ppxscal/embedding_network huggingface dataset:
Classification of Surface EMG Signal Based on Energy Spectra Change
Authors: Xiao Hu, Ping Yu, Qun Yu, Waixi Liu, Jian Qin
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

In this paper, we introduced a novel and simple methods of extracting the general features of two surface EMG signal patterns: forearm supination (FS) and forearm pronation (FP) surface EMG signals. The surface EMG signal was divided into two segments appropriately at the preparation stage and the action stages. Relative wavelet packet energy (RWPE, symbolized by pnp and pna respectively at the preparation stage and the action stages, where n denotes the nth frequency band (FB)) of the surface EMG signal was firstly calculated, and then the change (Pn=pna-pnp) was determined. The results show that Pn from some FBs could effectively characterize the general characteristics of the two surface EMG signal patterns. Compared with Pn in other FBs, P4 (in 93.75-125 Hz) had more appropriate features.
Automatic pronunciation scoring of words and sentences independent from the non-native's first language
Authors: Tobias Cincarek, Rainer Gruhn, Christian Hacker, Elmar Nöth, Satoshi Nakamura
Venue: Computer Speech and Language (2009)

This paper describes an approach for automatic scoring of pronunciation quality for non-native speech. It is applicable regardless of the foreign language student's mother tongue. Sentences and words are considered as scoring units. Additionally, mispronunciation and phoneme confusion statistics for the target language phoneme set are derived from human annotations and word level scoring results using a Markov chain model of mispronunciation detection. The proposed methods can be employed for building a part of the scoring module of a system for computer assisted pronunciation training (CAPT). Methods from pattern and speech recognition are applied to develop appropriate feature sets for sentence and word level scoring. Besides features well-known from and approved in previous research, e.g. phoneme accuracy, posterior score, duration score and recognition accuracy, new features such as high-level phoneme confidence measures are identified. The proposed method is evaluated with native English speech, non-native English speech from German, French, Japanese, Indonesian and Chinese adults and non-native speech from German school children. The speech data are annotated with tags for mispronounced words and sentence level ratings by native English teachers. Experimental results show, that the reliability of automatic sentence level scoring by the system is almost as high as the average human evaluator. Furthermore, a good performance for detecting mispronounced words is achieved. In a validation experiment, it could also be verified, that the system gives the highest pronunciation quality scores to 90% of native speakers' utterances. Automatic error diagnosis based on a automatically derived phoneme mispronunciation statistic showed reasonable results for five non-native speaker groups. The statistics can be exploited in order to provide the non-native feedback on mispronounced phonemes.
A new multilateral multi-issue negotiation protocol and its application to a crisis management problem
Authors: Miniar Hemaissia-Jeannin, Amal El Fallah Seghrouchni, Christophe Labreuche
Venue: Multiagent and Grid Systems (2008)

In this paper, a new protocol to address multilateral multi-issue negotiation in a cooperative context is presented. Complex dependencies between multiple issues are considered by modelling the preferences of the agents with a multi-criteria decision aid tool, also enabling to extract relevant information on a proposal assessment. This information is used in the protocol to help in accelerating the search for a consensus between the cooperative agents. In addition, the negotiation procedure is defined to address distributed allocation problem and applied in a crisis management context, with the common objective of the agents considered in the preferences of a mediator agent.
Rollout sampling approximate policy iteration
Authors: Christos Dimitrakakis, Michail G. Lagoudakis
Venue: Machine Learning (2008)

Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine. The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning domains: inverted pendulum and mountain-car.
Boundary Value Analysis Using Divide-and-Rule Approach
Authors: Karan Vij, Wenying Feng
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

A new Boundary Value Analysis algorithm using a divide and-rule approach is proposed in this paper. The idea comes from functional dependency among the input parameters. Based on the new algorithm, a testing tool is designed and implemented. Results from the testing tool show the advantages of the new algorithm over the traditional boundary value analysis methods. It generates some necessary testing cases that couldn’t be generated using the traditional methods.
Understanding Stories about Personal Documents
Authors: Daniel Gonçalves, Tiago Guerreiro, Joaquim A. Jorge
Venue: Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems (2008)

Hierarchies are the most common way to help users organize their personal information. However, their use is fraught with problems. In particular, the users' documents, stored in the filesystem, are notoriously difficult to manage and retrieve. A way to alleviate those problems is to resort to a wide range of knowledge about the users, their actions and the world that surrounds them. Systems that have done so lack an organizing principle that helps users refer to all the information that might be relevant. We propose a novel user interface paradigm, narrative-based interfaces, that provides such an organizing principle, showing how knowledge plays a central role in understanding the users' stories. An analysis of Quill, a prototype narrative-based interface for personal document retrieval, will show how narratives can successfully be used to help users retrieve their documents.
Frequency warping for VTLN and speaker adaptation by linear transformation of standard MFCC
Authors: Sankaran Panchapagesan, Abeer Alwan
Venue: Computer Speech and Language (2009)

Vocal tract length normalization (VTLN) for standard filterbank-based Mel frequency cepstral coefficient (MFCC) features is usually implemented by warping the center frequencies of the Mel filterbank, and the warping factor is estimated using the maximum likelihood score (MLS) criterion. A linear transform (LT) equivalent for frequency warping (FW) would enable more efficient MLS estimation. We recently proposed a novel LT to perform FW for VTLN and model adaptation with standard MFCC features. In this paper, we present the mathematical derivation of the LT and give a compact formula to calculate it for any FW function. We also show that our LT is closely related to different LTs previously proposed for FW with cepstral features, and these LTs for FW are all shown to be numerically almost identical for the sine-log all-pass transform (SLAPT) warping functions. Our formula for the transformation matrix is, however, computationally simpler and, unlike other previous LT approaches to VTLN with MFCC features, no modification of the standard MFCC feature extraction scheme is required. In VTLN and speaker adaptive modeling (SAM) experiments with the DARPA resource management (RM1) database, the performance of the new LT was comparable to that of regular VTLN implemented by warping the Mel filterbank, when the MLS criterion was used for FW estimation. This demonstrates that the approximations involved do not lead to any performance degradation. Performance comparable to front end VTLN was also obtained with LT adaptation of HMM means in the back end, combined with mean bias and variance adaptation according to the maximum likelihood linear regression (MLLR) framework. The FW methods performed significantly better than standard MLLR for very limited adaptation data (1 utterance), and were equally effective with unsupervised parameter estimation. We also performed speaker adaptive training (SAT) with feature space LT denoted CLTFW. Global CLTFW SAT gave results comparable to SAM and VTLN. By estimating multiple CLTFW transforms using a regression tree, and including an additive bias, we obtained significantly improved results compared to VTLN, with increasing adaptation data.
Single stage static level shifter design for subthreshold to I/O voltage conversion
Authors: Yi-Shiang Lin, Dennis M. Sylvester
Venue: Proceeding of the 13th international symposium on Low power electronics and design (2008)

A static subthreshold to I/O voltage level shifter is proposed. The proposed circuit employs a diode-connected pull-up transistor stack and a feedback structure to alleviate the drive strength requirement on the pull-down transistors. The proposed level shifter achieves less than 6 FO4 inverter delay under process and temperature variation when converting the input from 300mV to 2.5V. Compared to a conventional DCVS design, the new design consumes 8 times less power and is 10% faster under room temperature.
Chat mining: Predicting user and message attributes in computer-mediated communication
Authors: Tayfun Kucukyilmaz, B. Barla Cambazoglu, Cevdet Aykanat, Fazli Can
Venue: Information Processing and Management: an International Journal (2008)

The focus of this paper is to investigate the possibility of predicting several user and message attributes in text-based, real-time, online messaging services. For this purpose, a large collection of chat messages is examined. The applicability of various supervised classification techniques for extracting information from the chat messages is evaluated. Two competing models are used for defining the chat mining problem. A term-based approach is used to investigate the user and message attributes in the context of vocabulary use while a style-based approach is used to examine the chat messages according to the variations in the authors' writing styles. Among 100 authors, the identity of an author is correctly predicted with 99.7% accuracy. Moreover, the reverse problem is exploited, and the effect of author attributes on computer-mediated communications is discussed.
Order and entropy in picture passwords
Authors: Saranga Komanduri, Dugald R. Hutchings
Venue: Proceedings of graphics interface 2008 (2008)

Previous efforts involving picture-based passwords have not focused on maintaining a measurably high level of entropy. Since password systems usually allow user selection of passwords, their true entropy remains unknown. A 23-participant study was performed in which picture and character-based passwords of equal strength were randomly assigned. Memorability was tested with up to one week between sessions. The study found that both character and picture passwords of very high entropy were easily forgotten. However, when password inputs were analyzed to determine the source of input errors, serial ordering was found to be the main cause of failure. This supports a hypothesis stating that picture-password systems which do not require ordered input may produce memorable, high-entropy passwords. Input analysis produced another interesting result, that incorrect inputs by users are often duplicated. This reduces the number of distinct guesses users can make when authentication systems lock out users after a number of failed logins. A protocol for ignoring duplicate inputs is presented here. A shoulder-surfing resistant input method was also evaluated, with six out of 15 users performing an insecure behavior.
Dynamically creating virtual museums
Authors: Dionysios Politis, Gerasimos Vaiou, Marras Ioannis, Papaioannou Athanasios, Iaftsidis Charalampos
Venue: Proceedings of the 9th WSEAS International Conference on Systems (2005)

The idea of creating a virtual museum is far from new. However, creating a museum that an archaeologist could customize to match his needs is quite innovative. Here we present a system which can be used for online visualization of museums. Although, there are plenty of online virtual museums, none of them is customizable. These museums are designed statically and represent certain museums which makes it rather difficult to change. On the contrary, our Dynamic Virtual Museum is easily managed through database entries, which provide all necessary variables (rooms, models, exhibits) and interact with the renderer through scripts. Therefore, the virtual museum can be easily transformed to match any given exhibition or a visitor's specific choices.
Incorporating a non-additive decision making method into multi-layer neural networks and its application to financial distress analysis
Authors: Yi-Chung Hu
Venue: Knowledge-Based Systems (2008)

This paper presents a novel multi-layer perceptron using a non-additive decision making method and applies this model to the financial distress analysis, which is an important classification problem for a business, and the multi-layer perceptron has played a significant role in financial distress analysis. Traditionally, an activation function of an output neuron performs an additive method, namely the weighted sum method. Since the assumption of additivity among individual variables may not be reasonable, this paper uses a non-additive method, Choquet fuzzy integral, the fuzzy integral, to replace the weighted sum. In order to determine appropriate parameter specifications in the proposed model, a genetic algorithm is designed by considering the maximization of the number of correctly classified training patterns and the minimization of the training errors. The sample data obtained from Moody's Industrial Manuals are employed to examine the classification ability of the proposed model. The results demonstrate that the proposed model performs well in comparison with the traditional multi-layer perceptron and some multivariate techniques.
Interaction-aware energy management for wireless network cards
Authors: Igor Crk, Mingsong Bi, Chris Gniady
Venue: Proceedings of the 2008 ACM SIGMETRICS international conference on Measurement and modeling of computer systems (2008)

Wireless Network Interface Cards (WNICs) are part of every portable device, where efficient energy management plays a significant role in extending the device's battery life. The goal of efficient energy management is to match the performance of the WNIC to the network activity shaped by a running application. In the case of interactive applications on mobile systems, network I/O is largely driven by user interactions. Current solutions either require application modifications or lack a sufficient context of execution that is crucial in making accurate and timely predictions. This paper proposes a range of user-interaction-aware mechanisms that utilize a novel approach of monitoring a user's interaction with applications through the capture and classification of mouse events. This approach yields considerable improvements in energy savings and delay reductions of the WNIC, while significantly improving the accuracy, timeliness, and computational overhead of predictions when compared to existing state-of-the-art solutions.
A Conceptual Modeling Method for Critical Infrastructure Modeling
Authors: John Sokolowski, Charles Turnitsa, Saikou Diallo
Venue: Proceedings of the 41st Annual Simulation Symposium (anss-41 2008) (2008)

Conceptual Modeling often is perceived as a way of introducing the process of modeling a system, by concentrating on a reduced appreciation of that system, with a necessary reduction in the number of affecting variables and relations making up the model. As an alternative to this approach, rather than reduce the number of variables and relations, it has been found to be useful to include as many as possible variables and relations (resulting from a functional decomposition of a class of like systems) in a Potential Model (which represents the potential of all specific instances of the class of like systems), and then to move towards a Specific Model by applying contextual and situational values to the appropriate variables and relations that apply to the actual case. In so doing, the necessary reduction in variables and relations in moving from Potential Model to Specific Model allows the conceptual model to lead to further steps in the modeling process, ensuring that all relevance to the class of system is retained. This technique has been applied to a critical infrastructure modeling project, with both the method and results being presented here.
Physical Implementation of the DSPIN Network-on-Chip in the FAUST Architecture
Authors: Ivan Miro-Panades, Fabien Clermidy, Pascal Vivet, Alain Greiner
Venue: Proceedings of the Second ACM/IEEE International Symposium on Networks-on-Chip (2008)

This paper presents a physical implementation of the DSPIN network-on-chip in the FAUST architecture. FAUST is a stream-oriented multi-application SoC platform for telecommunications addressing IEEE 802.11a and MC-CDMA standards. The original asynchronous network-on-chip (ANOC) of FAUST has been replaced by the multi-synchronous DSPIN network-on-chip. In this paper, we analyze how the DSPIN network-on-chip, originally designed to support shared memory and multi-processors architectures, can support stream-oriented architectures. The physical implementation of both ANOC and DSPIN are presented. Finally, a comparison between ANOC and DSPIN designs in a 130nm technology is carried out in terms of area, throughput, packet latency, and power consumption.
Simultaneous real diagonalization of rectangular quaternionic matrix pairs and its algorithm
Authors: Wei Cheng, Lianggui Feng, Sen Yu
Venue: Computers Mathematics with Applications (2008)

The simultaneous real diagonalization(SRD) of a pair of rectangular quaternionic matrices is introduced, and some necessary and sufficient conditions for the existence of the SRD are derived. Based on one of the necessary and sufficient condition, an algorithm for gaining the SRD of a given matrix pair is presented.
Improving HFI within systems acquisition: methods, tools and future directions
Authors: Pamela Newman, Anne Bruseberg, Mel Lowe, Clare Borras, Kerry Tatlock
Venue: Cognition, Technology and Work (2008)

Recent years have seen an increased recognition of the role of the human operator in both the development and use of military systems. Human Factors Integration (HFI), the structured management process for ensuring the capture and accommodation of human capabilities and limitations in design has, however, a mixed record of success within military system developments. This paper describes research conducted by the HFI Defence Technology Centre (HFI DTC) to identify and address the barriers to HFI through the development of processes, methods and tools. Future changes in the operational context and military doctrine are also discussed in terms of the likely adaptations to the HFI process.
Finding the maximum subsequence sum on interconnection networks
Authors: K. Qiu, S. G. Akl
Venue: International Journal of Parallel, Emergent and Distributed Systems (2007)

We develop parallel algorithms for the maximum subsequence sum (or maximum sum for short) problem on several interconnection networks. For the 1-D version of the problem, we find an algorithm that computes the maximum sum of N elements on these networks of size p, where p ≤ N, with a running time of [image omitted] , which is optimal in view of the [image omitted]  lower bound. When [image omitted] , our algorithm computes the maximum sum in O(log N) time, resulting in an optimal cost of O(N). This result also matches the performance of two previous algorithms that are designed to run on the more powerful PRAM model. Our 1-D maximum sum algorithm can be used to solve the problem of maximum subarray, the 2-D version of the problem. In particular, for the same interconnection networks studied here, our parallel algorithm finds the maximum subarray of an N × N array in time O(log N) with [image omitted]  processors, once again, matching the performance of a previous PRAM algorithm.
On (k, d)-colorings and fractional nowhere-zero flows
Authors: Luis A. Goddyn, Michael Tarsi, Cun-Quan Zhang
Venue: Journal of Graph Theory (1998)

The concepts of (k, d)-coloring and the star chromatic number, studied by Vince, by Bondy and Hell, and by Zhu are shown to reflect the cographic instance of a wider concept, that of fractional nowhere-zero flows in regular matroids. &copy; 1998 John Wiley & Sons, Inc. J. Graph Theory 28: 155&ndash;161, 1998
Fibonacci mean and golden section mean
Authors: Hee Sik Kim, J. Neggers
Venue: Computers Mathematics with Applications (2008)

In this paper we show that there is a mapping D:M->DM on means such that if M is a Fibonacci mean so is DM, that if M is the harmonic mean, then DM is the arithmetic mean, and if M is a Fibonacci mean, then lim"n"->"~D^nM is the golden section mean.
Inferring the most important types of a query: a semantic approach
Authors: David Vallet, Hugo Zaragoza
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

In this paper we present a technique for ranking the most important types or categories for a given query. Rather than trying to find the category of the query, known as query categorization, our approach seeks to find the most important types related to the query results. Not necessarily the query category falls into this ranking of types and therefore our approach can be complementary.
Review: Cognitive radio technology: From distributed spectrum coordination to adaptive network collaboration
Authors: Dipankar Raychaudhuri, Xiangpeng Jing, Ivan Seskar, Khanh Le, Joseph B. Evans
Venue: Pervasive and Mobile Computing (2008)

This paper presents an integrated view of cognitive radio technologies for efficient wireless services in dense spectrum environments. The rationale for cognitive radio based systems is discussed, leading to an identification of the available design space that ranges from reactive interference avoidance to spectrum etiquette and eventually network collaboration. After reviewing prior work in the dynamic spectrum area, a specific distributed spectrum etiquette protocol called ''common spectrum coordination channel (CSCC)'' is introduced. Performance gains achieved with CSCC relative to simpler reactive time/frequency/power control algorithms are evaluated for example in WiFi/Bluetooth and WiFi/WiMax co-existence scenarios. The next level of system performance can be achieved through opportunistic collaboration between radios to form ad hoc multi-hop networks in which neighboring nodes associate with each other at high bit-rate and low power. Adaptive wireless networks of this type will require new protocol architectures which integrate flexible PHY/MAC and cross-layer capabilities with ad hoc network discovery and multi-hop routing. A specific ''CogNet'' protocol architecture based on the concept of a ''global control plane (GCP)'' is described. Major CogNet protocol modules for bootstrapping, discovery, data path setup and naming/addressing are outlined, and representative ns-2 simulation results are provided for validation. In conclusion, the paper gives a preview of the network-centric WiNC2R prototype under development at WINLAB as an experimental cognitive radio platform.