ppxscal/embedding_network huggingface dataset:
The Application of KL Transform to Remove Direct Wave in Ground Penetrating Radar Records
Authors: Huo Zhihua, Wang Minghui
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

In ground penetrating radar (GPR) records, because of different kinds of noises, especially direct wave of ground surface, the real target is not seen clearly in the radar echo section, which makes the detection of real targets difficult. Considering that the direct waves among traces are not change greatly and have strong correlation, so it can be restrained by certain methods. KL transform often be used to pick up coherent noises and random noises in multi channel seismic records[1,4]. In this paper, KL transform is used to GPR data processing, which fully uses the different second-order statistic characteristics of their correlations on the direct wave, target signals in multi channel GPR data. The target signals are successfully separated form noises according to the corresponding relation of the eigenvalue,s magnitude of the correlation matrix and correlation strength of each component in the multi channel GPR data.
Combining empirical experimentation and modeling techniques: A design research approach for personalized mobile advertising applications
Authors: David Jingjun Xu, Stephen Shaoyi Liao, Qiudan Li
Venue: Decision Support Systems (2008)

We propose a design research approach combining behaviour and engineering techniques to better support user modeling in personalized mobile advertising applications. User modeling is a practical means of enabling personalization; one important method to construct user models is that of Bayesian networks. To identify the Bayesian network structure variables and the prior probabilities, empirical experimentation is adopted and context, content, and user preferences are the salient variables. User data collected from the survey are used to set the prior probabilities for the Bayesian network. Experimental evaluation of the system shows it is effective in improving user attitude toward mobile advertising.
Framework for Web service query algebra and optimization
Authors: Qi Yu, Athman Bouguettaya
Venue: ACM Transactions on the Web (TWEB) (2008)

We present a query algebra that supports optimized access of Web services through service-oriented queries. The service query algebra is defined based on a formal service model that provides a high-level abstraction of Web services across an application domain. The algebra defines a set of algebraic operators. Algebraic service queries can be formulated using these operators. This allows users to query their desired services based on both functionality and quality. We provide the implementation of each algebraic operator. This enables the generation of Service Execution Plans (SEPs) that can be used by users to directly access services. We present an optimization algorithm by extending the Dynamic Programming (DP) approach to efficiently select the SEPs with the best user-desired quality. The experimental study validates the proposed algorithm by demonstrating significant performance improvement compared with the traditional DP approach.
An Unsupervised Audio Segmentation and Classification Approach
Authors: Wenjuan Pan, Yong Yao, Zhijing Liu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

This paper presents an unsupervised audio segmentation and classification approach. First, the multiple change-point segmentation is adopted, and a new feature named Mel-ICA is introduced to improve it. An audio type "uncertain" is proposed to represent mixed type. Three features of each sub-segment are extracted using Fourier and wavelet transform. Then, classification is performed over each sub-segment based on feature threshold, and the majority rule is applied to determine the final type. The experimental results have shown that the false alarm rate decreased using Mel-ICA, and high accuracy of classification achieved.
Design and Implementation of a Novel P2P-Based VOD System Using Media File Segments Selecting Algorithm
Authors: ZhiHui Lu, ShiYong Zhang, Jie Wu, WeiMing Fu, YiPing Zhong
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

From the analysis of some hard drawbacks faced server-centric VOD system today, a novel P2P-based VOD System Using Media File Segments Selecting Algorithm(P2P-VOD- FSS), is introduced in this paper. In this infrastructure, we emphasize on how to real- timely and orderly download and consume file segments from multiple peer nodes to guarantee streaming service. we firstly give a system model of selecting peer nodes with requested file segments in P2P- based VOD System. And then we propose a novel file segments selecting algorithm, including (1)Serving Node Classify (2) Speed Definition (3) Task Assigning Rule (4) Urgency Rule. And we further describe segments selecting and downloading module architecture and class design. Based on the novel algorithm and architecture, we analyze the typical P2P based VOD service flow. As part of experiment work, we discuss P2P-based VOD System scheme implementation and then analyze the experiment results. At last, from our research experiences and related survey, we analyze the prospective research direction and challenges in this field.
Approximate NN queries on streams with guaranteed error/performance bounds
Authors: Nick Koudas, Beng Chin Ooi, Kian-Lee Tan, Rui Zhang
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

In data stream applications, data arrive continuously and can only be scanned once as the query processor has very limited memory (relative to the size of the stream) to work with. Hence, queries on data streams do not have access to the entire data set and query answers are typically approximate. While there have been many studies on the k Nearest Neighbors (kNN) problem in conventional multi-dimensional databases, the solutions cannot be directly applied to data streams for the above reasons. In this paper, we investigate the kNN problem over data streams. We first introduce the e-approximate kNN (ekNN) problem that finds the approximate kNN answers of a query point Q such that the absolute error of the k-th nearest neighbor distance is bounded by e. To support ekNN queries over streams, we propose a technique called DISC (aDaptive Indexing on Streams by space-filling Curves). DISC can adapt to different data distributions to either (a) optimize memory utilization to answer ekNN queries under certain accuracy requirements or (b) achieve the best accuracy under a given memory constraint. At the same time, DISC provide efficient updates and query processing which are important requirements in data stream applications. Extensive experiments were conducted using both synthetic and real data sets and the results confirm the effectiveness and efficiency of DISC.
Dynamic Handwritten Keyword Spotting Based on the NSHP-HMM
Authors: Ch. Choisy
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

This paper presents a keyword spotting system based on the NSHP-HMM. This model allows to dynamically create global word models from letters models, and do not require any writing segmentation. The second section describes our system and its application to a keyword-based handwritten mail sorting task. Next section shows how to divide process- ing time by 4, using a fix-point arithmetic and a dynamic model desactivation approach based on the natural length complexity. First results are encouraging, particulary for a document-level analysis.
Verification of Possibility of Forecasting Economical Time Series Using Neural Network and Digital Filter
Authors: Susumu Saito
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

This paper describes research that was performed to verify the possibility of learning an economical time series using a neural network. An actual economical time series wasn't used for this research, but, instead, verification was performed using data obtained from an equation developed in the field of econophysics that simulates an economical time series. This data changes irregularly, and it is difficult to learn using a neural network, but by processing the data using a low pass digital filter, learning is possible with a low error rate, and short-term prediction is possible.
Special Section International Parallel Processing Projects: A Software Perspective
Authors: J. L. Martin
Venue: IEEE Software (1985)

Industrial and academic researchers provide a glimpse into efforts to develop a faster, more powerful computer through methods beyond purely technological advances.
The Research of a New Web Server Cluster Architecture Supporting QoS
Authors: Wu Yang, ShuangQing Li, DaiJie Cheng
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

A new Web server cluster architecture with high scalability and reliability which supports Web QoS is proposed. The functions previously concentrated on a single dispatcher are distributed in this architecture, the traffic bottleneck of the dispatcher is alleviated, and the single point fault of dispatcher is avoided, so the scalability and reliability of the cluster system can be enhanced. Accessing locality on server is guaranteed by synchronous load transferring. The load balancing among the servers is achieved through a mechanism based on load vector. By measuring in experimental system, the increasing of throughput has linear relationship with the number of servers. So the QoS of the whole system is guaranteed.
On automatic knowledge validation for Bayesian knowledge bases
Authors: Eugene Santos,  Jr., Hang T. Dinh
Venue: Data Knowledge Engineering (2008)

Knowledge validation, as part of knowledge base verification and validation, is a critical process in knowledge engineering. The ultimate goal of this process is to make the knowledge base satisfy all test cases given by human experts. This is further complicated by factors such as uncertainty and incompleteness. Our paper covers theoretical results in knowledge validation for Bayesian Knowledge Bases (BKBs), a probabilistic model extended from Bayesian Networks for representing knowledge in uncertain domains. First, we study the consistency of test case sets by identifying the necessary and sufficient conditions for a test case set such that there exists a knowledge base satisfying all of its test cases. Second, we analyze the thrashing problem which is the interminable oscillation of the knowledge base's state when validating by parameter refinement. We propose an approach to validating BKBs that effectively eliminates thrashing under certain conditions of the original knowledge base and the test case set.
High Speed Pattern Matching for Network IDS/IPS
Authors: Mansoor Alicherry, M. Muthuprasanna, Vijay Kumar
Venue: Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols (2006)

The phenomenal growth of the Internet in the last decade and society¿s increasing dependence on it has brought along, a floodof security attacks on the networking and computing infrastructure. Intrusion detection/prevention systems provide defensesagainst these attacks by monitoring headers and payload of packets flowing through the network. Multiple string matching thatcan compare hundreds of string patterns simultaneously is a critical component of these systems, and is a well-studied problem.Most of the string matching solutions today are based on the classic Aho-Corasick algorithm, which has an inherent limitation;they can process only one input character in one cycle. As memory speed is not growing at the same pace as network speed,this limitation has become a bottleneck in the current network, having speeds of tens of gigabits per second. In this paper,we propose a novel multiple string matching algorithm that can process multiple characters at a time thus achieving multi-gigabitrate search speeds. We also propose an architecture for an efficient implementation on TCAM-based hardware. We additionallypropose novel optimizations by making use of the properties of TCAMs to significantly reduce the memory requirements of theproposed algorithm. We finally present extensive simulation results of network-based virus/worm detection using real signaturedatabases to illustrate the effectiveness of the proposed scheme.
Managing resources and quality of service in heterogeneous wireless systems exploiting opportunism
Authors: Shailesh Patil, Gustavo de Veciana
Venue: IEEE/ACM Transactions on Networking (TON) (2007)

We propose a novel class of opportunistic scheduling disciplines to handle mixes of real-time and best-effort traffic at a wireless access point. The objective is to support probabilistic service rate guarantees to real-time sessions while still achieving opportunistic throughput gains across users and traffic types. We are able to show a "tight" stochastic lower bound on the service a real-time session would receive assuming that the users possibly heterogenous capacity variations are known or estimated, and are fast fading across slots. Such bounds are critical to enabling predictable quality of service and thus the development of complementary resource management and admission control strategies. Idealized simulation results show that the scheme can achieve 80%-90% of the maximum system throughput capacity while satisfying the quality of service (QoS) requirements for real-time traffic, and that the degradation in system throughput is slow in the number of real-time users, i.e., inter- and intra-class opportunism are being properly exploited. We note however, that there is a tradeoff between strictness of QoS requirements and the overall system throughput one can achieve. Thus if QoS requirements on real-time traffic are very tight, one would need to simply give priority to real-time traffic, and in the process lose the throughput gains of opportunism.
Commandments of UML for Safety
Authors: Akram Idani, Dieu-Donné Okalas Ossami, Jean-Louis Boulanger
Venue: Proceedings of the International Conference on Software Engineering Advances (2007)

Nowadays, the Unified Modeling Language (UML) is becoming a "de facto" standard for object oriented environments and then it is perceived as a part of the culture of software engineers. However, the luck of rigorous semantic basis is a great shortcoming of UML which upsets its use to address safety problems. Still, taking benefit of the richness of UML to model critical systems is worthwhile because it is aimed at reducing the certification effort required for the design phase. Currently, we undertake works to delimit a well-defined UML core which could be used to model such systems. In this paper, we explore some critical aspects and recommendations of basic UML constructs which should be approached when dealing with safety.
Development and test application of a screening-level mercury fate model and tool for evaluating wildlife exposure risk for surface waters with mercury-contaminated sediments (SERAFM)
Authors: Christopher D. Knightes
Venue: Environmental Modelling Software (2008)

Complex chemical cycling of mercury in aquatic ecosystems means that tracing the linkage between anthropogenic and natural loadings of mercury to watersheds and water bodies and associated concentrations in the environment are difficult to establish without the assistance of numerical models that describe biogeochemical controls on mercury distribution and availability to organisms. This paper presents an overview of a process-based, steady-state model developed for state and water quality managers and scientists to assist in ecological risk assessments for mercury in aquatic environments. SERAFM (Spreadsheet-based Ecological Risk Assessment for the Fate of Mercury) incorporates the chemical, physical, and biological processes governing mercury transport and fate in a surface water including atmospheric deposition, watershed transport and transformation, solid transport and cycling within the water body, and water body mercury processes. This modelling framework was designed to assist risk assessors in evaluating wildlife risk at the screening-level for an aquatic ecosystem with mercury-contaminated sediments. An example application of the model that is used to inform a regional risk assessment is presented in this manuscript. In the example provided, hazard quotients for exposed wildlife and humans are calculated by the model for three scenarios: historical case of mercury-contaminated sediments, required clean-up levels to protect the most sensitive species, and background conditions. The spreadsheet structure of SERAFM permits dismantling and reassembling of specific sub-modules, while maintaining transparency to permit flexibility in use and application.
Segmented Independent Component Analysis for Online Filtering Using Highly Segmented Detectors
Authors: Eduardo F. Simas Filho, Jose Manuel de Seixas, Luz Pereira Caloba
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

An online particle discrimination system is proposed for the ATLAS particle detector, which will be placed at one of the collision points of LHC, the next generation parti- cle collider experiment. Segmented Independent Compo- nent Analysis (SICA) is applied over a highly segmented calorimeter (energy measurement system) in order to cope with the different levels of granularity present at each seg- ment of the detector. A discrimination efficiency of 97% was achieved for a false alarm probability of 4.8%.
Computational modeling of micro-cellular carbon foams
Authors: Mesut Kırca, Ayşenur Gül, Ekrem Ekinci, Ferhat Yardım, Ata Mugan
Venue: Finite Elements in Analysis and Design (2007)

Similar to other cellular solids, the topology of carbon foam structures affects almost all of the mechanical and thermal properties which are superior to those of many materials. In order to evaluate the mechanical properties as well as thermal properties correctly, random based foam structure must be modeled close to real 3-D foam geometry as much as possible. In this paper, 3-D geometry of micro-cellular carbon foam is modeled in computer aided design (CAD) environment by using special scripts written for capturing real topology of carbon foams. Then, finite element stress analyses are carried out to obtain effective mechanical properties such as compressive Young's modulus and Poisson's ratio. It is shown that finite element results are in close agreement with the results in literature.
Workshop on Distributed Fault-Tolerant Computers
Authors: J. Goldberg
Venue: Computer (1977)

Important directions for research were defined at a workshop on distributed fault-tolerant computers, held November 3-5, 1976, in San Juan, Puerto Rico. Sponsored by the IEEE Computer Society's Technical Committee on Fault-Tolerant Computing, chaired by John Meyer, and the Micro/Mini Computers TC, chaired by William Dejka, the workshop attracted 46 participants to discuss this rapidly developing area.
The basic constructive logic for a weak sense of consistency
Authors: Gemma Robles, José M. Méndez
Venue: Journal of Logic, Language and Information (2008)

In this paper, consistency is understood as the absence of the negation of a theorem, and not, in general, as the absence of any contradiction. We define the basic constructive logic BKc1 adequate to this sense of consistency in the ternary relational semantics without a set of designated points. Then we show how to define a series of logics extending BKc1 within the spectrum delimited by contractionless minimal intuitionistic logic. All logics defined in the paper are paraconsistent logics.
Security under key-dependent inputs
Authors: Shai Halevi, Hugo Krawczyk
Venue: Proceedings of the 14th ACM conference on Computer and communications security (2007)

In this work we re-visit the question of building cryptographic primitives that remain secure even when queried on inputs that depend on the secret key. This was investigated by Black, Rogaway, and Shrimpton in the context of randomized encryption schemes and in the random oracle model. We extend the investigation to deterministic symmetric schemes (such as PRFs and block ciphers) and to the standard model. We term this notion "security against key-dependent-input attack", or KDI-security for short. Our motivation for studying KDI security is the existence of significant real-world implementations of deterministic encryption (in the context of storage encryption) that actually rely on their building blocks to be KDI secure. We consider many natural constructions for PRFs, ciphers, tweakable ciphers and randomized encryption, and examine them with respect to their KDI security. We exhibit inherent limitations of this notion and show many natural constructions that fail to be KDI secure in the standard model, including some schemes that have been proven in the random oracle model. On the positive side, we demonstrate examples where some measure of KDI security can be provably achieved (in particular, we show such examples in the standard model).
On cyclic decompositions of the complete graph into the 2-regular graphs
Authors: Zhihe Liang
Venue: Journal of Applied Mathematics and Computing (2007)

The symbol C(m1n1m2n2...msns) denotes a 2-regular graph consisting of ni cycles of length mi, i=1, 2, ..., s. In this paper, we give some construction methods of cyclic (Kv, G)-designs, and prove that there exists a cyclic (Kv, G)-design when G=C((4m1)n1 (4m2)n2...(4ms)ns and v ≡ 1 (mod 2|G|).
Estimation of Test Metrics for the Optimisation of Analogue Circuit Testing
Authors: Ahcène Bounceur, Salvador Mir, Emmanuel Simeu, Luis Rolíndez
Venue: Journal of Electronic Testing: Theory and Applications (2007)

The estimation of test metrics such as defect level, test yield or yield loss is important in order to quantify the quality and cost of a test approach. For design-for-test purposes, this is important in order to select the best test measurements but this must be done at the design stage, before production test data is made available. In the analogue domain, previous works have considered the estimation of these metrics for the case of single faults, either catastrophic or parametric. The consideration of single parametric faults is sensitive for a production test technique if the design is robust. However, in the case that production test limits are tight, test escapes resulting from multiple parametric deviations may become important. In addition, aging mechanisms result in field failures that are often caused by multiple parametric deviations. In this paper, we will consider the estimation of analogue test metrics under the presence of multiple parametric deviations (or process deviations) and under the presence of faults. A statistical model of a circuit is used for setting test limits under process deviations as a trade-off between test metrics calculated at the design stage. This model is obtained from a Monte Carlo circuit simulation, assuming Gaussian probability density functions (PDFs) for the parameter and performance deviations. After setting the test limits considering process deviations, the test metrics are calculated under the presence of catastrophic and parametric single faults for different potential test measurements. We will illustrate the technique for the case of a fully differential operational amplifier, proving the validity in the case of this circuit of the Gaussian PDF.