ppxscal/embedding_network huggingface dataset:
Achieving Secondary Capacity under Interference from a Primary Base Station
Authors: Shadi Ebrahimi Asl, Bahman Abolhassani
Venue: Proceedings of the 9th International Conference on Smart Spaces and Next Generation Wired/Wireless Networking and Second Conference on Smart Spaces (2009)

There are two main challenges for cognitive underlay transmission in a host channel. The first challenge is how to assign a host channel efficiently among a set of cognitive channel applicants such that primary users perceive no harmful interference. Further, the second challenge is how to achieve a good capacity under high power signal from primary transmitter of the host channel. In this paper, we propose a primary interference suppression technique for cognitive underlay transmission in a host channel by using direct sequence spread spectrum. We show that cognitive users can efficiently suppress high power signal from a primary base station by using adequate spreading factors. Further, we propose an adaptive cognitive underlay channel assignment (ACUCHA) algorithm in a host channel for an ad hoc cognitive network which is overlaid with a primary cell. We show that by using the proposed primary interference suppression in cognitive links the proposed secondary channel assignment algorithm achieves 261.14 Mbps capacity when there are 100 cognitive channel applicants and spreading factor is 100. Also, we show that the achieved capacity is gained without producing harmful interference temperature in the host channel and perceptible interference in adjacent channels.
How to establish a verbal paradigm on the basis of ancient Syriac manuscripts
Authors: W. Th. (Wido) van Peursen
Venue: Proceedings of the EACL 2009 Workshop on Computational Approaches to Semitic Languages (2009)

This paper describes a model that has been developed in the Turgama Project at Leiden University to meet the challenges encountered in the computational analysis of ancient Syriac Biblical manuscripts. The small size of the corpus, the absence of native speakers, and the variation attested in the multitude of textual witnesses require a model of encoding---rather than tagging---that moves from the formal distributional registration of linguistic elements to functional deductions. The model is illuminated by an example from verb inflection. It shows how a corpus-based analysis can improve upon the inflectional paradigms given in traditional grammars and how the various orthographic representations can be accounted for by an encoding system that registers both the paradigmatic forms and their attested realizations.
Tatiana: an environment to support the CSCL analysis process
Authors: Gregory Dyke, Kristine Lund, Jean-Jacques Girardot
Venue: Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1 (2009)

The analysis of multimodal computer-mediated human interaction data is difficult: the diverse nature of this data and its sheer quantity is challenging enough, but a further obstacle is introduced by the complex nature of these interactions. In this paper, we describe the kinds of activities performed by researchers wishing to analyze this data. We present a model for analysis based on these activities. We then introduce Tatiana (Trace Analysis Tool for Interaction Analysts) as an environment based on this model and designed to assist researchers in managing, synchronizing, visualizing and analyzing their data by iteratively creating artifacts which further their understanding or exhibit their current understanding of their data. We show how Tatiana can be used to perform analyses and its potential for sharing corpora and analyses within the research community.
Design of Four-Valued Operation Circuits of Adder and Subtraction Based on Neuron MOS Transistor
Authors: Pengjun Wang, Yuejun Zhang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

The neuron MOS transistor (neuMOS) is a new device with multiple-input gates and one floating gate. It is capable of obtaining a weighted sum calculation of multiple-input gates signals and then operating the threshold based on the result of summation. This paper presents a design scheme of four-valued operation circuits of adder and subtraction based on the characteristics of neuMOS. Firstly, the neuMOS four-valued T gate was designed. Then, the four-valued adder and subtraction circuits were designed by this T gate from the truth tables. The four-valued adder and subtraction is simple in structure, fast in speed, and lower in power consumption when comparing to the traditional adder and subtraction. Furthermore, it is easy to modify the circuit structure to design multi-valued circuits. Finally, PSPICE simulation has verified the designed circuits.
A Person-Centered Measurement System for Quantification of Physical Activity and Energy Expenditure at Workplaces
Authors: Britta Weber, Ingo Hermanns, Rolf Ellegast, Jens Kleinert
Venue: Proceedings of the International Conference on Ergonomics and Health Aspects of Work with Computers: Held as Part of HCI International 2009 (2009)

Accurate quantification of physical activity (PA) and energy expenditure (EE) is a basic prerequisite to evaluate activity promoting measures. A novel approach for determining EE by a person-centered measurement system which operates with motion sensors is presented. The new EE prediction model combines information on the type and intensity of PA as well as personal characteristics. For model calibration eight subjects performed standardized office and locomotion tasks while wearing the measurement system and an indirect calorimeter simultaneously. Via multiple regression analyses different EE prediction equations for sitting, standing, walking, climbing downstairs and climbing upstairs are developed. Model fit statistics revealed good results (adjusted R2 = 0.51 - 0.90). The developed model seems promising for precise EE prediction during the investigated activities.
Semantic role labeling via instance-based learning
Authors: Chi-San Althon Lin, Tony C. Smith
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

This paper demonstrates two methods to improve the performance of instance-based learning (IBL) algorithms for the problem of Semantic Role Labeling (SRL). Two IBL algorithms are utilized: k-Nearest Neighbor (kNN), and Priority Maximum Likelihood (PML) with a modified back-off combination method. The experimental data are the WSJ23 and Brown Corpus test sets from the CoNLL-2005 Shared Task. It is shown that applying the Tree-Based Predicate-Argument Recognition Algorithm (PARA) to the data as a preprocessing stage allows kNN and PML to deliver F1: 68.61 and 71.02 respectively on the WSJ23, and F1: 56.96 and 60.55 on the Brown Corpus; an increase of 8.28 in F1 measurement over the most recent published PML results for this problem (Palmer et al., 2005). Training times for IBL algorithms are very much faster than for other widely used techniques for SRL (e.g. parsing, support vector machines, perceptrons, etc); and the feature reduction effects of PARA yield testing and processing speeds of around 1.0 second per sentence for kNN and 0.9 second per sentence for PML respectively, suggesting that IBL could be a more practical way to perform SRL for NLP applications where it is employed; such as realtime Machine Translation or Automatic Speech Recognition.
Improvement of Practical Recurrent Learning Method and Application to a Pattern Classification Task
Authors: Mohamad Faizal Samsudin, Katsunari Shibata
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Practical Recurrent Learning (PRL) has been proposed as a simple learning algorithm for recurrent neural networks[1][2]. This algorithm enables learning with practical order O(n 2) of memory capacity and computational cost, which cannot be realized by conventional Back Propagation Through Time (BPTT) or Real Time Recurrent Learning (RTRL). It was shown in the previous work[1] that 3-bit parity problem could be learned successfully by PRL, but the learning performance was quite inferior to BPTT. In this paper, a simple calculation is introduced to prevent monotonous oscillations from being biased to the saturation range of the sigmoid function during learning. It is shown that the learning performance of the PRL method can be improved in the 3-bit parity problem. Finally, this improved PRL is applied to a scanned digit pattern classification task for which the results are inferior but comparable to the conventional BPTT.
Scalable language processing algorithms for the masses: a case study in computing word co-occurrence matrices with MapReduce
Authors: Jimmy Lin
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

This paper explores the challenge of scaling up language processing algorithms to increasingly large datasets. While cluster computing has been available in commercial environments for several years, academic researchers have fallen behind in their ability to work on large datasets. I discuss two barriers contributing to this problem: lack of a suitable programming model for managing concurrency and difficulty in obtaining access to hardware. Hadoop, an open-source implementation of Google's MapReduce framework, provides a compelling solution to both issues. Its simple programming model hides system-level details from the developer, and its ability to run on commodity hardware puts cluster computing within the reach of many academic research groups. This paper illustrates these points with a case study in building word cooccurrence matrices from large corpora. I conclude with an analysis of an alternative computing model based on renting instead of buying computer clusters.
Multicast in Third-Generation Mobile Networks: Services, Mechanisms and Performance
Authors: Robert Rummler, Alexander Daniel Gluhak, Hamid Aghvami
Venue:  (2009)

A hands-on tutorial on multicast in third-generation networks! In this book, the authors describe how to perform multicast, the one-to-many delivery of data to a group of destinations, in third-generation mobile networks. The authors provide an overview of the services that can be realized with multicast in third-generation networks, describe the mechanisms required to support these services and highlight the performance of several multicast mechanisms. The focus of this book is on multicast in UMTS and CDMA2000 networks, the dominant third-generation network standards. In addition to describing the standards for multicast, the authors also provide extensive performance results of multicast in third-generation networks. Key Features: Provides an in-depth review of the fundamentals of multicast Describes in detail the MBMS and BCMCS standards for multicast in UMTS and CDMA2000 networks, respectively Provides a comprehensive overview of the services that can be realized with multicast in third-generation networks Highlights the performance of multicast in third-generation networks Investigates how multicast can be achieved in heterogeneous networks consisting of cellular and broadcast networks This book is an invaluable resource for professional engineers and researchers working in the area of third-generation networks. Postgraduate and graduate students on networking and communications courses will also find this book an insightful and valuable reference.
Multiscale entropy approach to physiological fatigue during long-term Web browsing
Authors: C. H. Hung, Bernard C. Jiang
Venue: Human Factors in Ergonomics Manufacturing (2009)

Physiological fatigue during long-term Web browsing was investigated by the entropy-based method. A noninvasive instrument was used to gather 8-hour continuous electrocardiography signals from subjects who were asked to answer the psychological fatigue questionnaire every 2 hours. These data were used to calculate the heart rate (HR), traditional sample entropy (SampEn), and multiscale entropy (MSE). HR decreased as the browsing task began, but increased slightly after 4.5 hours. The psychological fatigue score gradually increased, implying that more severe subjective fatigue was experienced as Web browsing proceeded. In contrast, the traditional SampEn first increased and then oscillated after 2.5 hours. The browsing time of 2.5 hours may be a clue to physiological fatigue. The MSE results showed that the cardiac dynamic systems of undergraduates and males were more complex than those of graduates and females, respectively. Thus, SampEn may have the potential for estimating physiological fatigue during long-term Web browsing. &copy; 2009 Wiley Periodicals, Inc.
Implementation of Enterprise Instant Communicating System Based on Application Layer with Java Programming
Authors: Lin Jianbing, Zou Jinan
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Communication is important to enterprise, the paper constructed an enterprise instant communicating system based on application layer using the socket mechanism of java language, introduced briefly the establishment of communication mechanism of application layer in client and server side, then analyzed the design of the main function of client and the database on the server. The enterprise instanst communicating system adapted the three layers model as its basic frame with the socket and alternative network technology, it also utilized user login validating to manage and control the online users. The result of testing shows that the system is robust and has a friendly user interface. The system can be fit to the enterprise inner information communication and relating work.
Automatic acronym recognition
Authors: Dana Dannélls
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

This paper deals with the problem of recognizing and extracting acronymdefinition pairs in Swedish medical texts. This project applies a rule-based method to solve the acronym recognition task and compares and evaluates the results of different machine learning algorithms on the same task. The method proposed is based on the approach that acronym-definition pairs follow a set of patterns and other regularities that can be usefully applied for the acronym identification task. Supervised machine learning was applied to monitor the performance of the rule-based method, using Memory Based Learning (MBL). The rule-based algorithm was evaluated on a hand tagged acronym corpus and performance was measured using standard measures recall, precision and f-score. The results show that performance could further improve by increasing the training set and modifying the input settings for the machine learning algorithms. An analysis of the errors produced indicates that further improvement of the rule-based method requires the use of syntactic information and textual pre-processing.
Efficient Improvement for Adaboost Based Object Detection
Authors: Luo Sheng, Ye Xin-quan
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Object detection by the traditional Adaboost algorithm is very time-consuming mainly because the candidate feature number is large, and the feature number in the final strong detector is large. So this paper elevates 3 efficient optimization techniques and implements to reduce the training time. First we use some preprocessing technique to reduce the candidate features size to ten percent of the original, and then we use some implement skills to further reduce the training time. Besides these, we use double thresholds to describe each feature, which can improve the efficient of each feature, and reduce the required feature number for the final strong classifier. The experiment result show that the training of our system is hundred time faster than previous systems.
A relational data harmonization approach to XML
Authors: Timo Niemi, Turkka Näppilä, Kalervo Järvelin
Venue: Journal of Information Science (2009)

There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.
Image Semantic Search Engine
Authors: Chaoqing Lv, Takashi Kobayashi, Kiyoshi Agusa, Kun Wu, Qing Zhu
Venue: Proceedings of the 2009 First International Workshop on Database Technology and Applications (2009)

As the search technology rapidly developed, nowadays, main search engines are already able to meet users basic search desire. However, current search algorithms or methodologies mostly depend on keywords matching process, which could be effective for text search while not efficient for keywords-lacking or non-text search scenarios. This paper summarizes the solution adopted by current search engine vendors, and introduces a new approach that attaches content description index based on RDF standard to web images in order to achieve converting unstructured information search into structured information search. By injecting the Web 2.0 feature-Wisdom of Crowds, the engine has the characteristics of self-learning: as users amount increases, the knowledge base for semantic content of images accumulates, which makes the search engine more and more intelligent for search and semantics reasoning.
Physiologically Driven Rehabilitation Using Virtual Reality
Authors: Angela M. Salva, Antonio J. Alban, Mark D. Wiederhold, Brenda K. Wiederhold, Lingjun Kong
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

Creating a platform that allows the fusion of real-time physiological measurements and virtual reality (VR) simulation will greatly improve present human-computer interaction, adaptive displays, military training, and anxiety therapy. The Virtual Reality Medical Center (VRMC) has developed a physiologically-driven rehabilitation platform that correctly assesses user anxiety levels based on multiple real time physiological measures, determines the optimal level of physiological arousal for each individual user, and automates the virtual simulation to the proper intensity for each user. Additionally, VRMC collaborates with UCF to develop novel, state-of-the-art sensors to be integrated within the platform that are capable of measuring electrocardiogram, (EEG), skin conductance, gait, and pupillometry. In Phase I VRMC developed a capability to monitor, fuse, and evaluate physiological measures (heart rate, skin conductance, skin temperature, and respiration) in real time to assess user anxiety levels. The physiological data collected will be used to assess user anxiety levels in real time as neutral, low, or high with 90% accuracy and to determine the optimal level of physiological arousal for each individual user.
Pattern matching on objects in Java
Authors: Nadeem Abdul Hamid
Venue: Journal of Computing Sciences in Colleges (2009)

This paper presents a refinement of the Visitor design pattern, providing convenient pattern matching and deconstruction over objects in a Java class hierarchy. It develops the idea of extracting and passing the values of an object's subcomponents to the visitor operation so that it is not necessary to explicitly extract them using accessor methods. It further presents the use of the Java Reflection API to implement a flexible and extensible pattern matching framework.
Physics of Fluids, 1st edition
Authors: Uno Ingard
Venue:  (2009)

Written by a noted authority in the subject area, this book is a comprehensive study of the theory and the practical applications of fluid properties to numerous disciplines. It may be used as a reference in a variety of fields by scientists and engineers or as a text in senior-undergraduate or graduate-level courses. The book covers standard topics e.g., motion of a conducting fluid in a magnetic field, Brownian motion, charged particle motion, surface waves on a liquid, the kinetic theory of gases, and plasma physics. Many applications from aeronautics, acoustics, chemistry, mechanics, electricity, and others have been included to illustrate the mathematical and physical concepts. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Learned local Gabor patterns for face representation and recognition
Authors: Shufu Xie, Shiguang Shan, Xilin Chen, Xin Meng, Wen Gao
Venue: Signal Processing (2009)

In this paper, we propose Learned Local Gabor Patterns (LLGP) for face representation and recognition. The proposed method is based on Gabor feature and the concept of texton, and defines the feature cliques which appear frequently in Gabor features as the basic patterns. Different from Local Binary Patterns (LBP) whose patterns are predefined, the local patterns in our approach are learned from the patch set, which is constructed by sampling patches from Gabor filtered face images. Thus, the patterns in our approach are face-specific and desirable for face perception tasks. Based on these learned patterns, each facial image is converted into multiple pattern maps and the block-based histograms of these patterns are concatenated together to form the representation of the face image. In addition, we propose an effective weighting strategy to enhance the performances, which makes use of the discriminative powers of different facial parts as well as different patterns. The proposed approach is evaluated on two face databases: FERET and CAS-PEAL-R1. Extensive experimental results and comparisons with existing methods show the effectiveness of the LLGP representation method and the weighting strategy. Especially, heterogeneous testing results show that the LLGP codebook has very impressive generalizability for unseen data.