data Security: 12th International Conference, FC 2008, Cozumel, Mexico, January 28-31, 2008. Revised Selected Papers (2008)

An economic model of the online advertising market is presented, focusing on the effect of ad fraud. In the model, the market is comprised of three classes of players: publishers, advertising networks, and advertisers. The central question is whether ad networks have an incentive to aggressively combat fraud. The main outcome of the model is to answer this question in the affirmative.
VII International Workshop on Computer Graphics and Geometric Modeling --- CGGM'2008
Authors: Andrés Iglesias
Venue: Proceedings of the 8th international conference on Computational Science, Part II (2008)

This short paper is intended to give our readers a brief insight about the Seventh International Workshop on Computer Graphics and Geometric Modeling-CGGM'2008, held in Krakow (Poland), June 23-25 2008 as a part of the ICCS'2008 general conference.
Acoustic Tomography for Non Destructive Testing of Stone Masonry
Authors: M. Camplani, B. Cannas, S. Carcangiu, G. Concu, A. Fanni, A. Montisci, M. L. Mulas
Venue: Proceedings of the international conference on Computational Science and Its Applications, Part II (2008)

Acoustic methods seem to be very suitable for evaluating a building condition because they give information with immediacy, rapidity and relatively low cost. They are based on measurements of the velocity of acoustic waves propagating through the material. Those methods are often carried out applying the Through Transmission Technique, in which the wave is transmitted by a transducer through the test object and received by a second transducer on the opposite side. In this paper, the sonic tomography imaging based on this technique has been used for non destructive testing of a stone masonry. The tomography implies that a ill-posed linear equations system has to be solved, in order to determine the velocities distribution inside the tested structure, thus highlighting the presence of anomalies. Different inversion algorithms, chosen between the most commonly used, have been implemented for determining the distribution of waves velocity in selected sections of the tested masonry.
Rwa algorithm design and performance analysis for all-optical networks subject to physical impairments
Authors: Maite Brandt-Pearce
Venue:  (2008)

Thanks to the rapid development of optical signal processing functions for fiber communication systems, and novel routing techniques and switching node architectures, highly flexible and transparent so-called "wavelength routed all-optical network" solutions have emerged. All-optical networks eliminate the restrictions incurred by periodic electronic regeneration, as signals remain in the optical domain from end-to-end through a lightpath. As an optical signal propagates along a lightpath to its destination in wavelength-routed optical networks, the signal's quality of transmission is degraded by physical impairments. Consequently, the signal's bit error rate at the destination's receiver might become unacceptably high. Thus optical fiber components and intermediate switching nodes can be the dominant reason calls are blocked in networks. Moreover, estimating the impact of physical impairments on the quality of a lightpath before provisioning it can cause a significant delay, which also affects the performance of networks. In this dissertation, we provide a general mathematical formulation to the optimal routing and wavelength assignment in impaired optical networks. Several dominant degradations from the physical layer are exemplified and incorporated in the general formulation. Realizing that routing algorithms and wavelength assignment algorithms can both be powerful tools used to mitigate the effect of physical impairments, we study the problem of designing efficiently routing and wavelength assignment algorithms in all-optical networks with physical impairments. Several adaptive routing policies accounting for the quality of transmission in optical networks are proposed to efficiently and intelligently find a feasible lightpath. In particular, we propose using the impairments variance along the route as a selection criterion. In addition, several spectrum allocation techniques are presented to alleviate physical impairments and also decrease the processing delay due to the QoT estimation. To thoroughly understand the RWAs and evaluate their performance incorporating multiple physical layer impairments, we present an analytical technique and compare it to simulation results we are able to predict the network behavior correctly on various network topologies. We then investigate the impact of processing delay induced from QoT estimation. Simulations presented show that our design successfully remove not only part of the physical degradation but also decrease the delay due to QoT estimation.
Decentralized virtualization in systems administration education
Authors: Bill Stackpole, Jason Koppe, Thomas Haskell, Laura Guay, Yin Pan
Venue: Proceedings of the 9th ACM SIGITE conference on Information technology education (2008)

The Networking and Systems Administration Laboratories are vital components of the applied academic experience of the students of the Networking, Security and Systems Administration Department. Students are currently able to implement multiple heterogeneous computing infrastructures using Symantec's Ghost Solution Suite. This paper presents and explores virtual lab environments that support alternative preparation solutions that will increase laboratory utilization, student productivity, and provide students with exposure to virtualization technology.
Speeding Up IDM without Degradation of Retrieval Quality
Authors: Michael Springmann, Heiko Schuldt
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

The Image Distortion Model (IDM) has previously shown good retrieval quality. However, one of the limitations that may limit its use in a wider range of applications is computational complexity. In this paper, we present an approach that applies several optimizations to decrease the retrieval time of IDM without degrading the quality of query results. We were able to perform the IDM in less than 1.5 seconds per query on an 8-way server and 16 seconds on a standard Pentium 4. In particular, the early termination strategy we applied contributed a speedup of up to 4.9. We also extended the possible displacements to an area of 7×7 pixels with a local context of up to the same size. The results submitted to the medical automatic annotation task of ImageCLEF'2007 were ranked in the upper third. Most importantly, the proposed techniques are not limited to IDM but can also be applied to other expensive distance measures.
Estimating Sales Opportunity Using Similarity-Based Methods
Authors: Sholom M. Weiss, Nitin Indurkhya
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

We describe an application of predicting sales opportunity using similarity-based methods. Sales representatives interface with customers based on their potential for product sales. Estimates of this potential are made under optimistic conditions and referred to as the opportunity: How much can be sold if a sale were to be made? Since this can never be verified exactly, the direct use of predictive models is difficult. In building systems for estimating sales opportunity, the key issues are: (a) predictions for targets that cannot be verified, (b) explanatory capabilities (c) capability to incorporate external knowledge (d) parallel computation of multiple targets and other efficiencies (e) capability to calibrate optimism in the predictions. (f) method stability and ease of maintenance for incorporating new examples. Empirical experiments demonstrate excellent predictive accuracy while also meeting these objectives. The methods have been embedded in a widely-used similarity-based system for IBM's worldwide sales force.
Semantic Services for Grid-Based, Large-Scale Science
Authors: William E. Johnston
Venue: IEEE Intelligent Systems (2004)

The process of large-scale science must evolve to facilitate the next steps of scientific discovery. Grid technology and semantic tools will be valuable in dealing with the complex multidisciplinary simulation and data environments that next-generation science will require.
An Effective Signal De-noising Algorithm Combining Optimal Wavelet Packet Basis and Translation-Invariant Algorithm
Authors: Xiaojing Chen, Di Wu, Yong He, Shou Liu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

An effective algorithm combining optimal wavelet packet basis (OWPB) algorithm and translation-invariant (TI) wavelet transform algorithm was put forward. Based on wavelet packet analysis, according to least cost function principle, OWPB of signal decomposition was obtained, which would better match the requested localization in the frequency domain and ensure an efficient de-noising: Firstly, the estimated OWPB coefficients were gained by using thresholding methods, and then based on inverse discrete wavelet packet transform (IDWPT), the de-noised signals were obtained by using estimated OWPB coefficients. Because wavelet thresholding de-noising methods would result in Pseudo-Gibbs phenomenon in the neighborhood of discontinuities, in order to suppress it, this study adopt TI wavelet transform algorithm. The results of experiment indicated the algorithm proposed in the pager was better than traditional wavelet packet transform (WPT) thresholding de-noising methods.
On Neural Network Switched Stabilization of SISO Switched Nonlinear Systems with Actuator Saturation
Authors: Fei Long, Wei Wei
Venue: Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks (2007)

As we know, saturation, deadzone, backlash, and hysteresis are the most common actuator nonlinearities in practical control system applications. Saturation nonlinearity is unavoidable in most actuators. In this paper, we address the Neural Network saturation compensation for a class of switched nonlinear systems with actuator saturation. An actuator saturation compensation switching scheme for switched nonlinear systems with its subsystem in Brunovsky canonical form is presented using Neural Network. The actuator saturation is assumed to be unknown and the saturation compensator is introduced into a feed-forward path. The scheme that leads to switched stability and disturbance rejection is rigorously proved. The tracking performance of switched nonlinear system is guaranteed based on common Lyapunov approach under the designed switching strategy.
On the need of the 4th order of Daubechies wavelet transforms to denoise a nonstationary fatigue loading
Authors: S. Abdullah, S. N. Sahadan, M. Z. Nuawi, A. Zaharim, Z. M. Nopiah
Venue: Proceedings of the 7th WSEAS International Conference on Signal Processing, Robotics and Automation (2008)

This paper present the use of wavelet transforms for denoising a road load fatigue strain data set. For the purpose of this paper, the 4th order of Daubechies wavelet with fifteen decomposition levels was adopted. The denoised approach of a random data was seldom used in the noise and vibration research, but it rarely been used in the scope of fatigue data analysis. This study adopted the approach used in the previous related research, which was the application in a vibration analysis. It was hypothesized that this denoising method may be suited for the analysis of fatigue road load data, seems this data type is having similar pattern to the vibration random data. For the fatigue life assessment, high amplitude cycles in the fatigue data set are vital to be retained after the denoising process, as these cycles gave higher fatigue damage potential. After the fatigue signal being denoised, the statistical and fatigue analysis were performed in order to validate the applicable of this technique is applicable in fatigue signal analysis. From the analysis of this paper, it was found that the wavelet denoising approach, by means of the 4th order of Daubechies wavelet, was not suitable to analyse fatigue random data because. It is because of this approach diminished high amplitude cycles from the original signal.
FARS: A Multi-relational Feature and Relation Selection Approach for Efficient Classification
Authors: Bo Hu, Hongyan Liu, Jun He, Xiaoyong Du
Venue: Proceedings of the 4th international conference on Advanced Data Mining and Applications (2008)

Feature selection is an essential data processing step to remove the irrelevant and redundant attributes for shorter learning time, better accuracy and better comprehensibility. A number of algorithms have been proposed in both data mining and machine learning area. These algorithms are usually used in single table environment, where data are stored in one relational table or one flat file. They are not suitable for multi-relational environment, where data are stored in multiple tables joined each other by semantic relationships. To solve this problem, in this paper we propose a novel approach called FARS to do both feature and relation selection for efficient multi-relational classification. By this approach, we not only extend traditional feature selection method to selects relevant features from multi-relations, but also develop a new method to reconstruct the multi-relational database schema and get rid of irrelevant tables to further improve classification performance. Results of experiments conducted on several real databases show that FARS can effectively choose a small set of relevant features, enhancing the classification efficiency significantly and improving prediction accuracy.
Fractal evaluation of a discrete model for simulation of avascular tumor growth
Authors: Loretta Ichim, Ecaterina Oltean, Radu Dobrescu
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

The paper analyses a number of mathematical models describing the growth and development of nonvascular tumors and proposes a new lattice-based computer model to simulate the tumor growth with nutrient consumption constraints. The modeling solution is able to reproduce the classic three layer structure familiar from multicellular spheroids: cell proliferation, quiescent and necrosis. The accuracy of this model is tested by comparing with a fractal morphometric technique two patterns, one obtained by simulation, the other developed in-vitro. The evaluation of the geometrical complexity is made by measuring the irregularities of the boundary, typical for tumor growth, in a bi-dimensional representation.