ppxscal/embedding_network huggingface dataset:
Alternative Strategies to Explore the SNNB Algorithm Performance
Authors: Laura Cruz R., Joaquin Perez O., Rodolfo A. Pazos R., Vanesa Landero N., Victor M. Alvarez H., Claudia G. Gomez S.
Venue: Proceedings of the Fifth Mexican International Conference on Artificial Intelligence (2006)

Data mining is the process of extracting useful knowledge from large datasets. A subarea of data mining is the classification that induces a set of models for predicting the label of the unknown class. The Naive Bayes classifier is simple, efficient and robust; its performance has been improved by some works, which focused on finding an instances subset in a conditional way and selecting the appropriate classifier with the highest probability. In this paper we propose to modify the Selective Neighborhood based Naive Bayes (SNNB) algorithm, using and combining other distance measurements, instance organization, instance space search and model selection. The proposed combinations are aimed at exploring the classifying accuracy of the SNNB algorithm. Experimental results show that the best strategy found (using 26 datasets from the UCI repository) won in 15 cases and only lost in 3 cases
Extended methodology of RS design and instances based on GIP
Authors: Qian-Hong Wu, Bo Qin, Yu-Min Wang
Venue: Journal of Computer Science and Technology (2005)

Abe et al. proposed the methodology of ring signature (RS) design in 2002 and showed how to construct RS with a mixture of public keys based on factorization and/or discrete logarithms. Their methodology cannot be applied to knowledge signatures (KS) using the Fiat-Shamir heuristic and cut-and-choose techniques, for instance, the Goldreich KS. This paper presents a more general construction of RS from various public keys if there exists a secure signature using such a public key and an efficient algorithm to forge the relation to be checked if the challenges in such a signature are known in advance. The paper shows how to construct RS based on the graph isomorphism problem (GIP). Although it is unknown whether or not GIP is NP-Complete, there are no known arguments that it can be solved even in the quantum computation model. Hence, the scheme has a better security basis and it is plausibly secure against quantum adversaries.
Author Cocitation Analysis is to intellectual structure as Web Colink Analysis is to &hellip;?: Research Articles
Authors: Alesia Zuccala
Venue: Journal of the American Society for Information Science and Technology (2006)

Author Cocitation Analysis (ACA) and Web Colink Analysis (WCA) are examined as sister techniques in the related fields of bibliometrics and webometrics. Comparisons are made between the two techniques based on their data retrieval, mapping, and interpretation procedures, using mathematics as the subject in focus. An ACA is carried out and interpreted for a group of participants (authors) involved in an Isaac Newton Institute (2000) workshop&mdash;Singularity Theory and Its Applications to Wave Propagation Theory and Dynamical Systems&mdash;and compared&sol;contrasted with a WCA for a list of international mathematics research institute home pages on the Web. Although the practice of ACA may be used to inform a WCA, the two techniques do not share many elements in common. The most important departure between ACA and WCA exists at the interpretive stage when ACA maps become meaningful in light of citation theory, and WCA maps require interpretation based on hyperlink theory. Much of the research concerning link theory and motivations for linking is still new; therefore further studies based on colinking are needed, mainly map-based studies, to understand what makes a Web colink structure meaningful. &copy; 2006 Wiley Periodicals, Inc.
On Growing Self - Organizing Neural Networks without Fixed Dimensionality
Authors: Guojian Cheng, Ziqi Song, Jinquan Yang, Rongfang Gao
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Kohonen's Self-Organizing Maps (KSOM) can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappings are formation of topology preserving, feature mappings and probability distribution approximation of input patterns. However, KSOM have some limitations, e.g., a fixed number of neural units and a topology of fixed dimensionality, which makes KSOM impractical for applications where the optimal number of units is not known in advance and resulting in problems if this predefined dimensionality does not match the dimensionality of the feature manifold. Growing Self-Organizing Neural Networks (GSONN) can change their topological structures during learning. GSONN without fixed dimensionality has no topology of a fixed dimensionality imposed on the network. This paper first gives an introduction to neural gas network, a non-grid KSOM. Then, we discuss some GSONN without fixed dimensionality such as growing neural gas and the author's model: twin growing neural gas. It is ended with some testing results comparison and conclusions.
XHTML encoding and compression
Authors: Sathiamoorthy Manoharan
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

The wireless application environment uses the wireless markup language (WML) as the primary markup language. WML is based on XML and therefore is quite verbose. Mobile networks generally have low bandwidth and high latency, and verbose documents can therefore take a long time to transfer. Further, mobile devices, especially older ones, do not typically have the processing power or memory to process such verbosity. Since all WML documents have to go through a mobile gateway, WAP 1.x specifies that the WML files are encoded to make them smaller. This lowers the transfer times and simplifies processing on the mobile device. WAP 2.0 includes support for a restricted version of XHTML, called the XHTML mobile profile. This is to make content development and management easier. XHTML, though as verbose as WML, is never encoded by the gateway. This is mainly because WAP 2.0 does not require the use of a gateway. Besides, the advances in mobile processing power and mobile networks mitigate some of the issues arising from the verbosity of XML. This paper investigates what performance gains are possible if XHTML were encoded and compressed. The experiments show that while there is a substantial performance gain using compression, gains due to encoding are comparatively small. The empirical results justify that XHTML encoding is not generally useful.
An ERP Study of Second Language Learning after Childhood: Effects of Proficiency
Authors: Shiro Ojima, Hiroki Nakata, Ryusuke Kakigi
Venue: Journal of Cognitive Neuroscience (2005)

Whether there is an absolute critical period for acquiring language is a matter of continuous debate. One approach to address this issue is to compare the processes of second language (L2) learning after childhood and those of first language (L1) learning during childhood. To study the cortical process of postchildhood L2 learning, we compared event-related brain potentials recorded from two groups of adult Japanese speakers who attained either high or intermediate proficiency in English after childhood (J-High and J-Low), and adult native English speakers (ENG). Semantic anomalies embedded in English sentences evoked a clear N400 component in all three groups, with only the time course of the brain activation varying among the groups. Syntactic violations elicited a left-lateralized negativity similar to the left anterior negativity in ENG and J-High, but not in J-Low. In ENG, a P600 component was additionally found. These results suggest that semantic processing is robust from early on in L2 learning, whereas the development of syntactic processing is more dependent on proficiency as evidenced by the lack of the left-lateralized negativity in J-Low. Because early maturation and stability of semantic processing as opposed to syntactic processing are also a feature of L1 processing, postchildhood L2 learning may be governed by the same brain properties as those which govern childhood L1 learning. We argue that these processes are qualitatively similar in many respects, with only restricted domains of language processing being subject to absolute critical period effects.
Adapting workload distribution on software DSM clusters: Experiences with Auto-adaptive and Reconfigurable Systems
Authors: Yen-Tso Liu, Tyng-Yeu Liang, Ce-Kuen Shieh
Venue: Software&mdash;Practice Experience (2006)

Achieving an appropriate workload distribution is essential if user applications are to achieve a satisfactory performance on software distributed shared memory (SDSM) clusters. To address this problem, the present study develops a novel method for distributing program threads onto the individual computers of SDSM clusters. In contrast to alternative methods, the proposed approach takes account not only of processor speed and data-sharing aspects, but also memory availability, such that application performance can be enhanced through the implementation of appropriate workload distributions. In addition, when distributing the program threads, the proposed method specifically chooses only those computers that can enhance the performance of the application, rather than simply distributing the threads to all the available nodes in the cluster. This location policy makes it possible to specify the appropriate node combinations that optimize program performance while simultaneously maximizing resource utilization. The proposed method is implemented on a testbed referred to as Teamster. The experimental results demonstrate that, compared to alternative methods, the proposed approach delivers a 20&ndash;30&percnt; improvement in the performance of the chosen test applications. Importantly, it is shown that the proposed method can efficiently specify proper node combinations for the applications. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Microarchitectural Protection Against Stack-Based Buffer Overflow Attacks
Authors: Yong-Joon Park, Zhao Zhang, Gyungho Lee
Venue: IEEE Micro (2006)

Although researchers have proposed several software approaches to preventing buffer overflow attacks, adversaries still extensively exploit this vulnerability. A microarchitecture-based, software-transparent mechanism offers protection against stack-based buffer overflow attacks with moderate hardware cost and negligible performance overhead.
Effects of task difficulty and epistemological beliefs on metacognitive calibration: a pilot-study
Authors: Stephanie Pieschl, Elmar Stahl, Rainer Bromme
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

This article presents a pilot study, which is part of a comprehensive project to examine the impact of epistemological beliefs on metacognitive calibration during learning processes within a complex hypermedia information system. More specifically, this pilot study investigates (1) if learners differentiate between tasks of different complexity, set goals and plan accordingly and (2) whether such adaptive learning behavior is influenced by their epistemological beliefs. Students (n = 72) inspected a set of six learning tasks and answered multiple questions derived from the COPES-model of self-regulated learning (Winne & Hadwin, 1998), e.g. they judged the importance of specific learning strategies for a particular learning task. Furthermore, they filled in inventories measuring their epistemological beliefs. Results confirmed significant influences of task complexity and epistemological beliefs on students' judgments.
Learning Object Context on the Semantic Web
Authors: Jelena Jovanovic, Colin Knight, Dragan Gasevic, Griff Richards
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

The paper presents an ontology-based framework for capturing learning context related information important for personalization of both learning objects (LOs) and learning designs (LDs). The central part of the framework is the LO Context ontology, that bridges a learning content ontology and a LD ontology. The LO context ontology is aimed at capturing information about the actual usage of a LO inside a LD, such as the learning activity the LO was used in, the pedagogical role assumed by the LO (e.g. exercise), the learner's features (represented in the form of the learner model) and the like. Furthermore we suggest the architecture of an adaptive educational system that leverages the proposed approach to enable personalization and reuse of LOs and LDs.
DSP-based PID controller design for the PMDC motor
Authors: W. H. Ali, Y. Zhang, C. M. Akujuobi, C. L. Tolliver, L.-S. Shieh
Venue: International Journal of Modelling and Simulation (2006)

This paper presents a robust proportional-integral-derivative (PID) controller design method for permanent magnetic DC (PMDC) motor. The PID controller parameters are systematically developed through the linear quadratic regulator (LQR) approach, such that satisfactory performance with guaranteed closed-loop stability is achieved. In order to deal with modelling error and input saturation, an internal model control (IMC) structure is utilized, such that system robustness is improved, without the need for an observer. The proposed method is implemented through the dSPACE digital signal processor (DSP) system, and the experimental result confirms its effectiveness.
Geometrically Inspired Itemset Mining
Authors: Florian Verhein, Sanjay Chawla
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

In our geometric view, an itemset is a vector (itemvector) in the space of transactions. Linear and potentially non-linear transformations can be applied to the itemvectors before mining patterns. Aggregation functions and interestingness measures can be applied to the transformed vectors and pushed inside the mining process. We show that interesting itemset mining can be carried out by instantiating four abstract functions: a transformation (g), an algebraic aggregation operator () and measures (f and F). For Frequent Itemset Mining (FIM), g and F are identity transformations,is intersection and f is the cardinality. Based on this geometric view we present a novel algorithm that uses space linear in the number of 1-itemsets to mine all interesting itemsets in a single pass over the data, with no candidate generation. It scales (roughly) linearly in running time with the number of interesting itemsets. FIM experiments show that it outperforms FPGrowth on realistic datasets above a small support threshold (0.29% and 1.2% in our experiments) .
Resource Discovery in a European Spatial Data Infrastructure
Authors: Paul C. Smits
Venue: IEEE Transactions on Knowledge and Data Engineering (2007)

The geospatial community is moving toward distributed databases and Web services by following the general developments in information and communication technology. The sharing of resources across multiple information communities raises the need of new technologies that support resource discovery and information retrieval. This paper investigates if a common ontology is desirable and feasible for information retrieval in a European Spatial Data Infrastructure. It does so by reviewing relevant literature and proposes an approach for the automatic updating of existing ontologies, designed to facilitate access to multilingual descriptors of geospatial resources. We demonstrate by means of a prototype of an experimental system that the proposed approach is feasible. The experimental system is unique because it integrates a gazetteer, the EuroVoc multilingual vocabulary, the GEMET multilingual thesaurus, an automatic concept space generator, and graph matching into one system. Based on our study, we conclude that it will be impractical to rely only on one common ontology for resource discovery. We also conclude that the approach of using human-created ontologies in combination with automatic concept space generation and associative retrieval is a powerful means to the discovery of geospatial resources. In the absence of a consistent use of semantic Web technologies, a centralized approach to indexing of metadata is required, which has consequences for architectural choices.
Specification with Java IDL for Correctness and Maintainability of Distributed Software System
Authors: Keum-Young Sung
Venue: Proceedings of the International Conference on Autonomic and Autonomous Systems (2006)

In this study a specification language named Spec and its processor using JLEX and CUP are suggested to specify the correctness property of a distributed concurrent software system. The correctness property to be specified deals with such properties as partial correctness, invariant, mutually exclusive access to a critical section, data replication, and accessibility. The specification about data replication and accessibility are for describing the liveness property for the fault tolerance of a distributed application, while the specification about partial correctness, invariant, and mutual exclusiveness are for describing the safety property. The Spec processor is supposed to extract the constructs related to Java IDL and then invoke the Java Runtime command, idlj, which in turn generates stub and skeleton source files accompanied with some infrastructure code for connecting to the ORB. Making use of the specification along with Java IDL syntax, users can specify the desired behavior of a target system in the context of correctness property. Using the suggested specification technique, developers can be helped to enhance the understandability and maintainability of the final system by emphasizing the front-end of software development lifecycle.
An Autonomous Trust Construction System Based on Bayesian Method
Authors: Wei Wang, Guosun Zeng, Tao Liu
Venue: Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology (2006)

Though research on multi-agent systems have progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the multi-agent system is a large, uncensored system. This raises the question of how much dependability to give each information source. We cannot expect each user to know the trustworthiness of each source. Trust mechanism is regarded as a key for solving the problem of security in multi-agent systems. To achieve the trust management autonomy, this paper presents an autonomous trust construction model based on Bayesian method. The presented model adopts the Bayesian method to evaluate the trust value of each agent, and uses the graph theory to combination and path searching to construct the trust relation. The simulation experiment results prove that the autonomous trust construction is effective.
Design Considerations for a Reusable Medical Database
Authors: N Chandrashekar, S. M. Gautam, K. S. Srinivas, J Vijayananda
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Medical image databases play an integral role in a digitized clinical environment starting from storing of electronic patient records, scanned medical images generated by Modalities like X-Ray and MR to reporting and billing. The operations in the clinical environment such as image storage and retrieval, viewing, and post processing can be served by a reusable database component using which different modalities can develop their own clinical applications. For a Multi-modality vendor, like Philips Medical Systems, it is profitable to have a platform group serving the diverse needs of these modalities through reusable components. This paper talks about the design considerations in realizing such a reusable medical database component.
Adaptive resolution vector quantization technique and basic codebook design method for compound image compression
Authors: T. Nakayama, M. Konda, K. Takeuchi, K. Kotani, T. Ohmi
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

In order to increase the performance of image compression by vector quantization (VQ), we propose a systematic codebook design method without using learning sequences for 4/spl times/4 and 2/spl times/2 pixel blocks. According to the method, the codebook can be applied to all kinds of images and exhibits equivalent compression performance to the specific codebooks created individually by conventional learning method using corresponding images. Furthermore, we have developed a novel VQ-based image-coding algorithm suitable for compound images. Adaptive resolution VQ (AR-VQ) method, which is composed of three key techniques, i.e., the edge detection, the resolution conversion, and the entropy coding, can realize much superior compression performance than the JPEG and the JPEG-2000. On the compression of the XGA (1024/spl times/768 pixels) images including text, for instance, there exist an overwhelming performance difference of 5 to 40 dB in compressed image quality.
L-TFRC: an end-to-end congestion control mechanism for video streaming over the Internet
Authors: Zhen Li, Guobin Shen, Shipeng Li, E. J. Delp
Venue: Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1 (2003)

Real-time multimedia applications over the Internet have posed a lot of challenges due to the lack of quality of service (QoS) guarantees, frequent fluctuations in channel bandwidth, and packet losses. To address these issues, a great deal of research has been done in both video coding and video transmission fields. In this paper we present a logarithm-based TCP-friendly rate control (L-TFRC) mechanism, which can estimate the available bandwidth more accurately and improve the smoothness of the multimedia streaming significantly. We also apply it to a progressive fine granularity scalable (PFGS)-based video streaming. Both simulations and experiments over the Internet confirm the performance of L-TFRC.
The use of simulation modeling in healthcare planning
Authors: Susan O'Hara, Mark Sullivan, Henry Bell
Venue: Proceedings of the 36th conference on Winter simulation (2004)

In this case study we demonstrate the value of simulation modeling in the healthcare architecture design of a new ambulatory surgery unit. Through simulation we were able to explore the relationship between the number of operating rooms and recovery beds, the number of cases and the phases of recovery, bed capacity, staffing, and waiting room seat requirements as it affected the design. This information allowed time for variations in the design to meet the client's needs before the project was built. Furthermore, we show the positive outcome of combining the experience of three professional disciplines: healthcare planning, architecture, and simulation modeling for nurses, doctors and patients of the new ambulatory surgery unit.
Attribute Grammar-Based Event Recognition and Anomaly Detection
Authors: Seong-Wook Joo, Rama Chellappa
Venue: Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (2006)

We propose to use attribute grammars for recognizing normal events and detecting abnormal events in a video. Attribute grammars can describe constraints on features (attributes) in addition to the syntactic structure of the input. Events are recognized using an extension of the Earley parser that handles attributes and concurrent event threads. Abnormal events are detected when the input does not follow syntax of the grammar or the attributes do not satisfy the constraints in the attribute grammar to some degree. We demonstrate the effectiveness of our method for the task of recognizing normal events and detecting anomalies in a parking lot.