ppxscal/embedding_network huggingface dataset:
Efficient Biometric Verification in Encrypted Domain
Authors: Maneesh Upmanyu, Anoop M. Namboodiri, K. Srinathan, C. V. Jawahar
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Biometric authentication over public networks leads to a variety of privacy issues that needs to be addressed before it can become popular. The primary concerns are that the biometrics might reveal more information than the identity itself, as well as provide the ability to track users over an extended period of time. In this paper, we propose an authentication protocol that alleviates these concerns. The protocol takes care of user privacy, template protection and trust issues in biometric authentication systems. The protocol uses asymmetric encryption, and captures the advantages of biometric authentication. The protocol provides non-repudiable identity verification, while not revealing any additional information about the user to the server or vice versa. We show that the protocol is secure under various attacks. Experimental results indicate that the overall method is efficient to be used in practical scenarios.
Polyphone Recognition Using Neural Networks
Authors: Lishu Li, Qinghua Chen, Jiawei Chen, Fukang Fang
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

In this paper, we explore the recognition of polyphone. The cognition process is complex, which needs other additional information, otherwise it may cause uncertainty in decision. Recent research is almost focused on phonetics, while we plan to explore the question with neural networks. H. Haken used synergetic neural network to discuss the recognition of ambivalent patterns and the evolution equation of order parameters can interpret the oscillation in perception. Based on his idea, we argue that the process of cognition is phase transformation. Then we apply Hopfield network (associative memory network) with depressing synapse to simulate the recognition process. With our model, a Chinese polyphone is demonstrated. The result supports our interpretation strongly.
Asymptotic stability analysis of certain neutral differential equations: A descriptor system approach
Authors: Shaojiang Deng, Xiaofeng Liao, Songtao Guo
Venue: Mathematics and Computers in Simulation (2009)

Based on the descriptor and ''neutral type'' model transformation, some corresponding Lyapunov-Krasovskii functionals are introduced for stability analysis of certain neutral differential equations. Delay-dependent and delay-independent stability criteria are given in terms of linear matrix inequalities. The proposed criteria are less conservative and restrictive than other existing criteria since they are based on an equivalent neutral model transformation or parameterized transformation. Examples are given to illustrate advantages of our approach.
E-Business Development Services for SMEs in Selected ASEAN Countries and Southern China
Authors: United Nations
Venue:  (2007)

This publication attempts to promote the development of e-business services for SMEs by providing policymakers and enterprise support agencies with background information on the status of ICT use by SMEs, sharing experience on the development of strategic framework for the development of e-business services for SMEs, and sharing the results of the evaluation of the four pilot projects implemented. 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
Iris Recognition Using 3D Co-occurrence Matrix
Authors: Wen-Shiung Chen, Ren-Hung Huang, Lili Hsieh
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

This paper presents a biometric recognition based on the iris of a human eye using gray-level co-occurrence matrix (GLCM). A new approach of GLCM, called 3D-GLCM, which is expanded from the original 2D-GLCM is proposed and used to extract the iris features. The experimental results show that the proposed approach gains an encouraging performance on the UBIRIS iris database. The recognition rate up to 99.65% can be achieved.
Topics in massive data summarization
Authors: Martin J. Strauss
Venue:  (2008)

We consider three problems in this thesis. Two of them are about building near optimal histograms in non-uniform workload model and in probabilistic data streaming model respectively. The former has an associated weight vector with each streaming data vector, while the latter has a density function instead of a deterministic value as each data entry in the streaming data vector. The third one is to find approximate heavy hitters between two parties in a private model, in which, for every party no information is leaked unless necessary. More specifically, first, we want to construct a nearly workload-optimal histogram. Given B, we want to find the near optimal B bucket histogram under associated workload w within 1 + &epsis; error tolerance. In the cash register model where data is streamed as a series of updates, we can build a histogram using polylogarithmic space, polylogarithmic time to process each item, and polylogarithmic post-processing time to build the histogram. All these results need the workload to be explicitly stored since we show that if the workload is summarized in small space lossily, algorithmic results such as above do not exist. Then, we consider the problem of private computation of approximate Heavy Hitters. Alice and Bob each hold a vector and, in the vector sum, they want to find the B largest values along with their indices. We show how to solve the problem privately with polylogarithmic communication, polynomial work and constantly many rounds in the sense that nothing is learned by Alice and Bob beyond what is implied by their input, the ideal top-B output, and goodness of approximation (equivalently, the Euclidean norm of the vector sum). We give lower bounds showing that the Euclidean norm must leak by any efficient algorithm. In the third problem, we want to build a near optimal histogram on probabilistic data streams. Given B, we want to find the near optimal B bucket histogram on probabilistic data streams under both L1 measurement and L2 measurement. We give deterministic algorithms without sampling. We can build histograms using poly-logarithmic space, polylogarithmic time to process each item, and polylogarithmic post-processing time to build the histogram. The result we give under L2 measurement is within (1 + &epsis;)-error tolerance, and the result under L1 measurement is heuristic. We also give a direction to give guarantees to the heuristic.
Concurrent Design of a Manufacturing System Utilizing a Microfactory
Authors: N. Mishima
Venue: Proceeding of the 2006 conference on Leading the Web in Concurrent Engineering: Next Generation Concurrent Engineering (2006)

This paper first describes the concept of a microfactory and its design basics. The microfactory is a desktop-type miniature manufacturing system consists of miniature machine tools and manipulators. Since the prototyped microfactory was able to perform the whole process of machining parts and assembling them to a miniature ball bearing, it was able to say that it has a significant capability for micro mechanical fabrication. However, the possibility of the microfactory to improve manufacturing efficiencies of micro mechanical fabrications has not been considered enough. In the paper, the author proposes an evaluation method to calculate efficiencies of the system based on the required time for each process in the abovementioned microfactory project. The paper also tries to propose a concept of concurrent design of the product, manufacturing processes and system configuration, utilizing a microfactory-like system.
Pedagogical Agents in Multimedia Learning Environments: Do They Facilitate or Hinder Learning?
Authors: Steffi Domagk, Helmut M. Niegemann
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

What are the reasons for introducing an animated life-like character, referred to as a pedagogical agent, into a multimedia learning environment? On the one hand the definition of pedagogical agents implicitly implies a supportive role of these characters within the learning process (Johnson, Shaw et al., 1998). On the other hand research on pedagogical agents is still in its initial stages. We know little about the conditions under which the integration of pedagogical agents is appropriate and effective. The goal of this study is the differentiated examination of the pedagogical agent's effect on the learner's motivation and the actual learning outcome. In our study 175 university students worked with a multimedia learning environment on visual perception. In the experimental condition, a pedagogical agent guided the learning process by explaining the individual learning tasks. In the control condition, the same information was provided as on-screen text. The learner's motivation was measured during the learning period and subsequently the learner's performance in retention and transfer tasks was assessed. The results show no differences between the two experimental conditions, neither in motivation nor in retention and transfer tasks. This result is particularly important in light of the immense programming effort required to integrate pedagogical agents. The issue of whether it is reasonable to introduce pedagogical agents will be discussed in this paper.
Introducing Softness into Inductive Queries on String Databases
Authors: Ieva Mitasiunaite, Jean-François Boulicaut
Venue: Proceeding of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006 (2007)

In many application domains (e.g., WWW mining, molecular biology), large string datasets are available and yet under-exploited. The inductive database framework assumes that both such datasets and the various patterns holding within them might be queryable. In this setting, queries which return patterns are called inductive queries and solving them is one of the core research topics for data mining. Indeed, constraint-based mining techniques on string datasets have been studied extensively. Efficient algorithms enable to compute complete collections of patterns (e.g., substrings) which satisfy conjunctions of monotonic and/or anti-monotonic constraints in large datasets (e.g., conjunctions of minimal and maximal support constraints). We consider that fault-tolerance and softness are extremely important issues for tackling real-life data analysis. We address some of the open problems when evaluating soft-support constraint which implies the computations of pattern soft-occurrences instead of the classical exact matching ones. Solving efficiently soft-support constraints is challenging since it prevents from the clever use of monotonicity properties. We describe our proposal and we provide an experimental validation on real-life clickstream data which confirms the added value of this approach.
Securing the Internet's Routing Infrastructure
Authors: Sixto Ortiz Jr.
Venue: Computer (2009)

Experts have been concerned about the security of the Internet's routing infrastructure, which was designed many years ago. Now, organizations are developing proposals to secure the infrastructure.
Stream chaining: exploiting multiple levels of correlation in data prefetching
Authors: Pedro Diaz, Marcelo Cintra
Venue: ACM SIGARCH Computer Architecture News (2009)

Data prefetching has long been an important technique to amortize the effects of the memory wall, and is likely to remain so in the current era of multi-core systems. Most prefetchers operate by identifying patterns and correlations in the miss address stream. Separating streams according to the memory access instruction that generates the misses is an effective way of filtering out spurious addresses from predictable streams. On the other hand, by localizing streams based on the memory access instructions, such prefetchers both lose the complete time sequence information of misses and can only issue prefetches for a single memory access instruction at a time. This paper proposes a novel class of prefetchers based on the idea of linking various localized streams into predictable chains of missing memory access instructions such that the prefetcher can issue prefetches along multiple streams. In this way the prefetcher is not limited to prefetching deeply for a single missing memory access instruction but can instead adaptively prefetch for other memory access instructions closer in time. Experimental results show that the proposed prefetcher consistently achieves better performance than a state-of-the-art prefetcher -- 10% on average, being only outperformed in very few cases and then by only 2%, and outperforming that prefetcher by as much as 55% -- while consuming the same amount of memory bandwidth.
Online baseline identification algorithm using vector rules
Authors: Azlinah Mohamed, Rohayu Yusof, Norzaidah Md Noh, Shuzlina Abdul Rahman, Marina Yusoff, Sofianita Mutalib
Venue: Proceedings of the 10th WSEAS international conference on evolutionary computing (2009)

Signature verification and recognition can be divided into online and offline, depending on the sensing modality. In an online method, the dynamic information signature features such as direction, slant, baseline, pressure, speed and numbers of pen ups and downs can be captured. Method of extracting features signature depends on the requirement features to be extracted. Thus this paper discusses the construction of an algorithm to extract the baseline from signature. The Signature Extraction Features System (SEFS) uses the proposed algorithm and provides a set of tools that allow the systems to extract baseline features in signature automatically for analysis purposes. Signatures are taken from twenty randomly selected individuals with different background. These individuals will have to sign their signatures on the tablet and the SEFS system will gather and store the raw data. SEFS created the image of each signature and these images were used as samples for a developed questionnaire to be given to human expert for evaluation. These questionnaires are all about identifying the baseline of the signatures. Both results from SEFS and the questionnaire are compared, and it shows that the algorithm is 90% accurate. It can be concluded that the algorithm proposed are acceptable to represent extraction of signature features based on baseline.
Aerogility: an intelligent decision support system for managing service-based aftermarkets
Authors: Viet Dung Dang, Steve Osborn, Gary Vickers, Malcolm Bridgeford
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

This paper describes Aerogility - an intelligent decision support system for managing service-based aftermarkets. Aerogility uses multi-agent software technology to implement a dynamic model of an aerospace aftermarket. The model is realistic and includes all the assets, people and processes in a dynamic and interactive representation of the business. An initial model can be implemented quickly then enhanced and extended in stages. Individual stakeholders can contribute their understanding of the business to their part of the model. The operational parameters and business rules that drive the behaviour of the model can be easily changed. A management team can work through a variety of what-if scenarios and comparative simulations to evaluate options and policy innovations. Each scenario can be bench-marked with various analytical information that facilitates detailed analysis and powerful insight.
Evaluating dynamic protocols for open agent systems
Authors: Michael Apostolou, Alexander Artikis
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

We present a software system for evaluating 'dynamic' protocol specifications for open multi-agent systems, that is, specifications that are developed at design-time but may be modified at run-time by the protocol participants.
Instructional technologies in social science instruction in South Africa
Authors: Johann Louw, Cheryl Brown, Johan Muller, Crain Soudien
Venue: Computers Education (2009)

This study describes the results of a survey and a description of instructional technologies in place in the social sciences in South African Universities. Lecturers in the social sciences reported a well-established practice of information and communication technologies (ICTs) use for general purposes (although frequent use tended to be for email and searching the Internet). They had a high self-efficacy in terms of using ICTs both generally and for teaching and learning, and a high enthusiasm for the use of ICTs for teaching and learning. Half the lecturers had started using ICTs recently with the introduction of learning management systems (LMSs) whereas the other half had established practices that preceded the mainstreaming of LMSs across universities. Only about a quarter of the respondents felt able to develop and update ICTs themselves which indicates that support is a necessary part of teaching with technology. In terms of different types of use the focus was on putting content on the web and course administration. Use of ICTs for teaching of skills (whether information literacy, problem solving or critical thinking) was infrequent. There were different types of ICT use across the different sub-disciplines. Lecturers reported factors which constrained their use of ICTs for teaching and learning, such as inadequate technology, pedagogical issues (e.g. plagiarism), and students opting out of lectures when materials were available online. It is argued that user studies in are relevant to the future delivery of educational material, in terms of removing barriers to use and targeting training and supportive activities.
Pareto-improving and revenue-neutral congestion pricing schemes in two-mode traffic networks
Authors: Yang Liu, Xiaolei Guo, Hai Yang
Venue: Netnomics (2009)

This paper studies a Pareto-improving and revenue-neutral congestion pricing scheme on a simple two-mode (highway and transit) network: this scheme aims at simultaneously improving system performance, making every individual user better off, and having zero total revenue. Different Pareto-improving situations are explored when a two-mode transportation system serves for travel groups with different value-of-time (VOT) distributions. Since the congestion pricing scheme suggested here charges transit users negative tolls and automobile users positive tolls, it can be considered as a proper way to implement congestion pricing and transit subsidy in one step, while offsetting the inequity for the poor. For a general VOT distribution of commuters, the condition of Pareto-improving is established, and the impact of the VOT distribution on solving the inequity issue is explored. For a uniform VOT distribution, we show that a Pareto-improving and revenue-neutral pricing scheme always exists for any target modal split pattern that reduces the total system travel time.
Monitoring path nearest neighbor in road networks
Authors: Zaiben Chen, Heng Tao Shen, Xiaofang Zhou, Jeffrey Xu Yu
Venue: Proceedings of the 35th SIGMOD international conference on Management of data (2009)

This paper addresses the problem of monitoring the k nearest neighbors to a dynamically changing path in road networks. Given a destination where a user is going to, this new query returns the k-NN with respect to the shortest path connecting the destination and the user's current location, and thus provides a list of nearest candidates for reference by considering the whole coming journey. We name this query the k-Path Nearest Neighbor query (k-PNN). As the user is moving and may not always follow the shortest path, the query path keeps changing. The challenge of monitoring the k-PNN for an arbitrarily moving user is to dynamically determine the update locations and then refresh the k-PNN efficiently. We propose a three-phase Best-first Network Expansion (BNE) algorithm for monitoring the k-PNN and the corresponding shortest path. In the searching phase, the BNE finds the shortest path to the destination, during which a candidate set that guarantees to include the k-PNN is generated at the same time. Then in the verification phase, a heuristic algorithm runs for examining candidates' exact distances to the query path, and it achieves significant reduction in the number of visited nodes. The monitoring phase deals with computing update locations as well as refreshing the k-PNN in different user movements. Since determining the network distance is a costly process, an expansion tree and the candidate set are carefully maintained by the BNE algorithm, which can provide efficient update on the shortest path and the k-PNN results. Finally, we conduct extensive experiments on real road networks and show that our methods achieve satisfactory performance.
A framework for describing web repositories
Authors: Frank McCown, Michael L. Nelson
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

In prior work we have demonstrated that search engine caches and archiving projects like the Internet Archive's Wayback Machine can be used to "lazily preserve" website and reconstruct them when they are lost. We use the term "web repositories" for collections of automatically refreshed and migrated content, and collectively we refer to these repositories as the "web infrastructure". In this paper we present a framework for describing web repositories and the status of web resources in them. This includes an abstract API for web repository interaction, the concepts of deep vs. flat and light/dark/grey repositories and terminology of describing the recoverability of a web resource. Our API may serve as a foundation for future web repository interfaces.
Abstract storage: moving file format-specific abstractions intopetabyte-scale storage systems
Authors: Joe B. Buck, Noah Watkins, Carlos Maltzahn, Scott A. Brandt
Venue: Proceedings of the second international workshop on Data-aware distributed computing (2009)

High-end computing is increasingly I/O bound as computations become more data-intensive, and data transport technologies struggle to keep pace with the demands of large-scale, distributed computations. One approach to avoiding unnecessary I/O is to move the processing to the data, as seen in Google's successful, but relatively specialized, MapReduce system. This paper discusses our investigation towards a general solution for enabling in-situ computation in a peta-scale storage system. We believe our work with flexible, application-specific structured storage is the key to addressing the I/O overhead caused by data partitioning across storage nodes. In order to manage competing workloads on storage nodes, our research in system performance management is leveraged. Our ultimate goal is a general framework for in-situ data-intensive processing, indexing, and searching, which we expect to provide orders of magnitude performance increases for data-intensive workloads.