ppxscal/embedding_network huggingface dataset:
A Cellular Approach to Fault Detection and Recovery in Wireless Sensor Networks
Authors: M. Asim, H. Mokhtar, M. Merabti
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

In the past few years wireless sensor networks have received a greater interest in application such as disaster management, border protection, combat field reconnaissance and security surveillance.Sensor nodes are expected to operate autonomously in unattended environments and potentially in large numbers. Failures are inevitable in wireless sensor networks due to inhospitable environment and unattended deployment.The data communication and various network operations cause energy depletion in sensor nodes and therefore, it is common for sensor nodes to exhaust its energy completely and stop operating.This may cause connectivity and data loss. Therefore, it is necessary that network failures are detected in advance and appropriate measures are taken to sustain network operation.In this paper we extend our cellular architecture and proposed a new mechanism to sustain network operation in the event of failure cause of energy-drained nodes. In our solution the network is partitioned into a virtual grid of cells to perform fault detection and recovery locally with minimum energy consumption. Specifically, the grid based architecture permits the implementation of fault detection and recovery in a distributed manner and allows the failure report to be forwarded across cells. The proposed failure detection and recovery algorithm has been compared with some existing related work and proven to be more energy efficient.
Web software traffic characteristics and failure prediction model selection
Authors: Y. Wang, W. M. Lively, D. B. Simmons
Venue: Journal of Computational Methods in Sciences and Engineering (2009)

In this paper, we analyze web traffic characters and the relationship with software failures. Results indicate hourly web access traffic is the lowest from 3:00 to 4:00 am, while the traffic load gradually reaches peak between 14:00 and 16:00, before declining. In daily base, web traffic fluctuates in the 25 observed days. The hourly access hits appear in similar patterns to the software failures. The web site reliability is 0.9878. The mean time between failures is 82.03 hits. Five popular software reliability models are calibrated with real data. The validations show that Goel-Okumoto and Gompertz models accurately describe web software failures. Further investigations indicate that both models have some deviations in prediction accuracy starting from the 20th day. Using similar approach to change-point solutions, we recalibrate the models with different parameter values after 20th day. The results appear that two sets of parameter values greatly improve model prediction accuracy.
Information Extraction Based on Table Area Locating for E-Commerce Websites
Authors: Liubo Ouyang, Rui Dong, Beiji Zou
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 04 (2009)

Efficient extracting merchandise information is the key technology for e-commerce searching engine. By analyzing web table characters of HTML pages of e-commerce websites, this article proposes the notion of table area locating, and decomposes the merchandise information extraction into three key processes: searching Preparative Core Areas (PCA), locating Core Area (CA) and extracting attribute values from Core-Area, and then design the algorithm of locating Core Area and the algorithm of extracting attributes names and values. We experimented with the new approach on some HTML pages from various e-commerce websites. The results indicate that this approach can locate merchandise information area and extract attributes names and values efficiently, and have better performance of precise and recall.
ANN Ensembles vs DSP for Mobile Object Detection and Filtering
Authors: Kevin Emanuel Moorgas, Poobalan Govender
Venue: Proceedings of the Advances in Electrical and Electronics Engineering - IAENG Special Edition of the World Congress on Engineering and Computer Science 2008 (2008)

This paper presents a comparative study between digital signal processing (DSP) systems and artificial neural networks (ANN’s) for object motion detection and object extraction. The ANN’s are arranged as an ensemble to perform the motion detection and image subtraction function. The ANN system displays a superior performance over the DSP in terms of system complexity and image quality.
A Semantic Service Oriented Architecture for Enterprise Application Integration
Authors: Liyi Zhang, Si Zhou, Mingzhu Zhu
Venue: Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01 (2009)

Although Service Oriented Architecture (SOA) goes a long way toward providing interoperability in distributed and heterogeneous environments for Enterprise Application Integration (EAI), managing semantic differences in such environments remains a challenge. This paper proposes a framework of semantic SOA for Enterprise Application Integration, and uses Web Service Modeling Ontology (WSMO) as its semantic service model. Last, we introduce a running example using semantic SOA for Enterprise Application Integration.
An Integrated Approach towards the Homogeneous Provision of Geographically Dispersed Info-Mobility Services to Mobile Users
Authors: Dimitrios Giakoumis, Dimitrios Tzovaras, Dionisis Kehagias, Evangelos Bekiaris, George Hassapis
Venue: Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009 (2009)

In this paper we introduce a mechanism enabling applications to present information retrieved from different services, thus delivered with different structure, in a homogeneous and seamless fashion. This mechanism was an outcome of the research that took place within the European Integrated Project ASK-IT. The project developed an ambient intelligence framework which supports mobility impaired people on the move to access context-sensitive information dependant on user geographic location and the use case under consideration. The information derives from geographically dispersed web services and is rendered on mobile devices. The ASK-IT framework enables the presentation of information that covers a wide variety of domains which belong to the info-mobility scope (Points of Interest, Route Guidance etc.). Our approach deals with the integration of information-providing services, in order to facilitate the homogeneity of the final presentation of the content, through the end-user application.
Linear Structural Equation Model and Sas Procedure for Parameter Estimation
Authors: Yong Li
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 01 (2009)

The linear structural equation model is introduced in this paper. And as an example of the linear structural equation model, a new customer satisfaction indices model is built, Sas procedure for parameter estimation is given, and the model is fitted by using sampling data and the results are evaluated.
Continuous User Interfaces for Seamless Task Migration
Authors: Pardha S. Pyla, Manas Tungare, Jerome Holman, Manuel A. Pérez-Quiñones
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part III: Ubiquitous and Intelligent Interaction (2009)

In this paper, we propose the Task Migration framework that provides a vocabulary and constructs to decompose a task into its components, and to examine issues that arise when it is performed using multiple devices. In a world of mobile devices and multiple computing devices, users are often forced to interrupt their tasks, move their data and information back and forth among the various devices manually, recreate the interaction context, and then resume the task on another device. We refer to this break from the task at hand as a task disconnect. Our objective is to study how software can bridge this task disconnect, enabling users to seamlessly transition a task across devices using continuous user interface. The framework is intended to help designers of interactive systems understand where breaks in task continuity may occur, and to proactively incorporate features and capabilities to mitigate their impact or avoid such Task Disconnects altogether.
A New Method for Linear Dimensionality Reduction
Authors: Wenjun Wang, Junying Zhang, Jin Xu, Yue Wang
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

A novel class based linear dimensionality reduction method is proposed, called Class-Wise Correlation Preserving Projection (CWCPP). In CWCPP, the relation among the original gene expression data is preserved according to a certain kind of similarity between data points, which takes special consideration of both the correlation information and the class information. Different from the traditional method, i.e., Fisher Linear Discriminant Analysis (FLD), CWCPP utilizes correlation information to guide the procedure of linear projection directions searching. Experiments on yeast gene expression data and NCI gene expression data are performed to test and evaluate the proposed algorithm.
Linkages between manufacturing strategy, benchmarking, performance measurement and business process reengineering
Authors: Natasa Vujica Herzog, Stefano Tonchia, Andrej Polajnar
Venue: Computers and Industrial Engineering (2009)

An empirical analysis is presented for researching linkages between manufacturing strategy, benchmarking, performance measurement (PM) and business process reengineering (BPR). Although the importance of these linkages has been described in conceptual literature, it has not been widely demonstrated empirically. The survey research was carried out in 73 medium and large-sized Slovenian manufacturing companies within the mechanical, electro-mechanical and electronic industries. The resulting data were subjected to reliability and validity analyses. Canonical correlation analysis was used to test six hypotheses. The results confirmed the need for a strategically-driven BPR approach and the positive impact of performance measurement on BPR performance.
An Architecture for Programmable Multi-core IP Accelerated Platform with an Advanced Application of H.264 Codec Implementation
Authors: Yifeng Qiu, Wael Badawy, Robert Turney
Venue: Journal of Signal Processing Systems (2009)

A new integrated programmable platform architecture is presented, with the support of multiple accelerators and extensible processing cores. An advanced application for this architecture is to facilitate the implementation of H.264 baseline profile video codec. The platform architecture employs the novel concept of virtual socket and optimized memory access to increase the efficiency for video encoding. The proposed architecture is mapped on an integrated FPGA device, Annapolis WildCard-II¿ or WildCard-4¿, for verification. According to the evaluation under different configurations, the results show that the overall performance of the architecture, with the integrated accelerators, can sufficiently meet the real-time encoding requirement for H.264 BP at basic levels, and achieve about 2---5.5 and 1---3 dB improvement, in terms of PSNR, as compared with MPEG-2 MP and MPEG-4 SP, respectively. The architecture is highly extensible, and thus can be utilized to benefit the development of multi-standard video codec beyond the description in this paper.
Workshop Organizers' Message
Authors: Raymond Chi-Wing Wong, Ada Wai-Chee Fu
Venue: Database Systems for Advanced Applications: DASFAA 2009 International Workshops: BenchmarX, MCIS, WDPP, PPDA, MBC, PhD, Brisbane, Australia, April 20 - 23, 2009 (2009)

International Workshop on Privacy-Preserving Data Analysis (PPDA) 2009 took place at Brisbane, Australia on 21st April, 2009. There were two sessions for this workshop with 2 paper presentations in the first session and 3 presentations in the second session.With the advancement of information technology and declining hardware price, organizations and companies are able to collect large amount of personal data. Moreover, advanced data analysis and mining techniques have been proposed to derived patterns hidden in data. However, the increasing power in data processing and analysis also raises concerns over the proper usage of personal information. Without proper treatment of the threat of sensitive information leakage, organizations would be reluctant to disclose their data even when there may be great potential gains from the data exploration. Therefore research in the area of privacy preservation is deemed important for both theoretical and practical reasons. PPDA 2009 was held in conjunction with DASFAA 2009 conference, and aims to bring together researchers in different fields related to privacy preserving data analysis and to provide a forum where researchers and practitioners can share and exchange their knowledge and experiences.
Footprint: cellular assisted Wi-Fi AP discovery on mobile phones for energy saving
Authors: Haitao Wu, Kun Tan, Jiangfeng Liu, Yongguang Zhang
Venue: Proceedings of the 4th ACM international workshop on Experimental evaluation and characterization (2009)

Recently commercial mobile phones have been shipped with integrated Wi-Fi NIC (Network Interface Card), while a fundamental barrier for easily using such Wi-Fi is its high energy cost for phone. We profile two integrated mobile phone Wi-Fi NICs and observe that the energy cost on PSM (Power Saving Mode) is greatly reduced, yet the scan state still costs most of the energy when it's not connected on discovering potential AP (Access Point). In this paper, we propose footprint, leveraging the cellular information such as the overheard cellular tower IDs and signal strength, to guild the Wi-Fi scan and thus greatly reduce the number of unnecessary scans through the changes and history logs of the mobile user's locations. Our experiments and implementation demonstrate that our scheme effectively saves energy for mobile phone integrated with Wi-Fi.
RadialNet: An Interactive Network Topology Visualization Tool with Visual Auditing Support
Authors: João P. Medeiros, Selan R. Santos
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

The pervasive aspect of the Internet increases the demand for tools that support both monitoring and auditing of security aspects in computer networks. Ideally, these tools should provide a clear and objective presentation of security data in such a way as to let network administrators detect or even predict network security breaches. However, most of these data are still presented only in raw text form, or through inadequate data presentation techniques. Our work tackles this problem by designing and developing a powerful tool that aims at integrating several information visualization techniques in an effective and expressive visualization. We have tested our tool in the context of network security, presenting two case studies that demonstrate important features such as scalability and detection of critical network security issues.
An ISU dialogue system exhibiting reinforcement learning of dialogue policies: generic slot-filling in the TALK in-car system
Authors: Oliver Lemon, Kallirroi Georgila, James Henderson, Matthew Stuttle
Venue: Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations (2006)

We demonstrate a multimodal dialogue system using reinforcement learning for in-car scenarios, developed at Edinburgh University and Cambridge University for the TALK project. This prototype is the first "Information State Update" (ISU) dialogue system to exhibit reinforcement learning of dialogue strategies, and also has a fragmentary clarification feature. This paper describes the main components and functionality of the system, as well as the purposes and future use of the system, and surveys the research issues involved in its construction. Evaluation of this system (i.e. comparing the baseline system with handcoded vs. learnt dialogue policies) is ongoing, and the demonstration will show both.
Improving the efficiency of a wide-coverage CCG parser
Authors: Bojan Djordjevic, James R. Curran, Stephen Clark
Venue: Proceedings of the 10th International Conference on Parsing Technologies (2007)

The C&C CCG parser is a highly efficient linguistically motivated parser. The efficiency is achieved using a tightly-integrated supertagger, which assigns CCG lexical categories to words in a sentence. The integration allows the parser to request more categories if it cannot find a spanning analysis. We present several enhancements to the CKY chart parsing algorithm used by the parser. The first proposal is chart repair, which allows the chart to be efficiently updated by adding lexical categories individually, and we evaluate several strategies for adding these categories. The second proposal is to add constraints to the chart which require certain spans to be constituents. Finally, we propose partial beam search to further reduce the search space. Overall, the parsing speed is improved by over 35% with negligible loss of accuracy or coverage.
Decision Trees Using the Minimum Entropy-of-Error Principle
Authors: J. P. Sá, João Gama, Raquel Sebastião, Luís A. Alexandre
Venue: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns (2009)

Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estimates of the class distributions. In the present paper we introduce a new concept to binary tree design: instead of working with the class distributions of the data we work directly with the distribution of the errors originated by the node splits. Concretely, we search for the best splits using a minimum entropy-of-error (MEE) strategy. This strategy has recently been applied in other areas (e.g. regression, clustering, blind source separation, neural network training) with success. We show that MEE trees are capable of producing good results with often simpler trees, have interesting generalization properties and in the many experiments we have performed they could be used without pruning.
Semi-supervised Kernel Clustering Algorithm Based on Seed Set
Authors: Kunlun Li, Chao Zhang, Zheng Cao
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01 (2009)

Explore a semi-supervised clustering algorithm called Seed Kernel K-means (SKK-means) which is inspired by the kernel method and seeding strategy based on the classical K-means algorithm. The algorithm uses a certain ratio of data points as the seeds to generate initial cluster centers, and maps the data into feature space using kernel method. Our algorithm, which can be easily implemented, compares with respect to the other algorithm such as K-means and Kernel K-means, on 3 UCI databases (IRIS, Crabs and New-Thyroid) in some numeric experiment.
Research on Navigation Marks-Monitored Network System Based on WSN
Authors: Wu Wei, Yanan Zhang, Fuxing Zhang, Xinmei Wang
Venue: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 02 (2009)

This paper studies a Navigation Marks Remote Monitoring and Control System (NMRMCS) based on Wireless Sensor Network (WSN) and Differential Global Positioning System (DGPS). We designed NMRMCS installed in mountain area using WSN and DGPS to increase the positioning precision of navigation marks. We tested communicating distance of nodes by measuring the signal strength both in open region and wooden region, and record the number of flashing LED on ARM board with CC2420 chip, and tested relative parameters in some fixed points using Received Signal Strength Indication (RSSI) provided by highly integrated single-chip CC2420 with a method of least square curve fitting. The tested results show that the mean positioning error of Navigation Marks is less 2.5 meters, are of less positioning error than traditional NMRMCS. We select low power consumption ZigBee protocol based on IEEE 802.15.4 and use low energy-consumption RSSI position algorithm to reduce energy-consumption of NMRMCS.
A three-step decomposition method for the evolutionary design of sequential logic circuits
Authors: Houjun Liang, Wenjian Luo, Xufa Wang
Venue: Genetic Programming and Evolvable Machines (2009)

Evolvable hardware (EHW) refers to an automatic circuit design approach, which employs evolutionary algorithms (EAs) to generate the configurations of the programmable devices. The scalability is one of the main obstacles preventing EHW from being applied to real-world applications. Several techniques have been proposed to overcome the scalability problem. One of them is to decompose the whole circuit into several small evolvable sub-circuits. However, current techniques for scalability are mainly used to evolve combinational logic circuits. In this paper, in order to decompose a sequential logic circuit, the state decomposition, output decomposition and input decomposition are united as a three-step decomposition method (3SD). A novel extrinsic EHW system, namely 3SD---ES, which combines the 3SD method with the (μ, ¿) ES (evolution strategy), is proposed, and is used for the evolutionary designing of larger sequential logic circuits. The proposed extrinsic EHW system is tested extensively on sequential logic circuits taken from the Microelectronics Center of North Carolina (MCNC) benchmark library. The results demonstrate that 3SD---ES has much better performance in terms of scalability. It enables the evolutionary designing of larger sequential circuits than have ever been evolved before.
Computing backchannel distributions in multi-party conversations
Authors: Dirk Heylen, Rieks op den Akker
Venue: Proceedings of the Workshop on Embodied Language Processing (2007)

In multi-party conversations it may not always be obvious who is talking to whom. Backchannels may provide a partial answer to this question, possibly in combination with some other events, such as gaze behaviors of the interlocutors. We look at some patterns in multi-party interaction relating features of backchannel behaviours to aspects of the partipation framework.
Unsupervised modeling of objects and their hierarchical contextual interactions
Authors: Devi Parikh, Tsuhan Chen
Venue: Journal on Image and Video Processing (2009)

A successful representation of objects in literature is as a collection of patches, or parts, with a certain appearance and position. The relative locations of the different parts of an object are constrained by the geometry of the object. Going beyond a single object, consider a collection of images of a particular scene category containing multiple (recurring) objects. The parts belonging to different objects are not constrained by such a geometry. However, the objects themselves, arguably due to their semantic relationships, demonstrate a pattern in their relative locations. Hence, analyzing the interactions among the parts across the collection of images can allow for extraction of the foreground objects, and analyzing the interactions among these objects can allow for a semantically meaningful grouping of these objects, which characterizes the entire scene. These groupings are typically hierarchical. We introduce hierarchical semantics of objects (hSO) that captures this hierarchical grouping. We propose an approach for the unsupervised learning of the hSO from a collection of images of a particular scene. We also demonstrate the use of the hSO in providing context for enhanced object localization in the presence of significant occlusions, and show its superior performance over a fully connected graphical model for the same task.